Quantum storage of heralded polarization qubits in birefringent and anisotropically absorbing materials.

PubMed

Clausen, Christoph; Bussières, Félix; Afzelius, Mikael; Gisin, Nicolas

2012-05-11

Storage of quantum information encoded into heralded single photons is an essential constituent of long-distance quantum communication based on quantum repeaters and of optical quantum information processing. The storage of photonic polarization qubits is, however, difficult because many materials are birefringent and have polarization-dependent absorption. Here we present a simple scheme that eliminates these polarization effects, and we demonstrate it by storing heralded polarization qubits into a solid-state quantum memory. The quantum memory is implemented with a biaxial yttrium orthosilicate (Y2SiO5) crystal doped with rare-earth ions. Heralded single photons generated from a filtered spontaneous parametric down-conversion source are stored, and quantum state tomography of the retrieved polarization state reveals an average fidelity of 97.5±0.4%, which is significantly higher than what is achievable with a measure-and-prepare strategy.

Heralding efficiency and correlated-mode coupling of near-IR fiber-coupled photon pairs

DOE PAGES

Dixon, P. Ben; Rosenberg, Danna; Stelmakh, Veronika; ...

2014-10-06

We report on a systematic experimental study of heralding efficiency and generation rate of telecom-band infrared photon pairs generated by spontaneous parametric down-conversion and coupled to single mode optical fibers. We define the correlated-mode coupling efficiency--an inherent source efficiency--and explain its relation to heralding efficiency. For our experiment, we developed a reconfigurable computer controlled pump-beam and collection-mode optical apparatus which we used to measure the generation rate and correlated-mode coupling efficiency. The use of low-noise, high-efficiency superconducting-nanowire single-photon-detectors in this setup allowed us to explore focus configurations with low overall photon flux. The measured data agree well with theory andmore » we demonstrated a correlated-mode coupling efficiency of 97%±2%, which is the highest efficiency yet achieved for this type of system. These results confirm theoretical treatments and demonstrate that very high overall heralding efficiencies can, in principle, be achieved in quantum optical systems. We expect that these results and techniques will be widely incorporated into future systems that require, or benefit from, a high heralding efficiency.« less

Heralding efficiency and correlated-mode coupling of near-IR fiber-coupled photon pairs

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

Dixon, P. Ben; Rosenberg, Danna; Stelmakh, Veronika

We report on a systematic experimental study of heralding efficiency and generation rate of telecom-band infrared photon pairs generated by spontaneous parametric down-conversion and coupled to single mode optical fibers. We define the correlated-mode coupling efficiency--an inherent source efficiency--and explain its relation to heralding efficiency. For our experiment, we developed a reconfigurable computer controlled pump-beam and collection-mode optical apparatus which we used to measure the generation rate and correlated-mode coupling efficiency. The use of low-noise, high-efficiency superconducting-nanowire single-photon-detectors in this setup allowed us to explore focus configurations with low overall photon flux. The measured data agree well with theory andmore » we demonstrated a correlated-mode coupling efficiency of 97%±2%, which is the highest efficiency yet achieved for this type of system. These results confirm theoretical treatments and demonstrate that very high overall heralding efficiencies can, in principle, be achieved in quantum optical systems. We expect that these results and techniques will be widely incorporated into future systems that require, or benefit from, a high heralding efficiency.« less

Late Holocene sea ice conditions in Herald Canyon, Chukchi Sea

NASA Astrophysics Data System (ADS)

Pearce, C.; O'Regan, M.; Rattray, J. E.; Hutchinson, D. K.; Cronin, T. M.; Gemery, L.; Barrientos, N.; Coxall, H.; Smittenberg, R.; Semiletov, I. P.; Jakobsson, M.

2017-12-01

Sea ice in the Arctic Ocean has been in steady decline in recent decades and, based on satellite data, the retreat is most pronounced in the Chukchi and Beaufort seas. Historical observations suggest that the recent changes were unprecedented during the last 150 years, but for a longer time perspective, we rely on the geological record. For this study, we analyzed sediment samples from two piston cores from Herald Canyon in the Chukchi Sea, collected during the 2014 SWERUS-C3 Arctic Ocean Expedition. The Herald Canyon is a local depression across the Chukchi Shelf, and acts as one of the main pathways for Pacific Water to the Arctic Ocean after entering through the narrow and shallow Bering Strait. The study site lies at the modern-day seasonal sea ice minimum edge, and is thus an ideal location for the reconstruction of past sea ice variability. Both sediment cores contain late Holocene deposits characterized by high sediment accumulation rates (100-300 cm/kyr). Core 2-PC1 from the shallow canyon flank (57 m water depth) is 8 meter long and extends back to 4200 cal yrs BP, while the upper 3 meters of Core 4-PC1 from the central canyon (120 mwd) cover the last 3000 years. The chronologies of the cores are based on radiocarbon dates and the 3.6 ka Aniakchak CFE II tephra, which is used as an absolute age marker to calculate the marine radiocarbon reservoir age. Analysis of biomarkers for sea ice and surface water productivity indicate stable sea ice conditions throughout the entire late Holocene, ending with an abrupt increase of phytoplankton sterols in the very top of both sediment sequences. The shift is accompanied by a sudden increase in coarse sediments (> 125 µm) and a minor change in δ13Corg. We interpret this transition in the top sediments as a community turnover in primary producers from sea ice to open water biota. Most importantly, our results indicate that the ongoing rapid ice retreat in the Chukchi Sea of recent decades was unprecedented during the

76 FR 17446 - Wausau Daily Herald Advertising Production Division, a Subsidiary of Gannett Co., Inc.; Wausau...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-29

... DEPARTMENT OF LABOR Employment and Training Administration [TA-W-75,090] Wausau Daily Herald Advertising Production Division, a Subsidiary of Gannett Co., Inc.; Wausau, WI; Notice of Affirmative... workers of Wausau Daily Herald, Advertising Production Division, a subsidiary of Gannett Co., Inc., Wausau...

Realizing the measure-device-independent quantum-key-distribution with passive heralded-single photon sources

PubMed Central

Wang, Qin; Zhou, Xing-Yu; Guo, Guang-Can

2016-01-01

In this paper, we put forward a new approach towards realizing measurement-device-independent quantum key distribution with passive heralded single-photon sources. In this approach, both Alice and Bob prepare the parametric down-conversion source, where the heralding photons are labeled according to different types of clicks from the local detectors, and the heralded ones can correspondingly be marked with different tags at the receiver’s side. Then one can obtain four sets of data through using only one-intensity of pump light by observing different kinds of clicks of local detectors. By employing the newest formulae to do parameter estimation, we could achieve very precise prediction for the two-single-photon pulse contribution. Furthermore, by carrying out corresponding numerical simulations, we compare the new method with other practical schemes of measurement-device-independent quantum key distribution. We demonstrate that our new proposed passive scheme can exhibit remarkable improvement over the conventional three-intensity decoy-state measurement-device-independent quantum key distribution with either heralded single-photon sources or weak coherent sources. Besides, it does not need intensity modulation and can thus diminish source-error defects existing in several other active decoy-state methods. Therefore, if taking intensity modulating errors into account, our new method will show even more brilliant performance. PMID:27759085

Military Herald Indices (1975-1979). Volume 2

DTIC Science & Technology

1988-11-01

KALININ,V.COL., S "YEDIN.S.ENGR.LC.CTS. 1977 APR TRAINER EXERCISE.: KISELEV.P.. SHILOV.A. 1976 FEB TRAINER FOR FIRING TRAINING; A CLASSROOM .: YAROSHEVSKIY,V...Military Herald Indices (1975-1979) 0 C\\I Volume I! Allan S . Rehm Lauren Van Metre Charles B. Hall DTIC ELECTE JUN 02 1989 A Division of Hudson...AVAILABILITY OF REPORT . DECLASSIFIATIN /Approved for Public Release; Distribution unlimited 4. PERFORM NG ORGANIZATION REPORT NUMBER( S ) S . MONITORING

Highly efficient heralded single-photon source for telecom wavelengths based on a PPLN waveguide.

PubMed

Bock, Matthias; Lenhard, Andreas; Chunnilall, Christopher; Becher, Christoph

2016-10-17

We present the realization of a highly efficient photon pair source based on spontaneous parametric downconversion (SPDC) in a periodically poled lithium niobate (PPLN) ridge waveguide. The source is suitable for long distance quantum communication applications as the photon pairs are located at the centers of the telecommunication O- and C- band at 1312 nm and 1557 nm. The high efficiency is confirmed by a conversion efficiency of 4 × 10^-6 - which is to our knowledge among the highest conversion efficiencies reported so far - and a heralding efficiency of 64.1 ± 2.1%. The heralded single-photon properties are confirmed by the measurement of the photon statistics with a Click/No-Click method as well as the heralded g⁽²⁾-function. A minimum value for g⁽²⁾(0) of 0.001 ± 0.0003 indicating clear antibunching has been observed.

Heralded noiseless amplification for single-photon entangled state with polarization feature

NASA Astrophysics Data System (ADS)

Wang, Dan-Dan; Jin, Yu-Yu; Qin, Sheng-Xian; Zu, Hao; Zhou, Lan; Zhong, Wei; Sheng, Yu-Bo

2018-03-01

Heralded noiseless amplification is a promising method to overcome the transmission photon loss in practical noisy quantum channel and can effectively lengthen the quantum communication distance. Single-photon entanglement is an important resource in current quantum communications. Here, we construct two single-photon-assisted heralded noiseless amplification protocols for the single-photon two-mode entangled state and single-photon three-mode W state, respectively, where the single-photon qubit has an arbitrary unknown polarization feature. After the amplification, the fidelity of the single-photon entangled state can be increased, while the polarization feature of the single-photon qubit can be well remained. Both the two protocols only require the linear optical elements, so that they can be realized under current experimental condition. Our protocols may be useful in current and future quantum information processing.

Hong-Ou-Mandel Interference Between Triggered And Heralded Single Photons From Separate Atomic Systems

NASA Astrophysics Data System (ADS)

Cere, Alessandro; Leong, Victor; Kaur Gulati, Gurpreet; Srivathsan, Bharath; Kosen, Sandoko; Kurtsiefer, Christian

2015-05-01

The realization of quantum networks and long distance quantum communication rely on the capability of generating entanglement between separated nodes. We demonstrate the compatibility of two different sources of single photons: a single atom and four-wave mixing in a cold cloud of atoms. The four-wave mixing process in a cloud of cold 87Rb generates photon pairs. The cascade level scheme used ensures the generation of heralded single photons with exponentially decaying temporal envelope. The temporal shape of the heralding photons matches the shape of photons emitted by spontaneous decay but for the shorter coherence time A single 87Rb atom is trapped in an far-off-resonance optical dipole trap and can be excited with high probability using a short (~3 ns) intense pulse of resonant light, emitting a single photon by spontaneous decay. A large numerical aperture lens collects ~4% of the total fluorescence. The heralded and the triggered photons are launched into a Houng-Ou-Mandel interferometer: a symmetrical beam-splitter with outputs connected to single photon detectors. Scanning the relative delay between the two sources we observe the HOM dip with a maximum visibility of 70 +/-4%.

Measurement-device-independent quantum key distribution with multiple crystal heralded source with post-selection

NASA Astrophysics Data System (ADS)

Chen, Dong; Shang-Hong, Zhao; MengYi, Deng

2018-03-01

The multiple crystal heralded source with post-selection (MHPS), originally introduced to improve the single-photon character of the heralded source, has specific applications for quantum information protocols. In this paper, by combining decoy-state measurement-device-independent quantum key distribution (MDI-QKD) with spontaneous parametric downconversion process, we present a modified MDI-QKD scheme with MHPS where two architectures are proposed corresponding to symmetric scheme and asymmetric scheme. The symmetric scheme, which linked by photon switches in a log-tree structure, is adopted to overcome the limitation of the current low efficiency of m-to-1 optical switches. The asymmetric scheme, which shows a chained structure, is used to cope with the scalability issue with increase in the number of crystals suffered in symmetric scheme. The numerical simulations show that our modified scheme has apparent advances both in transmission distance and key generation rate compared to the original MDI-QKD with weak coherent source and traditional heralded source with post-selection. Furthermore, the recent advances in integrated photonics suggest that if built into a single chip, the MHPS might be a practical alternative source in quantum key distribution tasks requiring single photons to work.

Workplace ESL Literacy Program of the Los Angeles Herald Examiner Newspaper.

ERIC Educational Resources Information Center

Herald Examiner, Los Angeles, CA.

This packet of materials from the Los Angeles Herald Examiner's English-as-a-Second-Language (ESL) workplace literacy program, defunct since the newspaper's closing, contains the following items: an overview of the program; a list of units and subunits; two sample lesson plans; teacher guidelines about evaluation and progress; lists of specific…

Heralded entanglement of two ions in an optical cavity.

PubMed

Casabone, B; Stute, A; Friebe, K; Brandstätter, B; Schüppert, K; Blatt, R; Northup, T E

2013-09-06

We demonstrate precise control of the coupling of each of two trapped ions to the mode of an optical resonator. When both ions are coupled with near-maximum strength, we generate ion-ion entanglement heralded by the detection of two orthogonally polarized cavity photons. The entanglement fidelity with respect to the Bell state Ψ+ reaches F≥(91.9±2.5)%. This result represents an important step toward distributed quantum computing with cavities linking remote atom-based registers.

8. Photocopy of supplement to the Durango Herald, 1888. PORTION ...

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

8. Photocopy of supplement to the Durango Herald, 1888. PORTION OF DRAWING SHOWING DISTANT VIEW OF SAN JUAN SMELTING AND MINING COMPANY WORKS IN FOREGROUND, WITH EXTANT SMELTER STACK AT RIGHT AND CITY OF DURANGO IN BACKGROUND, LOOKING WEST. (Original in possession of Durango Public Library. Artist unknown.) - San Juan & New York Mining & Smelting Company, Smelter Stack, State Route 160, Durango, La Plata County, CO

Experimental protocol for high-fidelity heralded photon-to-atom quantum state transfer.

PubMed

Kurz, Christoph; Schug, Michael; Eich, Pascal; Huwer, Jan; Müller, Philipp; Eschner, Jürgen

2014-11-21

A quantum network combines the benefits of quantum systems regarding secure information transmission and calculational speed-up by employing quantum coherence and entanglement to store, transmit and process information. A promising platform for implementing such a network are atom-based quantum memories and processors, interconnected by photonic quantum channels. A crucial building block in this scenario is the conversion of quantum states between single photons and single atoms through controlled emission and absorption. Here we present an experimental protocol for photon-to-atom quantum state conversion, whereby the polarization state of an absorbed photon is mapped onto the spin state of a single absorbing atom with >95% fidelity, while successful conversion is heralded by a single emitted photon. Heralded high-fidelity conversion without affecting the converted state is a main experimental challenge, in order to make the transferred information reliably available for further operations. We record >80 s(-1) successful state transfer events out of 18,000 s(-1) repetitions.

Hybrid microfiber-lithium-niobate nanowaveguide structures as high-purity heralded single-photon sources

NASA Astrophysics Data System (ADS)

Main, Philip; Mosley, Peter J.; Ding, Wei; Zhang, Lijian; Gorbach, Andrey V.

2016-12-01

We propose a compact, fiber-integrated architecture for photon-pair generation by parametric downconversion with unprecedented flexibility in the properties of the photons produced. Our approach is based on a thin-film lithium niobate nanowaveguide, evanescently coupled to a tapered silica microfiber. We demonstrate how controllable mode hybridization between the fiber and waveguide yields control over the joint spectrum of the photon pairs. We also investigate how independent engineering of the linear and nonlinear properties of the structure can be achieved through the addition of a tapered, proton-exchanged layer to the waveguide. This allows further refinement of the joint spectrum through custom profiling of the effective nonlinearity, drastically improving the purity of the heralded photons. We give details of a source design capable of generating heralded single photons in the telecom wavelength range with purity of at least 0.95, and we provide a feasible fabrication methodology.

Secure Continuous Variable Teleportation and Einstein-Podolsky-Rosen Steering

NASA Astrophysics Data System (ADS)

He, Qiongyi; Rosales-Zárate, Laura; Adesso, Gerardo; Reid, Margaret D.

2015-10-01

We investigate the resources needed for secure teleportation of coherent states. We extend continuous variable teleportation to include quantum teleamplification protocols that allow nonunity classical gains and a preamplification or postattenuation of the coherent state. We show that, for arbitrary Gaussian protocols and a significant class of Gaussian resources, two-way steering is required to achieve a teleportation fidelity beyond the no-cloning threshold. This provides an operational connection between Gaussian steerability and secure teleportation. We present practical recipes suggesting that heralded noiseless preamplification may enable high-fidelity heralded teleportation, using minimally entangled yet steerable resources.

Heralded amplification of path entangled quantum states

NASA Astrophysics Data System (ADS)

Monteiro, F.; Verbanis, E.; Caprara Vivoli, V.; Martin, A.; Gisin, N.; Zbinden, H.; Thew, R. T.

2017-06-01

Device-independent quantum key distribution (DI-QKD) represents one of the most fascinating challenges in quantum communication, exploiting concepts of fundamental physics, namely Bell tests of nonlocality, to ensure the security of a communication link. This requires the loophole-free violation of a Bell inequality, which is intrinsically difficult due to losses in fibre optic transmission channels. Heralded photon amplification (HPA) is a teleportation-based protocol that has been proposed as a means to overcome transmission loss for DI-QKD. Here we demonstrate HPA for path entangled states and characterise the entanglement before and after loss by exploiting a recently developed displacement-based detection scheme. We demonstrate that by exploiting HPA we are able to reliably maintain high fidelity entangled states over loss-equivalent distances of more than 50 km.

Surpassing the no-cloning limit with a heralded hybrid linear amplifier for coherent states

PubMed Central

Haw, Jing Yan; Zhao, Jie; Dias, Josephine; Assad, Syed M.; Bradshaw, Mark; Blandino, Rémi; Symul, Thomas; Ralph, Timothy C.; Lam, Ping Koy

2016-01-01

The no-cloning theorem states that an unknown quantum state cannot be cloned exactly and deterministically due to the linearity of quantum mechanics. Associated with this theorem is the quantitative no-cloning limit that sets an upper bound to the quality of the generated clones. However, this limit can be circumvented by abandoning determinism and using probabilistic methods. Here, we report an experimental demonstration of probabilistic cloning of arbitrary coherent states that clearly surpasses the no-cloning limit. Our scheme is based on a hybrid linear amplifier that combines an ideal deterministic linear amplifier with a heralded measurement-based noiseless amplifier. We demonstrate the production of up to five clones with the fidelity of each clone clearly exceeding the corresponding no-cloning limit. Moreover, since successful cloning events are heralded, our scheme has the potential to be adopted in quantum repeater, teleportation and computing applications. PMID:27782135

Unilateral temporal myositis heralding polymyositis: ultrasonographic and elastographic findings. Case report.

PubMed

Damian, Laura; Botar Jid, Carolina; Rogojan, Liliana; Dinu, Cristian; Maniu, Alma; Fodor, Daniela; Rednic, Simona; Simon, Siao-Pin

2016-03-01

Temporal myositis is a rare inflammatory disease of the temporal muscle. We report a case of unilateral temporal myositis, in which a polymyositis was diagnosed two years thereafter. Although focal myositis may rarely herald polymyositis, isolated temporal myositis preceding inflammatory myopathies has not been described, to our knowledge. In the setting of a temporal pain and swelling, ultrasonography may help in diagnosis, biopsy guidance, disease extension, and progression assessment. Further studies are necessary to establish the role of elastography in differentiating between muscle inflammation and hypertrophy.

Engineering integrated photonics for heralded quantum gates

NASA Astrophysics Data System (ADS)

Meany, Thomas; Biggerstaff, Devon N.; Broome, Matthew A.; Fedrizzi, Alessandro; Delanty, Michael; Steel, M. J.; Gilchrist, Alexei; Marshall, Graham D.; White, Andrew G.; Withford, Michael J.

2016-06-01

Scaling up linear-optics quantum computing will require multi-photon gates which are compact, phase-stable, exhibit excellent quantum interference, and have success heralded by the detection of ancillary photons. We investigate the design, fabrication and characterisation of the optimal known gate scheme which meets these requirements: the Knill controlled-Z gate, implemented in integrated laser-written waveguide arrays. We show device performance to be less sensitive to phase variations in the circuit than to small deviations in the coupler reflectivity, which are expected given the tolerance values of the fabrication method. The mode fidelity is also shown to be less sensitive to reflectivity and phase errors than the process fidelity. Our best device achieves a fidelity of 0.931 ± 0.001 with the ideal 4 × 4 unitary circuit and a process fidelity of 0.680 ± 0.005 with the ideal computational-basis process.

Engineering integrated photonics for heralded quantum gates

PubMed Central

Meany, Thomas; Biggerstaff, Devon N.; Broome, Matthew A.; Fedrizzi, Alessandro; Delanty, Michael; Steel, M. J.; Gilchrist, Alexei; Marshall, Graham D.; White, Andrew G.; Withford, Michael J.

2016-01-01

Scaling up linear-optics quantum computing will require multi-photon gates which are compact, phase-stable, exhibit excellent quantum interference, and have success heralded by the detection of ancillary photons. We investigate the design, fabrication and characterisation of the optimal known gate scheme which meets these requirements: the Knill controlled-Z gate, implemented in integrated laser-written waveguide arrays. We show device performance to be less sensitive to phase variations in the circuit than to small deviations in the coupler reflectivity, which are expected given the tolerance values of the fabrication method. The mode fidelity is also shown to be less sensitive to reflectivity and phase errors than the process fidelity. Our best device achieves a fidelity of 0.931 ± 0.001 with the ideal 4 × 4 unitary circuit and a process fidelity of 0.680 ± 0.005 with the ideal computational-basis process. PMID:27282928

Engineering integrated photonics for heralded quantum gates.

PubMed

Meany, Thomas; Biggerstaff, Devon N; Broome, Matthew A; Fedrizzi, Alessandro; Delanty, Michael; Steel, M J; Gilchrist, Alexei; Marshall, Graham D; White, Andrew G; Withford, Michael J

2016-06-10

Scaling up linear-optics quantum computing will require multi-photon gates which are compact, phase-stable, exhibit excellent quantum interference, and have success heralded by the detection of ancillary photons. We investigate the design, fabrication and characterisation of the optimal known gate scheme which meets these requirements: the Knill controlled-Z gate, implemented in integrated laser-written waveguide arrays. We show device performance to be less sensitive to phase variations in the circuit than to small deviations in the coupler reflectivity, which are expected given the tolerance values of the fabrication method. The mode fidelity is also shown to be less sensitive to reflectivity and phase errors than the process fidelity. Our best device achieves a fidelity of 0.931 ± 0.001 with the ideal 4 × 4 unitary circuit and a process fidelity of 0.680 ± 0.005 with the ideal computational-basis process.

Heralded quantum steering over a high-loss channel.

PubMed

Weston, Morgan M; Slussarenko, Sergei; Chrzanowski, Helen M; Wollmann, Sabine; Shalm, Lynden K; Verma, Varun B; Allman, Michael S; Nam, Sae Woo; Pryde, Geoff J

2018-01-01

Entanglement is the key resource for many long-range quantum information tasks, including secure communication and fundamental tests of quantum physics. These tasks require robust verification of shared entanglement, but performing it over long distances is presently technologically intractable because the loss through an optical fiber or free-space channel opens up a detection loophole. We design and experimentally demonstrate a scheme that verifies entanglement in the presence of at least 14.8 ± 0.1 dB of added loss, equivalent to approximately 80 km of telecommunication fiber. Our protocol relies on entanglement swapping to herald the presence of a photon after the lossy channel, enabling event-ready implementation of quantum steering. This result overcomes the key barrier in device-independent communication under realistic high-loss scenarios and in the realization of a quantum repeater.

Heralded quantum steering over a high-loss channel

PubMed Central

Weston, Morgan M.; Slussarenko, Sergei; Chrzanowski, Helen M.; Wollmann, Sabine; Shalm, Lynden K.; Verma, Varun B.; Allman, Michael S.; Nam, Sae Woo; Pryde, Geoff J.

2018-01-01

Entanglement is the key resource for many long-range quantum information tasks, including secure communication and fundamental tests of quantum physics. These tasks require robust verification of shared entanglement, but performing it over long distances is presently technologically intractable because the loss through an optical fiber or free-space channel opens up a detection loophole. We design and experimentally demonstrate a scheme that verifies entanglement in the presence of at least 14.8 ± 0.1 dB of added loss, equivalent to approximately 80 km of telecommunication fiber. Our protocol relies on entanglement swapping to herald the presence of a photon after the lossy channel, enabling event-ready implementation of quantum steering. This result overcomes the key barrier in device-independent communication under realistic high-loss scenarios and in the realization of a quantum repeater. PMID:29322093

76 FR 46854 - Wausau Daily Herald, Advertising Production Division, a Subsidiary of Gannett Co., Inc.,Wausau...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-03

..., Advertising Production Division, a Subsidiary of Gannett Co., Inc.,Wausau, WI; Notice of Negative...) applicable to workers and former workers of Wausau Daily Herald, Advertising Production Division, a... information revealed that 2AdPro (an advertising firm located in India) handled an insignificant amount of...

Heralded quantum repeater based on the scattering of photons off single emitters using parametric down-conversion source.

PubMed

Song, Guo-Zhu; Wu, Fang-Zhou; Zhang, Mei; Yang, Guo-Jian

2016-06-28

Quantum repeater is the key element in quantum communication and quantum information processing. Here, we investigate the possibility of achieving a heralded quantum repeater based on the scattering of photons off single emitters in one-dimensional waveguides. We design the compact quantum circuits for nonlocal entanglement generation, entanglement swapping, and entanglement purification, and discuss the feasibility of our protocols with current experimental technology. In our scheme, we use a parametric down-conversion source instead of ideal single-photon sources to realize the heralded quantum repeater. Moreover, our protocols can turn faulty events into the detection of photon polarization, and the fidelity can reach 100% in principle. Our scheme is attractive and scalable, since it can be realized with artificial solid-state quantum systems. With developed experimental technique on controlling emitter-waveguide systems, the repeater may be very useful in long-distance quantum communication.

Heralded quantum repeater based on the scattering of photons off single emitters using parametric down-conversion source

PubMed Central

Song, Guo-Zhu; Wu, Fang-Zhou; Zhang, Mei; Yang, Guo-Jian

2016-01-01

Quantum repeater is the key element in quantum communication and quantum information processing. Here, we investigate the possibility of achieving a heralded quantum repeater based on the scattering of photons off single emitters in one-dimensional waveguides. We design the compact quantum circuits for nonlocal entanglement generation, entanglement swapping, and entanglement purification, and discuss the feasibility of our protocols with current experimental technology. In our scheme, we use a parametric down-conversion source instead of ideal single-photon sources to realize the heralded quantum repeater. Moreover, our protocols can turn faulty events into the detection of photon polarization, and the fidelity can reach 100% in principle. Our scheme is attractive and scalable, since it can be realized with artificial solid-state quantum systems. With developed experimental technique on controlling emitter-waveguide systems, the repeater may be very useful in long-distance quantum communication. PMID:27350159

The Founding of the Penny Press: Nothing New under "The Sun,""The Herald," or "The Tribune."

ERIC Educational Resources Information Center

Williams, Julie Hedgepeth

While the founders of the penny press did not set out to establish a truer form of journalism, they did popularize both low prices for newspapers and newspaper economics based on sales instead of political party backing. The history of "The Sun,""The Herald," and "The Tribune" disprove the idea (advanced by journalism…

Integrated-optics heralded controlled-NOT gate for polarization-encoded qubits

NASA Astrophysics Data System (ADS)

Zeuner, Jonas; Sharma, Aditya N.; Tillmann, Max; Heilmann, René; Gräfe, Markus; Moqanaki, Amir; Szameit, Alexander; Walther, Philip

2018-03-01

Recent progress in integrated-optics technology has made photonics a promising platform for quantum networks and quantum computation protocols. Integrated optical circuits are characterized by small device footprints and unrivalled intrinsic interferometric stability. Here, we take advantage of femtosecond-laser-written waveguides' ability to process polarization-encoded qubits and present an implementation of a heralded controlled-NOT gate on chip. We evaluate the gate performance in the computational basis and a superposition basis, showing that the gate can create polarization entanglement between two photons. Transmission through the integrated device is optimized using thermally expanded core fibers and adiabatically reduced mode-field diameters at the waveguide facets. This demonstration underlines the feasibility of integrated quantum gates for all-optical quantum networks and quantum repeaters.

Multi-photon absorption limits to heralded single photon sources

PubMed Central

Husko, Chad A.; Clark, Alex S.; Collins, Matthew J.; De Rossi, Alfredo; Combrié, Sylvain; Lehoucq, Gaëlle; Rey, Isabella H.; Krauss, Thomas F.; Xiong, Chunle; Eggleton, Benjamin J.

2013-01-01

Single photons are of paramount importance to future quantum technologies, including quantum communication and computation. Nonlinear photonic devices using parametric processes offer a straightforward route to generating photons, however additional nonlinear processes may come into play and interfere with these sources. Here we analyse spontaneous four-wave mixing (SFWM) sources in the presence of multi-photon processes. We conduct experiments in silicon and gallium indium phosphide photonic crystal waveguides which display inherently different nonlinear absorption processes, namely two-photon (TPA) and three-photon absorption (ThPA), respectively. We develop a novel model capturing these diverse effects which is in excellent quantitative agreement with measurements of brightness, coincidence-to-accidental ratio (CAR) and second-order correlation function g(2)(0), showing that TPA imposes an intrinsic limit on heralded single photon sources. We build on these observations to devise a new metric, the quantum utility (QMU), enabling further optimisation of single photon sources. PMID:24186400

High heralding-efficiency of near-IR fiber coupled photon pairs for quantum technologies

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

Dixon, P. Ben; Murphy, Ryan; Rosenberg, Danna

We report on the development and use of a high heralding-efficiency, single-mode-fiber coupled telecom-band source of entangled photons for quantum technology applications. The source development efforts consisted of theoretical and experimental efforts and we demonstrated a correlated-mode coupling efficiency of 97% 2%, the highest efficiency yet achieved for this type of system. We then incorporated these beneficial source development techniques in a Sagnac configured telecom-band entangled photon source that generates photon pairs entangled in both time/energy and polarization degrees of freedom. We made use of these highly desirable entangled states to investigate several promising quantum technologies.

Heralded entangling quantum gate via cavity-assisted photon scattering

NASA Astrophysics Data System (ADS)

Borges, Halyne S.; Rossatto, Daniel Z.; Luiz, Fabrício S.; Villas-Boas, Celso J.

2018-01-01

We theoretically investigate the generation of heralded entanglement between two identical atoms via cavity-assisted photon scattering in two different configurations, namely, either both atoms confined in the same cavity or trapped into locally separated ones. Our protocols are given by a very simple and elegant single-step process, the key mechanism of which is a controlled-phase-flip gate implemented by impinging a single photon on single-sided cavities. In particular, when the atoms are localized in remote cavities, we introduce a single-step parallel quantum circuit instead of the serial process extensively adopted in the literature. We also show that such parallel circuit can be straightforwardly applied to entangle two macroscopic clouds of atoms. Both protocols proposed here predict a high entanglement degree with a success probability close to unity for state-of-the-art parameters. Among other applications, our proposal and its extension to multiple atom-cavity systems step toward a suitable route for quantum networking, in particular for quantum state transfer, quantum teleportation, and nonlocal quantum memory.

Realization of a Cascaded Quantum System: Heralded Absorption of a Single Photon Qubit by a Single-Electron Charged Quantum Dot.

PubMed

Delteil, Aymeric; Sun, Zhe; Fält, Stefan; Imamoğlu, Atac

2017-04-28

Photonic losses pose a major limitation for the implementation of a quantum state transfer between nodes of a quantum network. A measurement that heralds a successful transfer without revealing any information about the qubit may alleviate this limitation. Here, we demonstrate the heralded absorption of a single photonic qubit, generated by a single neutral quantum dot, by a single-electron charged quantum dot that is located 5 m away. The transfer of quantum information to the spin degree of freedom takes place upon the emission of a photon; for a properly chosen or prepared quantum dot, the detection of this photon yields no information about the qubit. We show that this process can be combined with local operations optically performed on the destination node by measuring classical correlations between the absorbed photon color and the final state of the electron spin. Our work suggests alternative avenues for the realization of quantum information protocols based on cascaded quantum systems.

On the nature and origin of water masses in Herald Canyon, Chukchi Sea: Synoptic surveys in summer 2004, 2008, and 2009

NASA Astrophysics Data System (ADS)

Linders, Johanna; Pickart, Robert. S.; Björk, Göran; Moore, G. W. K.

2017-12-01

Hydrographic and velocity data from three high-resolution shipboard surveys of Herald Canyon in the northwest Chukchi Sea, in 2004, 2008, and 2009, are used to investigate the water masses in the canyon and their possible source regions. Both summer and winter Pacific waters were observed in varying amounts in the different years, although in general the summer waters resided on the eastern side of the canyon while the winter waters were located on the western flank. The predominant summer water was Bering summer water, although some Alaskan coastal water resided in the canyon in the two later years likely due to wind forcing. Both newly ventilated and remnant winter waters were found in the canyon, but the amount lessened in each successive survey. Using mooring data from Bering Strait it is shown that a large amount of Bering summer water in the western channel of the strait follows a relatively direct route into Herald Canyon during the summer months, with an estimated advective speed of 10-20 cm/s. However, while the winter water observed in 2004 was consistent with a Bering Strait source (with a slower advective speed of 5-8 cm/s), the dense water in the canyon during 2008 and 2009 was more in line with a northern source. This is consistent with sections to the west of the canyon and with previously reported measurements implying winter water formation on the East Siberian shelf. Large-scale wind patterns and polynya activity on the shelf are also investigated. It was found that the former appears to impact more strongly the presence of dense water in Herald Canyon.

Holocene Ostracoda from the Herald Canyon, Eastern Siberian Sea from the SWERUS-C3 Expedition 2014

NASA Astrophysics Data System (ADS)

Gemery, L.; Cronin, T. M.; Jakobsson, M.; Barrientos, N.; O'Regan, M.; Muschitiello, F.; Koshurnikov, A.; Gukov, A.

2015-12-01

We analyzed Arctic benthic ostracode assemblages from two piston cores (PC) and their complementary multicores from Herald Canyon in the Eastern Siberian Sea. The cores (SWERUS-L2-2-PC1 [8.1 m], 2-MUC4, 71.7 m water depth, and SWERUS-L2-4-PC1 [6.2 m], 4-MUC4, 119.7 m water depth) were collected during Leg 2 of the 2014 SWERUS-C3 Expedition. Radiocarbon dates on mollusks indicate that sediments from 2-PC1 and 4-PC1 were deposited over the last 5,000 and 10,000 years respectively. The dominant ostracode species include: Acanthocythereis dunelmensis, Cytheropteron elaeni, Elofsonella concinna, Kotoracythere janae, Normanicythere leioderma, Semicytherura complanata. Based on species' distributions obtained from a 1,200-sample modern ostracode database, these species are known to be typical of shallow mid- to outer-continental shelf environments in the modern Arctic Ocean. The abundant and diverse benthic ostracode assemblages found in these cores suggest the influence of nutrient-rich Pacific water flowing in through the Bering Strait. The faunal assemblages are fairly uniform throughout 2-PC1, suggesting minimal variability in Pacific water inflow since at least 5 ka. In the lower section of 4-PC1, there is a major change to ostracode assemblages containing typical inner shelf, often brackish-water species, such as Cytheromorpha macchesneyi, and associated shallow Arctic shelf species (Sarsicytheridea punctillata and several Cytheropteron species), reflecting a period of lower, deglacial sea level.

Heralded entanglement between solid-state qubits separated by three metres.

PubMed

Bernien, H; Hensen, B; Pfaff, W; Koolstra, G; Blok, M S; Robledo, L; Taminiau, T H; Markham, M; Twitchen, D J; Childress, L; Hanson, R

2013-05-02

Quantum entanglement between spatially separated objects is one of the most intriguing phenomena in physics. The outcomes of independent measurements on entangled objects show correlations that cannot be explained by classical physics. As well as being of fundamental interest, entanglement is a unique resource for quantum information processing and communication. Entangled quantum bits (qubits) can be used to share private information or implement quantum logical gates. Such capabilities are particularly useful when the entangled qubits are spatially separated, providing the opportunity to create highly connected quantum networks or extend quantum cryptography to long distances. Here we report entanglement of two electron spin qubits in diamond with a spatial separation of three metres. We establish this entanglement using a robust protocol based on creation of spin-photon entanglement at each location and a subsequent joint measurement of the photons. Detection of the photons heralds the projection of the spin qubits onto an entangled state. We verify the resulting non-local quantum correlations by performing single-shot readout on the qubits in different bases. The long-distance entanglement reported here can be combined with recently achieved initialization, readout and entanglement operations on local long-lived nuclear spin registers, paving the way for deterministic long-distance teleportation, quantum repeaters and extended quantum networks.

Variable Screening for Cluster Analysis.

ERIC Educational Resources Information Center

Donoghue, John R.

Inclusion of irrelevant variables in a cluster analysis adversely affects subgroup recovery. This paper examines using moment-based statistics to screen variables; only variables that pass the screening are then used in clustering. Normal mixtures are analytically shown often to possess negative kurtosis. Two related measures, "m" and…

Heralded creation of photonic qudits from parametric down-conversion using linear optics

NASA Astrophysics Data System (ADS)

Yoshikawa, Jun-ichi; Bergmann, Marcel; van Loock, Peter; Fuwa, Maria; Okada, Masanori; Takase, Kan; Toyama, Takeshi; Makino, Kenzo; Takeda, Shuntaro; Furusawa, Akira

2018-05-01

We propose an experimental scheme to generate, in a heralded fashion, arbitrary quantum superpositions of two-mode optical states with a fixed total photon number n based on weakly squeezed two-mode squeezed state resources (obtained via weak parametric down-conversion), linear optics, and photon detection. Arbitrary d -level (qudit) states can be created this way where d =n +1 . Furthermore, we experimentally demonstrate our scheme for n =2 . The resulting qutrit states are characterized via optical homodyne tomography. We also discuss possible extensions to more than two modes concluding that, in general, our approach ceases to work in this case. For illustration and with regards to possible applications, we explicitly calculate a few examples such as NOON states and logical qubit states for quantum error correction. In particular, our approach enables one to construct bosonic qubit error-correction codes against amplitude damping (photon loss) with a typical suppression of √{n }-1 losses and spanned by two logical codewords that each correspond to an n -photon superposition for two bosonic modes.

Telecom-Wavelength Atomic Quantum Memory in Optical Fiber for Heralded Polarization Qubits.

PubMed

Jin, Jeongwan; Saglamyurek, Erhan; Puigibert, Marcel lí Grimau; Verma, Varun; Marsili, Francesco; Nam, Sae Woo; Oblak, Daniel; Tittel, Wolfgang

2015-10-02

Polarization-encoded photons at telecommunication wavelengths provide a compelling platform for practical realizations of photonic quantum information technologies due to the ease of performing single qubit manipulations, the availability of polarization-entangled photon-pair sources, and the possibility of leveraging existing fiber-optic links for distributing qubits over long distances. An optical quantum memory compatible with this platform could serve as a building block for these technologies. Here we present the first experimental demonstration of an atomic quantum memory that directly allows for reversible mapping of quantum states encoded in the polarization degree of freedom of a telecom-wavelength photon. We show that heralded polarization qubits at a telecom wavelength are stored and retrieved with near-unity fidelity by implementing the atomic frequency comb protocol in an ensemble of erbium atoms doped into an optical fiber. Despite remaining limitations in our proof-of-principle demonstration such as small storage efficiency and storage time, our broadband light-matter interface reveals the potential for use in future quantum information processing.

A study of the Herald-Phillipstown fault in the Wabash Valley using drillhole and 3-D seismic reflection data

NASA Astrophysics Data System (ADS)

Kroenke, Samantha E.

In June 2009, a 2.2 square mile 3-D high resolution seismic reflection survey was shot in southeastern Illinois in the Phillipstown Consolidated oilfield. A well was drilled in the 3-D survey area to tie the seismic to the geological data with a synthetic seismogram from the sonic log. The objectives of the 3-D seismic survey were three-fold: (1) To image and interpret faulting of the Herald-Phillipstown Fault using drillhole-based geological and seismic cross-sections and structural contour maps created from the drillhole data and seismic reflection data, (2) To test the effectiveness of imaging the faults by selected seismic attributes, and (3) To compare spectral decomposition amplitude maps with an isochron map and an isopach map of a selected geologic interval (VTG interval). Drillhole and seismic reflection data show that various formation offsets increase near the main Herald-Phillipstown fault, and that the fault and its large offset subsidiary faults penetrate the Precambrian crystalline basement. A broad, northeast-trending 10,000 feet wide graben is consistently observed in the drillhole data. Both shallow and deep formations in the geological cross-sections reveal small horst and graben features within the broad graben created possibly in response to fault reactivations. The HPF faults have been interpreted as originally Precambrian age high-angle, normal faults reactivated with various amounts and types of offset. Evidence for strike-slip movement is also clear on several faults. Changes in the seismic attribute values in the selected interval and along various time slices throughout the whole dataset correlate with the Herald-Phillipstown faults. Overall, seismic attributes could provide a means of mapping large offset faults in areas with limited or absent drillhole data. Results of the spectral decomposition suggest that if the interval velocity is known for a particular formation or interval, high-resolution 3-D seismic reflection surveys could

Round-robin differential-phase-shift quantum key distribution with heralded pair-coherent sources

NASA Astrophysics Data System (ADS)

Wang, Le; Zhao, Shengmei

2017-04-01

Round-robin differential-phase-shift (RRDPS) quantum key distribution (QKD) scheme provides an effective way to overcome the signal disturbance from the transmission process. However, most RRDPS-QKD schemes use weak coherent pulses (WCPs) as the replacement of the perfect single-photon source. Considering the heralded pair-coherent source (HPCS) can efficiently remove the shortcomings of WCPs, we propose a RRDPS-QKD scheme with HPCS in this paper. Both infinite-intensity decoy-state method and practical three-intensity decoy-state method are adopted to discuss the tight bound of the key rate of the proposed scheme. The results show that HPCS is a better candidate for the replacement of the perfect single-photon source, and both the key rate and the transmission distance are greatly increased in comparison with those results with WCPs when the length of the pulse trains is small. Simultaneously, the performance of the proposed scheme using three-intensity decoy states is close to that result using infinite-intensity decoy states when the length of pulse trains is small.

Heralded wave packet manipulation and storage of a frequency-converted pair photon at telecom wavelength

NASA Astrophysics Data System (ADS)

Kroh, Tim; Ahlrichs, Andreas; Sprenger, Benjamin; Benson, Oliver

2017-09-01

Future quantum networks require a hybrid platform of dissimilar quantum systems. Within the platform, joint quantum states have to be mediated either by single photons, photon pairs or entangled photon pairs. The photon wavelength has to lie within the telecommunication band to enable long-distance fibre transmission. In addition, the temporal shape of the photons needs to be tailored to efficiently match the involved quantum systems. Altogether, this requires the efficient coherent wavelength-conversion of arbitrarily shaped single-photon wave packets. Here, we demonstrate the heralded temporal filtering of single photons as well as the synchronisation of state manipulation and detection as key elements in a typical experiment, besides of delaying a photon in a long fibre. All three are realised by utilising commercial telecommunication fibre-optical components which will permit the transition of quantum networks from the lab to real-world applications. The combination of these renders a temporally filtering single-photon storage in a fast switchable fibre loop possible.

Towards a heralded eigenstate-preserving measurement of multi-qubit parity in circuit QED

NASA Astrophysics Data System (ADS)

Huembeli, Patrick; Nigg, Simon E.

2017-07-01

Eigenstate-preserving multi-qubit parity measurements lie at the heart of stabilizer quantum error correction, which is a promising approach to mitigate the problem of decoherence in quantum computers. In this work we explore a high-fidelity, eigenstate-preserving parity readout for superconducting qubits dispersively coupled to a microwave resonator, where the parity bit is encoded in the amplitude of a coherent state of the resonator. Detecting photons emitted by the resonator via a current biased Josephson junction yields information about the parity bit. We analyze theoretically the measurement back action in the limit of a strongly coupled fast detector and show that in general such a parity measurement, while approximately quantum nondemolition is not eigenstate preserving. To remediate this shortcoming we propose a simple dynamical decoupling technique during photon detection, which greatly reduces decoherence within a given parity subspace. Furthermore, by applying a sequence of fast displacement operations interleaved with the dynamical decoupling pulses, the natural bias of this binary detector can be efficiently suppressed. Finally, we introduce the concept of a heralded parity measurement, where a detector click guarantees successful multi-qubit parity detection even for finite detection efficiency.

Heralded quantum repeater based on the scattering of photons off single emitters in one-dimensional waveguides

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

Song, Guo-Zhu; Zhang, Mei; Ai, Qing

We propose a heralded quantum repeater based on the scattering of photons off single emitters in one-dimensional waveguides. We show the details by implementing nonlocal entanglement generation, entanglement swapping, and entanglement purification modules with atoms in waveguides, and discuss the feasibility of the repeater with currently achievable technology. In our scheme, the faulty events can be discarded by detecting the polarization of the photons. That is, our protocols are accomplished with a fidelity of 100% in principle, which is advantageous for implementing realistic long-distance quantum communication. Moreover, additional atomic qubits are not required, but only a single-photon medium. Our schememore » is scalable and attractive since it can be realized in solid-state quantum systems. With the great progress on controlling atom-waveguide systems, the repeater may be very useful in quantum information processing in the future.« less

Improving the maximum transmission distance of continuous-variable quantum key distribution using a noiseless amplifier

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

Blandino, Rémi; Etesse, Jean; Grangier, Philippe

2014-12-04

We show that the maximum transmission distance of continuous-variable quantum key distribution in presence of a Gaussian noisy lossy channel can be arbitrarily increased using a heralded noiseless linear amplifier. We explicitly consider a protocol using amplitude and phase modulated coherent states with reverse reconciliation. Assuming that the secret key rate drops to zero for a line transmittance T{sub lim}, we find that a noiseless amplifier with amplitude gain g can improve this value to T{sub lim}/g{sup 2}, corresponding to an increase in distance proportional to log g. We also show that the tolerance against noise is increased.

Regression Analysis with Dummy Variables: Use and Interpretation.

ERIC Educational Resources Information Center

Hinkle, Dennis E.; Oliver, J. Dale

1986-01-01

Multiple regression analysis (MRA) may be used when both continuous and categorical variables are included as independent research variables. The use of MRA with categorical variables involves dummy coding, that is, assigning zeros and ones to levels of categorical variables. Caution is urged in results interpretation. (Author/CH)

Power calculator for instrumental variable analysis in pharmacoepidemiology

PubMed Central

Walker, Venexia M; Davies, Neil M; Windmeijer, Frank; Burgess, Stephen; Martin, Richard M

2017-01-01

Abstract Background Instrumental variable analysis, for example with physicians’ prescribing preferences as an instrument for medications issued in primary care, is an increasingly popular method in the field of pharmacoepidemiology. Existing power calculators for studies using instrumental variable analysis, such as Mendelian randomization power calculators, do not allow for the structure of research questions in this field. This is because the analysis in pharmacoepidemiology will typically have stronger instruments and detect larger causal effects than in other fields. Consequently, there is a need for dedicated power calculators for pharmacoepidemiological research. Methods and Results The formula for calculating the power of a study using instrumental variable analysis in the context of pharmacoepidemiology is derived before being validated by a simulation study. The formula is applicable for studies using a single binary instrument to analyse the causal effect of a binary exposure on a continuous outcome. An online calculator, as well as packages in both R and Stata, are provided for the implementation of the formula by others. Conclusions The statistical power of instrumental variable analysis in pharmacoepidemiological studies to detect a clinically meaningful treatment effect is an important consideration. Research questions in this field have distinct structures that must be accounted for when calculating power. The formula presented differs from existing instrumental variable power formulae due to its parametrization, which is designed specifically for ease of use by pharmacoepidemiologists. PMID:28575313

Biased three-intensity decoy-state scheme on the measurement-device-independent quantum key distribution using heralded single-photon sources.

PubMed

Zhang, Chun-Hui; Zhang, Chun-Mei; Guo, Guang-Can; Wang, Qin

2018-02-19

At present, most of the measurement-device-independent quantum key distributions (MDI-QKD) are based on weak coherent sources and limited in the transmission distance under realistic experimental conditions, e.g., considering the finite-size-key effects. Hence in this paper, we propose a new biased decoy-state scheme using heralded single-photon sources for the three-intensity MDI-QKD, where we prepare the decoy pulses only in X basis and adopt both the collective constraints and joint parameter estimation techniques. Compared with former schemes with WCS or HSPS, after implementing full parameter optimizations, our scheme gives distinct reduced quantum bit error rate in the X basis and thus show excellent performance, especially when the data size is relatively small.

Heralded high-efficiency quantum repeater with atomic ensembles assisted by faithful single-photon transmission

NASA Astrophysics Data System (ADS)

Li, Tao; Deng, Fu-Guo

2015-10-01

Quantum repeater is one of the important building blocks for long distance quantum communication network. The previous quantum repeaters based on atomic ensembles and linear optical elements can only be performed with a maximal success probability of 1/2 during the entanglement creation and entanglement swapping procedures. Meanwhile, the polarization noise during the entanglement distribution process is harmful to the entangled channel created. Here we introduce a general interface between a polarized photon and an atomic ensemble trapped in a single-sided optical cavity, and with which we propose a high-efficiency quantum repeater protocol in which the robust entanglement distribution is accomplished by the stable spatial-temporal entanglement and it can in principle create the deterministic entanglement between neighboring atomic ensembles in a heralded way as a result of cavity quantum electrodynamics. Meanwhile, the simplified parity-check gate makes the entanglement swapping be completed with unity efficiency, other than 1/2 with linear optics. We detail the performance of our protocol with current experimental parameters and show its robustness to the imperfections, i.e., detuning and coupling variation, involved in the reflection process. These good features make it a useful building block in long distance quantum communication.

Heralded high-efficiency quantum repeater with atomic ensembles assisted by faithful single-photon transmission.

PubMed

Li, Tao; Deng, Fu-Guo

2015-10-27

Quantum repeater is one of the important building blocks for long distance quantum communication network. The previous quantum repeaters based on atomic ensembles and linear optical elements can only be performed with a maximal success probability of 1/2 during the entanglement creation and entanglement swapping procedures. Meanwhile, the polarization noise during the entanglement distribution process is harmful to the entangled channel created. Here we introduce a general interface between a polarized photon and an atomic ensemble trapped in a single-sided optical cavity, and with which we propose a high-efficiency quantum repeater protocol in which the robust entanglement distribution is accomplished by the stable spatial-temporal entanglement and it can in principle create the deterministic entanglement between neighboring atomic ensembles in a heralded way as a result of cavity quantum electrodynamics. Meanwhile, the simplified parity-check gate makes the entanglement swapping be completed with unity efficiency, other than 1/2 with linear optics. We detail the performance of our protocol with current experimental parameters and show its robustness to the imperfections, i.e., detuning and coupling variation, involved in the reflection process. These good features make it a useful building block in long distance quantum communication.

Influence of ECG sampling rate in fetal heart rate variability analysis.

PubMed

De Jonckheere, J; Garabedian, C; Charlier, P; Champion, C; Servan-Schreiber, E; Storme, L; Debarge, V; Jeanne, M; Logier, R

2017-07-01

Fetal hypoxia results in a fetal blood acidosis (pH<;7.10). In such a situation, the fetus develops several adaptation mechanisms regulated by the autonomic nervous system. Many studies demonstrated significant changes in heart rate variability in hypoxic fetuses. So, fetal heart rate variability analysis could be of precious help for fetal hypoxia prediction. Commonly used fetal heart rate variability analysis methods have been shown to be sensitive to the ECG signal sampling rate. Indeed, a low sampling rate could induce variability in the heart beat detection which will alter the heart rate variability estimation. In this paper, we introduce an original fetal heart rate variability analysis method. We hypothesize that this method will be less sensitive to ECG sampling frequency changes than common heart rate variability analysis methods. We then compared the results of this new heart rate variability analysis method with two different sampling frequencies (250-1000 Hz).

Complex systems and the technology of variability analysis

PubMed Central

Seely, Andrew JE; Macklem, Peter T

2004-01-01

Characteristic patterns of variation over time, namely rhythms, represent a defining feature of complex systems, one that is synonymous with life. Despite the intrinsic dynamic, interdependent and nonlinear relationships of their parts, complex biological systems exhibit robust systemic stability. Applied to critical care, it is the systemic properties of the host response to a physiological insult that manifest as health or illness and determine outcome in our patients. Variability analysis provides a novel technology with which to evaluate the overall properties of a complex system. This review highlights the means by which we scientifically measure variation, including analyses of overall variation (time domain analysis, frequency distribution, spectral power), frequency contribution (spectral analysis), scale invariant (fractal) behaviour (detrended fluctuation and power law analysis) and regularity (approximate and multiscale entropy). Each technique is presented with a definition, interpretation, clinical application, advantages, limitations and summary of its calculation. The ubiquitous association between altered variability and illness is highlighted, followed by an analysis of how variability analysis may significantly improve prognostication of severity of illness and guide therapeutic intervention in critically ill patients. PMID:15566580

Review and classification of variability analysis techniques with clinical applications.

PubMed

Bravi, Andrea; Longtin, André; Seely, Andrew J E

2011-10-10

Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis.

Review and classification of variability analysis techniques with clinical applications

PubMed Central

2011-01-01

Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis. PMID:21985357

VStar: Variable star data visualization and analysis tool

NASA Astrophysics Data System (ADS)

VStar Team

2014-07-01

VStar is a multi-platform, easy-to-use variable star data visualization and analysis tool. Data for a star can be read from the AAVSO (American Association of Variable Star Observers) database or from CSV and TSV files. VStar displays light curves and phase plots, can produce a mean curve, and analyzes time-frequency with Weighted Wavelet Z-Transform. It offers tools for period analysis, filtering, and other functions.

Heralded high-efficiency quantum repeater with atomic ensembles assisted by faithful single-photon transmission

PubMed Central

Li, Tao; Deng, Fu-Guo

2015-01-01

Quantum repeater is one of the important building blocks for long distance quantum communication network. The previous quantum repeaters based on atomic ensembles and linear optical elements can only be performed with a maximal success probability of 1/2 during the entanglement creation and entanglement swapping procedures. Meanwhile, the polarization noise during the entanglement distribution process is harmful to the entangled channel created. Here we introduce a general interface between a polarized photon and an atomic ensemble trapped in a single-sided optical cavity, and with which we propose a high-efficiency quantum repeater protocol in which the robust entanglement distribution is accomplished by the stable spatial-temporal entanglement and it can in principle create the deterministic entanglement between neighboring atomic ensembles in a heralded way as a result of cavity quantum electrodynamics. Meanwhile, the simplified parity-check gate makes the entanglement swapping be completed with unity efficiency, other than 1/2 with linear optics. We detail the performance of our protocol with current experimental parameters and show its robustness to the imperfections, i.e., detuning and coupling variation, involved in the reflection process. These good features make it a useful building block in long distance quantum communication. PMID:26502993

Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.

PubMed

Cleophas, Ton J

2016-01-01

Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis

ERIC Educational Resources Information Center

Brusco, Michael J.; Singh, Renu; Steinley, Douglas

2009-01-01

The selection of a subset of variables from a pool of candidates is an important problem in several areas of multivariate statistics. Within the context of principal component analysis (PCA), a number of authors have argued that subset selection is crucial for identifying those variables that are required for correct interpretation of the…

Generation of heralded entanglement between distant quantum dot hole spins

NASA Astrophysics Data System (ADS)

Delteil, Aymeric

Entanglement plays a central role in fundamental tests of quantum mechanics as well as in the burgeoning field of quantum information processing. Particularly in the context of quantum networks and communication, some of the major challenges are the efficient generation of entanglement between stationary (spin) and propagating (photon) qubits, the transfer of information from flying to stationary qubits, and the efficient generation of entanglement between distant stationary (spin) qubits. In this talk, I will present such experimental implementations achieved in our team with semiconductor self-assembled quantum dots.Not only are self-assembled quantum dots good single-photon emitters, but they can host an electron or a hole whose spin serves as a quantum memory, and then present spin-dependent optical selection rules leading to an efficient spin-photon quantum interface. Moreover InGaAs quantum dots grown on GaAs substrate can profit from the maturity of III-V semiconductor technology and can be embedded in semiconductor structures like photonic cavities and Schottky diodes.I will report on the realization of heralded quantum entanglement between two semiconductor quantum dot hole spins separated by more than five meters. The entanglement generation scheme relies on single photon interference of Raman scattered light from both dots. A single photon detection projects the system into a maximally entangled state. We developed a delayed two-photon interference scheme that allows for efficient verification of quantum correlations. Moreover the efficient spin-photon interface provided by self-assembled quantum dots allows us to reach an unprecedented rate of 2300 entangled spin pairs per second, which represents an improvement of four orders of magnitude as compared to prior experiments carried out in other systems.Our results extend previous demonstrations in single trapped ions or neutral atoms, in atom ensembles and nitrogen vacancy centers to the domain of

[Quantitative analysis of drug expenditures variability in dermatology units].

PubMed

Moreno-Ramírez, David; Ferrándiz, Lara; Ramírez-Soto, Gabriel; Muñoyerro, M Dolores

2013-01-01

Variability in adjusted drug expenditures among clinical departments raises the possibility of difficult access to certain therapies at the time that avoidable expenditures may also exist. Nevertheless, drug expenditures are not usually applied to clinical practice variability analysis. To identify and quantify variability in drug expenditures in comparable dermatology department of the Servicio Andaluz de Salud. Comparative economic analysis regarding the drug expenditures adjusted to population and health care production in 18 dermatology departments of the Servicio Andaluz de Salud. The 2012 cost and production data (homogeneous production units -HPU-)were provided by Inforcoan, the cost accounting information system of the Servicio Andaluz de Salud. The observed drug expenditure ratio ranged from 0.97?/inh to 8.90?/inh and from 208.45?/HPU to 1,471.95?/ HPU. The Pearson correlation between drug expenditure and population was 0.25 and 0.35 for the correlation between expenditure and homogeneous production (p=0.32 and p=0,15, respectively), both Pearson coefficients confirming the lack of correlation and arelevant degree of variability in drug expenditures. The quantitative analysis of variability performed through Pearson correlation has confirmed the existence of drug expenditure variability among comparable dermatology departments. Copyright © 2013 SEFH. Published by AULA MEDICA. All rights reserved.

Statistical Analysis of Tsunami Variability

NASA Astrophysics Data System (ADS)

Zolezzi, Francesca; Del Giudice, Tania; Traverso, Chiara; Valfrè, Giulio; Poggi, Pamela; Parker, Eric J.

2010-05-01

similar to that seen in ground motion attenuation correlations used for seismic hazard assessment. The second issue was intra-event variability. This refers to the differences in tsunami wave run-up along a section of coast during a single event. Intra-event variability investigated directly considering field observations. The tsunami events used in the statistical evaluation were selected on the basis of the completeness and reliability of the available data. Tsunami considered for the analysis included the recent and well surveyed tsunami of Boxing Day 2004 (Great Indian Ocean Tsunami), Java 2006, Okushiri 1993, Kocaeli 1999, Messina 1908 and a case study of several historic events in Hawaii. Basic statistical analysis was performed on the field observations from these tsunamis. For events with very wide survey regions, the run-up heights have been grouped in order to maintain a homogeneous distance from the source. Where more than one survey was available for a given event, the original datasets were maintained separately to avoid combination of non-homogeneous data. The observed run-up measurements were used to evaluate the minimum, maximum, average, standard deviation and coefficient of variation for each data set. The minimum coefficient of variation was 0.12 measured for the 2004 Boxing Day tsunami at Nias Island (7 data) while the maximum is 0.98 for the Okushiri 1993 event (93 data). The average coefficient of variation is of the order of 0.45.

Using Log Linear Analysis for Categorical Family Variables.

ERIC Educational Resources Information Center

Moen, Phyllis

The Goodman technique of log linear analysis is ideal for family research, because it is designed for categorical (non-quantitative) variables. Variables are dichotomized (for example, married/divorced, childless/with children) or otherwise categorized (for example, level of permissiveness, life cycle stage). Contingency tables are then…

Variability Analysis: Detection and Classification

NASA Astrophysics Data System (ADS)

Eyer, L.

2005-01-01

The Gaia mission will offer an exceptional opportunity to perform variability studies. The data homogeneity, its optimised photometric systems, composed of 11 medium and 4-5 broad bands, the high photometric precision in G band of one milli-mag for V = 13-15, the radial velocity measurements and the exquisite astrometric precision for one billion stars will permit a detailed description of variable objects like stars, quasars and asteroids. However the time sampling and the total number of measurements change from one object to another because of the satellite scanning law. The data analysis is a challenge because of the huge amount of data, the complexity of the observed objects and the peculiarities of the satellite, and needs thorough preparation. Experience can be gained by the study of past and present survey analyses and results, and Gaia should be put in perspective with the future large scale surveys, like PanSTARRS or LSST. We present the activities of the Variable Star Working Group and a general plan to digest this unprecedented data set, focusing here on the photometry.

Genomic signal analysis of pathogen variability

NASA Astrophysics Data System (ADS)

Cristea, Paul Dan

2006-02-01

The paper presents results in the study of pathogen variability by using genomic signals. The conversion of symbolic nucleotide sequences into digital signals offers the possibility to apply signal processing methods to the analysis of genomic data. The method is particularly well suited to characterize small size genomic sequences, such as those found in viruses and bacteria, being a promising tool in tracking the variability of pathogens, especially in the context of developing drug resistance. The paper is based on data downloaded from GenBank [32], and comprises results on the variability of the eight segments of the influenza type A, subtype H5N1, virus genome, and of the Hemagglutinin (HA) gene, for the H1, H2, H3, H4, H5 and H16 types. Data from human and avian virus isolates are used.

Fourier analysis of blazar variability

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

Finke, Justin D.; Becker, Peter A., E-mail: justin.finke@nrl.navy.mil

Blazars display strong variability on multiple timescales and in multiple radiation bands. Their variability is often characterized by power spectral densities (PSDs) and time lags plotted as functions of the Fourier frequency. We develop a new theoretical model based on the analysis of the electron transport (continuity) equation, carried out in the Fourier domain. The continuity equation includes electron cooling and escape, and a derivation of the emission properties includes light travel time effects associated with a radiating blob in a relativistic jet. The model successfully reproduces the general shapes of the observed PSDs and predicts specific PSD and timemore » lag behaviors associated with variability in the synchrotron, synchrotron self-Compton, and external Compton emission components, from submillimeter to γ-rays. We discuss applications to BL Lacertae objects and to flat-spectrum radio quasars (FSRQs), where there are hints that some of the predicted features have already been observed. We also find that FSRQs should have steeper γ-ray PSD power-law indices than BL Lac objects at Fourier frequencies ≲ 10{sup –4} Hz, in qualitative agreement with previously reported observations by the Fermi Large Area Telescope.« less

Variability Analysis of Therapeutic Movements using Wearable Inertial Sensors.

PubMed

López-Nava, Irvin Hussein; Arnrich, Bert; Muñoz-Meléndez, Angélica; Güneysu, Arzu

2017-01-01

A variability analysis of upper limb therapeutic movements using wearable inertial sensors is presented. Five healthy young adults were asked to perform a set of movements using two sensors placed on the upper arm and forearm. Reference data were obtained from three therapists. The goal of the study is to determine an intra and inter-group difference between a number of given movements performed by young people with respect to the movements of therapists. This effort is directed toward studying other groups characterized by motion impairments, and it is relevant to obtain a quantified measure of the quality of movement of a patient to follow his/her recovery. The sensor signals were processed by applying two approaches, time-domain features and similarity distance between each pair of signals. The data analysis was divided into classification and variability using features and distances calculated previously. The classification analysis was made to determine if the movements performed by the test subjects of both groups are distinguishable among them. The variability analysis was conducted to measure the similarity of the movements. According to the results, the flexion/extension movement had a high intra-group variability. In addition, meaningful information were provided in terms of change of velocity and rotational motions for each individual.

Acute tubular necrosis (ATN) presenting with an unusually prolonged period of marked polyuria heralded by an abrupt oliguric phase.

PubMed

Ramoutar, Virin; Landa, Cristian; James, Leighton R

2014-08-22

A 50-year-old African-American man presented with acute tubular necrosis (ATN) secondary to hypotension from non-typhoid Salmonella gastroenteritis and bacteraemia. The oliguric phase lasted only 24 h followed by prolonged polyuria for 20 days, with urine output in excess of 16 L/day at maximum. As indexed in PubMed this is only the second published case of this nature since 1974, in which an abrupt oliguric phase of 24 h or less heralded prolonged polyuria in ATN. The diagnosis is challenging as fractional excretion of sodium early in the clinical course and rapid normalisation of serum creatinine with intravenous fluids (IVF) may point towards prerenal azotaemia resulting in a premature discharge from hospital. Patients with an abrupt oliguric phase may suffer a secondary renal insult from the profound fluid loss that is to follow and may need inpatient monitoring with supplemental IVF to prevent deleterious outcomes. 2014 BMJ Publishing Group Ltd.

Acute tubular necrosis (ATN) presenting with an unusually prolonged period of marked polyuria heralded by an abrupt oliguric phase

PubMed Central

Ramoutar, Virin; Landa, Cristian; James, Leighton R

2014-01-01

A 50-year-old African-American man presented with acute tubular necrosis (ATN) secondary to hypotension from non-typhoid Salmonella gastroenteritis and bacteraemia. The oliguric phase lasted only 24 h followed by prolonged polyuria for 20 days, with urine output in excess of 16 L/day at maximum. As indexed in PubMed this is only the second published case of this nature since 1974, in which an abrupt oliguric phase of 24 h or less heralded prolonged polyuria in ATN. The diagnosis is challenging as fractional excretion of sodium early in the clinical course and rapid normalisation of serum creatinine with intravenous fluids (IVF) may point towards prerenal azotaemia resulting in a premature discharge from hospital. Patients with an abrupt oliguric phase may suffer a secondary renal insult from the profound fluid loss that is to follow and may need inpatient monitoring with supplemental IVF to prevent deleterious outcomes. PMID:25150229

Entanglement with negative Wigner function of almost 3,000 atoms heralded by one photon.

PubMed

McConnell, Robert; Zhang, Hao; Hu, Jiazhong; Ćuk, Senka; Vuletić, Vladan

2015-03-26

Quantum-mechanically correlated (entangled) states of many particles are of interest in quantum information, quantum computing and quantum metrology. Metrologically useful entangled states of large atomic ensembles have been experimentally realized, but these states display Gaussian spin distribution functions with a non-negative Wigner quasiprobability distribution function. Non-Gaussian entangled states have been produced in small ensembles of ions, and very recently in large atomic ensembles. Here we generate entanglement in a large atomic ensemble via an interaction with a very weak laser pulse; remarkably, the detection of a single photon prepares several thousand atoms in an entangled state. We reconstruct a negative-valued Wigner function--an important hallmark of non-classicality--and verify an entanglement depth (the minimum number of mutually entangled atoms) of 2,910 ± 190 out of 3,100 atoms. Attaining such a negative Wigner function and the mutual entanglement of virtually all atoms is unprecedented for an ensemble containing more than a few particles. Although the achieved purity of the state is slightly below the threshold for entanglement-induced metrological gain, further technical improvement should allow the generation of states that surpass this threshold, and of more complex Schrödinger cat states for quantum metrology and information processing. More generally, our results demonstrate the power of heralded methods for entanglement generation, and illustrate how the information contained in a single photon can drastically alter the quantum state of a large system.

Dispositional Variables and Work-Family Conflict: A Meta-Analysis

ERIC Educational Resources Information Center

Allen, Tammy D.; Johnson, Ryan C.; Saboe, Kristin N.; Cho, Eunae; Dumani, Soner; Evans, Sarah

2012-01-01

Meta-analysis was used to comprehensively summarize the relationship between dispositional variables and both directions of work-family conflict. The largest effects detected were those associated with negative affect, neuroticism, and self-efficacy; all were in expected directions. In general, negative trait-based variables (e.g., negative affect…

Iterative Strain-Gage Balance Calibration Data Analysis for Extended Independent Variable Sets

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred

2011-01-01

A new method was developed that makes it possible to use an extended set of independent calibration variables for an iterative analysis of wind tunnel strain gage balance calibration data. The new method permits the application of the iterative analysis method whenever the total number of balance loads and other independent calibration variables is greater than the total number of measured strain gage outputs. Iteration equations used by the iterative analysis method have the limitation that the number of independent and dependent variables must match. The new method circumvents this limitation. It simply adds a missing dependent variable to the original data set by using an additional independent variable also as an additional dependent variable. Then, the desired solution of the regression analysis problem can be obtained that fits each gage output as a function of both the original and additional independent calibration variables. The final regression coefficients can be converted to data reduction matrix coefficients because the missing dependent variables were added to the data set without changing the regression analysis result for each gage output. Therefore, the new method still supports the application of the two load iteration equation choices that the iterative method traditionally uses for the prediction of balance loads during a wind tunnel test. An example is discussed in the paper that illustrates the application of the new method to a realistic simulation of temperature dependent calibration data set of a six component balance.

Nonlinear stratospheric variability: multifractal de-trended fluctuation analysis and singularity spectra

PubMed Central

Domeisen, Daniela I. V.

2016-01-01

Characterizing the stratosphere as a turbulent system, temporal fluctuations often show different correlations for different time scales as well as intermittent behaviour that cannot be captured by a single scaling exponent. In this study, the different scaling laws in the long-term stratospheric variability are studied using multifractal de-trended fluctuation analysis (MF-DFA). The analysis is performed comparing four re-analysis products and different realizations of an idealized numerical model, isolating the role of topographic forcing and seasonal variability, as well as the absence of climate teleconnections and small-scale forcing. The Northern Hemisphere (NH) shows a transition of scaling exponents for time scales shorter than about 1 year, for which the variability is multifractal and scales in time with a power law corresponding to a red spectrum, to longer time scales, for which the variability is monofractal and scales in time with a power law corresponding to white noise. Southern Hemisphere (SH) variability also shows a transition at annual scales. The SH also shows a narrower dynamical range in multifractality than the NH, as seen in the generalized Hurst exponent and in the singularity spectra. The numerical integrations show that the models are able to reproduce the low-frequency variability but are not able to fully capture the shorter term variability of the stratosphere. PMID:27493560

Sensitivity Analysis of Weather Variables on Offsite Consequence Analysis Tools in South Korea and the United States.

PubMed

Kim, Min-Uk; Moon, Kyong Whan; Sohn, Jong-Ryeul; Byeon, Sang-Hoon

2018-05-18

We studied sensitive weather variables for consequence analysis, in the case of chemical leaks on the user side of offsite consequence analysis (OCA) tools. We used OCA tools Korea Offsite Risk Assessment (KORA) and Areal Location of Hazardous Atmospheres (ALOHA) in South Korea and the United States, respectively. The chemicals used for this analysis were 28% ammonia (NH₃), 35% hydrogen chloride (HCl), 50% hydrofluoric acid (HF), and 69% nitric acid (HNO₃). The accident scenarios were based on leakage accidents in storage tanks. The weather variables were air temperature, wind speed, humidity, and atmospheric stability. Sensitivity analysis was performed using the Statistical Package for the Social Sciences (SPSS) program for dummy regression analysis. Sensitivity analysis showed that impact distance was not sensitive to humidity. Impact distance was most sensitive to atmospheric stability, and was also more sensitive to air temperature than wind speed, according to both the KORA and ALOHA tools. Moreover, the weather variables were more sensitive in rural conditions than in urban conditions, with the ALOHA tool being more influenced by weather variables than the KORA tool. Therefore, if using the ALOHA tool instead of the KORA tool in rural conditions, users should be careful not to cause any differences in impact distance due to input errors of weather variables, with the most sensitive one being atmospheric stability.

Frequency spectrum analysis of finger photoplethysmographic waveform variability during haemodialysis.

PubMed

Javed, Faizan; Middleton, Paul M; Malouf, Philip; Chan, Gregory S H; Savkin, Andrey V; Lovell, Nigel H; Steel, Elizabeth; Mackie, James

2010-09-01

This study investigates the peripheral circulatory and autonomic response to volume withdrawal in haemodialysis based on spectral analysis of photoplethysmographic waveform variability (PPGV). Frequency spectrum analysis was performed on the baseline and pulse amplitude variabilities of the finger infrared photoplethysmographic (PPG) waveform and on heart rate variability extracted from the ECG signal collected from 18 kidney failure patients undergoing haemodialysis. Spectral powers were calculated from the low frequency (LF, 0.04-0.145 Hz) and high frequency (HF, 0.145-0.45 Hz) bands. In eight stable fluid overloaded patients (fluid removal of >2 L) not on alpha blockers, progressive reduction in relative blood volume during haemodialysis resulted in significant increase in LF and HF powers of PPG baseline and amplitude variability (P < 0.01), when expressed in mean-scaled units. The augmentation of LF powers in PPGV during haemodialysis may indicate the recovery and possibly further enhancement of peripheral sympathetic vascular modulation subsequent to volume unloading, whilst the increase in respiratory HF power in PPGV is most likely a sign of preload reduction. Spectral analysis of finger PPGV may provide valuable information on the autonomic vascular response to blood volume reduction in haemodialysis, and can be potentially utilized as a non-invasive tool for assessing peripheral circulatory control during routine dialysis procedure.

Between-subject variability in asymmetry analysis of macular thickness.

PubMed

Alluwimi, Muhammed S; Swanson, William H; Malinovsky, Victor E

2014-05-01

To investigate the use of asymmetry analysis to reduce between-subject variability of macular thickness measurements using spectral domain optical coherence tomography. Sixty-three volunteers (33 young subjects [aged 21 to 35 years] and 30 older subjects [aged 45 to 85 years]) free of eye disease were recruited. Macular images were gathered with the Spectralis optical coherence tomography. An overlay 24- by 24-degree grid was divided into five zones per hemifield, and asymmetry analysis was computed as the difference between superior and inferior zone thicknesses. We hypothesized that the lowest variation and the highest density of ganglion cells will be found approximately 3 to 6 degrees from the foveola, corresponding to zones 1 and 2. For each zone and age group, between-subject SDs were compared for retinal thickness versus asymmetry analysis using an F test. To account for repeated comparisons, p < 0.0125 was required for statistical significance. Axial length and corneal curvature were measured with an IOLMaster. For OD, asymmetry analysis reduced between-subject variability in zones 1 and 2 in both groups (F > 3.2, p < 0.001). Standard deviation for zone 1 dropped from 12.0 to 3.0 μm in the young group and from 11.7 to 2.6 μm in the older group. Standard deviation for zone 2 dropped from 13.6 to 5.3 μm in the young group and from 11.1 to 5.8 μm in the older group. Combining all subjects, neither retinal thickness nor asymmetry analysis showed a strong correlation with axial length or corneal curvature (R² < 0.01). Analysis for OS yielded the same pattern of results, as did asymmetry analyses between eyes (F > 3.8, p < 0.0001). Asymmetry analysis reduced between-subject variability in zones 1 and 2. Combining the five zones together produced a higher between-subject variation of the retinal thickness asymmetry analysis; thus, we encourage clinicians to be cautious when interpreting the asymmetry analysis printouts.

Extrapolation of Functions of Many Variables by Means of Metric Analysis

NASA Astrophysics Data System (ADS)

Kryanev, Alexandr; Ivanov, Victor; Romanova, Anastasiya; Sevastianov, Leonid; Udumyan, David

2018-02-01

The paper considers a problem of extrapolating functions of several variables. It is assumed that the values of the function of m variables at a finite number of points in some domain D of the m-dimensional space are given. It is required to restore the value of the function at points outside the domain D. The paper proposes a fundamentally new method for functions of several variables extrapolation. In the presented paper, the method of extrapolating a function of many variables developed by us uses the interpolation scheme of metric analysis. To solve the extrapolation problem, a scheme based on metric analysis methods is proposed. This scheme consists of two stages. In the first stage, using the metric analysis, the function is interpolated to the points of the domain D belonging to the segment of the straight line connecting the center of the domain D with the point M, in which it is necessary to restore the value of the function. In the second stage, based on the auto regression model and metric analysis, the function values are predicted along the above straight-line segment beyond the domain D up to the point M. The presented numerical example demonstrates the efficiency of the method under consideration.

Differentially Variable Component Analysis (dVCA): Identifying Multiple Evoked Components using Trial-to-Trial Variability

NASA Technical Reports Server (NTRS)

Knuth, Kevin H.; Shah, Ankoor S.; Truccolo, Wilson; Ding, Ming-Zhou; Bressler, Steven L.; Schroeder, Charles E.

2003-01-01

Electric potentials and magnetic fields generated by ensembles of synchronously active neurons in response to external stimuli provide information essential to understanding the processes underlying cognitive and sensorimotor activity. Interpreting recordings of these potentials and fields is difficult as each detector records signals simultaneously generated by various regions throughout the brain. We introduce the differentially Variable Component Analysis (dVCA) algorithm, which relies on trial-to-trial variability in response amplitude and latency to identify multiple components. Using simulations we evaluate the importance of response variability to component identification, the robustness of dVCA to noise, and its ability to characterize single-trial data. Finally, we evaluate the technique using visually evoked field potentials recorded at incremental depths across the layers of cortical area VI, in an awake, behaving macaque monkey.

A comprehensive company database analysis of biological assay variability.

PubMed

Kramer, Christian; Dahl, Göran; Tyrchan, Christian; Ulander, Johan

2016-08-01

Analysis of data from various compounds measured in diverse biological assays is a central part of drug discovery research projects. However, no systematic overview of the variability in biological assays has been published and judgments on assay quality and robustness of data are often based on personal belief and experience within the drug discovery community. To address this we performed a reproducibility analysis of all biological assays at AstraZeneca between 2005 and 2014. We found an average experimental uncertainty of less than a twofold difference and no technologies or assay types had higher variability than others. This work suggests that robust data can be obtained from the most commonly applied biological assays. Copyright © 2016. Published by Elsevier Ltd.

[Relations between biomedical variables: mathematical analysis or linear algebra?].

PubMed

Hucher, M; Berlie, J; Brunet, M

1977-01-01

The authors, after a short reminder of one pattern's structure, stress on the possible double approach of relations uniting the variables of this pattern: use of fonctions, what is within the mathematical analysis sphere, use of linear algebra profiting by matricial calculation's development and automatiosation. They precise the respective interests on these methods, their bounds and the imperatives for utilization, according to the kind of variables, of data, and the objective for work, understanding phenomenons or helping towards decision.

A happy "thumbs up" from the crew of the Space Shuttle Endeavour and NASA Dryden Flight Research Center officials heralded the successful completion of mission STS-100

NASA Image and Video Library

2001-05-01

A happy "thumbs up" from the crew of the Space Shuttle Endeavour and NASA Dryden Flight Research Center officials heralded the successful completion of mission STS-100. Standing by the shuttle's rocket nozzles from left to right: Scott E. Prazynski, mission specialist (U.S.); Yuri V. Lonchakov, mission specialist (Russia); Kent V. Rominger, commander (U.S.); Wally Sawyer, NASA Dryden Flight Research Center deputy director; Kevin Petersen, NASA Dryden Flight Research Center director; Umberto Guidoni, mission specialist (European Space Agency); John L. Phillips, mission specialist (U.S.); Jeffrey S. Ashby, pilot (U.S.); and Chris A. Hadfield, mission specialist (Canadian Space Agency). The mission landed at Edwards Air Force Base, California, on May 1, 2001.

Discriminant Analysis of Time Series in the Presence of Within-Group Spectral Variability.

PubMed

Krafty, Robert T

2016-07-01

Many studies record replicated time series epochs from different groups with the goal of using frequency domain properties to discriminate between the groups. In many applications, there exists variation in cyclical patterns from time series in the same group. Although a number of frequency domain methods for the discriminant analysis of time series have been explored, there is a dearth of models and methods that account for within-group spectral variability. This article proposes a model for groups of time series in which transfer functions are modeled as stochastic variables that can account for both between-group and within-group differences in spectra that are identified from individual replicates. An ensuing discriminant analysis of stochastic cepstra under this model is developed to obtain parsimonious measures of relative power that optimally separate groups in the presence of within-group spectral variability. The approach possess favorable properties in classifying new observations and can be consistently estimated through a simple discriminant analysis of a finite number of estimated cepstral coefficients. Benefits in accounting for within-group spectral variability are empirically illustrated in a simulation study and through an analysis of gait variability.

Kubios HRV--heart rate variability analysis software.

PubMed

Tarvainen, Mika P; Niskanen, Juha-Pekka; Lipponen, Jukka A; Ranta-Aho, Perttu O; Karjalainen, Pasi A

2014-01-01

Kubios HRV is an advanced and easy to use software for heart rate variability (HRV) analysis. The software supports several input data formats for electrocardiogram (ECG) data and beat-to-beat RR interval data. It includes an adaptive QRS detection algorithm and tools for artifact correction, trend removal and analysis sample selection. The software computes all the commonly used time-domain and frequency-domain HRV parameters and several nonlinear parameters. There are several adjustable analysis settings through which the analysis methods can be optimized for different data. The ECG derived respiratory frequency is also computed, which is important for reliable interpretation of the analysis results. The analysis results can be saved as an ASCII text file (easy to import into MS Excel or SPSS), Matlab MAT-file, or as a PDF report. The software is easy to use through its compact graphical user interface. The software is available free of charge for Windows and Linux operating systems at http://kubios.uef.fi. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

NASA Astrophysics Data System (ADS)

Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

Heart rate variability alterations in late life depression: A meta-analysis.

PubMed

Brown, Lydia; Karmakar, Chandan; Gray, Richard; Jindal, Ripu; Lim, Terrence; Bryant, Christina

2018-08-01

There is strong evidence for a bi-directional relationship between heart-health and depression in later life, but the physiological mechanisms underlying this relationship remain unclear. Heart rate variability is one promising factor that might help explain this relationship. We present results of a meta-analysis that considers heart rate variability alterations in older adults with depression. Literature search of Embase, PsychInfo and Medline revealed five clinical studies and six observational studies that examined the relationship between heart rate variability and depression in adults with a mean age over 60. These studies were included in this meta-analysis. Heart rate variability was reduced among older adults with clinical depression (N = 550), relative to healthy controls (Hedges' g = -0.334, 95%CI [-0.579, -0.090], p = .007). When high-frequency and low-frequency heart rate variability were investigated separately, only low-frequency heart rate variability was significantly reduced in depressed patients (Hedges' g = -0.626, 95%CI [-1.083, -0.169], p = .007). A similar but weaker pattern of results was found in the observational studies. Most findings remained significant among unmedicated depressed older adults. Evidence of effect-size heterogeneity was found in the clinical studies, indicating the need for more well-designed research in the area. Heart rate variability is reduced among older adults with depression, and this effect is not fully attributable to antidepressant medication use. Specifically, low-frequency heart rate variability may be reduced in depressed older adults. Heart rate variability warrants further attention, as it could help inform research into the prevention and treatment of depression in later life. Copyright © 2018 Elsevier B.V. All rights reserved.

Problems and programming for analysis of IUE high resolution data for variability

NASA Technical Reports Server (NTRS)

Grady, C. A.

1981-01-01

Observations of variability in stellar winds provide an important probe of their dynamics. It is crucial however to know that any variability seen in a data set can be clearly attributed to the star and not to instrumental or data processing effects. In the course of analysis of IUE high resolution data of alpha Cam and other O, B and Wolf-Rayet stars several effects were found which cause spurious variability or spurious spectral features in our data. Programming was developed to partially compensate for these effects using the Interactive Data language (IDL) on the LASP PDP 11/34. Use of an interactive language such as IDL is particularly suited to analysis of variability data as it permits use of efficient programs coupled with the judgement of the scientist at each stage of processing.

An Evaluation of the Effects of Variable Sampling on Component, Image, and Factor Analysis.

ERIC Educational Resources Information Center

Velicer, Wayne F.; Fava, Joseph L.

1987-01-01

Principal component analysis, image component analysis, and maximum likelihood factor analysis were compared to assess the effects of variable sampling. Results with respect to degree of saturation and average number of variables per factor were clear and dramatic. Differential effects on boundary cases and nonconvergence problems were also found.…

Variability in sublingual microvessel density and flow measurements in healthy volunteers.

PubMed

Hubble, Sheena M A; Kyte, Hayley L; Gooding, Kim; Shore, Angela C

2009-02-01

As sublingual microvascular indices are increasingly heralded as new resuscitation end-points, better population data are required to power clinical studies. This paper describes improved methods to quantify sublingual microvessel flow and density in images obtained by sidestream dark field (SDF) technology in healthy volunteers, including vessels under 10 microm in diameter. Measurements of sublingual capillary density and flow were obtained by recording three 15-second images in 20 healthy volunteers over three days. Two independent observers quantified capillary density by using two methods: total vessel length (mm/mm2) and counting (number/mm). Both intraoral and temporal variabilities within subject and observer reproducibilities were determined by using coefficients of variability and reproducibility indices. For small (1-10 microm), medium (11-20 microm), and large (21-50 microm) diameter, mean vessel density with standard deviations (SDs) in volunteers was 21.3(+/- 4.9), 5.2 (+/- 1.2), and 2.7 (+/- 0.9) mm/mm2, respectively. Also, 94.0 +/- 1.4% of small vessels, 94.5 +/- 1.4% of medium vessels, and 94.5+/- 4.0% of large vessels had continuous perfusion. Within subjects, the means of all measurements over three days varied less than 13, 22, and 35% in small, medium, and large vessels, respectively. Interobserver reproducibility was good, especially for capillary (1-10 microm) density and flow measurements. Our methods of microvessel flow and density quantification have low observer variability and confirm the stability of microcirculatory measurements over time. These results facilitate the development of SDF-acquired sublingual microvascular indices as feasible microperfusion markers in shock resuscitation.

Insights into gait disorders: walking variability using phase plot analysis, Huntington's disease.

PubMed

Collett, Johnny; Esser, Patrick; Khalil, Hanan; Busse, Monica; Quinn, Lori; DeBono, Katy; Rosser, Anne; Nemeth, Andrea H; Dawes, Helen

2014-09-01

Huntington's disease (HD) is a progressive inherited neurodegenerative disorder. Identifying sensitive methodologies to quantitatively measure early motor changes have been difficult to develop. This exploratory observational study investigated gait variability and symmetry in HD using phase plot analysis. We measured the walking of 22 controls and 35 HD gene carriers (7 premanifest (PreHD)), 16 early/mid (HD1) and 12 late stage (HD2) in Oxford and Cardiff, UK. The unified Huntington's disease rating scale-total motor scores (UHDRS-TMS) and disease burden scores (DBS) were used to quantify disease severity. Data was collected during a clinical walk test (8.8 or 10 m) using an inertial measurement unit attached to the trunk. The 6 middle strides were used to calculate gait variability determined by spatiotemporal parameters (co-efficient of variation (CoV)) and phase plot analysis. Phase plots considered the variability in consecutive wave forms from vertical movement and were quantified by SDA (spatiotemporal variability), SDB (temporal variability), ratio ∀ (ratio SDA:SDB) and Δangleβ (symmetry). Step time CoV was greater in manifest HD (p<0.01, both manifest groups) than controls, as was stride length CoV for HD2 (p<0.01). No differences were found in spatiotemporal variability between PreHD and controls (p>0.05). Phase plot analysis identified differences between manifest HD and controls for SDB, Ratio ∀ and Δangle (all p<0.01, both manifest groups). Furthermore Ratio ∀ was smaller in PreHD compared with controls (p<0.01). Ratio ∀ also produced the strongest correlation with UHDRS-TMS (r=-0.61, p<0.01) and was correlated with DBS (r=-0.42, p=0.02). Phase plot analysis may be a sensitive method of detecting gait changes in HD and can be performed quickly during clinical walking tests. Copyright © 2014 Elsevier B.V. All rights reserved.

Regression Analysis of Stage Variability for West-Central Florida Lakes

USGS Publications Warehouse

Sacks, Laura A.; Ellison, Donald L.; Swancar, Amy

2008-01-01

The variability in a lake's stage depends upon many factors, including surface-water flows, meteorological conditions, and hydrogeologic characteristics near the lake. An understanding of the factors controlling lake-stage variability for a population of lakes may be helpful to water managers who set regulatory levels for lakes. The goal of this study is to determine whether lake-stage variability can be predicted using multiple linear regression and readily available lake and basin characteristics defined for each lake. Regressions were evaluated for a recent 10-year period (1996-2005) and for a historical 10-year period (1954-63). Ground-water pumping is considered to have affected stage at many of the 98 lakes included in the recent period analysis, and not to have affected stage at the 20 lakes included in the historical period analysis. For the recent period, regression models had coefficients of determination (R2) values ranging from 0.60 to 0.74, and up to five explanatory variables. Standard errors ranged from 21 to 37 percent of the average stage variability. Net leakage was the most important explanatory variable in regressions describing the full range and low range in stage variability for the recent period. The most important explanatory variable in the model predicting the high range in stage variability was the height over median lake stage at which surface-water outflow would occur. Other explanatory variables in final regression models for the recent period included the range in annual rainfall for the period and several variables related to local and regional hydrogeology: (1) ground-water pumping within 1 mile of each lake, (2) the amount of ground-water inflow (by category), (3) the head gradient between the lake and the Upper Floridan aquifer, and (4) the thickness of the intermediate confining unit. Many of the variables in final regression models are related to hydrogeologic characteristics, underscoring the importance of ground

Factor analysis of some socio-economic and demographic variables for Bangladesh.

PubMed

Islam, S M

1986-01-01

The author carries out an exploratory factor analysis of some socioeconomic and demographic variables for Bangladesh using the classical or common factor approach with the varimax rotation method. The socioeconomic and demographic indicators used in this study include literacy, rate of growth, female employment, economic development, urbanization, population density, childlessness, sex ratio, proportion of women ever married, and fertility. The 18 administrative districts of Bangladesh constitute the unit of analysis. 3 common factors--modernization, fertility, and social progress--are identified in this study to explain the correlations among the set of selected socioeconomic and demographic variables.

Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

PubMed Central

Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc

2017-01-01

Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780

On the Choice of Variable for Atmospheric Moisture Analysis

NASA Technical Reports Server (NTRS)

Dee, Dick P.; DaSilva, Arlindo M.; Atlas, Robert (Technical Monitor)

2002-01-01

The implications of using different control variables for the analysis of moisture observations in a global atmospheric data assimilation system are investigated. A moisture analysis based on either mixing ratio or specific humidity is prone to large extrapolation errors, due to the high variability in space and time of these parameters and to the difficulties in modeling their error covariances. Using the logarithm of specific humidity does not alleviate these problems, and has the further disadvantage that very dry background estimates cannot be effectively corrected by observations. Relative humidity is a better choice from a statistical point of view, because this field is spatially and temporally more coherent and error statistics are therefore easier to obtain. If, however, the analysis is designed to preserve relative humidity in the absence of moisture observations, then the analyzed specific humidity field depends entirely on analyzed temperature changes. If the model has a cool bias in the stratosphere this will lead to an unstable accumulation of excess moisture there. A pseudo-relative humidity can be defined by scaling the mixing ratio by the background saturation mixing ratio. A univariate pseudo-relative humidity analysis will preserve the specific humidity field in the absence of moisture observations. A pseudorelative humidity analysis is shown to be equivalent to a mixing ratio analysis with flow-dependent covariances. In the presence of multivariate (temperature-moisture) observations it produces analyzed relative humidity values that are nearly identical to those produced by a relative humidity analysis. Based on a time series analysis of radiosonde observed-minus-background differences it appears to be more justifiable to neglect specific humidity-temperature correlations (in a univariate pseudo-relative humidity analysis) than to neglect relative humidity-temperature correlations (in a univariate relative humidity analysis). A pseudo

Variable mass pendulum behaviour processed by wavelet analysis

NASA Astrophysics Data System (ADS)

Caccamo, M. T.; Magazù, S.

2017-01-01

The present work highlights how, in order to characterize the motion of a variable mass pendulum, wavelet analysis can be an effective tool in furnishing information on the time evolution of the oscillation spectral content. In particular, the wavelet transform is applied to process the motion of a hung funnel that loses fine sand at an exponential rate; it is shown how, in contrast to the Fourier transform which furnishes only an average frequency value for the motion, the wavelet approach makes it possible to perform a joint time-frequency analysis. The work is addressed at undergraduate and graduate students.

Meta-Analysis of Scale Reliability Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2013-01-01

A latent variable modeling approach is outlined that can be used for meta-analysis of reliability coefficients of multicomponent measuring instruments. Important limitations of efforts to combine composite reliability findings across multiple studies are initially pointed out. A reliability synthesis procedure is discussed that is based on…

Using principal component analysis to understand the variability of PDS 456

NASA Astrophysics Data System (ADS)

Parker, M. L.; Reeves, J. N.; Matzeu, G. A.; Buisson, D. J. K.; Fabian, A. C.

2018-02-01

We present a spectral-variability analysis of the low-redshift quasar PDS 456 using principal component analysis. In the XMM-Newton data, we find a strong peak in the first principal component at the energy of the Fe absorption line from the highly blueshifted outflow. This indicates that the absorption feature is more variable than the continuum, and that it is responding to the continuum. We find qualitatively different behaviour in the Suzaku data, which is dominated by changes in the column density of neutral absorption. In this case, we find no evidence of the absorption produced by the highly ionized gas being correlated with this variability. Additionally, we perform simulations of the source variability, and demonstrate that PCA can trivially distinguish between outflow variability correlated, anticorrelated and un-correlated with the continuum flux. Here, the observed anticorrelation between the absorption line equivalent width and the continuum flux may be due to the ionization of the wind responding to the continuum. Finally, we compare our results with those found in the narrow-line Seyfert 1 IRAS 13224-3809. We find that the Fe K UFO feature is sharper and more prominent in PDS 456, but that it lacks the lower energy features from lighter elements found in IRAS 13224-3809, presumably due to differences in ionization.

[Design of hand-held heart rate variability acquisition and analysis system].

PubMed

Li, Kaiyuan; Wang, Buqing; Wang, Weidong

2012-07-01

A design of handheld heart rate variability acquisition and analysis system is proposed. The system collects and stores the patient's ECG every five minutes through both hands touching on the electrodes, and then -uploads data to a PC through USB port. The system uses software written in LabVIEW to analyze heart rate variability parameters, The parameters calculated function is programmed and generated to components in Matlab.

Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

2017-10-01

Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of <24%, 24-30%, >30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

Variability of Soil Temperature: A Spatial and Temporal Analysis.

ERIC Educational Resources Information Center

Walsh, Stephen J.; And Others

1991-01-01

Discusses an analysis of the relationship of soil temperatures at 3 depths to various climatic variables along a 200-kilometer transect in west-central Oklahoma. Reports that temperature readings increased from east to west. Concludes that temperature variations were explained by a combination of spatial, temporal, and biophysical factors. (SG)

Phytoscreening with SPME: Variability Analysis.

PubMed

Limmer, Matt A; Burken, Joel G

2015-01-01

Phytoscreening has been demonstrated at a variety of sites over the past 15 years as a low-impact, sustainable tool in delineation of shallow groundwater contaminated with chlorinated solvents. Collection of tree cores is rapid and straightforward, but low concentrations in tree tissues requires sensitive analytics. Solid-phase microextraction (SPME) is amenable to the complex matrix while allowing for solvent-less extraction. Accurate quantification requires the absence of competitive sorption, examined here both in laboratory experiments and through comprehensive examination of field data. Analysis of approximately 2,000 trees at numerous field sites also allowed testing of the tree genus and diameter effects on measured tree contaminant concentrations. Collectively, while these variables were found to significantly affect site-adjusted perchloroethylene (PCE) concentrations, the explanatory power of these effects was small (adjusted R(2) = 0.031). 90th quantile chemical concentrations in trees were significantly reduced by increasing Henry's constant and increasing hydrophobicity. Analysis of replicate tree core data showed no correlation between replicate relative standard deviation (RSD) and wood type or tree diameter, with an overall median RSD of 30%. Collectively, these findings indicate SPME is an appropriate technique for sampling and analyzing chlorinated solvents in wood and that phytoscreening is robust against changes in tree type and diameter.

Causality and cointegration analysis between macroeconomic variables and the Bovespa.

PubMed

da Silva, Fabiano Mello; Coronel, Daniel Arruda; Vieira, Kelmara Mendes

2014-01-01

The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI), industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa). The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988) causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988) long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship) in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelfth month, followed by the country risk, with less than 5%.

CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability

EPA Pesticide Factsheets

Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

Omitted Variable Sensitivity Analysis with the Annotated Love Plot

ERIC Educational Resources Information Center

Hansen, Ben B.; Fredrickson, Mark M.

2014-01-01

The goal of this research is to make sensitivity analysis accessible not only to empirical researchers but also to the various stakeholders for whom educational evaluations are conducted. To do this it derives anchors for the omitted variable (OV)-program participation association intrinsically, using the Love plot to present a wide range of…

Approaches for modeling within subject variability in pharmacometric count data analysis: dynamic inter-occasion variability and stochastic differential equations.

PubMed

Deng, Chenhui; Plan, Elodie L; Karlsson, Mats O

2016-06-01

Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis. These approaches were applied to published count models for seizure counts and Likert pain scores. Both approaches improved the model fits significantly. In addition, stochastic simulation and estimation were used to explore further the capability of the two approaches to diagnose and improve models where existing WSV is not recognized. The results of simulations confirmed the gain in introducing WSV as dIOV and SDEs when parameters vary randomly over time. Further, the approaches were also informative as diagnostics of model misspecification, when parameters changed systematically over time but this was not recognized in the structural model. The proposed approaches in this study offer strategies to characterize WSV and are not restricted to count data.

gHRV: Heart rate variability analysis made easy.

PubMed

Rodríguez-Liñares, L; Lado, M J; Vila, X A; Méndez, A J; Cuesta, P

2014-08-01

In this paper, the gHRV software tool is presented. It is a simple, free and portable tool developed in python for analysing heart rate variability. It includes a graphical user interface and it can import files in multiple formats, analyse time intervals in the signal, test statistical significance and export the results. This paper also contains, as an example of use, a clinical analysis performed with the gHRV tool, namely to determine whether the heart rate variability indexes change across different stages of sleep. Results from tests completed by researchers who have tried gHRV are also explained: in general the application was positively valued and results reflect a high level of satisfaction. gHRV is in continuous development and new versions will include suggestions made by testers. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

State-variable analysis of non-linear circuits with a desk computer

NASA Technical Reports Server (NTRS)

Cohen, E.

1981-01-01

State variable analysis was used to analyze the transient performance of non-linear circuits on a desk top computer. The non-linearities considered were not restricted to any circuit element. All that is required for analysis is the relationship defining each non-linearity be known in terms of points on a curve.

Joint Multifractal Analysis of penetration resistance variability in an olive orchard.

NASA Astrophysics Data System (ADS)

Lopez-Herrera, Juan; Herrero-Tejedor, Tomas; Saa-Requejo, Antonio; Villeta, Maria; Tarquis, Ana M.

2016-04-01

Spatial variability of soil properties is relevant for identifying those zones with physical degradation. We used descriptive statistics and multifractal analysis for characterizing the spatial patterns of soil penetrometer resistance (PR) distributions and compare them at different soil depths and soil water content to investigate the tillage effect in soil compactation. The study was conducted on an Inceptisol dedicated to olive orchard for the last 70 years. Two parallel transects of 64 m were selected as different soil management plots, conventional tillage (CT) and no tillage (NT). Penetrometer resistance readings were carried out at 50 cm intervals within the first 20 cm of soil depth (López de Herrera et al., 2015a). Two way ANOVA highlighted that tillage system, soil depth and their interaction are statistically significant to explain the variance of PR data. The comparison of CT and NT results at different depths showed that there are significant differences deeper than 10 cm but not in the first two soil layers. The scaling properties of each PR profile was characterized by τ(q) function, calculated in the range of moment orders (q) between -5 and +5 taken at 0.5 lag increments. Several parameters were calculated from this to establish different comparisons (López de Herrera et al., 2015b). While the multifractal analysis characterizes the distribution of a single variable along its spatial support, the joint multifractal analysis can be used to characterize the joint distribution of two or more variables along a common spatial support (Kravchenko et al., 2000; Zeleke and Si, 2004). This type of analysis was performed to study the scaling properties of the joint distribution of PR at different depths. The results showed that this type of analysis added valuable information to describe the spatial arrangement of depth-dependent penetrometer data sets in all the soil layers. References Kravchenko AN, Bullock DG, Boast CW (2000) Joint multifractal

Multilocus variable-number tandem repeat analysis for molecular typing and phylogenetic analysis of Shigella flexneri

PubMed Central

2009-01-01

Background Shigella flexneri is one of the causative agents of shigellosis, a major cause of childhood mortality in developing countries. Multilocus variable-number tandem repeat (VNTR) analysis (MLVA) is a prominent subtyping method to resolve closely related bacterial isolates for investigation of disease outbreaks and provide information for establishing phylogenetic patterns among isolates. The present study aimed to develop an MLVA method for S. flexneri and the VNTR loci identified were tested on 242 S. flexneri isolates to evaluate their variability in various serotypes. The isolates were also analyzed by pulsed-field gel electrophoresis (PFGE) to compare the discriminatory power and to evaluate the usefulness of MLVA as a tool for phylogenetic analysis of S. flexneri. Results Thirty-six VNTR loci were identified by exploring the repeat sequence loci in genomic sequences of Shigella species and by testing the loci on nine isolates of different subserotypes. The VNTR loci in different serotype groups differed greatly in their variability. The discriminatory power of an MLVA assay based on four most variable VNTR loci was higher, though not significantly, than PFGE for the total isolates, a panel of 2a isolates, which were relatively diverse, and a panel of 4a/Y isolates, which were closely-related. Phylogenetic groupings based on PFGE patterns and MLVA profiles were considerably concordant. The genetic relationships among the isolates were correlated with serotypes. The phylogenetic trees constructed using PFGE patterns and MLVA profiles presented two distinct clusters for the isolates of serotype 3 and one distinct cluster for each of the serotype groups, 1a/1b/NT, 2a/2b/X/NT, 4a/Y, and 6. Isolates that had different serotypes but had closer genetic relatedness than those with the same serotype were observed between serotype Y and subserotype 4a, serotype X and subserotype 2b, subserotype 1a and 1b, and subserotype 3a and 3b. Conclusions The 36 VNTR loci

Spectral analysis of variable-length coded digital signals

NASA Astrophysics Data System (ADS)

Cariolaro, G. L.; Pierobon, G. L.; Pupolin, S. G.

1982-05-01

A spectral analysis is conducted for a variable-length word sequence by an encoder driven by a stationary memoryless source. A finite-state sequential machine is considered as a model of the line encoder, and the spectral analysis of the encoded message is performed under the assumption that the sourceword sequence is composed of independent identically distributed words. Closed form expressions for both the continuous and discrete parts of the spectral density are derived in terms of the encoder law and sourceword statistics. The jump part exhibits jumps at multiple integers of per lambda(sub 0)T, where lambda(sub 0) is the greatest common divisor of the possible codeword lengths, and T is the symbol period. The derivation of the continuous part can be conveniently factorized, and the theory is applied to the spectral analysis of BnZS and HDBn codes.

Impacts analysis of car following models considering variable vehicular gap policies

NASA Astrophysics Data System (ADS)

Xin, Qi; Yang, Nan; Fu, Rui; Yu, Shaowei; Shi, Zhongke

2018-07-01

Due to the important roles playing in the vehicles' adaptive cruise control system, variable vehicular gap polices were employed to full velocity difference model (FVDM) to investigate the traffic flow properties. In this paper, two new car following models were put forward by taking constant time headway(CTH) policy and variable time headway(VTH) policy into optimal velocity function, separately. By steady state analysis of the new models, an equivalent optimal velocity function was defined. To determine the linear stable conditions of the new models, we introduce equivalent expressions of safe vehicular gap, and then apply small amplitude perturbation analysis and long terms of wave expansion techniques to obtain the new models' linear stable conditions. Additionally, the first order approximate solutions of the new models were drawn at the stable region, by transforming the models into typical Burger's partial differential equations with reductive perturbation method. The FVDM based numerical simulations indicate that the variable vehicular gap polices with proper parameters directly contribute to the improvement of the traffic flows' stability and the avoidance of the unstable traffic phenomena.

Variability of African Farming Systems from Phenological Analysis of NDVI Time Series

NASA Technical Reports Server (NTRS)

Vrieling, Anton; deBeurs, K. M.; Brown, Molly E.

2011-01-01

Food security exists when people have access to sufficient, safe and nutritious food at all times to meet their dietary needs. The natural resource base is one of the many factors affecting food security. Its variability and decline creates problems for local food production. In this study we characterize for sub-Saharan Africa vegetation phenology and assess variability and trends of phenological indicators based on NDVI time series from 1982 to 2006. We focus on cumulated NDVI over the season (cumNDVI) which is a proxy for net primary productivity. Results are aggregated at the level of major farming systems, while determining also spatial variability within farming systems. High temporal variability of cumNDVI occurs in semiarid and subhumid regions. The results show a large area of positive cumNDVI trends between Senegal and South Sudan. These correspond to positive CRU rainfall trends found and relate to recovery after the 1980's droughts. We find significant negative cumNDVI trends near the south-coast of West Africa (Guinea coast) and in Tanzania. For each farming system, causes of change and variability are discussed based on available literature (Appendix A). Although food security comprises more than the local natural resource base, our results can perform an input for food security analysis by identifying zones of high variability or downward trends. Farming systems are found to be a useful level of analysis. Diversity and trends found within farming system boundaries underline that farming systems are dynamic.

Causality and Cointegration Analysis between Macroeconomic Variables and the Bovespa

PubMed Central

da Silva, Fabiano Mello; Coronel, Daniel Arruda; Vieira, Kelmara Mendes

2014-01-01

The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI), industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa). The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988) causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988) long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship) in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelth month, followed by the country risk, with less than 5%. PMID:24587019

Radiograph and passive data analysis using mixed variable optimization

DOEpatents

Temple, Brian A.; Armstrong, Jerawan C.; Buescher, Kevin L.; Favorite, Jeffrey A.

2015-06-02

Disclosed herein are representative embodiments of methods, apparatus, and systems for performing radiography analysis. For example, certain embodiments perform radiographic analysis using mixed variable computation techniques. One exemplary system comprises a radiation source, a two-dimensional detector for detecting radiation transmitted through a object between the radiation source and detector, and a computer. In this embodiment, the computer is configured to input the radiographic image data from the two-dimensional detector and to determine one or more materials that form the object by using an iterative analysis technique that selects the one or more materials from hierarchically arranged solution spaces of discrete material possibilities and selects the layer interfaces from the optimization of the continuous interface data.

[Meta analysis of variables related to attention deficit hyperactivity disorder in school-age children].

PubMed

Park, Wan Ju; Seo, Ji Yeong; Kim, Mi Ye

2011-04-01

The purpose of this study was to use meta-analysis to examine recent domestic articles related to attention deficit hyperactivity disorder (ADHD) in school-age children. After reviewing 213 articles published between 1990 and 2009 from and cited in RISS, KISS, and DBpia, the researchers identified 24 studies with 440 research variables that had appropriate data for methodological study. SPSS 17.0 program was used. The outcome variables were divided into five types: Inattention, hyperactive impulsive, intrinsic, extrinsic, and academic ability variables. Effects size of overall core symptoms was 0.47 which is moderate level in terms of Cohen criteria and effects size of overall negative variables related ADHD was 0.27 which is small level. The most dominant variable related to ADHD was obtained from hyperactive-impulsive (0.70). Also academic ability (0.45), inattention (0.37), and intrinsic variables (0.29) had a small effect whereas extrinsic variables (0.13) had little effect on descriptive ADHD study. The results reveal that ADHD core symptoms have moderate effect size and peripheral negative variables related ADHD have small effect size. To improve the reliability of the meta-analysis results by minimizing publication bias, more intervention studies using appropriate study designs should be done.

Bias and Bias Correction in Multi-Site Instrumental Variables Analysis of Heterogeneous Mediator Effects

ERIC Educational Resources Information Center

Reardon, Sean F.; Unlu, Faith; Zhu, Pei; Bloom, Howard

2013-01-01

We explore the use of instrumental variables (IV) analysis with a multi-site randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, as assumption known in the instrumental variables literature as the…

Variable cost of ICU care, a micro-costing analysis.

PubMed

Karabatsou, Dimitra; Tsironi, Maria; Tsigou, Evdoxia; Boutzouka, Eleni; Katsoulas, Theodoros; Baltopoulos, George

2016-08-01

Intensive care unit (ICU) costs account for a great part of a hospital's expenses. The objective of the present study was to measure the patient-specific cost of ICU treatment, to identify the most important cost drivers in ICU and to examine the role of various contributing factors in cost configuration. A retrospective cost analysis of all ICU patients who were admitted during 2011 in a Greek General, seven-bed ICU and stayed for at least 24hours was performed, by applying bottom-up analysis. Data collected included demographics and the exact cost of every single material used for patients' care. Prices were yielded from the hospital's purchasing costs and from the national price list of the imaging and laboratory tests, which was provided by the Ministry of Health. A total of 138 patients were included. Variable cost per ICU day was €573.18. A substantial cost variation was found in the total costs obtained for individual patients (median: €3443, range: €243.70-€116,355). Medicines were responsible for more than half of the cost and antibiotics accounted for the largest part of it, followed by blood products and cardiovascular drugs. Medical cause of admission, severe illness and increased length of stay, mechanical ventilation and dialysis were the factors associated with cost escalation. ICU variable cost is patient-specific, varies according to each patient's needs and is influenced by several factors. The exact estimation of variable cost is a pre-requisite in order to control ICU expenses. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modelling and analysis of FMS productivity variables by ISM, SEM and GTMA approach

NASA Astrophysics Data System (ADS)

Jain, Vineet; Raj, Tilak

2014-09-01

Productivity has often been cited as a key factor in a flexible manufacturing system (FMS) performance, and actions to increase it are said to improve profitability and the wage earning capacity of employees. Improving productivity is seen as a key issue for survival and success in the long term of a manufacturing system. The purpose of this paper is to make a model and analysis of the productivity variables of FMS. This study was performed by different approaches viz. interpretive structural modelling (ISM), structural equation modelling (SEM), graph theory and matrix approach (GTMA) and a cross-sectional survey within manufacturing firms in India. ISM has been used to develop a model of productivity variables, and then it has been analyzed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are powerful statistical techniques. CFA is carried by SEM. EFA is applied to extract the factors in FMS by the statistical package for social sciences (SPSS 20) software and confirming these factors by CFA through analysis of moment structures (AMOS 20) software. The twenty productivity variables are identified through literature and four factors extracted, which involves the productivity of FMS. The four factors are people, quality, machine and flexibility. SEM using AMOS 20 was used to perform the first order four-factor structures. GTMA is a multiple attribute decision making (MADM) methodology used to find intensity/quantification of productivity variables in an organization. The FMS productivity index has purposed to intensify the factors which affect FMS.

Quantitative analysis of spatial variability of geotechnical parameters

NASA Astrophysics Data System (ADS)

Fang, Xing

2018-04-01

Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

Establishing Factor Validity Using Variable Reduction in Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Hofmann, Rich

1995-01-01

Using a 21-statement attitude-type instrument, an iterative procedure for improving confirmatory model fit is demonstrated within the context of the EQS program of P. M. Bentler and maximum likelihood factor analysis. Each iteration systematically eliminates the poorest fitting statement as identified by a variable fit index. (SLD)

Frequency Analysis of the RRc Variables of the MACHO Database for the LMC

NASA Astrophysics Data System (ADS)

Kovács, G.; Alcock, C.; Allsman, R.; Alves, D.; Axelrod, T.; Becker, A.; Bennett, D.; Clement, C.; Cook, K. H.; Drake, A.; Freeman, K.; Geha, M.; Griest, K.; Kurtz, D. W.; Lehner, M.; Marshall, S.; Minniti, D.; Nelson, C.; Peterson, B.; Popowski, P.; Pratt, M.; Quinn, P.; Rodgers, A.; Rowe, J.; Stubbs, C.; Sutherland, W.; Tomaney, A.; Vandehei, T.; Welch, D. L.; MACHO Collaboration

We present the first massive frequency analysis of the 1200 first overtone RR Lyrae stars in the Large Magellanic Cloud observed in the first 4.3 yr of the MACHO project. Besides the many new double-mode variables, we also discovered stars with closely spaced frequencies. These variables are most probably nonradial pulsators.

Variability search in M 31 using principal component analysis and the Hubble Source Catalogue

NASA Astrophysics Data System (ADS)

Moretti, M. I.; Hatzidimitriou, D.; Karampelas, A.; Sokolovsky, K. V.; Bonanos, A. Z.; Gavras, P.; Yang, M.

2018-06-01

Principal component analysis (PCA) is being extensively used in Astronomy but not yet exhaustively exploited for variability search. The aim of this work is to investigate the effectiveness of using the PCA as a method to search for variable stars in large photometric data sets. We apply PCA to variability indices computed for light curves of 18 152 stars in three fields in M 31 extracted from the Hubble Source Catalogue. The projection of the data into the principal components is used as a stellar variability detection and classification tool, capable of distinguishing between RR Lyrae stars, long-period variables (LPVs) and non-variables. This projection recovered more than 90 per cent of the known variables and revealed 38 previously unknown variable stars (about 30 per cent more), all LPVs except for one object of uncertain variability type. We conclude that this methodology can indeed successfully identify candidate variable stars.

The cross wavelet analysis of dengue fever variability influenced by meteorological conditions

NASA Astrophysics Data System (ADS)

Lin, Yuan-Chien; Yu, Hwa-Lung; Lee, Chieh-Han

2015-04-01

The multiyear variation of meteorological conditions induced by climate change causes the changing diffusion pattern of infectious disease and serious epidemic situation. Among them, dengue fever is one of the most serious vector-borne diseases distributed in tropical and sub-tropical regions. Dengue virus is transmitted by several species of mosquito and causing lots amount of human deaths every year around the world. The objective of this study is to investigate the impact of meteorological variables to the temporal variation of dengue fever epidemic in southern Taiwan. Several extreme and average indices of meteorological variables, i.e. temperature and humidity, were used for this analysis, including averaged, maximum and minimum temperature, and average rainfall, maximum 1-hr rainfall, and maximum 24-hr rainfall. This study plans to identify and quantify the nonlinear relationship of meteorological variables and dengue fever epidemic, finding the non-stationary time-frequency relationship and phase lag effects of those time series from 1998-2011 by using cross wavelet method. Results show that meteorological variables all have a significant time-frequency correlation region to dengue fever epidemic in frequency about one year (52 weeks). The associated phases can range from 0 to 90 degrees (0-13 weeks lag from meteorological factors to dengue incidences). Keywords: dengue fever, cross wavelet analysis, meteorological factor

A comparative modeling analysis of multiscale temporal variability of rainfall in Australia

NASA Astrophysics Data System (ADS)

Samuel, Jos M.; Sivapalan, Murugesu

2008-07-01

The effects of long-term natural climate variability and human-induced climate change on rainfall variability have become the focus of much concern and recent research efforts. In this paper, we present the results of a comparative analysis of observed multiscale temporal variability of rainfall in the Perth, Newcastle, and Darwin regions of Australia. This empirical and stochastic modeling analysis explores multiscale rainfall variability, i.e., ranging from short to long term, including within-storm patterns, and intra-annual, interannual, and interdecadal variabilities, using data taken from each of these regions. The analyses investigated how storm durations, interstorm periods, and average storm rainfall intensities differ for different climate states and demonstrated significant differences in this regard between the three selected regions. In Perth, the average storm intensity is stronger during La Niña years than during El Niño years, whereas in Newcastle and Darwin storm duration is longer during La Niña years. Increase of either storm duration or average storm intensity is the cause of higher average annual rainfall during La Niña years as compared to El Niño years. On the other hand, within-storm variability does not differ significantly between different ENSO states in all three locations. In the case of long-term rainfall variability, the statistical analyses indicated that in Newcastle the long-term rainfall pattern reflects the variability of the Interdecadal Pacific Oscillation (IPO) index, whereas in Perth and Darwin the long-term variability exhibits a step change in average annual rainfall (up in Darwin and down in Perth) which occurred around 1970. The step changes in Perth and Darwin and the switch in IPO states in Newcastle manifested differently in the three study regions in terms of changes in the annual number of rainy days or the average daily rainfall intensity or both. On the basis of these empirical data analyses, a stochastic

Choice of Control Variables in Variational Data Assimilation and Its Analysis and Forecast Impact

NASA Astrophysics Data System (ADS)

Xie, Yuanfu; Sun, Jenny; Fang, Wei-ting

2014-05-01

Choice of control variables directly impacts the analysis qualify of a variational data assimilation and its forecasts. A theory on selecting control variables for wind and moisture field is introduced for 3DVAR or 4DVAR. For a good control variable selection, Parseval's theory is applied to 3-4DVAR and the behavior of different control variables is illustrated in physical and Fourier space in terms of minimization condition, meteorological dynamic scales and practical implementation. The computational and meteorological benefits will be discussed. Numerical experiments have been performed using WRF-DA for wind control variables and CRTM for moisture control variables. It is evident of the WRF forecast improvement and faster convergence of CRTM satellite data assimilation.

Bias and Bias Correction in Multisite Instrumental Variables Analysis of Heterogeneous Mediator Effects

ERIC Educational Resources Information Center

Reardon, Sean F.; Unlu, Fatih; Zhu, Pei; Bloom, Howard S.

2014-01-01

We explore the use of instrumental variables (IV) analysis with a multisite randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, an assumption known in the IV literature as the exclusion restriction.…

Wavelet and receiver operating characteristic analysis of heart rate variability

NASA Astrophysics Data System (ADS)

McCaffery, G.; Griffith, T. M.; Naka, K.; Frennaux, M. P.; Matthai, C. C.

2002-02-01

Multiresolution wavelet analysis has been used to study the heart rate variability in two classes of patients with different pathological conditions. The scale dependent measure of Thurner et al. was found to be statistically significant in discriminating patients suffering from hypercardiomyopathy from a control set of normal subjects. We have performed Receiver Operating Characteristc (ROC) analysis and found the ROC area to be a useful measure by which to label the significance of the discrimination, as well as to describe the severity of heart dysfunction.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

PubMed

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-04

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis

NASA Astrophysics Data System (ADS)

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-01

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Clinical periodontal variables in patients with and without dementia-a systematic review and meta-analysis.

PubMed

Maldonado, Alejandra; Laugisch, Oliver; Bürgin, Walter; Sculean, Anton; Eick, Sigrun

2018-06-22

Considering the increasing number of elderly people, dementia has gained an important role in today's society. Although the contributing factors for dementia have not been fully understood, chronic periodontitis (CP) seems to have a possible link to dementia. To conduct a systematic review including meta-analysis in order to assess potential differences in clinical periodontal variables between patients with dementia and non-demented individuals. The following focused question was evaluated: is periodontitis associated with dementia? Electronic searches in two databases, MEDLINE and EMBASE, were conducted. Meta-analysis was performed with the collected data in order to find a statistically significant difference in clinical periodontal variables between the group of dementia and the cognitive normal controls. Forty-two articles remained for full text reading. Finally, seven articles met the inclusion criteria and only five studies provided data suitable for meta-analysis. Periodontal probing depth (PPD), bleeding on probing (BOP), gingival bleeding index (GBI), clinical attachment level (CAL), and plaque index (PI) were included as periodontal variables in the meta-analysis. Each variable revealed a statistically significant difference between the groups. In an attempt to reveal an overall difference between the periodontal variables in dementia patients and non-demented individuals, the chosen variables were transformed into units that resulted in a statistically significant overall difference (p < 0.00001). The current findings indicate that compared to systemically healthy individuals, demented patients show significantly worse clinical periodontal variables. However, further epidemiological studies including a high numbers of participants, the use of exact definitions both for dementia and chronic periodontitis and adjusted for cofounders is warranted. These findings appear to support the putative link between CP and dementia. Consequently, the need for

Variable Dynamic Testbed Vehicle Dynamics Analysis

DOT National Transportation Integrated Search

1996-03-01

ANTI-ROLL BAR, EMULATION, FOUR-WHEEL-STEERING, LATERAL RESPONSE CHARACTERISTICS, SIMULATION, VARIABLE DYNAMIC TESTBED VEHICLE, INTELLIGENT VEHICLE INITIATIVE OR IVI : THE VARIABLE DYNAMIC TESTBED VEHICLE (VDTV) CONCEPT HAS BEEN PROPOSED AS A TOOL...

Meta-analysis of variables affecting mouse protection efficacy of whole organism Brucella vaccines and vaccine candidates

PubMed Central

2013-01-01

Background Vaccine protection investigation includes three processes: vaccination, pathogen challenge, and vaccine protection efficacy assessment. Many variables can affect the results of vaccine protection. Brucella, a genus of facultative intracellular bacteria, is the etiologic agent of brucellosis in humans and multiple animal species. Extensive research has been conducted in developing effective live attenuated Brucella vaccines. We hypothesized that some variables play a more important role than others in determining vaccine protective efficacy. Using Brucella vaccines and vaccine candidates as study models, this hypothesis was tested by meta-analysis of Brucella vaccine studies reported in the literature. Results Nineteen variables related to vaccine-induced protection of mice against infection with virulent brucellae were selected based on modeling investigation of the vaccine protection processes. The variable "vaccine protection efficacy" was set as a dependent variable while the other eighteen were set as independent variables. Discrete or continuous values were collected from papers for each variable of each data set. In total, 401 experimental groups were manually annotated from 74 peer-reviewed publications containing mouse protection data for live attenuated Brucella vaccines or vaccine candidates. Our ANOVA analysis indicated that nine variables contributed significantly (P-value < 0.05) to Brucella vaccine protection efficacy: vaccine strain, vaccination host (mouse) strain, vaccination dose, vaccination route, challenge pathogen strain, challenge route, challenge-killing interval, colony forming units (CFUs) in mouse spleen, and CFU reduction compared to control group. The other 10 variables (e.g., mouse age, vaccination-challenge interval, and challenge dose) were not found to be statistically significant (P-value > 0.05). The protection level of RB51 was sacrificed when the values of several variables (e.g., vaccination route, vaccine viability

Effect analysis of design variables on the disc in a double-eccentric butterfly valve.

PubMed

Kang, Sangmo; Kim, Da-Eun; Kim, Kuk-Kyeom; Kim, Jun-Oh

2014-01-01

We have performed a shape optimization of the disc in an industrial double-eccentric butterfly valve using the effect analysis of design variables to enhance the valve performance. For the optimization, we select three performance quantities such as pressure drop, maximum stress, and mass (weight) as the responses and three dimensions regarding the disc shape as the design variables. Subsequently, we compose a layout of orthogonal array (L16) by performing numerical simulations on the flow and structure using a commercial package, ANSYS v13.0, and then make an effect analysis of the design variables on the responses using the design of experiments. Finally, we formulate a multiobjective function consisting of the three responses and then propose an optimal combination of the design variables to maximize the valve performance. Simulation results show that the disc thickness makes the most significant effect on the performance and the optimal design provides better performance than the initial design.

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis

PubMed Central

van de Schoot, Rens; Hox, Joop

2014-01-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation coefficient (ICC) and estimation method; maximum likelihood estimation with robust chi-squares and standard errors and Bayesian estimation, on the convergence rate are investigated. The other variables of interest were rate of inadmissible solutions and the relative parameter and standard error bias on the between level. The results showed that inadmissible solutions were obtained when there was between level collinearity and the estimation method was maximum likelihood. In the within level multicollinearity condition, all of the solutions were admissible but the bias values were higher compared with the between level collinearity condition. Bayesian estimation appeared to be robust in obtaining admissible parameters but the relative bias was higher than for maximum likelihood estimation. Finally, as expected, high ICC produced less biased results compared to medium ICC conditions. PMID:29795827

Histomorphological analysis of the variability of the human skeleton: forensic implications.

PubMed

Cummaudo, Marco; Cappella, Annalisa; Biraghi, Miranda; Raffone, Caterina; Màrquez-Grant, Nicholas; Cattaneo, Cristina

2018-01-20

One of the fundamental questions in forensic medicine and anthropology is whether or not a bone or bone fragment is human. Surprisingly at times for the extreme degradation of the bone (charred, old), DNA cannot be successfully performed and one must turn to other methods. Histological analysis at times can be proposed. However, the variability of a single human skeleton has never been tested. Forty-nine thin sections of long, flat, irregular and short bones were obtained from a well-preserved medieval adult human skeleton. A qualitative histomorphological analysis was performed in order to assess the presence of primary and secondary bone and the presence, absence and orientation of vascular canals. No histological sections exhibited woven or fibro-lamellar bone. Long bones showed a higher variability with an alternation within the same section of areas characterized by tightly packed secondary osteons and areas with scattered secondary osteons immersed in a lamellar matrix. Flat and irregular bones appeared to be characterized by a greater uniformity with scattered osteons in abundant interstitial lamellae. Some cases of "osteon banding" and "drifting osteons" were observed. Although Haversian bone represent the most frequent pattern, a histomorphological variability between different bones of the same individual, in different portions of the same bone, and in different parts of the same section has been observed. Therefore, the present study has highlighted the importance of extending research to whole skeletons without focusing only on single bones, in order to have a better understanding of the histological variability of both human and non-human bone.

The Effects of Variability and Risk in Selection Utility Analysis: An Empirical Comparison.

ERIC Educational Resources Information Center

Rich, Joseph R.; Boudreau, John W.

1987-01-01

Investigated utility estimate variability for the selection utility of using the Programmer Aptitude Test to select computer programmers. Comparison of Monte Carlo results to other risk assessment approaches (sensitivity analysis, break-even analysis, algebraic derivation of the distribtion) suggests that distribution information provided by Monte…

Analysis of watershed topography effects on summer precipitation variability in the southwestern United States

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, Dagbegnon C.; Singh, Vijay P.; Frauenfeld, Oliver W.

2014-04-01

With climate change, precipitation variability is projected to increase. The present study investigates the potential interactions between watershed characteristics and precipitation variability. The watershed is considered as a functional unit that may impact seasonal precipitation. The study uses historical precipitation data from 370 meteorological stations over the last five decades, and digital elevation data from regional watersheds in the southwestern United States. This domain is part of the North American Monsoon region, and the summer period (June-July-August, JJA) was considered. Based on an initial analysis for 1895-2011, the JJA precipitation accounts, on average, for 22-43% of the total annual precipitation, with higher percentages in the arid part of the region. The unique contribution of this research is that entropy theory is used to address precipitation variability in time and space. An entropy-based disorder index was computed for each station's precipitation record. The JJA total precipitation and number of precipitation events were considered in the analysis. The precipitation variability potentially induced by watershed topography was investigated using spatial regionalization combining principal component and cluster analysis. It was found that the disorder in precipitation total and number of events tended to be higher in arid regions. The spatial pattern showed that the entropy-based variability in precipitation amount and number of events gradually increased from east to west in the southwestern United States. Regarding the watershed topography influence on summer precipitation patterns, hilly relief has a stabilizing effect on seasonal precipitation variability in time and space. The results show the necessity to include watershed topography in global and regional climate model parameterizations.

Genome-wide analysis of multiethnic cohorts identifies new loci influencing intraocular pressure and susceptibility to glaucoma

PubMed Central

Vitart, Veronique; Nag, Abhishek; Hewitt, Alex W; Höhn, René; Venturini, Cristina; Mirshahi, Alireza; Ramdas, Wishal D.; Thorleifsson, Gudmar; Vithana, Eranga; Khor, Chiea-Chuen; Stefansson, Arni B; Liao, Jiemin; Haines, Jonathan L; Amin, Najaf; Wang, Ya Xing; Wild, Philipp S; Ozel, Ayse B; Li, Jun Z; Fleck, Brian W; Zeller, Tanja; Staffieri, Sandra E; Teo, Yik-Ying; Cuellar-Partida, Gabriel; Luo, Xiaoyan; Allingham, R Rand; Richards, Julia E; Senft, Andrea; Karssen, Lennart C; Zheng, Yingfeng; Bellenguez, Céline; Xu, Liang; Iglesias, Adriana I; Wilson, James F; Kang, Jae H; van Leeuwen, Elisabeth M; Jonsson, Vesteinn; Thorsteinsdottir, Unnur; Despriet, Dominiek D.G.; Ennis, Sarah; Moroi, Sayoko E; Martin, Nicholas G; Jansonius, Nomdo M; Yazar, Seyhan; Tai, E-Shyong; Amouyel, Philippe; Kirwan, James; van Koolwijk, Leonieke M.E.; Hauser, Michael A; Jonasson, Fridbert; Leo, Paul; Loomis, Stephanie J; Fogarty, Rhys; Rivadeneira, Fernando; Kearns, Lisa; Lackner, Karl J; de Jong, Paulus T.V.M.; Simpson, Claire L; Pennell, Craig E; Oostra, Ben A; Uitterlinden, André G; Saw, Seang-Mei; Lotery, Andrew J; Bailey-Wilson, Joan E; Hofman, Albert; Vingerling, Johannes R; Maubaret, Cécilia; Pfeiffer, Norbert; Wolfs, Roger C.W.; Lemij, Hans G; Young, Terri L; Pasquale, Louis R; Delcourt, Cécile; Spector, Timothy D; Klaver, Caroline C.W.; Small, Kerrin S; Burdon, Kathryn P; Stefansson, Kari; Wong, Tien-Yin; Viswanathan, Ananth; Mackey, David A; Craig, Jamie E; Wiggs, Janey L; van Duijn, Cornelia M; Hammond, Christopher J; Aung, Tin

2014-01-01

Elevated intraocular pressure (IOP) is an important risk factor in developing glaucoma and IOP variability may herald glaucomatous development or progression. We report the results of a genome-wide association study meta-analysis of 18 population cohorts from the International Glaucoma Genetics Consortium (IGGC), comprising 35,296 multiethnic participants for IOP. We confirm genetic association of known loci for IOP and primary open angle glaucoma (POAG) and identify four new IOP loci located on chromosome 3q25.31 within the FNDC3B gene (p=4.19×10−08 for rs6445055), two on chromosome 9 (p=2.80×10−11 for rs2472493 near ABCA1 and p=6.39×10−11 for rs8176693 within ABO) and one on chromosome 11p11.2 (best p=1.04×10−11 for rs747782). Separate meta-analyses of four independent POAG cohorts, totaling 4,284 cases and 95,560 controls, show that three of these IOP loci are also associated with POAG. PMID:25173106

Finite-size analysis of a continuous-variable quantum key distribution

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

Leverrier, Anthony; Grosshans, Frederic; Grangier, Philippe

2010-06-15

The goal of this paper is to extend the framework of finite-size analysis recently developed for quantum key distribution to continuous-variable protocols. We do not solve this problem completely here, and we mainly consider the finite-size effects on the parameter estimation procedure. Despite the fact that some questions are left open, we are able to give an estimation of the secret key rate for protocols which do not contain a postselection procedure. As expected, these results are significantly more pessimistic than those obtained in the asymptotic regime. However, we show that recent continuous-variable protocols are able to provide fully securemore » secret keys in the finite-size scenario, over distances larger than 50 km.« less

Video pulse rate variability analysis in stationary and motion conditions.

PubMed

Melchor Rodríguez, Angel; Ramos-Castro, J

2018-01-29

In the last few years, some studies have measured heart rate (HR) or heart rate variability (HRV) parameters using a video camera. This technique focuses on the measurement of the small changes in skin colour caused by blood perfusion. To date, most of these works have obtained HRV parameters in stationary conditions, and there are practically no studies that obtain these parameters in motion scenarios and by conducting an in-depth statistical analysis. In this study, a video pulse rate variability (PRV) analysis is conducted by measuring the pulse-to-pulse (PP) intervals in stationary and motion conditions. Firstly, given the importance of the sampling rate in a PRV analysis and the low frame rate of commercial cameras, we carried out an analysis of two models to evaluate their performance in the measurements. We propose a selective tracking method using the Viola-Jones and KLT algorithms, with the aim of carrying out a robust video PRV analysis in stationary and motion conditions. Data and results of the proposed method are contrasted with those reported in the state of the art. The webcam achieved better results in the performance analysis of video cameras. In stationary conditions, high correlation values were obtained in PRV parameters with results above 0.9. The PP time series achieved an RMSE (mean ± standard deviation) of 19.45 ± 5.52 ms (1.70 ± 0.75 bpm). In the motion analysis, most of the PRV parameters also achieved good correlation results, but with lower values as regards stationary conditions. The PP time series presented an RMSE of 21.56 ± 6.41 ms (1.79 ± 0.63 bpm). The statistical analysis showed good agreement between the reference system and the proposed method. In stationary conditions, the results of PRV parameters were improved by our method in comparison with data reported in related works. An overall comparative analysis of PRV parameters in motion conditions was more limited due to the lack of studies or studies

SVAw - a web-based application tool for automated surrogate variable analysis of gene expression studies

PubMed Central

2013-01-01

Background Surrogate variable analysis (SVA) is a powerful method to identify, estimate, and utilize the components of gene expression heterogeneity due to unknown and/or unmeasured technical, genetic, environmental, or demographic factors. These sources of heterogeneity are common in gene expression studies, and failing to incorporate them into the analysis can obscure results. Using SVA increases the biological accuracy and reproducibility of gene expression studies by identifying these sources of heterogeneity and correctly accounting for them in the analysis. Results Here we have developed a web application called SVAw (Surrogate variable analysis Web app) that provides a user friendly interface for SVA analyses of genome-wide expression studies. The software has been developed based on open source bioconductor SVA package. In our software, we have extended the SVA program functionality in three aspects: (i) the SVAw performs a fully automated and user friendly analysis workflow; (ii) It calculates probe/gene Statistics for both pre and post SVA analysis and provides a table of results for the regression of gene expression on the primary variable of interest before and after correcting for surrogate variables; and (iii) it generates a comprehensive report file, including graphical comparison of the outcome for the user. Conclusions SVAw is a web server freely accessible solution for the surrogate variant analysis of high-throughput datasets and facilitates removing all unwanted and unknown sources of variation. It is freely available for use at http://psychiatry.igm.jhmi.edu/sva. The executable packages for both web and standalone application and the instruction for installation can be downloaded from our web site. PMID:23497726

Analysis of trends and dominant periodicities in drought variables in India: A wavelet transform based approach

NASA Astrophysics Data System (ADS)

Joshi, Nitin; Gupta, Divya; Suryavanshi, Shakti; Adamowski, Jan; Madramootoo, Chandra A.

2016-12-01

In this study, seasonal trends as well as dominant and significant periods of variability of drought variables were analyzed for 30 rainfall subdivisions in India over 141 years (1871-2012). Standardized precipitation index (SPI) was used as a meteorological drought indicator, and various drought variables (monsoon SPI, non-monsoon SPI, yearly SPI, annual drought duration, annual drought severity and annual drought peak) were analyzed. Discrete wavelet transform was used in conjunction with the Mann-Kendall test to analyze trends and dominant periodicities associated with the drought variables. Furthermore, continuous wavelet transform (CWT) based global wavelet spectrum was used to analyze significant periods of variability associated with the drought variables. From the trend analysis, we observed that over the second half of the 20th century, drought occurrences increased significantly in subdivisions of Northeast and Central India. In both short-term (2-8 years) and decadal (16-32 years) periodicities, the drought variables were found to influence the trend. However, CWT analysis indicated that the dominant periodic components were not significant for most of the geographical subdivisions. Although inter-annual and inter-decadal periodic components play an important role, they may not completely explain the variability associated with the drought variables across the country.

NASA GEOS-3/TRMM Re-analysis: Capturing Observed Tropical Rainfall Variability in Global Analysis for Climate Research

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.

2004-01-01

Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has

Ratio Variables in Aggregate Data Analysis: Their Uses, Problems, and Alternatives.

ERIC Educational Resources Information Center

Bollen, Kenneth A.; Ward, Sally

1979-01-01

Three different uses of ratio variables in aggregate data analysis are discussed: (1) as measures of theoretical concepts, (2) as a means to control an extraneous factor, and (3) as a correction for heteroscedasticity. Alternatives to ratios for each of these cases are discussed and evaluated. (Author/JKS)

Conjoint Analysis: A Study of the Effects of Using Person Variables.

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

Three statistical techniques--conjoint analysis, a multiple linear regression model, and a multiple linear regression model with a surrogate person variable--were used to estimate the relative importance of five university attributes for students in the process of selecting a college. The five attributes include: availability and variety of…

Fourier Analysis of First-Overtone RR Lyrae Variables in the LMC

NASA Astrophysics Data System (ADS)

Clement, C. M.; Muzzin, A. V.; Rowe, J. F.; MACHO Collaboration

2002-05-01

Simon's (1989, ApJ, 343, L17) Fourier decomposition technique has been applied to the V magnitudes of the first-overtone RR Lyrae (RR1) variables in 16 LMC fields observed by the MACHO collaboration. The Fourier coefficients R21 and φ 31 derived for these stars have been compared with the coefficients of RR1 variables in the galactic globular clusters Omega Centauri, M2, M3, M5, M68, M107 (NGC 6171) and NGC 6441. Our analysis indicates that the majority of the LMC RR1 variables have coefficients similar to those in the Oosterhoff type I (OoI) clusters M3 and M5 and to the OoI variables in Omega Centauri. In a study of hydrodynamic pulsation models of first overtone RR Lyrae variables, Simon & Clement (1993, ApJ, 410, 526) found that the Fourier phase parameter φ 31 depends essentially on mass and luminosity. From this, we conclude that the masses and luminosities of most of the RR1 variables in the LMC are comparable to those of the OoI RR1 variables in Omega Centauri, M3 and M5, a fact that should be considered when RR Lyrae variables are used for determining the distance to the LMC. The MACHO collaboration includes C. Alcock, R. A. Allsman, D. R. Alves, T. S. Axelrod, A. C. Becker, D. P. Bennet, K. H. Cook, A. J. Drake, K. C. Freeman, M. Geha, K. Griest, M. J. Lehner, S. L. Marshall, D. Minniti, C. A. Nelson, B. A. Peterson, P. Popowski, M. R. Pratt, P. J. Quinn, C. W. Stubbs, W. Sutherland, T. Vandehel and D. L. Welch. This research has been supported in part by the Natural Sciences and Engineering Research Council of Canada.

The association between mood state and chronobiological characteristics in bipolar I disorder: a naturalistic, variable cluster analysis-based study.

PubMed

Gonzalez, Robert; Suppes, Trisha; Zeitzer, Jamie; McClung, Colleen; Tamminga, Carol; Tohen, Mauricio; Forero, Angelica; Dwivedi, Alok; Alvarado, Andres

2018-02-19

Multiple types of chronobiological disturbances have been reported in bipolar disorder, including characteristics associated with general activity levels, sleep, and rhythmicity. Previous studies have focused on examining the individual relationships between affective state and chronobiological characteristics. The aim of this study was to conduct a variable cluster analysis in order to ascertain how mood states are associated with chronobiological traits in bipolar I disorder (BDI). We hypothesized that manic symptomatology would be associated with disturbances of rhythm. Variable cluster analysis identified five chronobiological clusters in 105 BDI subjects. Cluster 1, comprising subjective sleep quality was associated with both mania and depression. Cluster 2, which comprised variables describing the degree of rhythmicity, was associated with mania. Significant associations between mood state and cluster analysis-identified chronobiological variables were noted. Disturbances of mood were associated with subjectively assessed sleep disturbances as opposed to objectively determined, actigraphy-based sleep variables. No associations with general activity variables were noted. Relationships between gender and medication classes in use and cluster analysis-identified chronobiological characteristics were noted. Exploratory analyses noted that medication class had a larger impact on these relationships than the number of psychiatric medications in use. In a BDI sample, variable cluster analysis was able to group related chronobiological variables. The results support our primary hypothesis that mood state, particularly mania, is associated with chronobiological disturbances. Further research is required in order to define these relationships and to determine the directionality of the associations between mood state and chronobiological characteristics.

A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

PubMed Central

2009-01-01

Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical. Conclusion Feature variability can

Design sensitivity analysis with Applicon IFAD using the adjoint variable method

NASA Technical Reports Server (NTRS)

Frederick, Marjorie C.; Choi, Kyung K.

1984-01-01

A numerical method is presented to implement structural design sensitivity analysis using the versatility and convenience of existing finite element structural analysis program and the theoretical foundation in structural design sensitivity analysis. Conventional design variables, such as thickness and cross-sectional areas, are considered. Structural performance functionals considered include compliance, displacement, and stress. It is shown that calculations can be carried out outside existing finite element codes, using postprocessing data only. That is, design sensitivity analysis software does not have to be imbedded in an existing finite element code. The finite element structural analysis program used in the implementation presented is IFAD. Feasibility of the method is shown through analysis of several problems, including built-up structures. Accurate design sensitivity results are obtained without the uncertainty of numerical accuracy associated with selection of a finite difference perturbation.

Methodological Variables in the Analysis of Cell-Free DNA.

PubMed

Bronkhorst, Abel Jacobus; Aucamp, Janine; Pretorius, Piet J

2016-01-01

In recent years, cell-free DNA (cfDNA) analysis has received increasing amounts of attention as a potential non-invasive screening tool for the early detection of genetic aberrations and a wide variety of diseases, especially cancer. However, except for some prenatal tests and BEAMing, a technique used to detect mutations in various genes of cancer patients, cfDNA analysis is not yet routinely applied in clinical practice. Although some confusing biological factors inherent to the in vivo setting play a key part, it is becoming increasingly clear that this struggle is mainly due to the lack of an analytical consensus, especially as regards quantitative analyses of cfDNA. In order to use quantitative analysis of cfDNA with confidence, process optimization and standardization are crucial. In this work we aim to elucidate the most confounding variables of each preanalytical step that must be considered for process optimization and equivalence of procedures.

Jitter Reduces Response-Time Variability in ADHD: An Ex-Gaussian Analysis.

PubMed

Lee, Ryan W Y; Jacobson, Lisa A; Pritchard, Alison E; Ryan, Matthew S; Yu, Qilu; Denckla, Martha B; Mostofsky, Stewart; Mahone, E Mark

2015-09-01

"Jitter" involves randomization of intervals between stimulus events. Compared with controls, individuals with ADHD demonstrate greater intrasubject variability (ISV) performing tasks with fixed interstimulus intervals (ISIs). Because Gaussian curves mask the effect of extremely slow or fast response times (RTs), ex-Gaussian approaches have been applied to study ISV. This study applied ex-Gaussian analysis to examine the effects of jitter on RT variability in children with and without ADHD. A total of 75 children, aged 9 to 14 years (44 ADHD, 31 controls), completed a go/no-go test with two conditions: fixed ISI and jittered ISI. ADHD children showed greater variability, driven by elevations in exponential (tau), but not normal (sigma) components of the RT distribution. Jitter decreased tau in ADHD to levels not statistically different than controls, reducing lapses in performance characteristic of impaired response control. Jitter may provide a nonpharmacologic mechanism to facilitate readiness to respond and reduce lapses from sustained (controlled) performance. © 2012 SAGE Publications.

Staging Sleep in Polysomnograms: Analysis of Inter-Scorer Variability

PubMed Central

Younes, Magdy; Raneri, Jill; Hanly, Patrick

2016-01-01

Study Objectives: To determine the reasons for inter-scorer variability in sleep staging of polysomnograms (PSGs). Methods: Fifty-six PSGs were scored (5-stage sleep scoring) by 2 experienced technologists, (first manual, M1). Months later, the technologists edited their own scoring (second manual, M2) based upon feedback from the investigators that highlighted differences between their scoring. The PSGs were then scored with an automatic system (Auto) and the technologists edited them, epoch-by-epoch (Edited-Auto). This resulted in 6 different manual scores for each PSG. Epochs were classified as scorer errors (one M1 score differed from the other 5 scores), scorer bias (all 3 scores of each technologist were similar, but differed from the other technologist) and equivocal (sleep scoring was inconsistent within and between technologists). Results: Percent agreement after M1 was 78.9% ± 9.0% and was unchanged after M2 (78.1% ± 9.7%) despite numerous edits (≈40/PSG) by the scorers. Agreement in Edited-Auto was higher (86.5% ± 6.4%, p < 1E−9). Scorer errors (< 2% of epochs) and scorer bias (3.5% ± 2.3% of epochs) together accounted for < 20% of M1 disagreements. A large number of epochs (92 ± 44/PSG) with scoring agreement in M1 were subsequently changed in M2 and/or Edited-Auto. Equivocal epochs, which showed scoring inconsistency, accounted for 28% ± 12% of all epochs, and up to 76% of all epochs in individual patients. Disagreements were largely between awake/NREM, N1/N2, and N2/N3 sleep. Conclusion: Inter-scorer variability is largely due to epochs that are difficult to classify. Availability of digitally identified events (e.g., spindles) or calculated variables (e.g., depth of sleep, delta wave duration) during scoring may greatly reduce scoring variability. Citation: Younes M, Raneri J, Hanly P. Staging sleep in polysomnograms: analysis of inter-scorer variability. J Clin Sleep Med 2016;12(6):885–894. PMID:27070243

[A meta-analysis of the variables related to depression in Korean patients with a stroke].

PubMed

Park, Eun Young; Shin, In Soo; Kim, Jung Hee

2012-08-01

The purpose of this study was to use meta-analysis to evaluate the variables related to depression in patients who have had a stroke. The materials of this study were based on 16 variables obtained from 26 recent studies over a span of 10 years which were selected from doctoral dissertations, master's thesis and published articles. Related variables were categorized into sixteen variables and six variable groups which included general characteristics of the patients, disease characteristics, psychological state, physical function, basic needs, and social variables. Also, the classification of six defensive and three risk variables group was based on the negative or positive effect of depression. The quality of life (ES=-.79) and acceptance of disability (ES=-.64) were highly correlated with depression in terms of defensive variables. For risk variables, anxiety (ES=.66), stress (ES=.53) showed high correlation effect size among the risk variables. These findings showed that defensive and risk variables were related to depression among stroke patients. Psychological interventions and improvement in physical functions should be effective in decreasing depression among stroke patients.

Clinical and multiple gene expression variables in survival analysis of breast cancer: Analysis with the hypertabastic survival model

PubMed Central

2012-01-01

Background We explore the benefits of applying a new proportional hazard model to analyze survival of breast cancer patients. As a parametric model, the hypertabastic survival model offers a closer fit to experimental data than Cox regression, and furthermore provides explicit survival and hazard functions which can be used as additional tools in the survival analysis. In addition, one of our main concerns is utilization of multiple gene expression variables. Our analysis treats the important issue of interaction of different gene signatures in the survival analysis. Methods The hypertabastic proportional hazards model was applied in survival analysis of breast cancer patients. This model was compared, using statistical measures of goodness of fit, with models based on the semi-parametric Cox proportional hazards model and the parametric log-logistic and Weibull models. The explicit functions for hazard and survival were then used to analyze the dynamic behavior of hazard and survival functions. Results The hypertabastic model provided the best fit among all the models considered. Use of multiple gene expression variables also provided a considerable improvement in the goodness of fit of the model, as compared to use of only one. By utilizing the explicit survival and hazard functions provided by the model, we were able to determine the magnitude of the maximum rate of increase in hazard, and the maximum rate of decrease in survival, as well as the times when these occurred. We explore the influence of each gene expression variable on these extrema. Furthermore, in the cases of continuous gene expression variables, represented by a measure of correlation, we were able to investigate the dynamics with respect to changes in gene expression. Conclusions We observed that use of three different gene signatures in the model provided a greater combined effect and allowed us to assess the relative importance of each in determination of outcome in this data set. These

Multi-locus variable number tandem repeat analysis for Escherichia coli causing extraintestinal infections.

PubMed

Manges, Amee R; Tellis, Patricia A; Vincent, Caroline; Lifeso, Kimberley; Geneau, Geneviève; Reid-Smith, Richard J; Boerlin, Patrick

2009-11-01

Discriminatory genotyping methods for the analysis of Escherichia coli other than O157:H7 are necessary for public health-related activities. A new multi-locus variable number tandem repeat analysis protocol is presented; this method achieves an index of discrimination of 99.5% and is reproducible and valid when tested on a collection of 836 diverse E. coli.

Heterogeneity of Prognostic Studies of 24-Hour Blood Pressure Variability: Systematic Review and Meta-Analysis

PubMed Central

Taylor, Kathryn S.; Heneghan, Carl J.; Stevens, Richard J.; Adams, Emily C.; Nunan, David; Ward, Alison

2015-01-01

In addition to mean blood pressure, blood pressure variability is hypothesized to have important prognostic value in evaluating cardiovascular risk. We aimed to assess the prognostic value of blood pressure variability within 24 hours. Using MEDLINE, EMBASE and Cochrane Library to April 2013, we conducted a systematic review of prospective studies of adults, with at least one year follow-up and any day, night or 24-hour blood pressure variability measure as a predictor of one or more of the following outcomes: all-cause mortality, cardiovascular mortality, all cardiovascular events, stroke and coronary heart disease. We examined how blood pressure variability is defined and how its prognostic use is reported. We analysed relative risks adjusted for covariates including the appropriate mean blood pressure and considered the potential for meta-analysis. Our analysis of methods included 24 studies and analysis of predictions included 16 studies. There were 36 different measures of blood pressure variability and 13 definitions of night- and day-time periods. Median follow-up was 5.5 years (interquartile range 4.2–7.0). Comparing measures of dispersion, coefficient of variation was less well researched than standard deviation. Night dipping based on percentage change was the most researched measure and the only measure for which data could be meaningfully pooled. Night dipping or lower night-time blood pressure was associated with lower risk of cardiovascular events. The interpretation and use in clinical practice of 24-hour blood pressure variability, as an important prognostic indicator of cardiovascular events, is hampered by insufficient evidence and divergent methodologies. We recommend greater standardisation of methods. PMID:25984791

Analysis of variability of tropical Pacific sea surface temperatures

NASA Astrophysics Data System (ADS)

Davies, Georgina; Cressie, Noel

2016-11-01

Sea surface temperature (SST) in the Pacific Ocean is a key component of many global climate models and the El Niño-Southern Oscillation (ENSO) phenomenon. We shall analyse SST for the period November 1981-December 2014. To study the temporal variability of the ENSO phenomenon, we have selected a subregion of the tropical Pacific Ocean, namely the Niño 3.4 region, as it is thought to be the area where SST anomalies indicate most clearly ENSO's influence on the global atmosphere. SST anomalies, obtained by subtracting the appropriate monthly averages from the data, are the focus of the majority of previous analyses of the Pacific and other oceans' SSTs. Preliminary data analysis showed that not only Niño 3.4 spatial means but also Niño 3.4 spatial variances varied with month of the year. In this article, we conduct an analysis of the raw SST data and introduce diagnostic plots (here, plots of variability vs. central tendency). These plots show strong negative dependence between the spatial standard deviation and the spatial mean. Outliers are present, so we consider robust regression to obtain intercept and slope estimates for the 12 individual months and for all-months-combined. Based on this mean-standard deviation relationship, we define a variance-stabilizing transformation. On the transformed scale, we describe the Niño 3.4 SST time series with a statistical model that is linear, heteroskedastic, and dynamical.

An Analysis of the Beaufort Sea Thermohaline Structure and Variability, and Its Effects on Acoustic Propagation

DTIC Science & Technology

2016-06-01

BEAUFORT SEA THERMOHALINE STRUCTURE AND VARIABILITY, AND ITS EFFECTS ON ACOUSTIC PROPAGATION by Annalise N. Pearson June 2016 Thesis...STRUCTURE AND VARIABILITY, AND ITS EFFECTS ON ACOUSTIC PROPAGATION 5. FUNDING NUMBERS 6. AUTHOR(S) Annalise N. Pearson 7. PERFORMING ORGANIZATION...public release; distribution is unlimited AN ANALYSIS OF THE BEAUFORT SEA THERMOHALINE STRUCTURE AND VARIABILITY, AND ITS EFFECTS ON ACOUSTIC

Quantifying inter-laboratory variability in stable isotope analysis of ancient skeletal remains.

PubMed

Pestle, William J; Crowley, Brooke E; Weirauch, Matthew T

2014-01-01

Over the past forty years, stable isotope analysis of bone (and tooth) collagen and hydroxyapatite has become a mainstay of archaeological and paleoanthropological reconstructions of paleodiet and paleoenvironment. Despite this method's frequent use across anthropological subdisciplines (and beyond), the present work represents the first attempt at gauging the effects of inter-laboratory variability engendered by differences in a) sample preparation, and b) analysis (instrumentation, working standards, and data calibration). Replicate analyses of a 14C-dated ancient human bone by twenty-one archaeological and paleoecological stable isotope laboratories revealed significant inter-laboratory isotopic variation for both collagen and carbonate. For bone collagen, we found a sizeable range of 1.8‰ for δ13Ccol and 1.9‰ for δ15Ncol among laboratories, but an interpretatively insignificant average pairwise difference of 0.2‰ and 0.4‰ for δ13Ccol and δ15Ncol respectively. For bone hydroxyapatite the observed range increased to a troublingly large 3.5‰ for δ13Cap and 6.7‰ for δ18Oap, with average pairwise differences of 0.6‰ for δ13Cap and a disquieting 2.0‰ for δ18Oap. In order to assess the effects of preparation versus analysis on isotopic variability among laboratories, a subset of the samples prepared by the participating laboratories were analyzed a second time on the same instrument. Based on this duplicate analysis, it was determined that roughly half of the isotopic variability among laboratories could be attributed to differences in sample preparation, with the other half resulting from differences in analysis (instrumentation, working standards, and data calibration). These findings have serious implications for choices made in the preparation and extraction of target biomolecules, the comparison of results obtained from different laboratories, and the interpretation of small differences in bone collagen and hydroxyapatite isotope values

Quantifying Inter-Laboratory Variability in Stable Isotope Analysis of Ancient Skeletal Remains

PubMed Central

Pestle, William J.; Crowley, Brooke E.; Weirauch, Matthew T.

2014-01-01

Over the past forty years, stable isotope analysis of bone (and tooth) collagen and hydroxyapatite has become a mainstay of archaeological and paleoanthropological reconstructions of paleodiet and paleoenvironment. Despite this method's frequent use across anthropological subdisciplines (and beyond), the present work represents the first attempt at gauging the effects of inter-laboratory variability engendered by differences in a) sample preparation, and b) analysis (instrumentation, working standards, and data calibration). Replicate analyses of a 14C-dated ancient human bone by twenty-one archaeological and paleoecological stable isotope laboratories revealed significant inter-laboratory isotopic variation for both collagen and carbonate. For bone collagen, we found a sizeable range of 1.8‰ for δ13Ccol and 1.9‰ for δ15Ncol among laboratories, but an interpretatively insignificant average pairwise difference of 0.2‰ and 0.4‰ for δ13Ccol and δ15Ncol respectively. For bone hydroxyapatite the observed range increased to a troublingly large 3.5‰ for δ13Cap and 6.7‰ for δ18Oap, with average pairwise differences of 0.6‰ for δ13Cap and a disquieting 2.0‰ for δ18Oap. In order to assess the effects of preparation versus analysis on isotopic variability among laboratories, a subset of the samples prepared by the participating laboratories were analyzed a second time on the same instrument. Based on this duplicate analysis, it was determined that roughly half of the isotopic variability among laboratories could be attributed to differences in sample preparation, with the other half resulting from differences in analysis (instrumentation, working standards, and data calibration). These findings have serious implications for choices made in the preparation and extraction of target biomolecules, the comparison of results obtained from different laboratories, and the interpretation of small differences in bone collagen and hydroxyapatite isotope values

Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer.

PubMed

Pacheco Castro, Roger; Pacheco Ávila, Julia; Ye, Ming; Cabrera Sansores, Armando

2018-01-01

This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box-plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously. © 2017, National Ground Water Association.

The use of functional data analysis to study variability in childrens speech: Further data

NASA Astrophysics Data System (ADS)

Koenig, Laura L.; Lucero, Jorge C.

2002-05-01

Much previous research has reported increased token-to-token variability in children relative to adults, but the sources and implications of this variability remain matters of debate. Recently, functional data analysis has been used as a tool to gain greater insight into the nature of variability in children's and adults' speech data. In FDA, signals are time-normalized using a smooth function of time. The magnitude of the time-warping function provides an index of phasing (temporal) variability, and a separate index of amplitude variability is calculated from the time-normalized signal. Here, oral airflow data are analyzed from 5-year-olds, 10-year-olds, and adult women producing laryngeal and oral fricatives (/h, s, z/). The preliminary FDA results show that children generally have higher temporal and amplitude indices than adults, suggesting greater variability both in gestural timing and magnitude. However, individual patterns are evident in the relative magnitude of the two indices, and in which consonants show the highest values. The time-varying patterns of flow variability over time in /s/ are also explored as a method of inferring relative variability among laryngeal and oral gestures. [Work supported by NIH and CNPq, Brazil.

Psychosocial variables and time to injury onset: a hurdle regression analysis model.

PubMed

Sibold, Jeremy; Zizzi, Samuel

2012-01-01

Psychological variables have been shown to be related to athletic injury and time missed from participation in sport. We are unaware of any empirical examination of the influence of psychological variables on time to onset of injury. To examine the influence of orthopaedic and psychosocial variables on time to injury in college athletes. One hundred seventy-seven (men 5 116, women 5 61; age 5 19.45 6 1.39 years) National Collegiate Athletic Association Division II athletes. Hurdle regression analysis (HRA) was used to determine the influence of predictor variables on days to first injury. Worry (z = 2.98, P = .003), concentration disruption (z = -3.95, P < .001), and negative life-event stress (z = 5.02, P < .001) were robust predictors of days to injury. Orthopaedic risk score was not a predictor (z = 1.28, P = .20). These findings support previous research on the stress-injury relationship, and our group is the first to use HRA in athletic injury data. These data support the addition of psychological screening as part of preseason health examinations for collegiate athletes.

Receiver Operating Characteristic Curve Analysis of Beach Water Quality Indicator Variables

PubMed Central

Morrison, Ann Michelle; Coughlin, Kelly; Shine, James P.; Coull, Brent A.; Rex, Andrea C.

2003-01-01

Receiver operating characteristic (ROC) curve analysis is a simple and effective means to compare the accuracies of indicator variables of bacterial beach water quality. The indicator variables examined in this study were previous day's Enterococcus density and antecedent rainfall at 24, 48, and 96 h. Daily Enterococcus densities and 15-min rainfall values were collected during a 5-year (1996 to 2000) study of four Boston Harbor beaches. The indicator variables were assessed for their ability to correctly classify water as suitable or unsuitable for swimming at a maximum threshold Enterococcus density of 104 CFU/100 ml. Sensitivity and specificity values were determined for each unique previous day's Enterococcus density and antecedent rainfall volume and used to construct ROC curves. The area under the ROC curve was used to compare the accuracies of the indicator variables. Twenty-four-hour antecedent rainfall classified elevated Enterococcus densities more accurately than previous day's Enterococcus density (P = 0.079). An empirically derived threshold for 48-h antecedent rainfall, corresponding to a sensitivity of 0.75, was determined from the 1996 to 2000 data and evaluated to ascertain if the threshold would produce a 0.75 sensitivity with independent water quality data collected in 2001 from the same beaches. PMID:14602593

Dark Endothelial Spots After Descemet Membrane Endothelial Keratoplasty May Appear as Recurrent Fuchs Dystrophy or Herald Graft Failure or Rejection.

PubMed

Zygoura, Vasiliki; Baydoun, Lamis; Monnereau, Claire; Satué, Maria; Oellerich, Silke; Melles, Gerrit R J

2017-12-01

To evaluate the clinical significance of dark spots in the donor endothelial cell layer as observed with specular microscopy, in patients who underwent Descemet membrane endothelial keratoplasty (DMEK) for Fuchs endothelial dystrophy (FED). Specular microscopy images of 83 consecutive eyes up to 7 years after DMEK were retrospectively reviewed in a masked fashion for the presence of dark spots and morphologic changes in the endothelial cell layer and processed for endothelial cell density (ECD) measurements. A normal endothelial cell layer was found in 52/83 eyes (62.7%) (group 0). In the remaining 31/83 eyes, various dark discolorations with or without altered endothelial cell morphology were categorized into 4 groups. Dark spots were classified as artifacts in 10/83 (12.0%) eyes (group I) and as "superimposed" dots in 10/83 (12.0%) eyes (group II), that is, optical irregularities slightly anterior to a healthy endothelial cell layer. In 11/83 (13.3%) eyes, endothelial stress was characterized by dark grayish discolorations and/or nuclear activation (group III). Most of the latter eyes also had a significant ECD decrease; 3 of these eyes later developed secondary graft failure, of which one was preceded by allograft rejection. None of the eyes showed recurrent guttae typical for FED (group IV). Dark endothelial spots after DMEK for FED may not represent a recurrent disease, but tissue irregularities just anterior to the graft. However, if associated with changes in endothelial cell morphology, nuclear activation and/or ECD decrease, dark discolorations may reflect "cellular stress" heralding secondary graft failure or (subclinical) allograft rejection.

Levey-Jennings Analysis Uncovers Unsuspected Causes of Immunohistochemistry Stain Variability.

PubMed

Vani, Kodela; Sompuram, Seshi R; Naber, Stephen P; Goldsmith, Jeffrey D; Fulton, Regan; Bogen, Steven A

Almost all clinical laboratory tests use objective, quantitative measures of quality control (QC), incorporating Levey-Jennings analysis and Westgard rules. Clinical immunohistochemistry (IHC) testing, in contrast, relies on subjective, qualitative QC review. The consequences of using Levey-Jennings analysis for QC assessment in clinical IHC testing are not known. To investigate this question, we conducted a 1- to 2-month pilot test wherein the QC for either human epidermal growth factor receptor 2 (HER-2) or progesterone receptor (PR) in 3 clinical IHC laboratories was quantified and analyzed with Levey-Jennings graphs. Moreover, conventional tissue controls were supplemented with a new QC comprised of HER-2 or PR peptide antigens coupled onto 8 μm glass beads. At institution 1, this more stringent analysis identified a decrease in the HER-2 tissue control that had escaped notice by subjective evaluation. The decrement was due to heterogeneity in the tissue control itself. At institution 2, we identified a 1-day sudden drop in the PR tissue control, also undetected by subjective evaluation, due to counterstain variability. At institution 3, a QC shift was identified, but only with 1 of 2 controls mounted on each slide. The QC shift was due to use of the instrument's selective reagent drop zones dispense feature. None of these events affected patient diagnoses. These case examples illustrate that subjective QC evaluation of tissue controls can detect gross assay failure but not subtle changes. The fact that QC issues arose from each site, and in only a pilot study, suggests that immunohistochemical stain variability may be an underappreciated problem.

An investigation of dynamic-analysis methods for variable-geometry structures

NASA Technical Reports Server (NTRS)

Austin, F.

1980-01-01

Selected space structure configurations were reviewed in order to define dynamic analysis problems associated with variable geometry. The dynamics of a beam being constructed from a flexible base and the relocation of the completed beam by rotating the remote manipulator system about the shoulder joint were selected. Equations of motion were formulated in physical coordinates for both of these problems, and FORTRAN programs were developed to generate solutions by numerically integrating the equations. These solutions served as a standard of comparison to gauge the accuracy of approximate solution techniques that were developed and studied. Good control was achieved in both problems. Unstable control system coupling with the system flexibility did not occur. An approximate method was developed for each problem to enable the analyst to investigate variable geometry effects during a short time span using standard fixed geometry programs such as NASTRAN. The average angle and average length techniques are discussed.

CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability: SSD Plot Diagrams

EPA Pesticide Factsheets

Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

The Effect of Birth Weight on Academic Performance: Instrumental Variable Analysis.

PubMed

Lin, Shi Lin; Leung, Gabriel Matthew; Schooling, C Mary

2017-05-01

Observationally, lower birth weight is usually associated with poorer academic performance; whether this association is causal or the result of confounding is unknown. To investigate this question, we obtained an effect estimate, which can have a causal interpretation under specific assumptions, of birth weight on educational attainment using instrumental variable analysis based on single nucleotide polymorphisms determining birth weight combined with results from the Social Science Genetic Association Consortium study of 126,559 Caucasians. We similarly obtained an estimate of the effect of birth weight on academic performance in 4,067 adolescents from Hong Kong's (Chinese) Children of 1997 birth cohort (1997-2016), using twin status as an instrumental variable. Birth weight was not associated with years of schooling (per 100-g increase in birth weight, -0.006 years, 95% confidence interval (CI): -0.02, 0.01) or college completion (odds ratio = 1.00, 95% CI: 0.96, 1.03). Birth weight was also unrelated to academic performance in adolescents (per 100-g increase in birth weight, -0.004 grade, 95% CI: -0.04, 0.04) using instrumental variable analysis, although conventional regression gave a small positive association (0.02 higher grade, 95% CI: 0.01, 0.03). Observed associations of birth weight with academic performance may not be causal, suggesting that interventions should focus on the contextual factors generating this correlation. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evaluation of Reliability Coefficients for Two-Level Models via Latent Variable Analysis

ERIC Educational Resources Information Center

Raykov, Tenko; Penev, Spiridon

2010-01-01

A latent variable analysis procedure for evaluation of reliability coefficients for 2-level models is outlined. The method provides point and interval estimates of group means' reliability, overall reliability of means, and conditional reliability. In addition, the approach can be used to test simple hypotheses about these parameters. The…

A meta-analysis of variability in continuous-culture ruminal fermentation and digestibility data.

PubMed

Hristov, A N; Lee, C; Hristova, R; Huhtanen, P; Firkins, J L

2012-09-01

A meta-analysis was conducted to compare ruminal fermentation and digestibility data and variability between continuous-culture (CC) experiments and in vivo data. One hundred eighty CC studies representing 1,074 individual treatments, published in refereed journals between 1980 and 2010 were used in this analysis. Studies were classified into 2 groups based on the type of CC used: CC systems specified as rumen simulation techniques (RUSITEC) and non-RUSITEC CC systems (non-RUSITEC). The latter was a diverse group of systems, all of which were termed CC by the investigators. The CC data were compared with a data set of in vivo trials with ruminally cannulated lactating dairy cows (data from a total of 366 individual cows). The reported neutral detergent fiber (NDF) concentration of the diets fed in the 3 data sets was, on average (dry matter basis), 44, 34, and 32%, respectively. The average total volatile fatty acid (VFA) concentration for the RUSITEC and non-RUSITEC data sets was 67 and 80% (respectively) of the total VFA concentration in vivo. The average concentration of acetate was also lower for the CC data sets compared with in vivo and that of propionate was considerably lower for RUSITEC compared with in vivo, but butyrate concentrations were similar between the CC and in vivo data sets. Variability in the VFA data was generally the highest (higher coefficients of variation and variance) for the non-RUSITEC data set, followed by RUSITEC, and was the lowest for in vivo. Digestibilities of NDF and particularly organic matter were lower in the CC data sets compared with in vivo; the average NDF digestibility was 34.2, 45.5, and 53.0% for RUSITEC, non-RUSITEC, and in vivo, respectively. Variability in nutrient digestibility data followed the pattern of variability of the VFA data: highest variability for the non-RUSITEC data set, followed by RUSITEC, and the lowest for in vivo. This analysis showed that CC systems are generally characterized by lower total VFA

Elsaesser variable analysis of fluctuations in the ion foreshock and undisturbed solar wind

NASA Technical Reports Server (NTRS)

Labelle, James; Treumann, Rudolf A.; Marsch, Eckart

1994-01-01

Magnetohydrodynamics (MHD) fluctuations in the solar wind have been investigated previously by use of Elsaesser variables. In this paper, we present a comparison of the spectra of Elsaesser variables in the undisturbed solar wind at 1 AU and in the ion foreshock in front of the Earth. Both observations take place under relatively strong solar wind flow speed conditions (approximately equal 600 km/s). In the undisturbed solar wind we find that outward propagating Alfven waves dominate, as reported by other observers. In the ion foreshock the situation is more complex, with neither outward nor inward propagation dominating over the entire range investigated (1-10 mHz). Measurements of the Poynting vectors associated with the fluctuations are consistent with the Elsaesser variable analysis. These results generally support interpretations of the Elsaesser variables which have been made based strictly on solar wind data and provide additional insight into the nature of the ion foreshock turbulence.

Speech production variability in fricatives of children and adults: Results of functional data analysis

PubMed Central

Koenig, Laura L.; Lucero, Jorge C.; Perlman, Elizabeth

2008-01-01

This study investigates token-to-token variability in fricative production of 5 year olds, 10 year olds, and adults. Previous studies have reported higher intrasubject variability in children than adults, in speech as well as nonspeech tasks, but authors have disagreed on the causes and implications of this finding. The current work assessed the characteristics of age-related variability across articulators (larynx and tongue) as well as in temporal versus spatial domains. Oral airflow signals, which reflect changes in both laryngeal and supralaryngeal apertures, were obtained for multiple productions of ∕h s z∕. The data were processed using functional data analysis, which provides a means of obtaining relatively independent indices of amplitude and temporal (phasing) variability. Consistent with past work, both temporal and amplitude variabilities were higher in children than adults, but the temporal indices were generally less adultlike than the amplitude indices for both groups of children. Quantitative and qualitative analyses showed considerable speaker- and consonant-specific patterns of variability. The data indicate that variability in ∕s∕ may represent laryngeal as well as supralaryngeal control and further that a simple random noise factor, higher in children than in adults, is insufficient to explain developmental differences in speech production variability. PMID:19045800

Electromagnetic fields from mobile phone base station - variability analysis.

PubMed

Bienkowski, Pawel; Zubrzak, Bartlomiej

2015-09-01

The article describes the character of electromagnetic field (EMF) in mobile phone base station (BS) surroundings and its variability in time with an emphasis on the measurement difficulties related to its pulse and multi-frequency nature. Work also presents long-term monitoring measurements performed recently in different locations in Poland - small city with dispersed building development and in major polish city - dense urban area. Authors tried to determine the trends in changing of EMF spectrum analyzing daily changes of measured EMF levels in those locations. Research was performed using selective electromagnetic meters and also EMF meter with spectrum analysis.

Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

PubMed

Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

2017-09-01

In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Optimized Next-Generation Sequencing Genotype-Haplotype Calling for Genome Variability Analysis

PubMed Central

Navarro, Javier; Nevado, Bruno; Hernández, Porfidio; Vera, Gonzalo; Ramos-Onsins, Sebastián E

2017-01-01

The accurate estimation of nucleotide variability using next-generation sequencing data is challenged by the high number of sequencing errors produced by new sequencing technologies, especially for nonmodel species, where reference sequences may not be available and the read depth may be low due to limited budgets. The most popular single-nucleotide polymorphism (SNP) callers are designed to obtain a high SNP recovery and low false discovery rate but are not designed to account appropriately the frequency of the variants. Instead, algorithms designed to account for the frequency of SNPs give precise results for estimating the levels and the patterns of variability. These algorithms are focused on the unbiased estimation of the variability and not on the high recovery of SNPs. Here, we implemented a fast and optimized parallel algorithm that includes the method developed by Roesti et al and Lynch, which estimates the genotype of each individual at each site, considering the possibility to call both bases from the genotype, a single one or none. This algorithm does not consider the reference and therefore is independent of biases related to the reference nucleotide specified. The pipeline starts from a BAM file converted to pileup or mpileup format and the software outputs a FASTA file. The new program not only reduces the running times but also, given the improved use of resources, it allows its usage with smaller computers and large parallel computers, expanding its benefits to a wider range of researchers. The output file can be analyzed using software for population genetics analysis, such as the R library PopGenome, the software VariScan, and the program mstatspop for analysis considering positions with missing data. PMID:28894353

Symbolic Analysis of Heart Rate Variability During Exposure to Musical Auditory Stimulation.

PubMed

Vanderlei, Franciele Marques; de Abreu, Luiz Carlos; Garner, David Matthew; Valenti, Vitor Engrácia

2016-01-01

In recent years, the application of nonlinear methods for analysis of heart rate variability (HRV) has increased. However, studies on the influence of music on cardiac autonomic modulation in those circumstances are rare. The research team aimed to evaluate the acute effects on HRV of selected auditory stimulation by 2 musical styles, measuring the results using nonlinear methods of analysis: Shannon entropy, symbolic analysis, and correlation-dimension analysis. Prospective control study in which the volunteers were exposed to music and variables were compared between control (no auditory stimulation) and during exposure to music. All procedures were performed in a sound-proofed room at the Faculty of Science and Technology at São Paulo State University (UNESP), São Paulo, Brazil. Participants were 22 healthy female students, aged between 18 and 30 y. Prior to the actual intervention, the participants remained at rest for 20 min, and then they were exposed to one of the selected types of music, either classical baroque (64-84 dB) or heavy-metal (75-84 dB). Each musical session lasted a total of 5 min and 15 s. At a point occurring up to 1 wk after that day, the participants listened to the second type of music. The 2 types of music were delivered in a random sequence that depended on the group to which the participant was assigned. The study analyzed the following HRV indices through Shannon entropy; symbolic analysis-0V%, 1V%, 2LV%, and 2ULV%; and correlation-dimension analysis. During exposure to auditory stimulation by heavy-metal or classical baroque music, the study established no statistically significant variations regarding the indices for the Shannon entropy; the symbolic analysis-0V%, 1V%, and 2ULV%; and the correlation-dimension analysis. However, during heavy-metal music, the 2LV% index in the symbolic analysis was reduced compared with the controls. Auditory stimulation with the heavy-metal music reduced the parasympathetic modulation of HRV

Reliability of the Parabola Approximation Method in Heart Rate Variability Analysis Using Low-Sampling-Rate Photoplethysmography.

PubMed

Baek, Hyun Jae; Shin, JaeWook; Jin, Gunwoo; Cho, Jaegeol

2017-10-24

Photoplethysmographic signals are useful for heart rate variability analysis in practical ambulatory applications. While reducing the sampling rate of signals is an important consideration for modern wearable devices that enable 24/7 continuous monitoring, there have not been many studies that have investigated how to compensate the low timing resolution of low-sampling-rate signals for accurate heart rate variability analysis. In this study, we utilized the parabola approximation method and measured it against the conventional cubic spline interpolation method for the time, frequency, and nonlinear domain variables of heart rate variability. For each parameter, the intra-class correlation, standard error of measurement, Bland-Altman 95% limits of agreement and root mean squared relative error were presented. Also, elapsed time taken to compute each interpolation algorithm was investigated. The results indicated that parabola approximation is a simple, fast, and accurate algorithm-based method for compensating the low timing resolution of pulse beat intervals. In addition, the method showed comparable performance with the conventional cubic spline interpolation method. Even though the absolute value of the heart rate variability variables calculated using a signal sampled at 20 Hz were not exactly matched with those calculated using a reference signal sampled at 250 Hz, the parabola approximation method remains a good interpolation method for assessing trends in HRV measurements for low-power wearable applications.

An analysis of rotor blade twist variables associated with different Euler sequences and pretwist treatments

NASA Technical Reports Server (NTRS)

Alkire, K.

1984-01-01

A nonlinear analysis which is necessary to adequately model elastic helicopter rotor blades experiencing moderately large deformations was examined. The analysis must be based on an appropriate description of the blade's deformation geometry including elastic bending and twist. Built-in pretwist angles complicate the deformation process ant its definition. Relationships between the twist variables associated with different rotation sequences and corresponding forms of the transformation matrix are lasted. Relationships between the twist variables associated with first, the pretwist combined with the deformation twist are included. Many of the corresponding forms of the transformation matrix for the two cases are listed. It is shown that twist variables connected with the combined twist treatment are related to those where the pretwist is applied initially. A method to determine the relationships and some results are outlined. A procedure to evaluate the transformation matrix that eliminates the Eulerlike sequence altogether is demonstrated. The resulting form of the transformation matrix is unaffected by rotation sequence or pretwist treatment.

Analysis of blocking probability for OFDM-based variable bandwidth optical network

NASA Astrophysics Data System (ADS)

Gong, Lei; Zhang, Jie; Zhao, Yongli; Lin, Xuefeng; Wu, Yuyao; Gu, Wanyi

2011-12-01

Orthogonal Frequency Division Multiplexing (OFDM) has recently been proposed as a modulation technique. For optical networks, because of its good spectral efficiency, flexibility, and tolerance to impairments, optical OFDM is much more flexible compared to traditional WDM systems, enabling elastic bandwidth transmissions, and optical networking is the future trend of development. In OFDM-based optical network the research of blocking rate has very important significance for network assessment. Current research for WDM network is basically based on a fixed bandwidth, in order to accommodate the future business and the fast-changing development of optical network, our study is based on variable bandwidth OFDM-based optical networks. We apply the mathematical analysis and theoretical derivation, based on the existing theory and algorithms, research blocking probability of the variable bandwidth of optical network, and then we will build a model for blocking probability.

Variability And Uncertainty Analysis Of Contaminant Transport Model Using Fuzzy Latin Hypercube Sampling Technique

NASA Astrophysics Data System (ADS)

Kumar, V.; Nayagum, D.; Thornton, S.; Banwart, S.; Schuhmacher2, M.; Lerner, D.

2006-12-01

Characterization of uncertainty associated with groundwater quality models is often of critical importance, as for example in cases where environmental models are employed in risk assessment. Insufficient data, inherent variability and estimation errors of environmental model parameters introduce uncertainty into model predictions. However, uncertainty analysis using conventional methods such as standard Monte Carlo sampling (MCS) may not be efficient, or even suitable, for complex, computationally demanding models and involving different nature of parametric variability and uncertainty. General MCS or variant of MCS such as Latin Hypercube Sampling (LHS) assumes variability and uncertainty as a single random entity and the generated samples are treated as crisp assuming vagueness as randomness. Also when the models are used as purely predictive tools, uncertainty and variability lead to the need for assessment of the plausible range of model outputs. An improved systematic variability and uncertainty analysis can provide insight into the level of confidence in model estimates, and can aid in assessing how various possible model estimates should be weighed. The present study aims to introduce, Fuzzy Latin Hypercube Sampling (FLHS), a hybrid approach of incorporating cognitive and noncognitive uncertainties. The noncognitive uncertainty such as physical randomness, statistical uncertainty due to limited information, etc can be described by its own probability density function (PDF); whereas the cognitive uncertainty such estimation error etc can be described by the membership function for its fuzziness and confidence interval by ?-cuts. An important property of this theory is its ability to merge inexact generated data of LHS approach to increase the quality of information. The FLHS technique ensures that the entire range of each variable is sampled with proper incorporation of uncertainty and variability. A fuzzified statistical summary of the model results will

Fear of falling and gait variability in older adults: a systematic review and meta-analysis.

PubMed

Ayoubi, Farah; Launay, Cyrille P; Annweiler, Cédric; Beauchet, Olivier

2015-01-01

Fear of falling (FOF) and increased gait variability are both independent markers of gait instability. There is a complex interplay between both entities. The purposes of this study were (1) to perform a qualitative analysis of all published studies on FOF-related changes in gait variability through a systematic review, and (2) to quantitatively synthesize FOF-related changes in gait variability. A systematic Medline literature search was conducted in May 2014 using the Medical Subject Heading (MeSH) terms "Fear" OR "fear of falling" combined with "Accidental Falls" AND "Gait" OR "Gait Apraxia" OR "Gait Ataxia" OR "Gait disorders, Neurologic" OR "Gait assessment" OR "Functional gait assessment" AND "Self efficacy" OR "Self confidence" AND "Aged" OR "Aged, 80 and over." Systematic review and fixed-effects meta-analysis using an inverse-variance method were performed. Of the 2184 selected studies, 10 observational studies (including 5 cross-sectional studies, 4 prospective cohort studies, and 1 case-control study) met the selection criteria. All were of good quality. The number of participants ranged from 52 to 1307 older community-dwellers (26.2%-85.0% women). The meta-analysis was performed on 10 studies with a total of 999 cases and 4502 controls. In one study, the higher limits of the effect size's confidence interval (CI) were lower than zero. In the remaining studies, the higher limits of the CI were positive. The summary random effect size of 0.29 (95% CI 0.13-0.45) was significant albeit of small magnitude, and indicated that gait variability was overall 0.29 SD higher in FOF cases compared with controls. Our findings show that FOF is associated with a statistically significant, albeit of small magnitude, increase in gait variability. Copyright © 2015 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

The Impact of Probe Variability on Brief Experimental Analysis of Reading Skills

ERIC Educational Resources Information Center

Mercer, Sterett H.; Harpole, Lauren Lestremau; Mitchell, Rachel R.; McLemore, Chandler; Hardy, Christina

2012-01-01

The purpose of this study was to examine the impact of probe variability on the ability to replicate results in brief experimental analysis (BEA) of reading. In the first phase of the study, 41 first- and second- grade students completed 16 oral reading fluency probes. Calculations of probe difficulty were used to identify Low and High Variability…

An analysis of variability in the manufacturing of dexosomes: implications for development of an autologous therapy.

PubMed

Patel, Sanjay; Mehta-Damani, Anita; Shu, Helen; Le Pecq, Jean-Bernard

2005-10-20

Dexosomes are nanometer-size vesicles released by dendritic-cells, possessing much of the cellular machinery required to stimulate an immune response (i.e. MHC Class I and II). The ability of patient-derived dexosomes loaded with tumor antigens to elicit anti-tumor activity is currently being evaluated in clinical trials. Unlike conventional biologics, where variability between lots of product arises mostly from the manufacturing process, an autologous product has inherent variability in the starting material due to heterogeneity in the human population. In an effort to assess the variability arising from the dexosome manufacturing process versus the human starting material, 144 dexosome preparations from normal donors (111) and cancer patients (33) from two Phase I clinical trials were analyzed. A large variability in the quantity of dexosomes (measured as the number of MHC Class II molecules) produced between individual lots was observed ( > 50-fold). An analysis of intra-lot variability shows that the manufacturing process introduces relatively little of this variability. To identify the source(s) of variability arising from the human starting material, distributions of the key parameters involved in dexosome production were established, and a model created. Computer simulations using this model were performed, and compared to the actual data observed. The main conclusion from these simulations is that the number of cells collected per individual and the productivity of these cells of are the principal sources of variability in the production of Class II. The approach described here can be extended to other autologous therapies in general to evaluate control of manufacturing processes. Moreover, this analysis of process variability is directly applicable to production at a commercial scale, since the large scale manufacture of autologous products entails an exact process replication rather than scale-up in volume, as is the case with traditional drugs or

Read margin analysis of crossbar arrays using the cell-variability-aware simulation method

NASA Astrophysics Data System (ADS)

Sun, Wookyung; Choi, Sujin; Shin, Hyungsoon

2018-02-01

This paper proposes a new concept of read margin analysis of crossbar arrays using cell-variability-aware simulation. The size of the crossbar array should be considered to predict the read margin characteristic of the crossbar array because the read margin depends on the number of word lines and bit lines. However, an excessively high-CPU time is required to simulate large arrays using a commercial circuit simulator. A variability-aware MATLAB simulator that considers independent variability sources is developed to analyze the characteristics of the read margin according to the array size. The developed MATLAB simulator provides an effective method for reducing the simulation time while maintaining the accuracy of the read margin estimation in the crossbar array. The simulation is also highly efficient in analyzing the characteristic of the crossbar memory array considering the statistical variations in the cell characteristics.

Mortality patterns associated with the 1918 influenza pandemic in Mexico: evidence for a spring herald wave and lack of pre-existing immunity in older populations

PubMed Central

Chowell, Gerardo; Viboud, Cécile; Simonsen, Lone; Miller, Mark A.; Acuna-Soto, Rodolfo

2010-01-01

Background While the mortality burden of the devastating 1918 influenza pandemic has been carefully quantified in the US, Japan, and European countries, little is known about the pandemic experience elsewhere. Here, we compiled extensive archival records to quantify the pandemic mortality patterns in two Mexican cities, Mexico City and Toluca. Methods We applied seasonal excess mortality models to age-specific respiratory mortality rates for 1915–1920 and quantified the reproduction number from daily data. Results We identified 3 pandemic waves in Mexico City in spring 1918, fall 1918, and winter 1920, characterized by unusual excess mortality in 25–44 years old. Toluca experienced 2-fold higher excess mortality rates than Mexico City, but did not have a substantial 3rd wave. All age groups including those over 65 years experienced excess mortality during 1918–20. Reproduction number estimates were below 2.5 assuming a 3-day generation interval. Conclusion Mexico experienced a herald pandemic wave with elevated young adult mortality in spring 1918, similar to the US and Europe. In contrast to the US and Europe, there was no mortality sparing in Mexican seniors, highlighting potential geographical differences in pre-existing immunity to the 1918 virus. We discuss the relevance of our findings to the 2009 pandemic mortality patterns. PMID:20594109

Shifts of environmental and phytoplankton variables in a regulated river: A spatial-driven analysis.

PubMed

Sabater-Liesa, Laia; Ginebreda, Antoni; Barceló, Damià

2018-06-18

The longitudinal structure of the environmental and phytoplankton variables was investigated in the Ebro River (NE Spain), which is heavily affected by water abstraction and regulation. A first exploration indicated that the phytoplankton community did not resist the impact of reservoirs and barely recovered downstream of them. The spatial analysis showed that the responses of the phytoplankton and environmental variables were not uniform. The two set of variables revealed spatial variability discontinuities and river fragmentation upstream and downstream from the reservoirs. Reservoirs caused the replacement of spatially heterogeneous habitats by homogeneous spatially distributed water bodies, these new environmental conditions downstream benefiting the opportunist and cosmopolitan algal taxa. The application of a spatial auto-regression model to algal biomass (chlorophyll-a) permitted to capture the relevance and contribution of extra-local influences in the river ecosystem. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Analysis of the in vivo confocal Raman spectral variability in human skin

NASA Astrophysics Data System (ADS)

Mogilevych, Borys; dos Santos, Laurita; Rangel, Joao L.; Grancianinov, Karen J. S.; Sousa, Mariane P.; Martin, Airton A.

2015-06-01

Biochemical composition of the skin changes in each layer and, therefore, the skin spectral profile vary with the depth. In this work, in vivo Confocal Raman spectroscopy studies were performed at different skin regions and depth profile (from the surface down to 10 μm) of the stratum corneum, to verify the variability and reproducibility of the intra- and interindividual Raman data. The Raman spectra were collected from seven healthy female study participants using a confocal Raman system from Rivers Diagnostic, with 785 nm excitation line and a CCD detector. Measurements were performed in the volar forearm region, at three different points at different depth, with the step of 2 μm. For each depth point, three spectra were acquired. Data analysis included the descriptive statistics (mean, standard deviation and residual) and Pearson's correlation coefficient calculation. Our results show that inter-individual variability is higher than intraindividual variability, and variability inside the SC is higher than on the skin surface. In all these cases we obtained r values, higher than 0.94, which correspond to high correlation between Raman spectra. It reinforces the possibility of the data reproducibility and direct comparison of in vivo results obtained with different study participants of the same age group and phototype.

24-Hour Blood Pressure Variability Assessed by Average Real Variability: A Systematic Review and Meta-Analysis.

PubMed

Mena, Luis J; Felix, Vanessa G; Melgarejo, Jesus D; Maestre, Gladys E

2017-10-19

Although 24-hour blood pressure (BP) variability (BPV) is predictive of cardiovascular outcomes independent of absolute BP levels, it is not regularly assessed in clinical practice. One possible limitation to routine BPV assessment is the lack of standardized methods for accurately estimating 24-hour BPV. We conducted a systematic review to assess the predictive power of reported BPV indexes to address appropriate quantification of 24-hour BPV, including the average real variability (ARV) index. Studies chosen for review were those that presented data for 24-hour BPV in adults from meta-analysis, longitudinal or cross-sectional design, and examined BPV in terms of the following issues: (1) methods used to calculate and evaluate ARV; (2) assessment of 24-hour BPV determined using noninvasive ambulatory BP monitoring; (3) multivariate analysis adjusted for covariates, including some measure of BP; (4) association of 24-hour BPV with subclinical organ damage; and (5) the predictive value of 24-hour BPV on target organ damage and rate of cardiovascular events. Of the 19 assessed studies, 17 reported significant associations between high ARV and the presence and progression of subclinical organ damage, as well as the incidence of hard end points, such as cardiovascular events. In all these cases, ARV remained a significant independent predictor ( P <0.05) after adjustment for BP and other clinical factors. In addition, increased ARV in systolic BP was associated with risk of all cardiovascular events (hazard ratio, 1.18; 95% confidence interval, 1.09-1.27). Only 2 cross-sectional studies did not find that high ARV was a significant risk factor. Current evidence suggests that ARV index adds significant prognostic information to 24-hour ambulatory BP monitoring and is a useful approach for studying the clinical value of BPV. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Operant Variability: A Conceptual Analysis

ERIC Educational Resources Information Center

Barba, Lourenco de Souza

2012-01-01

Some researchers claim that variability is an operant dimension of behavior. The present paper reviews the concept of operant behavior and emphasizes that differentiation is the behavioral process that demonstrates an operant relation. Differentiation is conceived as change in the overlap between two probability distributions: the distribution of…

Comprehensive Modeling and Analysis of Rotorcraft Variable Speed Propulsion System With Coupled Engine/Transmission/Rotor Dynamics

NASA Technical Reports Server (NTRS)

DeSmidt, Hans A.; Smith, Edward C.; Bill, Robert C.; Wang, Kon-Well

2013-01-01

This project develops comprehensive modeling and simulation tools for analysis of variable rotor speed helicopter propulsion system dynamics. The Comprehensive Variable-Speed Rotorcraft Propulsion Modeling (CVSRPM) tool developed in this research is used to investigate coupled rotor/engine/fuel control/gearbox/shaft/clutch/flight control system dynamic interactions for several variable rotor speed mission scenarios. In this investigation, a prototypical two-speed Dual-Clutch Transmission (DCT) is proposed and designed to achieve 50 percent rotor speed variation. The comprehensive modeling tool developed in this study is utilized to analyze the two-speed shift response of both a conventional single rotor helicopter and a tiltrotor drive system. In the tiltrotor system, both a Parallel Shift Control (PSC) strategy and a Sequential Shift Control (SSC) strategy for constant and variable forward speed mission profiles are analyzed. Under the PSC strategy, selecting clutch shift-rate results in a design tradeoff between transient engine surge margins and clutch frictional power dissipation. In the case of SSC, clutch power dissipation is drastically reduced in exchange for the necessity to disengage one engine at a time which requires a multi-DCT drive system topology. In addition to comprehensive simulations, several sections are dedicated to detailed analysis of driveline subsystem components under variable speed operation. In particular an aeroelastic simulation of a stiff in-plane rotor using nonlinear quasi-steady blade element theory was conducted to investigate variable speed rotor dynamics. It was found that 2/rev and 4/rev flap and lag vibrations were significant during resonance crossings with 4/rev lagwise loads being directly transferred into drive-system torque disturbances. To capture the clutch engagement dynamics, a nonlinear stick-slip clutch torque model is developed. Also, a transient gas-turbine engine model based on first principles mean

Automated margin analysis of contemporary adhesive systems in vitro: evaluation of discriminatory variables.

PubMed

Heintze, Siegward D; Forjanic, Monika; Roulet, François-Jean

2007-08-01

Using an optical sensor, to automatically evaluate the marginal seal of restorations placed with 21 adhesive systems of all four adhesive categories in cylindrical cavities of bovine dentin applying different outcome variables, and to evaluate their discriminatory power. Twenty-one adhesive systems were evaluated: three 3-step etch-and-rinse systems, three 2-step etch-and-rinse systems, five 2-step self-etching systems, and ten 1-step self-etching systems. All adhesives were applied in cylindrical cavities in bovine dentin together with Tetric Ceram (n=8). In the control group, no adhesive system was used. After 24 h of storage in water at 37 degrees C, the surface was polished with 4000-grit SiC paper, and epoxy resin replicas were produced. An optical sensor (FRT MicroProf) created 100 profiles of the restoration margin, and an algorithm detected gaps and calculated their depths and widths. The following evaluation criteria were used: percentage of specimens without gaps, the percentage of gap-free profiles in relation to all profiles per specimen, mean gap width, mean gap depth, largest gap, modified marginal integrity index MI. The statistical analysis was carried out on log-transformed data for all variables with ANOVA and post-hoc Tukey's test for multiple comparisons. The correlation between the variables was tested with regression analysis, and the pooled data accordingto the four adhesive categories were compared by applying the Mann-Whitney nonparametric test (p < 0.05). For all the variables that characterized the marginal adaptation, there was a great variation from material to material. In general, the etch-and-rinse adhesive systems demonstrated the best marginal adaptation, followed by the 2-step self-etching and the 1-step self-etching adhesives; the latter showed the highest variability in test results between materials and within the same material. The only exception to this rule was Xeno IV, which showed a marginal adaptation that was comparable

Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

USGS Publications Warehouse

Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.

2010-01-01

This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.

Detailed heart rate variability analysis in athletes.

PubMed

Kiss, Orsolya; Sydó, Nóra; Vargha, Péter; Vágó, Hajnalka; Czimbalmos, Csilla; Édes, Eszter; Zima, Endre; Apponyi, Györgyi; Merkely, Gergő; Sydó, Tibor; Becker, Dávid; Allison, Thomas G; Merkely, Béla

2016-08-01

Heart rate variability (HRV) analysis has been used to evaluate patients with various cardiovascular diseases. While the vast majority of HRV studies have focused on pathological states, our study focuses on the less explored area of HRV analysis across different training intensity and sports. We aimed to measure HRV in healthy elite and masters athletes and compare to healthy, but non-athletic controls. Time-domain HRV analysis was applied in 138 athletes (male 110, age 28.4 ± 8.3) and 100 controls (male 56, age 28.3 ± 6.9) during Holter monitoring (21.3 ± 3.0 h). All studied parameters were higher in elite athletes compared to controls [SDNN (CI) 225.3 (216.2-234.5) vs 158.6 (150.2-167.1) ms; SDNN Index (CI) 99.6 (95.6-103.7) vs 72.4 (68.7-76.2) ms; pNN50 (CI) 24.2 (22.2-26.3) vs 14.4 (12.7-16.3) %; RMSSD (CI) 71.8 (67.6-76.2) vs 50.8 (46.9-54.8) ms; p < 0.001]. Masters had higher HRV values than controls, but no significant differences were found between elite athletes and masters athletes. Some parameters were higher in canoeists-kayakers and bicyclists than runners. Lower cut-off values in elite athletes were SDNN: 147.4 ms, SDNN Index: 66.6 ms, pNN50: 9.7 %, RMSSD: 37.9 ms. Autonomic regulation in elite athletes described with HRV is significantly different than in healthy controls. Sports modality and level of performance, but not age- or sex-influenced HRV. Our study provides athletic normal HRV values. Further investigations are needed to determine its role in risk stratification, optimization of training, or identifying overtraining.

Molecular and agronomic analysis of intraspecific variability in Capsicum baccatum var. pendulum accessions.

PubMed

Leite, P S S; Rodrigues, R; Silva, R N O; Pimenta, S; Medeiros, A M; Bento, C S; Gonçalves, L S A

2016-10-05

Capsicum baccatum is one of the most important chili peppers in South America, since this region is considered to be the center of origin and diversity of this species. In Brazil, C. baccatum has been widely explored by family farmers and there are different local names for each fruit phenotype, such as cambuci and dedo-de-moça (lady's finger). Although very popular among farmers and consumers, C. baccatum has been less extensively studied than other Capsicum species. This study describes the phenotypic and genotypic variability in C. baccatum var. pendulum accessions. Twenty-nine accessions from the Universidade Estadual do Norte Fluminense Darcy Ribeiro gene bank, and one commercial genotype ('BRS-Mari') were evaluated for 53 morphoagronomic descriptors (31 qualitative and 22 quantitative traits). In addition, accessions were genotyped using 30 microsatellite primers. Three accessions from the C. annuum complex were included in the molecular characterization. Nine of 31 qualitative descriptors were monomorphic, while all quantitative descriptors were highly significant different between accessions (P < 0.01). Using the unweighted pair group method using arithmetic averages, four groups were obtained based on multicategoric variables and five groups were obtained based on quantitative variables. In the genotyping analysis, 12 polymorphic simple sequence repeat primers amplified in C. baccatum with dissimilarity between accessions ranging from 0.13 to 0.91, permitting the formation of two distinct groups for Bayesian analysis. These results indicate wide variability among the accessions comparing phenotypic and genotypic data and revealed distinct patterns of dissimilarity between matrices, indicating that both steps are valuable for the characterization of C. baccatum var. pendulum accessions.

Comparison of variance estimators for meta-analysis of instrumental variable estimates

PubMed Central

Schmidt, AF; Hingorani, AD; Jefferis, BJ; White, J; Groenwold, RHH; Dudbridge, F

2016-01-01

Abstract Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two versions of the delta method (IV before or after pooling), four bootstrap estimators, a jack-knife estimator and a heteroscedasticity-consistent (HC) variance estimator were compared using simulation. Two types of meta-analyses were compared, a two-stage meta-analysis pooling results, and a one-stage meta-analysis pooling datasets. Results: Using a two-stage meta-analysis, coverage of the point estimate using bootstrapped estimators deviated from nominal levels at weak instrument settings and/or outcome probabilities ≤ 0.10. The jack-knife estimator was the least biased resampling method, the HC estimator often failed at outcome probabilities ≤ 0.50 and overall the delta method estimators were the least biased. In the presence of between-study heterogeneity, the delta method before meta-analysis performed best. Using a one-stage meta-analysis all methods performed equally well and better than two-stage meta-analysis of greater or equal size. Conclusions: In the presence of between-study heterogeneity, two-stage meta-analyses should preferentially use the delta method before meta-analysis. Weak instrument bias can be reduced by performing a one-stage meta-analysis. PMID:27591262

The use of cognitive ability measures as explanatory variables in regression analysis

PubMed Central

Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

2015-01-01

Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual’s wage, or a decision such as an individual’s education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score, constructed via standard psychometric practice from individuals’ responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a “mixed effects structural equations” (MESE) model, may be more appropriate in many circumstances. PMID:26998417

The use of cognitive ability measures as explanatory variables in regression analysis.

PubMed

Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

2012-12-01

Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual's wage, or a decision such as an individual's education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score , constructed via standard psychometric practice from individuals' responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a "mixed effects structural equations" (MESE) model, may be more appropriate in many circumstances.

Analysis and Design of Variable Stiffness Composite Cylinders

NASA Technical Reports Server (NTRS)

Tatting, Brian F.; Guerdal, Zafer

1998-01-01

An investigation of the possible performance improvements of thin circular cylindrical shells through the use of the variable stiffness concept is presented. The variable stiffness concept implies that the stiffness parameters change spatially throughout the structure. This situation is achieved mainly through the use of curvilinear fibers within a fiber-reinforced composite laminate, though the possibility of thickness variations and discrete stiffening elements is also allowed. These three mechanisms are incorporated into the constitutive laws for thin shells through the use of Classical Lamination Theory. The existence of stiffness variation within the structure warrants a formulation of the static equilibrium equations from the most basic principles. The governing equations include sufficient detail to correctly model several types of nonlinearity, including the formation of a nonlinear shell boundary layer as well as the Brazier effect due to nonlinear bending of long cylinders. Stress analysis and initial buckling estimates are formulated for a general variable stiffness cylinder. Results and comparisons for several simplifications of these highly complex governing equations are presented so that the ensuing numerical solutions are considered reliable and efficient enough for in-depth optimization studies. Four distinct cases of loading and stiffness variation are chosen to investigate possible areas of improvement that the variable stiffness concept may offer over traditional constant stiffness and/or stiffened structures. The initial investigation deals with the simplest solution for cylindrical shells in which all quantities are constant around the circumference of the cylinder. This axisymmetric case includes a stiffness variation exclusively in the axial direction, and the only pertinent loading scenarios include constant loads of axial compression, pressure, and torsion. The results for these cases indicate that little improvement over traditional

Variable Selection through Correlation Sifting

NASA Astrophysics Data System (ADS)

Huang, Jim C.; Jojic, Nebojsa

Many applications of computational biology require a variable selection procedure to sift through a large number of input variables and select some smaller number that influence a target variable of interest. For example, in virology, only some small number of viral protein fragments influence the nature of the immune response during viral infection. Due to the large number of variables to be considered, a brute-force search for the subset of variables is in general intractable. To approximate this, methods based on ℓ1-regularized linear regression have been proposed and have been found to be particularly successful. It is well understood however that such methods fail to choose the correct subset of variables if these are highly correlated with other "decoy" variables. We present a method for sifting through sets of highly correlated variables which leads to higher accuracy in selecting the correct variables. The main innovation is a filtering step that reduces correlations among variables to be selected, making the ℓ1-regularization effective for datasets on which many methods for variable selection fail. The filtering step changes both the values of the predictor variables and output values by projections onto components obtained through a computationally-inexpensive principal components analysis. In this paper we demonstrate the usefulness of our method on synthetic datasets and on novel applications in virology. These include HIV viral load analysis based on patients' HIV sequences and immune types, as well as the analysis of seasonal variation in influenza death rates based on the regions of the influenza genome that undergo diversifying selection in the previous season.

Analysis and modeling of wafer-level process variability in 28 nm FD-SOI using split C-V measurements

NASA Astrophysics Data System (ADS)

Pradeep, Krishna; Poiroux, Thierry; Scheer, Patrick; Juge, André; Gouget, Gilles; Ghibaudo, Gérard

2018-07-01

This work details the analysis of wafer level global process variability in 28 nm FD-SOI using split C-V measurements. The proposed approach initially evaluates the native on wafer process variability using efficient extraction methods on split C-V measurements. The on-wafer threshold voltage (VT) variability is first studied and modeled using a simple analytical model. Then, a statistical model based on the Leti-UTSOI compact model is proposed to describe the total C-V variability in different bias conditions. This statistical model is finally used to study the contribution of each process parameter to the total C-V variability.

Spectroscopic analysis of Cepheid variables with 2D radiation-hydrodynamic simulations

NASA Astrophysics Data System (ADS)

Vasilyev, Valeriy

2018-06-01

The analysis of chemical enrichment history of dwarf galaxies allows to derive constraints on their formation and evolution. In this context, Cepheids play a very important role, as these periodically variable stars provide a means to obtain accurate distances. Besides, chemical composition of Cepheids can provide a strong constraint on the chemical evolution of the system. Standard spectroscopic analysis of Cepheids is based on using one-dimensional (1D) hydrostatic model atmospheres, with convection parametrised using the mixing-length theory. However, this quasi-static approach has theoretically not been validated. In my talk, I will discuss the validity of the quasi-static approximation in spectroscopy of short-periodic Cepheids. I will show the results obtained using a 2D time-dependent envelope model of a pulsating star computed with the radiation-hydrodynamics code CO5BOLD. I will then describe the impact of new models on the spectroscopic diagnostic of the effective temperature, surface gravity, microturbulent velocity, and metallicity. One of the interesting findings of my work is that 1D model atmospheres provide unbiased estimates of stellar parameters and abundances of Cepheid variables for certain phases of their pulsations. Convective inhomogeneities, however, also introduce biases. I will then discuss how these results can be used in a wider parameter space of pulsating stars and present an outlook for the future studies.

Analysis of source regions and meteorological factors for the variability of spring PM10 concentrations in Seoul, Korea

NASA Astrophysics Data System (ADS)

Lee, Jangho; Kim, Kwang-Yul

2018-02-01

CSEOF analysis is applied for the springtime (March, April, May) daily PM10 concentrations measured at 23 Ministry of Environment stations in Seoul, Korea for the period of 2003-2012. Six meteorological variables at 12 pressure levels are also acquired from the ERA Interim reanalysis datasets. CSEOF analysis is conducted for each meteorological variable over East Asia. Regression analysis is conducted in CSEOF space between the PM10 concentrations and individual meteorological variables to identify associated atmospheric conditions for each CSEOF mode. By adding the regressed loading vectors with the mean meteorological fields, the daily atmospheric conditions are obtained for the first five CSEOF modes. Then, HYSPLIT model is run with the atmospheric conditions for each CSEOF mode in order to back trace the air parcels and dust reaching Seoul. The K-means clustering algorithm is applied to identify major source regions for each CSEOF mode of the PM10 concentrations in Seoul. Three main source regions identified based on the mean fields are: (1) northern Taklamakan Desert (NTD), (2) Gobi Desert and (GD), and (3) East China industrial area (ECI). The main source regions for the mean meteorological fields are consistent with those of previous study; 41% of the source locations are located in GD followed by ECI (37%) and NTD (21%). Back trajectory calculations based on CSEOF analysis of meteorological variables identify distinct source characteristics associated with each CSEOF mode and greatly facilitate the interpretation of the PM10 variability in Seoul in terms of transportation route and meteorological conditions including the source area.

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

DOE PAGES

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie; ...

2016-10-18

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

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

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and

Variability in surface infrared reflectance of thirteen nitrile rubber gloves at key wavelengths for analysis of captan.

PubMed

Phalen, R N; Que Hee, Shane S

2007-02-01

The aim of this study was to investigate the surface variability of 13 powder-free, unlined, and unsupported nitrile rubber gloves using attenuated total reflection Fourier transform infrared (ATR-FT-IR) spectrophotometry at key wavelengths for analysis of captan contamination. The within-glove, within-lot, and between-lot variability was measured at 740, 1124, 1252, and 1735 cm(-1), the characteristic captan reflectance minima wavelengths. Three glove brands were assessed after conditioning overnight at relative humidity (RH) values ranging from 2 +/- 1 to 87 +/- 4% and temperatures ranging from -8.6 +/- 0.7 to 59.2 +/- 0.9 degrees C. For all gloves, 1735 cm(-1) provided the lowest background absorbance and greatest potential sensitivity for captan analysis on the outer glove surface: absorbances ranged from 0.0074 +/- 0.0005 (Microflex) to 0.0195 +/- 0.0024 (SafeSkin); average within-glove coefficients of variation (CV) ranged from 2.7% (Best, range 0.9-5.3%) to 10% (SafeSkin, 1.2-17%); within-glove CVs greater than 10% were for one brand (SafeSkin); within-lot CVs ranged from 2.8% (Best N-Dex) to 28% (SafeSkin Blue); and between-lot variation was statistically significant (p < or = 0.05) for all but two SafeSkin lots. The RH had variable effects dependent on wavelength, being minimal at 1735, 1252, and 1124 cm(-1) and highest at 3430 cm(-1) (O-H stretch region). There was no significant effect of temperature conditioning. Substantial within-glove, within-lot, and between-lot variability was observed. Thus, surface analysis using ATR-FT-IR must treat glove brands and lots as different. ATR-FT-IR proved to be a useful real-time analytical tool for measuring glove variability, detecting surface humidity effects, and choosing selective and sensitive wavelengths for analysis of nonvolatile surface contaminants.

An Analysis of Inter-annual Variability and Uncertainty of Continental Surface Heat Fluxes

NASA Astrophysics Data System (ADS)

Huang, S. Y.; Deng, Y.; Wang, J.

2016-12-01

The inter-annual variability and the corresponding uncertainty of land surface heat fluxes during the first decade of the 21st century are re-evaluated at continental scale based on the heat fluxes estimated by the maximum entropy production (MEP) model. The MEP model predicted heat fluxes are constrained by surface radiation fluxes, automatically satisfy surface energy balance, and are independent of temperature/moisture gradient, wind speed, and roughness lengths. The surface radiation fluxes and temperature data from Clouds and the Earth's Radiant Energy System and the surface specific humidity data from Modern-Era Retrospective analysis for Research and Applications were used to reproduce the global surface heat fluxes with land-cover data from the NASA Energy and Water cycle Study (NEWS). Our analysis shows that the annual means of continental latent heat fluxes have increasing trends associated with increasing trends in surface net radiative fluxes. The sensible heat fluxes also have increasing trends over most continents except for South America. Ground heat fluxes have little trends. The continental-scale analysis of the MEP fluxes are compared with other existing global surface fluxes data products and the implications of the results for inter-annual to decadal variability of regional surface energy budget are discussed.

An oilspill trajectory analysis model with a variable wind deflection angle

USGS Publications Warehouse

Samuels, W.B.; Huang, N.E.; Amstutz, D.E.

1982-01-01

The oilspill trajectory movement algorithm consists of a vector sum of the surface drift component due to wind and the surface current component. In the U.S. Geological Survey oilspill trajectory analysis model, the surface drift component is assumed to be 3.5% of the wind speed and is rotated 20 degrees clockwise to account for Coriolis effects in the Northern Hemisphere. Field and laboratory data suggest, however, that the deflection angle of the surface drift current can be highly variable. An empirical formula, based on field observations and theoretical arguments relating wind speed to deflection angle, was used to calculate a new deflection angle at each time step in the model. Comparisons of oilspill contact probabilities to coastal areas calculated for constant and variable deflection angles showed that the model is insensitive to this changing angle at low wind speeds. At high wind speeds, some statistically significant differences in contact probabilities did appear. ?? 1982.

Directional semivariogram analysis to identify and rank controls on the spatial variability of fracture networks

NASA Astrophysics Data System (ADS)

Hanke, John R.; Fischer, Mark P.; Pollyea, Ryan M.

2018-03-01

In this study, the directional semivariogram is deployed to investigate the spatial variability of map-scale fracture network attributes in the Paradox Basin, Utah. The relative variability ratio (R) is introduced as the ratio of integrated anisotropic semivariogram models, and R is shown to be an effective metric for quantifying the magnitude of spatial variability for any two azimuthal directions. R is applied to a GIS-based data set comprising roughly 1200 fractures, in an area which is bounded by a map-scale anticline and a km-scale normal fault. This analysis reveals that proximity to the fault strongly influences the magnitude of spatial variability for both fracture intensity and intersection density within 1-2 km. Additionally, there is significant anisotropy in the spatial variability, which is correlated with trends of the anticline and fault. The direction of minimum spatial correlation is normal to the fault at proximal distances, and gradually rotates and becomes subparallel to the fold axis over the same 1-2 km distance away from the fault. We interpret these changes to reflect varying scales of influence of the fault and the fold on fracture network development: the fault locally influences the magnitude and variability of fracture network attributes, whereas the fold sets the background level and structure of directional variability.

A comprehensive analysis of coherent rainfall patterns in China and potential drivers. Part I: Interannual variability

NASA Astrophysics Data System (ADS)

Stephan, Claudia Christine; Klingaman, Nicholas Pappas; Vidale, Pier Luigi; Turner, Andrew George; Demory, Marie-Estelle; Guo, Liang

2018-06-01

Interannual rainfall variability in China affects agriculture, infrastructure and water resource management. To improve its understanding and prediction, many studies have associated precipitation variability with particular causes for specific seasons and regions. Here, a consistent and objective method, Empirical Orthogonal Teleconnection (EOT) analysis, is applied to 1951-2007 high-resolution precipitation observations over China in all seasons. Instead of maximizing the explained space-time variance, the method identifies regions in China that best explain the temporal variability in domain-averaged rainfall. The EOT method is validated by the reproduction of known relationships to the El Niño Southern Oscillation (ENSO): high positive correlations with ENSO are found in eastern China in winter, along the Yangtze River in summer, and in southeast China during spring. New findings include that wintertime rainfall variability along the southeast coast is associated with anomalous convection over the tropical eastern Atlantic and communicated to China through a zonal wavenumber-three Rossby wave. Furthermore, spring rainfall variability in the Yangtze valley is related to upper-tropospheric midlatitude perturbations that are part of a Rossby wave pattern with its origin in the North Atlantic. A circumglobal wave pattern in the northern hemisphere is also associated with autumn precipitation variability in eastern areas. The analysis is objective, comprehensive, and produces timeseries that are tied to specific locations in China. This facilitates the interpretation of associated dynamical processes, is useful for understanding the regional hydrological cycle, and allows the results to serve as a benchmark for assessing general circulation models.

Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

NASA Astrophysics Data System (ADS)

Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

2018-01-01

Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

Discriminant analysis of cardiovascular and respiratory variables for classification of road cyclists by specialty.

PubMed

Nikolić, Biljana; Martinović, Jelena; Matić, Milan; Stefanović, Đorđe

2018-05-29

Different variables determine the performance of cyclists, which brings up the question how these parameters may help in their classification by specialty. The aim of the study was to determine differences in cardiorespiratory parameters of male cyclists according to their specialty, flat rider (N=21), hill rider (N=35) and sprinter (N=20) and obtain the multivariate model for further cyclists classification by specialties, based on selected variables. Seventeen variables were measured at submaximal and maximum load on the cycle ergometer Cosmed E 400HK (Cosmed, Rome, Italy) (initial 100W with 25W increase, 90-100 rpm). Multivariate discriminant analysis was used to determine which variables group cyclists within their specialty, and to predict which variables can direct cyclists to a particular specialty. Among nine variables that statistically contribute to the discriminant power of the model, achieved power on the anaerobic threshold and the produced CO2 had the biggest impact. The obtained discriminatory model correctly classified 91.43% of flat riders, 85.71% of hill riders, while sprinters were classified completely correct (100%), i.e. 92.10% of examinees were correctly classified, which point out the strength of the discriminatory model. Respiratory indicators mostly contribute to the discriminant power of the model, which may significantly contribute to training practice and laboratory tests in future.

[Use of multiple locus variable number tandem repeats analysis for the Brucella systematization].

PubMed

Kulakov, Iu K; Kovalev, D A; Misetova, E N; Golovneva, S I; Liapustina, L V; Zheludkov, M M

2012-01-01

The methods of molecular-genetic differentiation to strain level acquire increasing significance in the current system of struggle with brucellosis. MLVA (multiple locus variable number tandem repeats analysis) was selected for molecular-genetic differentiation to strain level and simultaneous establishment of the genetic relationship of investigated Brucella strains. The goal of this work was MLVA typing of three pathogenic Brucella species strains with the analysis of stability of chosen loci, discrimination power and concordance to conventional phenotypic methods of the Brucella differentiation for use in systematization of brucellosis causing agents. Twenty six Brucella strains representing reference (n = 15), vaccine (n = 2) and field strains of three pathogenic Brucella species were tested: B. melitensis (n = 3), B. abortus (n = 2), B. suis (n = 2), and isolates (n = 2) with unidentified taxonomic position using MLVA with 9 pairs primers on known variable loci of Brucella genome. The analysis of the stability of chosen loci, discrimination power on Hunter-Gaston discrimination index (HGDI) and consistency to phenotypic methods of identification was performed. MLVA was confirmed for the results of phenotypic methods of identification, stability of the chosen loci in majority reference, and vaccine strains with a high index of variability HGDI 0.9969 for all loci. A dendrogram was plotted on the basis of MLVA data on distributed Brucella strains in related clusters according to its taxonomic species and biovar positions and construction of 25 genotypes. B. melitensis strains formed cluster related to the reference strain of B. melitensis 63/9 biovar 2. Australian isolates of Brucella 83-4 and Brucella 83-6 isolated from rodents formed a cluster distant from other strains of Brucella. MLVA is a promising method for differentiation of Brucella strains with known and unresolved taxonomic status for their systematization and creation of MLVA genotype catalogue that

Computational analysis of Variable Thrust Engine (VTE) performance

NASA Technical Reports Server (NTRS)

Giridharan, M. G.; Krishnan, A.; Przekwas, A. J.

1993-01-01

The Variable Thrust Engine (VTE) of the Orbital Maneuvering Vehicle (OMV) uses a hypergolic propellant combination of Monomethyl Hydrazine (MMH) and Nitrogen Tetroxide (NTO) as fuel and oxidizer, respectively. The performance of the VTE depends on a number of complex interacting phenomena such as atomization, spray dynamics, vaporization, turbulent mixing, convective/radiative heat transfer, and hypergolic combustion. This study involved the development of a comprehensive numerical methodology to facilitate detailed analysis of the VTE. An existing Computational Fluid Dynamics (CFD) code was extensively modified to include the following models: a two-liquid, two-phase Eulerian-Lagrangian spray model; a chemical equilibrium model; and a discrete ordinate radiation heat transfer model. The modified code was used to conduct a series of simulations to assess the effects of various physical phenomena and boundary conditions on the VTE performance. The details of the models and the results of the simulations are presented.

Standard cell electrical and physical variability analysis based on automatic physical measurement for design-for-manufacturing purposes

NASA Astrophysics Data System (ADS)

Shauly, Eitan; Parag, Allon; Khmaisy, Hafez; Krispil, Uri; Adan, Ofer; Levi, Shimon; Latinski, Sergey; Schwarzband, Ishai; Rotstein, Israel

2011-04-01

A fully automated system for process variability analysis of high density standard cell was developed. The system consists of layout analysis with device mapping: device type, location, configuration and more. The mapping step was created by a simple DRC run-set. This database was then used as an input for choosing locations for SEM images and for specific layout parameter extraction, used by SPICE simulation. This method was used to analyze large arrays of standard cell blocks, manufactured using Tower TS013LV (Low Voltage for high-speed applications) Platforms. Variability of different physical parameters like and like Lgate, Line-width-roughness and more as well as of electrical parameters like drive current (Ion), off current (Ioff) were calculated and statistically analyzed, in order to understand the variability root cause. Comparison between transistors having the same W/L but with different layout configurations and different layout environments (around the transistor) was made in terms of performances as well as process variability. We successfully defined "robust" and "less-robust" transistors configurations, and updated guidelines for Design-for-Manufacturing (DfM).

Rapid clinical diagnosis of Legionnaires' disease during the "herald wave" of the swine influenza (H1N1) pandemic: the Legionnaires' disease triad.

PubMed

Cunha, Burke A; Mickail, Nardeen; Syed, Uzma; Strollo, Stephanie; Laguerre, Marianne

2010-01-01

In adults hospitalized with atypical community-acquired pneumonia (CAP), Legionnaires' disease is not uncommon. Legionnaire's disease can be differentiated from typical CAPs and from other atypical CAPs based on its characteristic pattern of extrapulmonary organ involvement. The first clinically useful diagnostic weighted point score system for the clinical diagnosis of Legionnaires' disease was developed by the Infectious Disease Division at Winthrop-University Hospital in the 1980s. It has proven to be diagnostically accurate and useful for more than two decades, but was time-consuming. Because Legionella spp. diagnostic tests are time-dependent and problematic, a need was perceived for a rapid, simple way to render a clinical, syndromic diagnosis of Legionnaires' disease pending Legionella test results. During the "herald wave" of the swine influenza (H1N1) pandemic in the New York area, our hospital, like others, was inundated with patients who presented to the Emergency Department with influenza-like illnesses (ILIs) for H1N1 testing/evaluation. Most patients with ILIs did not have swine influenza. Hospitalized patients with ILIs who tested positive with rapid influenza diagnostic tests (RIDTs) were placed on influenza precautions and treated with oseltamivir. Unfortunately, approximately 30% of adult patients admitted with an ILI had negative RIDTs. Because the definitive laboratory diagnosis of H1N1 pneumonia by reverse transcription-polymerase chain reaction(RT-PCR), testing was restricted by health departments, resulted in clinical and infection control dilemmas in determining which RIDT-negative patients did, in fact, have H1N1 pneumonia. Accordingly, a diagnostic weighted point score system was developed for H1N1 pneumonia patients, based on RT-PCR positivity by the Infectious Disease Division at Winthrop-University Hospital. This diagnostic point score system for hospitalized adults with negative RIDTs was time-consuming. As the pandemic progressed, a

IRAS variables as galactic structure tracers - Classification of the bright variables

NASA Technical Reports Server (NTRS)

Allen, L. E.; Kleinmann, S. G.; Weinberg, M. D.

1993-01-01

The characteristics of the 'bright infrared variables' (BIRVs), a sample consisting of the 300 brightest stars in the IRAS Point Source Catalog with IRAS variability index VAR of 98 or greater, are investigated with the purpose of establishing which of IRAS variables are AGB stars (e.g., oxygen-rich Miras and carbon stars, as was assumed by Weinberg (1992)). Results of the analysis of optical, infrared, and microwave spectroscopy of these stars indicate that, out of 88 stars in the BIRV sample identified with cataloged variables, 86 can be classified as Miras. Results of a similar analysis performed for a color-selected sample of stars, using the color limits employed by Habing (1988) to select AGB stars, showed that, out of 52 percent of classified stars, 38 percent are non-AGB stars, including H II regions, planetary nebulae, supergiants, and young stellar objects, indicating that studies using color-selected samples are subject to misinterpretation.

Random Initialisation of the Spectral Variables: an Alternate Approach for Initiating Multivariate Curve Resolution Alternating Least Square (MCR-ALS) Analysis.

PubMed

Kumar, Keshav

2017-11-01

Multivariate curve resolution alternating least square (MCR-ALS) analysis is the most commonly used curve resolution technique. The MCR-ALS model is fitted using the alternate least square (ALS) algorithm that needs initialisation of either contribution profiles or spectral profiles of each of the factor. The contribution profiles can be initialised using the evolve factor analysis; however, in principle, this approach requires that data must belong to the sequential process. The initialisation of the spectral profiles are usually carried out using the pure variable approach such as SIMPLISMA algorithm, this approach demands that each factor must have the pure variables in the data sets. Despite these limitations, the existing approaches have been quite a successful for initiating the MCR-ALS analysis. However, the present work proposes an alternate approach for the initialisation of the spectral variables by generating the random variables in the limits spanned by the maxima and minima of each spectral variable of the data set. The proposed approach does not require that there must be pure variables for each component of the multicomponent system or the concentration direction must follow the sequential process. The proposed approach is successfully validated using the excitation-emission matrix fluorescence data sets acquired for certain fluorophores with significant spectral overlap. The calculated contribution and spectral profiles of these fluorophores are found to correlate well with the experimental results. In summary, the present work proposes an alternate way to initiate the MCR-ALS analysis.

Multivariate and multiorgan analysis of cardiorespiratory variability signals: the CAP sleep case.

PubMed

Bianchi, Anna M; Ferini-Strambi, Luigi; Castronovo, Vincenza; Cerutti, Sergio

2006-10-01

Signals from different systems are analyzed during sleep on a beat-to-beat basis to provide a quantitative measure of synchronization with the heart rate variability (HRV) signal, oscillations of which reflect the action of the autonomic nervous system. Beat-to-beat variability signals synchronized to QRS occurrence on ECG signals were extracted from respiration, electroencephalogram (EEG) and electromyogram (EMG) traces. The analysis was restricted to sleep stage 2. Cyclic alternating pattern (CAP) periods were detected from EEG signals and the following conditions were identified: stage 2 non-CAP (2 NCAP), stage 2 CAP (2 CAP) and stage 2 CAP with myoclonus (2 CAP MC). The coupling relationships between pairs of variability signals were studied in both the time and frequency domains. Passing from 2 NCAP to 2 CAP, sympathetic activation is indicated by tachycardia and reduced respiratory arrhythmia in the heart rate signal. At the same time, we observed a marked link between EEG and HRV at the CAP frequency. During 2 CAP MC, the increased synchronization involved myoclonus and respiration. The underlying mechanism seems to be related to a global control system at the central level that involves the different systems.

Decreasing Cloudiness Over China: An Updated Analysis Examining Additional Variables

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

Kaiser, D.P.

2000-01-14

As preparation of the IPCC's Third Assessment Report takes place, one of the many observed climate variables of key interest is cloud amount. For several nations of the world, there exist records of surface-observed cloud amount dating back to the middle of the 20th Century or earlier, offering valuable information on variations and trends. Studies using such databases include Sun and Groisman (1999) and Kaiser and Razuvaev (1995) for the former Soviet Union, Angel1 et al. (1984) for the United States, Henderson-Sellers (1986) for Europe, Jones and Henderson-Sellers (1992) for Australia, and Kaiser (1998) for China. The findings of Kaisermore » (1998) differ from the other studies in that much of China appears to have experienced decreased cloudiness over recent decades (1954-1994), whereas the other land regions for the most part show evidence of increasing cloud cover. This paper expands on Kaiser (1998) by analyzing trends in additional meteorological variables for Chi na [station pressure (p), water vapor pressure (e), and relative humidity (rh)] and extending the total cloud amount (N) analysis an additional two years (through 1996).« less

Economic Analysis of a Multi-Site Prevention Program: Assessment of Program Costs and Characterizing Site-level Variability

PubMed Central

Corso, Phaedra S.; Ingels, Justin B.; Kogan, Steven M.; Foster, E. Michael; Chen, Yi-Fu; Brody, Gene H.

2013-01-01

Programmatic cost analyses of preventive interventions commonly have a number of methodological difficulties. To determine the mean total costs and properly characterize variability, one often has to deal with small sample sizes, skewed distributions, and especially missing data. Standard approaches for dealing with missing data such as multiple imputation may suffer from a small sample size, a lack of appropriate covariates, or too few details around the method used to handle the missing data. In this study, we estimate total programmatic costs for a prevention trial evaluating the Strong African American Families-Teen program. This intervention focuses on the prevention of substance abuse and risky sexual behavior. To account for missing data in the assessment of programmatic costs we compare multiple imputation to probabilistic sensitivity analysis. The latter approach uses collected cost data to create a distribution around each input parameter. We found that with the multiple imputation approach, the mean (95% confidence interval) incremental difference was $2149 ($397, $3901). With the probabilistic sensitivity analysis approach, the incremental difference was $2583 ($778, $4346). Although the true cost of the program is unknown, probabilistic sensitivity analysis may be a more viable alternative for capturing variability in estimates of programmatic costs when dealing with missing data, particularly with small sample sizes and the lack of strong predictor variables. Further, the larger standard errors produced by the probabilistic sensitivity analysis method may signal its ability to capture more of the variability in the data, thus better informing policymakers on the potentially true cost of the intervention. PMID:23299559

Economic analysis of a multi-site prevention program: assessment of program costs and characterizing site-level variability.

PubMed

Corso, Phaedra S; Ingels, Justin B; Kogan, Steven M; Foster, E Michael; Chen, Yi-Fu; Brody, Gene H

2013-10-01

Programmatic cost analyses of preventive interventions commonly have a number of methodological difficulties. To determine the mean total costs and properly characterize variability, one often has to deal with small sample sizes, skewed distributions, and especially missing data. Standard approaches for dealing with missing data such as multiple imputation may suffer from a small sample size, a lack of appropriate covariates, or too few details around the method used to handle the missing data. In this study, we estimate total programmatic costs for a prevention trial evaluating the Strong African American Families-Teen program. This intervention focuses on the prevention of substance abuse and risky sexual behavior. To account for missing data in the assessment of programmatic costs we compare multiple imputation to probabilistic sensitivity analysis. The latter approach uses collected cost data to create a distribution around each input parameter. We found that with the multiple imputation approach, the mean (95 % confidence interval) incremental difference was $2,149 ($397, $3,901). With the probabilistic sensitivity analysis approach, the incremental difference was $2,583 ($778, $4,346). Although the true cost of the program is unknown, probabilistic sensitivity analysis may be a more viable alternative for capturing variability in estimates of programmatic costs when dealing with missing data, particularly with small sample sizes and the lack of strong predictor variables. Further, the larger standard errors produced by the probabilistic sensitivity analysis method may signal its ability to capture more of the variability in the data, thus better informing policymakers on the potentially true cost of the intervention.

Factors Related to Instructional Leadership Perception and Effect of Instructional Leadership on Organizational Variables: A Meta-Analysis

ERIC Educational Resources Information Center

Sisman, Mehmet

2016-01-01

In this meta-analysis, effects of teacher characteristics on instructional leadership perceptions and some organizational variables is tested. Findings of the total of 67 independent studies are gathered in the meta-analysis which represents a population of 36,756. According to the findings of this meta-analysis performed by using random effects…

Quantitative effects of composting state variables on C/N ratio through GA-aided multivariate analysis.

PubMed

Sun, Wei; Huang, Guo H; Zeng, Guangming; Qin, Xiaosheng; Yu, Hui

2011-03-01

It is widely known that variation of the C/N ratio is dependent on many state variables during composting processes. This study attempted to develop a genetic algorithm aided stepwise cluster analysis (GASCA) method to describe the nonlinear relationships between the selected state variables and the C/N ratio in food waste composting. The experimental data from six bench-scale composting reactors were used to demonstrate the applicability of GASCA. Within the GASCA framework, GA searched optimal sets of both specified state variables and SCA's internal parameters; SCA established statistical nonlinear relationships between state variables and the C/N ratio; to avoid unnecessary and time-consuming calculation, a proxy table was introduced to save around 70% computational efforts. The obtained GASCA cluster trees had smaller sizes and higher prediction accuracy than the conventional SCA trees. Based on the optimal GASCA tree, the effects of the GA-selected state variables on the C/N ratio were ranged in a descending order as: NH₄+-N concentration>Moisture content>Ash Content>Mean Temperature>Mesophilic bacteria biomass. Such a rank implied that the variation of ammonium nitrogen concentration, the associated temperature and the moisture conditions, the total loss of both organic matters and available mineral constituents, and the mesophilic bacteria activity, were critical factors affecting the C/N ratio during the investigated food waste composting. This first application of GASCA to composting modelling indicated that more direct search algorithms could be coupled with SCA or other multivariate analysis methods to analyze complicated relationships during composting and many other environmental processes. Copyright © 2010 Elsevier B.V. All rights reserved.

smRithm: Graphical user interface for heart rate variability analysis.

PubMed

Nara, Sanjeev; Kaur, Manvinder; Datta, Saurav

2015-01-01

Over the past 25 years, Heart rate variability (HRV) has become a non-invasive research and clinical tool for indirectly carrying out investigation of both cardiac and autonomic system function in both healthy and diseased. It provides valuable information about a wide range of cardiovascular disorders, pulmonary diseases, neurological diseases, etc. Its primary purpose is to access the functioning of the nervous system. The source of information for HRV analysis is the continuous beat to beat measurement of inter-beat intervals. The electrocardiography (ECG or EKG) is considered as the best way to measure inter-beat intervals. This paper proposes an open source Graphical User Interface (GUI): smRithm developed in MATLAB for HRV analysis that will apply effective techniques on the raw ECG signals to process and decompose it in a simpler manner to obtain more useful information out of signals that can be utilized for more powerful and efficient applications in the near future related to HRV.

a Latent Variable Path Analysis Model of Secondary Physics Enrollments in New York State.

NASA Astrophysics Data System (ADS)

Sobolewski, Stanley John

The Percentage of Enrollment in Physics (PEP) at the secondary level nationally has been approximately 20% for the past few decades. For a more scientifically literate citizenry as well as specialists to continue scientific research and development, it is desirable that more students enroll in physics. Some of the predictor variables for physics enrollment and physics achievement that have been identified previously includes a community's socioeconomic status, the availability of physics, the sex of the student, the curriculum, as well as teacher and student data. This study isolated and identified predictor variables for PEP of secondary schools in New York. Data gathered by the State Education Department for the 1990-1991 school year was used. The source of this data included surveys completed by teachers and administrators on student characteristics and school facilities. A data analysis similar to that done by Bryant (1974) was conducted to determine if the relationships between a set of predictor variables related to physics enrollment had changed in the past 20 years. Variables which were isolated included: community, facilities, teacher experience, number of type of science courses, school size and school science facilities. When these variables were isolated, latent variable path diagrams were proposed and verified by the Linear Structural Relations computer modeling program (LISREL). These diagrams differed from those developed by Bryant in that there were more manifest variables used which included achievement scores in the form of Regents exam results. Two criterion variables were used, percentage of students enrolled in physics (PEP) and percent of students enrolled passing the Regents physics exam (PPP). The first model treated school and community level variables as exogenous while the second model treated only the community level variables as exogenous. The goodness of fit indices for the models was 0.77 for the first model and 0.83 for the second

Influence of variable selection on partial least squares discriminant analysis models for explosive residue classification

NASA Astrophysics Data System (ADS)

De Lucia, Frank C., Jr.; Gottfried, Jennifer L.

2011-02-01

Using a series of thirteen organic materials that includes novel high-nitrogen energetic materials, conventional organic military explosives, and benign organic materials, we have demonstrated the importance of variable selection for maximizing residue discrimination with partial least squares discriminant analysis (PLS-DA). We built several PLS-DA models using different variable sets based on laser induced breakdown spectroscopy (LIBS) spectra of the organic residues on an aluminum substrate under an argon atmosphere. The model classification results for each sample are presented and the influence of the variables on these results is discussed. We found that using the whole spectra as the data input for the PLS-DA model gave the best results. However, variables due to the surrounding atmosphere and the substrate contribute to discrimination when the whole spectra are used, indicating this may not be the most robust model. Further iterative testing with additional validation data sets is necessary to determine the most robust model.

Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

2018-05-01

In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

Single Cell Analysis: From Technology to Biology and Medicine.

PubMed

Pan, Xinghua

2014-01-01

Single-cell analysis heralds a new era that allows "omics" analysis, notably genomics, transcriptomics, epigenomics and proteomics at the single-cell level. It enables the identification of the minor subpopulations that may play a critical role in a biological process of a population of cells, which conventionally are regarded as homogeneous. It provides an ultra-sensitive tool to clarify specific molecular mechanisms and pathways and reveal the nature of cell heterogeneity. It also facilitates the clinical investigation of patients when a very low quantity or a single cell is available for analysis, such as noninvasive prenatal diagnosis and cancer screening, and genetic evaluation for in vitro fertilization. Within a few short years, single-cell analysis, especially whole genomic sequencing and transcriptomic sequencing, is becoming robust and broadly accessible, although not yet a routine practice. Here, with single cell RNA-seq emphasized, an overview of the discipline, progresses, and prospects of single-cell analysis and its applications in biology and medicine are given with a series of logic and theoretical considerations.

Using robust principal component analysis to alleviate day-to-day variability in EEG based emotion classification.

PubMed

Ping-Keng Jao; Yuan-Pin Lin; Yi-Hsuan Yang; Tzyy-Ping Jung

2015-08-01

An emerging challenge for emotion classification using electroencephalography (EEG) is how to effectively alleviate day-to-day variability in raw data. This study employed the robust principal component analysis (RPCA) to address the problem with a posed hypothesis that background or emotion-irrelevant EEG perturbations lead to certain variability across days and somehow submerge emotion-related EEG dynamics. The empirical results of this study evidently validated our hypothesis and demonstrated the RPCA's feasibility through the analysis of a five-day dataset of 12 subjects. The RPCA allowed tackling the sparse emotion-relevant EEG dynamics from the accompanied background perturbations across days. Sequentially, leveraging the RPCA-purified EEG trials from more days appeared to improve the emotion-classification performance steadily, which was not found in the case using the raw EEG features. Therefore, incorporating the RPCA with existing emotion-aware machine-learning frameworks on a longitudinal dataset of each individual may shed light on the development of a robust affective brain-computer interface (ABCI) that can alleviate ecological inter-day variability.

Variable mechanical ventilation

PubMed Central

Fontela, Paula Caitano; Prestes, Renata Bernardy; Forgiarini Jr., Luiz Alberto; Friedman, Gilberto

2017-01-01

Objective To review the literature on the use of variable mechanical ventilation and the main outcomes of this technique. Methods Search, selection, and analysis of all original articles on variable ventilation, without restriction on the period of publication and language, available in the electronic databases LILACS, MEDLINE®, and PubMed, by searching the terms "variable ventilation" OR "noisy ventilation" OR "biologically variable ventilation". Results A total of 36 studies were selected. Of these, 24 were original studies, including 21 experimental studies and three clinical studies. Conclusion Several experimental studies reported the beneficial effects of distinct variable ventilation strategies on lung function using different models of lung injury and healthy lungs. Variable ventilation seems to be a viable strategy for improving gas exchange and respiratory mechanics and preventing lung injury associated with mechanical ventilation. However, further clinical studies are necessary to assess the potential of variable ventilation strategies for the clinical improvement of patients undergoing mechanical ventilation. PMID:28444076

Preserving subject variability in group fMRI analysis: performance evaluation of GICA vs. IVA

PubMed Central

Michael, Andrew M.; Anderson, Mathew; Miller, Robyn L.; Adalı, Tülay; Calhoun, Vince D.

2014-01-01

Independent component analysis (ICA) is a widely applied technique to derive functionally connected brain networks from fMRI data. Group ICA (GICA) and Independent Vector Analysis (IVA) are extensions of ICA that enable users to perform group fMRI analyses; however a full comparison of the performance limits of GICA and IVA has not been investigated. Recent interest in resting state fMRI data with potentially higher degree of subject variability makes the evaluation of the above techniques important. In this paper we compare component estimation accuracies of GICA and an improved version of IVA using simulated fMRI datasets. We systematically change the degree of inter-subject spatial variability of components and evaluate estimation accuracy over all spatial maps (SMs) and time courses (TCs) of the decomposition. Our results indicate the following: (1) at low levels of SM variability or when just one SM is varied, both GICA and IVA perform well, (2) at higher levels of SM variability or when more than one SMs are varied, IVA continues to perform well but GICA yields SM estimates that are composites of other SMs with errors in TCs, (3) both GICA and IVA remove spatial correlations of overlapping SMs and introduce artificial correlations in their TCs, (4) if number of SMs is over estimated, IVA continues to perform well but GICA introduces artifacts in the varying and extra SMs with artificial correlations in the TCs of extra components, and (5) in the absence or presence of SMs unique to one subject, GICA produces errors in TCs and IVA estimates are accurate. In summary, our simulation experiments (both simplistic and realistic) and our holistic analyses approach indicate that IVA produces results that are closer to ground truth and thereby better preserves subject variability. The improved version of IVA is now packaged into the GIFT toolbox (http://mialab.mrn.org/software/gift). PMID:25018704

Comparison of Two- and Three-Dimensional Methods for Analysis of Trunk Kinematic Variables in the Golf Swing.

PubMed

Smith, Aimée C; Roberts, Jonathan R; Wallace, Eric S; Kong, Pui; Forrester, Stephanie E

2016-02-01

Two-dimensional methods have been used to compute trunk kinematic variables (flexion/extension, lateral bend, axial rotation) and X-factor (difference in axial rotation between trunk and pelvis) during the golf swing. Recent X-factor studies advocated three-dimensional (3D) analysis due to the errors associated with two-dimensional (2D) methods, but this has not been investigated for all trunk kinematic variables. The purpose of this study was to compare trunk kinematic variables and X-factor calculated by 2D and 3D methods to examine how different approaches influenced their profiles during the swing. Trunk kinematic variables and X-factor were calculated for golfers from vectors projected onto the global laboratory planes and from 3D segment angles. Trunk kinematic variable profiles were similar in shape; however, there were statistically significant differences in trunk flexion (-6.5 ± 3.6°) at top of backswing and trunk right-side lateral bend (8.7 ± 2.9°) at impact. Differences between 2D and 3D X-factor (approximately 16°) could largely be explained by projection errors introduced to the 2D analysis through flexion and lateral bend of the trunk and pelvis segments. The results support the need to use a 3D method for kinematic data calculation to accurately analyze the golf swing.

32 CFR 507.12 - Possession and wearing.

Code of Federal Regulations, 2012 CFR

2012-07-01

... HERALDIC DESIGNS AND HERALDIC QUALITY CONTROL PROGRAM Commercial Use of Heraldic Designs § 507.12..., society, or other group of persons without prior approval in writing by the Secretary of the Army or the...

32 CFR 507.12 - Possession and wearing.

Code of Federal Regulations, 2010 CFR

2010-07-01

... HERALDIC DESIGNS AND HERALDIC QUALITY CONTROL PROGRAM Commercial Use of Heraldic Designs § 507.12..., society, or other group of persons without prior approval in writing by the Secretary of the Army or the...

32 CFR 507.12 - Possession and wearing.

Code of Federal Regulations, 2013 CFR

2013-07-01

... HERALDIC DESIGNS AND HERALDIC QUALITY CONTROL PROGRAM Commercial Use of Heraldic Designs § 507.12..., society, or other group of persons without prior approval in writing by the Secretary of the Army or the...

32 CFR 507.12 - Possession and wearing.

Code of Federal Regulations, 2011 CFR

2011-07-01

... HERALDIC DESIGNS AND HERALDIC QUALITY CONTROL PROGRAM Commercial Use of Heraldic Designs § 507.12..., society, or other group of persons without prior approval in writing by the Secretary of the Army or the...

32 CFR 507.12 - Possession and wearing.

Code of Federal Regulations, 2014 CFR

2014-07-01

... HERALDIC DESIGNS AND HERALDIC QUALITY CONTROL PROGRAM Commercial Use of Heraldic Designs § 507.12..., society, or other group of persons without prior approval in writing by the Secretary of the Army or the...

Urban vs. Rural CLIL: An Analysis of Input-Related Variables, Motivation and Language Attainment

ERIC Educational Resources Information Center

Alejo, Rafael; Piquer-Píriz, Ana

2016-01-01

The present article carries out an in-depth analysis of the differences in motivation, input-related variables and linguistic attainment of the students at two content and language integrated learning (CLIL) schools operating within the same institutional and educational context, the Spanish region of Extremadura, and differing only in terms of…

Classical Item Analysis Using Latent Variable Modeling: A Note on a Direct Evaluation Procedure

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2011-01-01

A directly applicable latent variable modeling procedure for classical item analysis is outlined. The method allows one to point and interval estimate item difficulty, item correlations, and item-total correlations for composites consisting of categorical items. The approach is readily employed in empirical research and as a by-product permits…

Controlling for exogenous environmental variables when using data envelopment analysis for regional environmental assessments.

PubMed

Macpherson, Alexander J; Principe, Peter P; Shao, Yang

2013-04-15

Researchers are increasingly using data envelopment analysis (DEA) to examine the efficiency of environmental policies and resource allocations. An assumption of the basic DEA model is that decisionmakers operate within homogeneous environments. But, this assumption is not valid when environmental performance is influenced by variables beyond managerial control. Understanding the influence of these variables is important to distinguish between characterizing environmental conditions and identifying opportunities to improve environmental performance. While environmental assessments often focus on characterizing conditions, the point of using DEA is to identify opportunities to improve environmental performance and thereby prevent (or rectify) an inefficient allocation of resources. We examine the role of exogenous variables such as climate, hydrology, and topography in producing environmental impacts such as deposition, runoff, invasive species, and forest fragmentation within the United States Mid-Atlantic region. We apply a four-stage procedure to adjust environmental impacts in a DEA model that seeks to minimize environmental impacts while obtaining given levels of socioeconomic outcomes. The approach creates a performance index that bundles multiple indicators while adjusting for variables that are outside management control, offering numerous advantages for environmental assessment. Published by Elsevier Ltd.

Mixture Factor Analysis for Approximating a Nonnormally Distributed Continuous Latent Factor with Continuous and Dichotomous Observed Variables

ERIC Educational Resources Information Center

Wall, Melanie M.; Guo, Jia; Amemiya, Yasuo

2012-01-01

Mixture factor analysis is examined as a means of flexibly estimating nonnormally distributed continuous latent factors in the presence of both continuous and dichotomous observed variables. A simulation study compares mixture factor analysis with normal maximum likelihood (ML) latent factor modeling. Different results emerge for continuous versus…

Environmental forcing and Southern Ocean marine predator populations: effects of climate change and variability.

PubMed

Trathan, P N; Forcada, J; Murphy, E J

2007-12-29

The Southern Ocean is a major component within the global ocean and climate system and potentially the location where the most rapid climate change is most likely to happen, particularly in the high-latitude polar regions. In these regions, even small temperature changes can potentially lead to major environmental perturbations. Climate change is likely to be regional and may be expressed in various ways, including alterations to climate and weather patterns across a variety of time-scales that include changes to the long interdecadal background signals such as the development of the El Niño-Southern Oscillation (ENSO). Oscillating climate signals such as ENSO potentially provide a unique opportunity to explore how biological communities respond to change. This approach is based on the premise that biological responses to shorter-term sub-decadal climate variability signals are potentially the best predictor of biological responses over longer time-scales. Around the Southern Ocean, marine predator populations show periodicity in breeding performance and productivity, with relationships with the environment driven by physical forcing from the ENSO region in the Pacific. Wherever examined, these relationships are congruent with mid-trophic-level processes that are also correlated with environmental variability. The short-term changes to ecosystem structure and function observed during ENSO events herald potential long-term changes that may ensue following regional climate change. For example, in the South Atlantic, failure of Antarctic krill recruitment will inevitably foreshadow recruitment failures in a range of higher trophic-level marine predators. Where predator species are not able to accommodate by switching to other prey species, population-level changes will follow. The Southern Ocean, though oceanographically interconnected, is not a single ecosystem and different areas are dominated by different food webs. Where species occupy different positions in

HERALD (health economics using routine anonymised linked data).

PubMed

Husain, Muhammad J; Brophy, Sinead; Macey, Steven; Pinder, Leila M; Atkinson, Mark D; Cooksey, Roxanne; Phillips, Ceri J; Siebert, Stefan

2012-03-29

Health economic analysis traditionally relies on patient derived questionnaire data, routine datasets, and outcomes data from experimental randomised control trials and other clinical studies, which are generally used as stand-alone datasets. Herein, we outline the potential implications of linking these datasets to give one single joined up data-resource for health economic analysis. The linkage of individual level data from questionnaires with routinely-captured health care data allows the entire patient journey to be mapped both retrospectively and prospectively. We illustrate this with examples from an Ankylosing Spondylitis (AS) cohort by linking patient reported study dataset with the routinely collected general practitioner (GP) data, inpatient (IP) and outpatient (OP) datasets, and Accident and Emergency department data in Wales. The linked data system allows: (1) retrospective and prospective tracking of patient pathways through multiple healthcare facilities; (2) validation and clarification of patient-reported recall data, complementing the questionnaire/routine data information; (3) obtaining objective measure of the costs of chronic conditions for a longer time horizon, and during the pre-diagnosis period; (4) assessment of health service usage, referral histories, prescribed drugs and co-morbidities; and (5) profiling and stratification of patients relating to disease manifestation, lifestyles, co-morbidities, and associated costs. Using the GP data system we tracked about 183 AS patients retrospectively and prospectively from the date of questionnaire completion to gather the following information: (a) number of GP events; (b) presence of a GP 'drug' read codes; and (c) the presence of a GP 'diagnostic' read codes. We tracked 236 and 296 AS patients through the OP and IP data systems respectively to count the number of OP visits; and IP admissions and duration. The results are presented under several patient stratification schemes based on disease

Variability Analysis based on POSS1/POSS2 Photometry

NASA Astrophysics Data System (ADS)

Mickaelian, Areg M.; Sarkissian, Alain; Sinamyan, Parandzem K.

2012-04-01

We introduce accurate magnitudes as combined calculations from catalogues based on accurate measurements of POSS1- and POSS2-epoch plates. The photometric accuracy of various catalogues was established, and statistical weights for each of them have been calculated. To achieve the best possible magnitudes, we used weighted averaging of data from APM, MAPS, USNO-A2.0, USNO-B1.0 (for POSS1-epoch), and USNO-B1.0 and GSC 2.3.2 (for POSS2-epoch) catalogues. The r.m.s. accuracy of magnitudes achieved for POSS1 is 0.184 in B and 0.173 mag in R, or 0.138 in B and 0.128 in R for POSS2. By adopting those new magnitudes we examined the First Byurakan Survey (FBS) of blue stellar objects for variability, and uncovered 336 probable and possible variables among 1103 objects with POSS2-POSS1 >= 3σ of the errors, including 161 highly probable variables. We have developed methods to control and exclude accidental errors for any survey. We compared and combined our results with those given in Northern Sky Variability Survey (NSVS) database, and obtained firm candidates for variability. By such an approach it will be possible to conduct investigations of variability for large numbers of objects.

Multiband Fourier Analysis and Interstellar Reddening of the Variable Stars in the Globular Cluster NGC 6402 (M14)

NASA Astrophysics Data System (ADS)

Weinschenk, Sedrick; Murphy, Brian; Villiger, Nathan J.

2018-01-01

We present a detailed study of the variable stars in the globular cluster NGC 6402 (M14). Approximately 1500 B and V band images were collected from July 2016 to August 2017 using the SARA Consortium Jacobus Kaptyen 1-meter telescope located in the Canary Islands. Using difference image analysis, we were able to identify 145 probable variable stars, confirming the 133 previously known variables and adding 12 new variables. The variables consisted of 117 RR Lyrae stars, 18 long period variables, 2 eclipsing variables, 6 Cepheid variables, and 2 SX Phoenix variables. Of the RR Lyrae variables 55 were of fundamental mode RR0 stars, of which 18 exhibited the Blazhko effect, 57 were of 1st overtone RR1, of which 7 appear to exhibit the Blazhko effect, 1 2nd overtone RR2, and 2 double mode variables. We found an average period of 0.59016 days for RR0 stars and 0.30294 days for RR1 stars. Using the multiband light curves of both the RR0 and RR1 variables we found an average E(B-V) of 0.604 with a scatter of 0.15 magnitudes. Using Fourier decomposition of the RR Lyrae light curves we also determined the metallicity and distance of the NGC 6402.

Initiating an ergonomic analysis. A process for jobs with highly variable tasks.

PubMed

Conrad, K M; Lavender, S A; Reichelt, P A; Meyer, F T

2000-09-01

Occupational health nurses play a vital role in addressing ergonomic problems in the workplace. Describing and documenting exposure to ergonomic risk factors is a relatively straightforward process in jobs in which the work is repetitive. In other types of work, the analysis becomes much more challenging because tasks may be repeated infrequently, or at irregular time intervals, or under different environmental and temporal conditions, thereby making it difficult to observe a "representative" sample of the work performed. This article describes a process used to identify highly variable job tasks for ergonomic analyses. The identification of tasks for ergonomic analysis was a two step process involving interviews and a survey of firefighters and paramedics from a consortium of 14 suburban fire departments. The interviews were used to generate a list of frequently performed, physically strenuous job tasks and to capture clear descriptions of those tasks and associated roles. The goals of the survey were to confirm the interview findings across the entire target population and to quantify the frequency and degree of strenuousness of each task. In turn, the quantitative results from the survey were used to prioritize job tasks for simulation. Although this process was used to study firefighters and paramedics, the approach is likely to be suitable for many other types of occupations in which the tasks are highly variable in content and irregular in frequency.

A comparison of spectral mixture analysis an NDVI for ascertaining ecological variables

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Bateson, C. Ann; Curtiss, Brian; Benning, Tracy L.

1993-01-01

In this study, we compare the performance of spectral mixture analysis to the Normalized Difference Vegetation Index (NDVI) in detecting change in a grassland across topographically-induced nutrient gradients and different management schemes. The Konza Prairie Research Natural Area, Kansas, is a relatively homogeneous tallgrass prairie in which change in vegetation productivity occurs with respect to topographic positions in each watershed. The area is the site of long-term studies of the influence of fire and grazing on tallgrass production and was the site of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) from 1987 to 1989. Vegetation indices such as NDVI are commonly used with imagery collected in few (less than 10) spectral bands. However, the use of only two bands (e.g. NDVI) does not adequately account for the complex of signals making up most surface reflectance. Influences from background spectral variation and spatial heterogeneity may confound the direct relationship with biological or biophysical variables. High dimensional multispectral data allows for the application position of techniques such as derivative analysis and spectral curve fitting, thereby increasing the probability of successfully modeling the reflectance from mixed surfaces. The higher number of bands permits unmixing of a greater number of surface components, separating the vegetation signal for further analyses relevant to biological variables.

Variable system: An alternative approach for the analysis of mediated moderation.

PubMed

Kwan, Joyce Lok Yin; Chan, Wai

2018-06-01

Mediated moderation (meMO) occurs when the moderation effect of the moderator (W) on the relationship between the independent variable (X) and the dependent variable (Y) is transmitted through a mediator (M). To examine this process empirically, 2 different model specifications (Type I meMO and Type II meMO) have been proposed in the literature. However, both specifications are found to be problematic, either conceptually or statistically. For example, it can be shown that each type of meMO model is statistically equivalent to a particular form of moderated mediation (moME), another process that examines the condition when the indirect effect from X to Y through M varies as a function of W. Consequently, it is difficult for one to differentiate these 2 processes mathematically. This study therefore has 2 objectives. First, we attempt to differentiate moME and meMO by proposing an alternative specification for meMO. Conceptually, this alternative specification is intuitively meaningful and interpretable, and, statistically, it offers meMO a unique representation that is no longer identical to its moME counterpart. Second, using structural equation modeling, we propose an integrated approach for the analysis of meMO as well as for other general types of conditional path models. VS, a computer software program that implements the proposed approach, has been developed to facilitate the analysis of conditional path models for applied researchers. Real examples are considered to illustrate how the proposed approach works in practice and to compare its performance against the traditional methods. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The contextual effects of social capital on health: a cross-national instrumental variable analysis.

PubMed

Kim, Daniel; Baum, Christopher F; Ganz, Michael L; Subramanian, S V; Kawachi, Ichiro

2011-12-01

Past research on the associations between area-level/contextual social capital and health has produced conflicting evidence. However, interpreting this rapidly growing literature is difficult because estimates using conventional regression are prone to major sources of bias including residual confounding and reverse causation. Instrumental variable (IV) analysis can reduce such bias. Using data on up to 167,344 adults in 64 nations in the European and World Values Surveys and applying IV and ordinary least squares (OLS) regression, we estimated the contextual effects of country-level social trust on individual self-rated health. We further explored whether these associations varied by gender and individual levels of trust. Using OLS regression, we found higher average country-level trust to be associated with better self-rated health in both women and men. Instrumental variable analysis yielded qualitatively similar results, although the estimates were more than double in size in both sexes when country population density and corruption were used as instruments. The estimated health effects of raising the percentage of a country's population that trusts others by 10 percentage points were at least as large as the estimated health effects of an individual developing trust in others. These findings were robust to alternative model specifications and instruments. Conventional regression and to a lesser extent IV analysis suggested that these associations are more salient in women and in women reporting social trust. In a large cross-national study, our findings, including those using instrumental variables, support the presence of beneficial effects of higher country-level trust on self-rated health. Previous findings for contextual social capital using traditional regression may have underestimated the true associations. Given the close linkages between self-rated health and all-cause mortality, the public health gains from raising social capital within and across

The contextual effects of social capital on health: a cross-national instrumental variable analysis

PubMed Central

Kim, Daniel; Baum, Christopher F; Ganz, Michael; Subramanian, S V; Kawachi, Ichiro

2011-01-01

Past observational studies of the associations of area-level/contextual social capital with health have revealed conflicting findings. However, interpreting this rapidly growing literature is difficult because estimates using conventional regression are prone to major sources of bias including residual confounding and reverse causation. Instrumental variable (IV) analysis can reduce such bias. Using data on up to 167 344 adults in 64 nations in the European and World Values Surveys and applying IV and ordinary least squares (OLS) regression, we estimated the contextual effects of country-level social trust on individual self-rated health. We further explored whether these associations varied by gender and individual levels of trust. Using OLS regression, we found higher average country-level trust to be associated with better self-rated health in both women and men. Instrumental variable analysis yielded qualitatively similar results, although the estimates were more than double in size in women and men using country population density and corruption as instruments. The estimated health effects of raising the percentage of a country's population that trusts others by 10 percentage points were at least as large as the estimated health effects of an individual developing trust in others. These findings were robust to alternative model specifications and instruments. Conventional regression and to a lesser extent IV analysis suggested that these associations are more salient in women and in women reporting social trust. In a large cross-national study, our findings, including those using instrumental variables, support the presence of beneficial effects of higher country-level trust on self-rated health. Past findings for contextual social capital using traditional regression may have underestimated the true associations. Given the close linkages between self-rated health and all-cause mortality, the public health gains from raising social capital within countries may

Analysis of Uncertainty and Variability in Finite Element Computational Models for Biomedical Engineering: Characterization and Propagation

PubMed Central

Mangado, Nerea; Piella, Gemma; Noailly, Jérôme; Pons-Prats, Jordi; Ballester, Miguel Ángel González

2016-01-01

Computational modeling has become a powerful tool in biomedical engineering thanks to its potential to simulate coupled systems. However, real parameters are usually not accurately known, and variability is inherent in living organisms. To cope with this, probabilistic tools, statistical analysis and stochastic approaches have been used. This article aims to review the analysis of uncertainty and variability in the context of finite element modeling in biomedical engineering. Characterization techniques and propagation methods are presented, as well as examples of their applications in biomedical finite element simulations. Uncertainty propagation methods, both non-intrusive and intrusive, are described. Finally, pros and cons of the different approaches and their use in the scientific community are presented. This leads us to identify future directions for research and methodological development of uncertainty modeling in biomedical engineering. PMID:27872840

Analysis of Uncertainty and Variability in Finite Element Computational Models for Biomedical Engineering: Characterization and Propagation.

PubMed

Mangado, Nerea; Piella, Gemma; Noailly, Jérôme; Pons-Prats, Jordi; Ballester, Miguel Ángel González

2016-01-01

Computational modeling has become a powerful tool in biomedical engineering thanks to its potential to simulate coupled systems. However, real parameters are usually not accurately known, and variability is inherent in living organisms. To cope with this, probabilistic tools, statistical analysis and stochastic approaches have been used. This article aims to review the analysis of uncertainty and variability in the context of finite element modeling in biomedical engineering. Characterization techniques and propagation methods are presented, as well as examples of their applications in biomedical finite element simulations. Uncertainty propagation methods, both non-intrusive and intrusive, are described. Finally, pros and cons of the different approaches and their use in the scientific community are presented. This leads us to identify future directions for research and methodological development of uncertainty modeling in biomedical engineering.

Analysis of walking variability through simultaneous evaluation of the head, lumbar, and lower-extremity acceleration in healthy youth

PubMed Central

Toda, Haruki; Nagano, Akinori; Luo, Zhiwei

2016-01-01

[Purpose] The purpose of this study was to clarify whether walking speed affects acceleration variability of the head, lumbar, and lower extremity by simultaneously evaluating of acceleration. [Subjects and Methods] Twenty young individuals recruited from among the staff at Kurashiki Heisei Hospital participated in this study. Eight accelerometers were used to measure the head, lumbar and lower extremity accelerations. The participants were instructed to walk at five walking speeds prescribed by a metronome. Acceleration variability was assessed by a cross-correlation analysis normalized using z-transform in order to evaluate stride-to-stride variability. [Results] Vertical acceleration variability was the smallest in all body parts, and walking speed effect had laterality. Antero-posterior acceleration variability was significantly associated with walking speed at sites other than the head. Medio-lateral acceleration variability of the bilateral hip alone was smaller than the antero-posterior variability. [Conclusion] The findings of this study suggest that the effect of walking speed changes on the stride-to-stride acceleration variability was individual for each body parts, and differs among directions. PMID:27390419

Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions

NASA Astrophysics Data System (ADS)

Jiang, H.; Lin, T.

2017-12-01

Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.

An Unexpected Surge in Plasma BKPyV Viral Load Heralds the Development of BKPyV-Associated Metastatic Bladder Cancer in a Lung Transplant Recipient With BKPyV Nephropathy.

PubMed

Kuppachi, S; Holanda, D; Eberlein, M; Alexiev, B; Tyler, A J; Wissel, M C; Kleiboeker, S B; Thomas, C P

2017-03-01

We report a lung transplant recipient who developed BK polyoma virus (BKPyV) DNAemia and BKPyV nephropathy. With careful management of his immunosuppression he achieved significant reduction in BKPyV DNAemia and stabilization of his kidney function. He later developed a high-grade bladder cancer and shortly thereafter he experienced a major upsurge in the level of BKPyV DNAemia that coincided with the discovery of hepatic metastasis. Retrospectively, the bladder cancer and the hepatic secondary tumor stained uniformly for SV40 large T antigen, and the BKPyV DNA sequences identified in plasma corresponded to BKPyV DNA within hepatic tissue, indicating that the spike in BKPyV load was likely derived from the circulating tumor cells or cell-free tumor DNA following metastases of a BKV-associated cancer. To the best of our knowledge, this is the first description of a surge in BKPyV load in a patient with controlled BKPyVN that heralded the appearance of a metastatic urothelial malignancy. This report discusses the literature on BKPyV-associated malignancies and the possibility that unexplained increases in BKPyV DNAemia may be a biomarker for metastatic BKPyV-related urothelial cancer. © Copyright 2016 The American Society of Transplantation and the American Society of Transplant Surgeons.

A Comparison of Approaches for the Analysis of Interaction Effects between Latent Variables Using Partial Least Squares Path Modeling

ERIC Educational Resources Information Center

Henseler, Jorg; Chin, Wynne W.

2010-01-01

In social and business sciences, the importance of the analysis of interaction effects between manifest as well as latent variables steadily increases. Researchers using partial least squares (PLS) to analyze interaction effects between latent variables need an overview of the available approaches as well as their suitability. This article…

The Use of Multiple Correspondence Analysis to Explore Associations between Categories of Qualitative Variables in Healthy Ageing.

PubMed

Costa, Patrício Soares; Santos, Nadine Correia; Cunha, Pedro; Cotter, Jorge; Sousa, Nuno

2013-01-01

The main focus of this study was to illustrate the applicability of multiple correspondence analysis (MCA) in detecting and representing underlying structures in large datasets used to investigate cognitive ageing. Principal component analysis (PCA) was used to obtain main cognitive dimensions, and MCA was used to detect and explore relationships between cognitive, clinical, physical, and lifestyle variables. Two PCA dimensions were identified (general cognition/executive function and memory), and two MCA dimensions were retained. Poorer cognitive performance was associated with older age, less school years, unhealthier lifestyle indicators, and presence of pathology. The first MCA dimension indicated the clustering of general/executive function and lifestyle indicators and education, while the second association was between memory and clinical parameters and age. The clustering analysis with object scores method was used to identify groups sharing similar characteristics. The weaker cognitive clusters in terms of memory and executive function comprised individuals with characteristics contributing to a higher MCA dimensional mean score (age, less education, and presence of indicators of unhealthier lifestyle habits and/or clinical pathologies). MCA provided a powerful tool to explore complex ageing data, covering multiple and diverse variables, showing if a relationship exists and how variables are related, and offering statistical results that can be seen both analytically and visually.

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis.

PubMed

Adeola, Abiodun M; Botai, Joel O; Rautenbach, Hannes; Adisa, Omolola M; Ncongwane, Katlego P; Botai, Christina M; Adebayo-Ojo, Temitope C

2017-11-08

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease's transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998-2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables' and malaria cases' time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature ( R ² = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in

Comparison of yellow poplar growth models on the basis of derived growth analysis variables

Treesearch

Keith F. Jensen; Daniel A. Yaussy

1986-01-01

Quadratic and cubic polynomials, and Gompertz and Richards asymptotic models were fitted to yellow poplar growth data. These data included height, leaf area, leaf weight and new shoot height for 23 weeks. Seven growth analysis variables were estimated from each function. The Gompertz and Richards models fitted the data best and provided the most accurate derived...

Job Satisfaction in Mexican Faculty: An Analysis of its Predictor Variables. ASHE Annual Meeting Paper.

ERIC Educational Resources Information Center

Galaz-Fontes, Jesus Francisco; Gil-Anton, Manuel

This study examined overall job satisfaction among college faculty in Mexico. The study used data from a 1992-93 Carnegie International Faculty Survey. Secondary multiple regression analysis identified predictor variables for several faculty subgroups. Results were interpreted by differentiating between work-related and intrinsic factors, as well…

Miniature Variable Pressure Scanning Electron Microscope for In-Situ Imaging and Chemical Analysis

NASA Technical Reports Server (NTRS)

Gaskin, Jessica A.; Jerman, Gregory; Gregory, Don; Sampson, Allen R.

2012-01-01

NASA Marshall Space Flight Center (MSFC) is leading an effort to develop a Miniaturized Variable Pressure Scanning Electron Microscope (MVP-SEM) for in-situ imaging and chemical analysis of uncoated samples. This instrument development will be geared towards operation on Mars and builds on a previous MSFC design of a mini-SEM for the moon (funded through the NASA Planetary Instrument Definition and Development Program). Because Mars has a dramatically different environment than the moon, modifications to the MSFC lunar mini-SEM are necessary. Mainly, the higher atmospheric pressure calls for the use of an electron gun that can operate at High Vacuum, rather than Ultra-High Vacuum. The presence of a CO2-rich atmosphere also allows for the incorporation of a variable pressure system that enables the in-situ analysis of nonconductive geological specimens. Preliminary testing of Mars meteorites in a commercial Environmental SEM(Tradmark) (FEI) confirms the usefulness of lowcurrent/low-accelerating voltage imaging and highlights the advantages of using the Mars atmosphere for environmental imaging. The unique capabilities of the MVP-SEM make it an ideal tool for pursuing key scientific goals of NASA's Flagship Mission Max-C; to perform in-situ science and collect and cache samples in preparation for sample return from Mars.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering.

PubMed

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor; Essex, M

2015-05-01

To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice.

Exploratory factor analysis for differentiating sensory and mechanical variables related to muscle-tendon unit elongation

PubMed Central

Chagas, Mauro H.; Magalhães, Fabrício A.; Peixoto, Gustavo H. C.; Pereira, Beatriz M.; Andrade, André G. P.; Menzel, Hans-Joachim K.

2016-01-01

ABSTRACT Background Stretching exercises are able to promote adaptations in the muscle-tendon unit (MTU), which can be tested through physiological and biomechanical variables. Identifying the key variables in MTU adaptations is crucial to improvements in training. Objective To perform an exploratory factor analysis (EFA) involving the variables often used to evaluate the response of the MTU to stretching exercises. Method Maximum joint range of motion (ROMMAX), ROM at first sensation of stretching (FSTROM), peak torque (torqueMAX), passive stiffness, normalized stiffness, passive energy, and normalized energy were investigated in 36 participants during passive knee extension on an isokinetic dynamometer. Stiffness and energy values were normalized by the muscle cross-sectional area and their passive mode assured by monitoring the EMG activity. Results EFA revealed two major factors that explained 89.68% of the total variance: 53.13% was explained by the variables torqueMAX, passive stiffness, normalized stiffness, passive energy, and normalized energy, whereas the remaining 36.55% was explained by the variables ROMMAX and FSTROM. Conclusion This result supports the literature wherein two main hypotheses (mechanical and sensory theories) have been suggested to describe the adaptations of the MTU to stretching exercises. Contrary to some studies, in the present investigation torqueMAX was significantly correlated with the variables of the mechanical theory rather than those of the sensory theory. Therefore, a new approach was proposed to explain the behavior of the torqueMAX during stretching exercises. PMID:27437715

Spatio-temporal analysis of the relationship between WNV dissemination and environmental variables in Indianapolis, USA.

PubMed

Liu, Hua; Weng, Qihao; Gaines, David

2008-12-18

This study developed a multi-temporal analysis on the relationship between West Nile Virus (WNV) dissemination and environmental variables by using an integrated approach of remote sensing, GIS, and statistical techniques. WNV mosquito cases in seven months (April-October) of the six years (2002-2007) were collected in Indianapolis, USA. Epidemic curves were plotted to identify the temporal outbreaks of WNV. Spatial-temporal analysis and k-mean cluster analysis were further applied to determine the high-risk areas. Finally, the relationship between environmental variables and WNV outbreaks were examined by using Discriminant Analysis. The results show that the WNV epidemic curve reached its peak in August for all years in the study area except in 2007, where the peak was reached in July. WNV dissemination started from the central longitudinal corridor of the city and spread out to the east and west. Different years and seasons had different high-risk areas, but the southwest and southeast corners show the highest risk for WNV infection due to their high percentages of agriculture and water sources. Major environmental factors contributing to the outbreak of WNV in Indianapolis were the percentages of agriculture and water, total length of streams, and total size of wetlands. This study provides important information for urban public health prevention and management. It also contributes to the optimization of mosquito control and arrangement of future sampling efforts.

Trend analysis of hydro-climatic variables in the north of Iran

NASA Astrophysics Data System (ADS)

Nikzad Tehrani, E.; Sahour, H.; Booij, M. J.

2018-04-01

Trend analysis of climate variables such as streamflow, precipitation, and temperature provides useful information for understanding the hydrological changes associated with climate change. In this study, a nonparametric Mann-Kendall test was employed to evaluate annual, seasonal, and monthly trends of precipitation and streamflow for the Neka basin in the north of Iran over a 44-year period (1972 to 2015). In addition, the Inverse Distance Weight (IDW) method was used for annual seasonal, monthly, and daily precipitation trends in order to investigate the spatial correlation between precipitation and streamflow trends in the study area. Results showed a downward trend in annual and winter precipitation (Z < -1.96) and an upward trend in annual maximum daily precipitation. Annual and monthly mean flows for most of the months in the Neka basin decreased by 14% significantly, but the annual maximum daily flow increased by 118%. Results for the trend analysis of streamflow and climatic variables showed that there are statistically significant relationships between precipitation and streamflow (p value < 0.05). Correlation coefficients for Kendall, Spearman's rank and linear regression are 0.43, 0.61, and 0.67, respectively. The spatial presentation of the detected precipitation and streamflow trends showed a downward trend for the mean annual precipitation observed in the upstream part of the study area which is consistent with the streamflow trend. Also, there is a good correlation between monthly and seasonal precipitation and streamflow for all sub-basins (Sefidchah, Gelvard, Abelu). In general, from a hydro-climatic point of view, the results showed that the study area is moving towards a situation with more severe drought events.

Insights into gait disorders: walking variability using phase plot analysis, Parkinson's disease.

PubMed

Esser, Patrick; Dawes, Helen; Collett, Johnny; Howells, Ken

2013-09-01

Gait variability may have greater utility than spatio-temporal parameters and can, be an indication for risk of falling in people with Parkinson's disease (PD). Current methods rely on prolonged data collection in order to obtain large datasets which may be demanding to obtain. We set out to explore a phase plot variability analysis to differentiate typically developed adults (TDAs) from PD obtained from two 10 m walks. Fourteen people with PD and good mobility (Rivermead Mobility Index≥8) and ten aged matched TDA were recruited and walked over 10-m at self-selected walking speed. An inertial measurement unit was placed over the projected centre of mass (CoM) sampling at 100 Hz. Vertical CoM excursion was derived to determine modelled spatiotemporal data after which the phase plot analysis was applied producing a cloud of datapoints. SDA described the spread and SDB the width of the cloud with β the angular vector of the data points. The ratio (∀) was defined as SDA: SDB. Cadence (p=.342) and stride length (p=.615) did not show a significance between TDA and PD. A difference was found for walking speed (p=.041). Furthermore a significant difference was found for β (p=.010), SDA (p=.004) other than SDB (p=.385) or ratio ∀ (p=.830). Two sequential 10-m walks showed no difference in PD for cadence (p=.193), stride length (p=.683), walking speed (p=.684) and β (p=.194), SDA (p=.051), SDB (p=.145) or ∀ (p=.226). The proposed phase plot analysis, performed on CoM motion could be used to reliably differentiate PD from TDA over a 10-m walk. Copyright © 2013 Elsevier B.V. All rights reserved.

[Comparative analysis of variable regions in the genomes of variola virus].

PubMed

Babkin, I V; Nepomniashchikh, T S; Maksiutov, R A; Gutorov, V V; Babkina, I N; Shchelkunov, S N

2008-01-01

Nucleotide sequences of two extended segments of the terminal variable regions in variola virus genome were determined. The size of the left segment was 13.5 kbp and of the right, 10.5 kbp. Totally, over 540 kbp were sequenced for 22 variola virus strains. The conducted phylogenetic analysis and the data published earlier allowed us to find the interrelations between 70 variola virus isolates, the character of their clustering, and the degree of intergroup and intragroup variations of the clusters of variola virus strains. The most polymorphic loci of the genome segments studied were determined. It was demonstrated that that these loci are localized to either noncoding genome regions or to the regions of destroyed open reading frames, characteristic of the ancestor virus. These loci are promising for development of the strategy for genotyping variola virus strains. Analysis of recombination using various methods demonstrated that, with the only exception, no statistically significant recombinational events in the genomes of variola virus strains studied were detectable.

Analysis of Within-Test Variability of Non-Destructive Test Methods to Evaluate Compressive Strength of Normal Vibrated and Self-Compacting Concretes

NASA Astrophysics Data System (ADS)

Nepomuceno, Miguel C. S.; Lopes, Sérgio M. R.

2017-10-01

Non-destructive tests (NDT) have been used in the last decades for the assessment of in-situ quality and integrity of concrete elements. An important step in the application of NDT methods concerns to the interpretation and validation of the test results. In general, interpretation of NDT results should involve three distinct phases leading to the development of conclusions: processing of collected data, analysis of within-test variability and quantitative evaluation of property under investigation. The analysis of within-test variability can provide valuable information, since this can be compared with that of within-test variability associated with the NDT method in use, either to provide a measure of the quality control or to detect the presence of abnormal circumstances during the in-situ application. This paper reports the analysis of the experimental results of within-test variability of NDT obtained for normal vibrated concrete and self-compacting concrete. The NDT reported includes the surface hardness test, ultrasonic pulse velocity test, penetration resistance test, pull-off test, pull-out test and maturity test. The obtained results are discussed and conclusions are presented.

Instrumental Variable Analysis with a Nonlinear Exposure–Outcome Relationship

PubMed Central

Davies, Neil M.; Thompson, Simon G.

2014-01-01

Background: Instrumental variable methods can estimate the causal effect of an exposure on an outcome using observational data. Many instrumental variable methods assume that the exposure–outcome relation is linear, but in practice this assumption is often in doubt, or perhaps the shape of the relation is a target for investigation. We investigate this issue in the context of Mendelian randomization, the use of genetic variants as instrumental variables. Methods: Using simulations, we demonstrate the performance of a simple linear instrumental variable method when the true shape of the exposure–outcome relation is not linear. We also present a novel method for estimating the effect of the exposure on the outcome within strata of the exposure distribution. This enables the estimation of localized average causal effects within quantile groups of the exposure or as a continuous function of the exposure using a sliding window approach. Results: Our simulations suggest that linear instrumental variable estimates approximate a population-averaged causal effect. This is the average difference in the outcome if the exposure for every individual in the population is increased by a fixed amount. Estimates of localized average causal effects reveal the shape of the exposure–outcome relation for a variety of models. These methods are used to investigate the relations between body mass index and a range of cardiovascular risk factors. Conclusions: Nonlinear exposure–outcome relations should not be a barrier to instrumental variable analyses. When the exposure–outcome relation is not linear, either a population-averaged causal effect or the shape of the exposure–outcome relation can be estimated. PMID:25166881

Temporal Patterns of Variable Relationships in Person-Oriented Research: Longitudinal Models of Configural Frequency Analysis

ERIC Educational Resources Information Center

von Eye, Alexander; Mun, Eun Young; Bogat, G. Anne

2008-01-01

This article reviews the premises of configural frequency analysis (CFA), including methods of choosing significance tests and base models, as well as protecting [alpha], and discusses why CFA is a useful approach when conducting longitudinal person-oriented research. CFA operates at the manifest variable level. Longitudinal CFA seeks to identify…

Evaluating measurement models in clinical research: covariance structure analysis of latent variable models of self-conception.

PubMed

Hoyle, R H

1991-02-01

Indirect measures of psychological constructs are vital to clinical research. On occasion, however, the meaning of indirect measures of psychological constructs is obfuscated by statistical procedures that do not account for the complex relations between items and latent variables and among latent variables. Covariance structure analysis (CSA) is a statistical procedure for testing hypotheses about the relations among items that indirectly measure a psychological construct and relations among psychological constructs. This article introduces clinical researchers to the strengths and limitations of CSA as a statistical procedure for conceiving and testing structural hypotheses that are not tested adequately with other statistical procedures. The article is organized around two empirical examples that illustrate the use of CSA for evaluating measurement models with correlated error terms, higher-order factors, and measured and latent variables.

A sensitivity analysis on the variability in accelerometer data processing for monitoring physical activity.

PubMed

Lee, Paul H

2015-02-01

Accelerometers are gaining popularity for measuring physical activity, but there are many different ways to process accelerometer data. A sensitivity analysis was conducted to study the effect of varying accelerometer data processing protocols on estimating the association between PA level and socio-demographic characteristics using the National Health and Nutrition Examination Survey (NHANES) accelerometer data. The NHANES waves 2003-2004 and 2005-2006 accelerometer data (n=14,072) were used to investigate the effect of changing the accelerometer non-wearing time and valid day definitions on the demographic composition of the filtered datasets and the association between physical activity (PA) and socio-demographic characteristics (sex, age, race, educational level, marital status). Under different filtering rules (minimum number of valid day and definition of non-wear time), the demographic characteristics of the final sample varied. The proportion of participants aged 20-29 decreased from 18.9% to 15.8% when the minimum number of valid days required increased from 1 to 4 (p for trend<0.001), whereas that for aged ≥70 years increased from 18.9% to 20.6% (p for trend<0.001). Furthermore, with different filters, the effect of these demographic variables and PA varied, with some variables being significant under certain filtering rules but becoming insignificant under some other rules. The sensitivity analysis showed that the significance of the association between socio-demographic variables and PA could be varied with the definition of non-wearing time and minimum number of valid days. Copyright © 2014 Elsevier B.V. All rights reserved.

Critical Consciousness: A Critique and Critical Analysis of the Literature

ERIC Educational Resources Information Center

Jemal, Alexis

2017-01-01

The education system has been heralded as a tool of liberation and simultaneously critiqued as a tool of social control to maintain the oppressive status quo. Critical consciousness (CC), developed by the Brazilian educator, Paulo Freire, advanced an educational pedagogy to liberate the masses from systemic inequity maintained and perpetuated by…

Dynamic analysis of four bar planar mechanism extended to six-bar planar mechanism with variable topology

NASA Astrophysics Data System (ADS)

Belleri, Basayya K.; Kerur, Shravankumar B.

2018-04-01

A computer-oriented procedure for solving the dynamic force analysis problem for general planar mechanisms is presented. This paper provides position analysis, velocity analysis, acceleration analysis and force analysis of six bar mechanism with variable topology approach. Six bar mechanism is constructed by joining two simple four bar mechanisms. Initially the position, velocity and acceleration analysis of first four bar mechanism are determined by using the input parameters. The outputs (angular displacement, velocity and acceleration of rocker)of first four bar mechanism are used as input parameter for the second four bar mechanism and the position, velocity, acceleration and forces are analyzed. With out-put parameters of second four-bar mechanism the force analysis of first four-bar mechanism is carried out.

Design and analysis of variable-twist tiltrotor blades using shape memory alloy hybrid composites

NASA Astrophysics Data System (ADS)

Park, Jae-Sang; Kim, Seong-Hwan; Jung, Sung Nam; Lee, Myeong-Kyu

2011-01-01

The tiltrotor blade, or proprotor, acts as a rotor in the helicopter mode and as a propeller in the airplane mode. For a better performance, the proprotor should have different built-in twist distributions along the blade span, suitable for each operational mode. This paper proposes a new variable-twist proprotor concept that can adjust the built-in twist distribution for given flight modes. For a variable-twist control, the present proprotor adopts shape memory alloy hybrid composites (SMAHC) containing shape memory alloy (SMA) wires embedded in the composite matrix. The proprotor of the Korea Aerospace Research Institute (KARI) Smart Unmanned Aerial Vehicle (SUAV), which is based on the tiltrotor concept, is used as a baseline proprotor model. The cross-sectional properties of the variable-twist proprotor are designed to maintain the cross-sectional properties of the original proprotor as closely as possible. However, the torsion stiffness is significantly reduced to accommodate the variable-twist control. A nonlinear flexible multibody dynamic analysis is employed to investigate the dynamic characteristics of the proprotor such as natural frequency and damping in the whirl flutter mode, the blade structural loads in a transition flight and the rotor performance in hover. The numerical results show that the present proprotor is designed to have a strong similarity to the baseline proprotor in dynamic and load characteristics. It is demonstrated that the present proprotor concept could be used to improve the hover performance adaptively when the variable-twist control using the SMAHC is applied appropriately.

Spatio-temporal analysis of preterm birth in Portugal and its relation with environmental variables

NASA Astrophysics Data System (ADS)

Oliveira, M.; Teodoro, Ana C.; Freitas, A.; Bernardes, J.; Gonçalves, H.

2016-10-01

Preterm birth (PTB), one of the major concerns in obstetrics, is conventionally defined as the delivery of a live infant before 37 completed weeks of gestation, and one of its causes may be environmental factors. Remote sensing is a valuable approach for monitoring environmental variables, including in health sciences. In this work, remote sensing data were used to explore the relation of the environment with PTB. Time-series with monthly rates of male/female ratio and PTB were obtained from Portugal in 2000-2014. The environmental variables included in this study were monthly mean temperatures (T), relative humidity (RH), NDVI, concentrations of NO2 and PM10 in 2003-2008. A temporal and spatial analysis of each health-related and environmental variable was performed, as well as their correlation. PTB has been increasing over time, from below 5% in 2000 to around 7% in 2014, with predominance of higher rates in districts with larger population. From 2003 to 2008, T and PM10 decreased significantly. A positive and significant correlation was found between male/female ratio and NO2 and RH, and to a lesser extent with PM10 and NDVI. PTB was also positively and significantly correlated with NO2 and T, and to a lesser extent with RH and PM10. These preliminary results suggest an association of PTB with most of the environmental variables studied, showing that more polluted and populated districts have higher rates of PTB. Further studies are warranted to explore interaction between the considered environmental factors and other variables related with risk for PTB.

Optimization of rainfall networks using information entropy and temporal variability analysis

NASA Astrophysics Data System (ADS)

Wang, Wenqi; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

2018-04-01

Rainfall networks are the most direct sources of precipitation data and their optimization and evaluation are essential and important. Information entropy can not only represent the uncertainty of rainfall distribution but can also reflect the correlation and information transmission between rainfall stations. Using entropy this study performs optimization of rainfall networks that are of similar size located in two big cities in China, Shanghai (in Yangtze River basin) and Xi'an (in Yellow River basin), with respect to temporal variability analysis. Through an easy-to-implement greedy ranking algorithm based on the criterion called, Maximum Information Minimum Redundancy (MIMR), stations of the networks in the two areas (each area is further divided into two subareas) are ranked during sliding inter-annual series and under different meteorological conditions. It is found that observation series with different starting days affect the ranking, alluding to the temporal variability during network evaluation. We propose a dynamic network evaluation framework for considering temporal variability, which ranks stations under different starting days with a fixed time window (1-year, 2-year, and 5-year). Therefore, we can identify rainfall stations which are temporarily of importance or redundancy and provide some useful suggestions for decision makers. The proposed framework can serve as a supplement for the primary MIMR optimization approach. In addition, during different periods (wet season or dry season) the optimal network from MIMR exhibits differences in entropy values and the optimal network from wet season tended to produce higher entropy values. Differences in spatial distribution of the optimal networks suggest that optimizing the rainfall network for changing meteorological conditions may be more recommended.

On FIA Variables For Ecological Use

Treesearch

David C. Chojnacky

2001-01-01

The Forest Inventory and Analysis (FIA) program collects or calculates over 300 variables for its national network of permanent forest plots. However, considerable ecological analysis can be done with only a few key variables. Two examples--Mexican spotted owl habitat in New Mexico and down deadwood in Maine--are used to illustrate the potential of FIA data for...

Bayesian Factor Analysis as a Variable Selection Problem: Alternative Priors and Consequences

PubMed Central

Lu, Zhao-Hua; Chow, Sy-Miin; Loken, Eric

2016-01-01

Factor analysis is a popular statistical technique for multivariate data analysis. Developments in the structural equation modeling framework have enabled the use of hybrid confirmatory/exploratory approaches in which factor loading structures can be explored relatively flexibly within a confirmatory factor analysis (CFA) framework. Recently, a Bayesian structural equation modeling (BSEM) approach (Muthén & Asparouhov, 2012) has been proposed as a way to explore the presence of cross-loadings in CFA models. We show that the issue of determining factor loading patterns may be formulated as a Bayesian variable selection problem in which Muthén and Asparouhov’s approach can be regarded as a BSEM approach with ridge regression prior (BSEM-RP). We propose another Bayesian approach, denoted herein as the Bayesian structural equation modeling with spike and slab prior (BSEM-SSP), which serves as a one-stage alternative to the BSEM-RP. We review the theoretical advantages and disadvantages of both approaches and compare their empirical performance relative to two modification indices-based approaches and exploratory factor analysis with target rotation. A teacher stress scale data set (Byrne, 2012; Pettegrew & Wolf, 1982) is used to demonstrate our approach. PMID:27314566

Multiscale entropy-based methods for heart rate variability complexity analysis

NASA Astrophysics Data System (ADS)

Silva, Luiz Eduardo Virgilio; Cabella, Brenno Caetano Troca; Neves, Ubiraci Pereira da Costa; Murta Junior, Luiz Otavio

2015-03-01

Physiologic complexity is an important concept to characterize time series from biological systems, which associated to multiscale analysis can contribute to comprehension of many complex phenomena. Although multiscale entropy has been applied to physiological time series, it measures irregularity as function of scale. In this study we purpose and evaluate a set of three complexity metrics as function of time scales. Complexity metrics are derived from nonadditive entropy supported by generation of surrogate data, i.e. SDiffqmax, qmax and qzero. In order to access accuracy of proposed complexity metrics, receiver operating characteristic (ROC) curves were built and area under the curves was computed for three physiological situations. Heart rate variability (HRV) time series in normal sinus rhythm, atrial fibrillation, and congestive heart failure data set were analyzed. Results show that proposed metric for complexity is accurate and robust when compared to classic entropic irregularity metrics. Furthermore, SDiffqmax is the most accurate for lower scales, whereas qmax and qzero are the most accurate when higher time scales are considered. Multiscale complexity analysis described here showed potential to assess complex physiological time series and deserves further investigation in wide context.

Analysis of spatio-temporal variability of C-factor derived from remote sensing data

NASA Astrophysics Data System (ADS)

Pechanec, Vilem; Benc, Antonin; Purkyt, Jan; Cudlin, Pavel

2016-04-01

In some risk areas water erosion as the present task has got the strong influence on agriculture and can threaten inhabitants. In our country combination of USLE and RUSLE models has been used for water erosion assessment (Krása et al., 2013). Role of vegetation cover is characterized by the help of vegetation protection factor, so-called C- factor. Value of C-factor is given by the ratio of washing-off on a plot with arable crops to standard plot which is kept as fallow regularly spud after any rain (Janeček et al., 2012). Under conditions we cannot identify crop structure and its turn, determination of C-factor can be problem in large areas. In such case we only determine C-factor according to the average crop representation. New technologies open possibilities for acceleration and specification of the approach. Present-day approach for the C-factor determination is based on the analysis of multispectral image data. Red and infrared spectrum is extracted and these parts of image are used for computation of vegetation index series (NDVI, TSAVI). Acquired values for fractional time sections (during vegetation period) are averaged out. At the same time values of vegetation indices for a forest and cleared area are determined. Also regressive coefficients are computed. Final calculation is done by the help of regressive equations expressing relation between values of NDVI and C-factor (De Jong, 1994; Van der Knijff, 1999; Karaburun, 2010). Up-to-date land use layer is used for the determination of erosion threatened areas on the base of selection of individual landscape segments of erosion susceptible categories of land use. By means of Landsat 7 data C-factor has been determined for the whole area of the Czech Republic in every month of the year of 2014. At the model area in a small watershed C-factor has been determined by the conventional (tabular) procedure. Analysis was focused on: i) variability assessment of C-factor values while using the conventional

Multiwavelength variability analysis of the FSRQ 3C 279

NASA Astrophysics Data System (ADS)

Patiño-Álvarez, V.; Chavushyan, V.; León-Tavares, J.; Carramiñana, A.; Carrasco, L.; Fernandes, S.; Schlegel, E. M.; López-Rodríguez, E.

2015-03-01

We present a multifrequency analysis of the variability in the flat-spectrum radio quasar 3C 279 from 2008 to 2014. Our multiwavelength dataset includes gamma-ray data from Fermi/LAT (Abdo et al. 2009), observations in 1mm from SMA (Gurwell et al. 2007), Near Infrared from OAGH (Carramiñana & Carrasco 2009) and SMARTS (Bonning et al. 2012); optical V band from the Steward Observatory (Smith et al. 2009) and SMARTS; optical spectra from OAGH (Patiño-Álvarez et al. 2013) and the Steward Observatory; and polarization spectra from the Steward Observatory. The light curves are shown in Fig. 1. Six out of seven optical activity periods identified within our dataset show clear counterparts in mm, NIR and gamma-rays, however, the late 2011 - early 2012 optical flare does not have a counterpart in the GeV regime. In this contribution, we discuss the flaring evolution of 3C 279 and speculate about the production of the anomalous activity period.

Multiscale adaptive analysis of circadian rhythms and intradaily variability: Application to actigraphy time series in acute insomnia subjects

PubMed Central

Rivera, Ana Leonor; Toledo-Roy, Juan C.; Ellis, Jason; Angelova, Maia

2017-01-01

Circadian rhythms become less dominant and less regular with chronic-degenerative disease, such that to accurately assess these pathological conditions it is important to quantify not only periodic characteristics but also more irregular aspects of the corresponding time series. Novel data-adaptive techniques, such as singular spectrum analysis (SSA), allow for the decomposition of experimental time series, in a model-free way, into a trend, quasiperiodic components and noise fluctuations. We compared SSA with the traditional techniques of cosinor analysis and intradaily variability using 1-week continuous actigraphy data in young adults with acute insomnia and healthy age-matched controls. The findings suggest a small but significant delay in circadian components in the subjects with acute insomnia, i.e. a larger acrophase, and alterations in the day-to-day variability of acrophase and amplitude. The power of the ultradian components follows a fractal 1/f power law for controls, whereas for those with acute insomnia this power law breaks down because of an increased variability at the 90min time scale, reminiscent of Kleitman’s basic rest-activity (BRAC) cycles. This suggests that for healthy sleepers attention and activity can be sustained at whatever time scale required by circumstances, whereas for those with acute insomnia this capacity may be impaired and these individuals need to rest or switch activities in order to stay focused. Traditional methods of circadian rhythm analysis are unable to detect the more subtle effects of day-to-day variability and ultradian rhythm fragmentation at the specific 90min time scale. PMID:28753669

Confirmatory Factor Analysis of Ordinal Variables with Misspecified Models

ERIC Educational Resources Information Center

Yang-Wallentin, Fan; Joreskog, Karl G.; Luo, Hao

2010-01-01

Ordinal variables are common in many empirical investigations in the social and behavioral sciences. Researchers often apply the maximum likelihood method to fit structural equation models to ordinal data. This assumes that the observed measures have normal distributions, which is not the case when the variables are ordinal. A better approach is…

Low-Frequency Temporal Variability in Mira and Semiregular Variables

NASA Astrophysics Data System (ADS)

Templeton, Matthew R.; Karovska, M.; Waagen, E. O.

2012-01-01

We investigate low-frequency variability in a large sample of Mira and semiregular variables with long-term visual light curves from the AAVSO International Database. Our aim is to determine whether we can detect and measure long-timescale variable phenomena in these stars, for example photometric variations that might be associated with supergranular convection. We analyzed the long-term light curves of 522 variable stars of the Mira and SRa, b, c, and d classes. We calculated their low-frequency time-series spectra to characterize rednoise with the power density spectrum index, and then correlate this index with other observable characteristics such as spectral type and primary pulsation period. In our initial analysis of the sample, we see that the semiregular variables have a much broader range of spectral index than the Mira types, with the SRb subtype having the broadest range. Among Mira variables we see that the M- and S-type Miras have similarly wide ranges of index, while the C-types have the narrowest with generally shallower slopes. There is also a trend of steeper slope with larger amplitude, but at a given amplitude, a wide range of slopes are seen. The ultimate goal of the project is to identify stars with strong intrinsic red noise components as possible targets for resolved surface imaging with interferometry.

RR Lyrae variables in M33: two new fields and an analysis of the galaxy's population

NASA Astrophysics Data System (ADS)

Tanakul, Nahathai; Yang, Soung-Chul; Sarajedini, Ata

2017-06-01

We present a re-analysis of M33 RR Lyrae variables in four different fields: two inner disc fields and two outer disc fields. These are located at 8.5, 8.7, 36 and 46 arcmin from the centre of M33, respectively. We identify 48 new RR Lyrae variable stars and refine the light-curve properties of 51 previously identified variables. From the light curves, we calculate reddenings and metallicities for each star. Using data in this paper and previously published material, we are able to construct a radial density profile for the RR Lyrae stars in M33. This profile, when plotted in log space, has a slope of ˜-2.0 ± 0.15 which agrees with the radial distribution of halo stars in the Milky Way and M31. This suggests that the majority of M33 RR Lyrae variables observed so far belong to the halo. We also examine the RR Lyrae specific frequency and absolute magnitude relation in M33 and find good agreement with previous studies.

Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis

PubMed Central

Hirayama, Jun-ichiro; Hyvärinen, Aapo; Kiviniemi, Vesa; Kawanabe, Motoaki; Yamashita, Okito

2016-01-01

Characterizing the variability of resting-state functional brain connectivity across subjects and/or over time has recently attracted much attention. Principal component analysis (PCA) serves as a fundamental statistical technique for such analyses. However, performing PCA on high-dimensional connectivity matrices yields complicated “eigenconnectivity” patterns, for which systematic interpretation is a challenging issue. Here, we overcome this issue with a novel constrained PCA method for connectivity matrices by extending the idea of the previously proposed orthogonal connectivity factorization method. Our new method, modular connectivity factorization (MCF), explicitly introduces the modularity of brain networks as a parametric constraint on eigenconnectivity matrices. In particular, MCF analyzes the variability in both intra- and inter-module connectivities, simultaneously finding network modules in a principled, data-driven manner. The parametric constraint provides a compact module-based visualization scheme with which the result can be intuitively interpreted. We develop an optimization algorithm to solve the constrained PCA problem and validate our method in simulation studies and with a resting-state functional connectivity MRI dataset of 986 subjects. The results show that the proposed MCF method successfully reveals the underlying modular eigenconnectivity patterns in more general situations and is a promising alternative to existing methods. PMID:28002474

Variable-number-of-tandem-repeats analysis of genetic diversity in Pasteuria ramosa.

PubMed

Mouton, L; Ebert, D

2008-05-01

Variable-number-of-tandem-repeats (VNTR) markers are increasingly being used in population genetic studies of bacteria. They were recently developed for Pasteuria ramosa, an endobacterium that infects Daphnia species. In the present study, we genotyped P. ramosa in 18 infected hosts from the United Kingdom, Belgium, and two lakes in the United States using seven VNTR markers. Two Daphnia species were collected: D. magna and D. dentifera. Six loci showed length polymorphism, with as many as five alleles identified for a single locus. Similarity coefficient calculations showed that the extent of genetic variation between pairs of isolates within populations differed according to the population, but it was always less than the genetic distances among populations. Analysis of the genetic distances performed using principal component analysis revealed strong clustering by location of origin, but not by host Daphnia species. Our study demonstrated that the VNTR markers available for P. ramosa are informative in revealing genetic differences within and among populations and may therefore become an important tool for providing detailed analysis of population genetics and epidemiology.

Temporal patterns of variable relationships in person-oriented research: longitudinal models of configural frequency analysis.

PubMed

von Eye, Alexander; Mun, Eun Young; Bogat, G Anne

2008-03-01

This article reviews the premises of configural frequency analysis (CFA), including methods of choosing significance tests and base models, as well as protecting alpha, and discusses why CFA is a useful approach when conducting longitudinal person-oriented research. CFA operates at the manifest variable level. Longitudinal CFA seeks to identify those temporal patterns that stand out as more frequent (CFA types) or less frequent (CFA antitypes) than expected with reference to a base model. A base model that has been used frequently in CFA applications, prediction CFA, and a new base model, auto-association CFA, are discussed for analysis of cross-classifications of longitudinal data. The former base model takes the associations among predictors and among criteria into account. The latter takes the auto-associations among repeatedly observed variables into account. Application examples of each are given using data from a longitudinal study of domestic violence. It is demonstrated that CFA results are not redundant with results from log-linear modeling or multinomial regression and that, of these approaches, CFA shows particular utility when conducting person-oriented research.

Tutorial in Biostatistics: Instrumental Variable Methods for Causal Inference*

PubMed Central

Baiocchi, Michael; Cheng, Jing; Small, Dylan S.

2014-01-01

A goal of many health studies is to determine the causal effect of a treatment or intervention on health outcomes. Often, it is not ethically or practically possible to conduct a perfectly randomized experiment and instead an observational study must be used. A major challenge to the validity of observational studies is the possibility of unmeasured confounding (i.e., unmeasured ways in which the treatment and control groups differ before treatment administration which also affect the outcome). Instrumental variables analysis is a method for controlling for unmeasured confounding. This type of analysis requires the measurement of a valid instrumental variable, which is a variable that (i) is independent of the unmeasured confounding; (ii) affects the treatment; and (iii) affects the outcome only indirectly through its effect on the treatment. This tutorial discusses the types of causal effects that can be estimated by instrumental variables analysis; the assumptions needed for instrumental variables analysis to provide valid estimates of causal effects and sensitivity analysis for those assumptions; methods of estimation of causal effects using instrumental variables; and sources of instrumental variables in health studies. PMID:24599889

Influence of management of variables, sampling zones and land units on LR analysis for landslide spatial prevision

NASA Astrophysics Data System (ADS)

Greco, R.; Sorriso-Valvo, M.

2013-09-01

Several authors, according to different methodological approaches, have employed logistic Regression (LR), a multivariate statistical analysis adopted to assess the spatial probability of landslide, even though its fundamental principles have remained unaltered. This study aims at assessing the influence of some of these methodological approaches on the performance of LR, through a series of sensitivity analyses developed over a test area of about 300 km2 in Calabria (southern Italy). In particular, four types of sampling (1 - the whole study area; 2 - transects running parallel to the general slope direction of the study area with a total surface of about 1/3 of the whole study area; 3 - buffers surrounding the phenomena with a 1/1 ratio between the stable and the unstable area; 4 - buffers surrounding the phenomena with a 1/2 ratio between the stable and the unstable area), two variable coding modes (1 - grouped variables; 2 - binary variables), and two types of elementary land (1 - cells units; 2 - slope units) units have been tested. The obtained results must be considered as statistically relevant in all cases (Aroc values > 70%), thus confirming the soundness of the LR analysis which maintains high predictive capacities notwithstanding the features of input data. As for the area under investigation, the best performing methodological choices are the following: (i) transects produced the best results (0 < P(y) ≤ 93.4%; Aroc = 79.5%); (ii) as for sampling modalities, binary variables (0 < P(y) ≤ 98.3%; Aroc = 80.7%) provide better performance than ordinated variables; (iii) as for the choice of elementary land units, slope units (0 < P(y) ≤ 100%; Aroc = 84.2%) have obtained better results than cells matrix.

A Generalized Stability Analysis of the AMOC in Earth System Models: Implication for Decadal Variability and Abrupt Climate Change

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

Fedorov, Alexey V.

2015-01-14

The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth systemmore » models, to the stability and variability of the AMOC in past climates.« less

32 CFR 507.11 - Reproduction of designs.

Code of Federal Regulations, 2012 CFR

2012-07-01

... HERALDIC DESIGNS AND HERALDIC QUALITY CONTROL PROGRAM Commercial Use of Heraldic Designs § 507.11 Reproduction of designs. (a) The photographing, printing, or, in any manner making or executing any engraving... 32 National Defense 3 2012-07-01 2009-07-01 true Reproduction of designs. 507.11 Section 507.11...

32 CFR 507.11 - Reproduction of designs.

Code of Federal Regulations, 2013 CFR

2013-07-01

... HERALDIC DESIGNS AND HERALDIC QUALITY CONTROL PROGRAM Commercial Use of Heraldic Designs § 507.11 Reproduction of designs. (a) The photographing, printing, or, in any manner making or executing any engraving... 32 National Defense 3 2013-07-01 2013-07-01 false Reproduction of designs. 507.11 Section 507.11...

32 CFR 507.11 - Reproduction of designs.

Code of Federal Regulations, 2014 CFR

2014-07-01

... HERALDIC DESIGNS AND HERALDIC QUALITY CONTROL PROGRAM Commercial Use of Heraldic Designs § 507.11 Reproduction of designs. (a) The photographing, printing, or, in any manner making or executing any engraving... 32 National Defense 3 2014-07-01 2014-07-01 false Reproduction of designs. 507.11 Section 507.11...

32 CFR 507.11 - Reproduction of designs.

Code of Federal Regulations, 2010 CFR

2010-07-01

... HERALDIC DESIGNS AND HERALDIC QUALITY CONTROL PROGRAM Commercial Use of Heraldic Designs § 507.11 Reproduction of designs. (a) The photographing, printing, or, in any manner making or executing any engraving... 32 National Defense 3 2010-07-01 2010-07-01 true Reproduction of designs. 507.11 Section 507.11...

32 CFR 507.11 - Reproduction of designs.

Code of Federal Regulations, 2011 CFR

2011-07-01

... HERALDIC DESIGNS AND HERALDIC QUALITY CONTROL PROGRAM Commercial Use of Heraldic Designs § 507.11 Reproduction of designs. (a) The photographing, printing, or, in any manner making or executing any engraving... 32 National Defense 3 2011-07-01 2009-07-01 true Reproduction of designs. 507.11 Section 507.11...

Exome sequence analysis suggests genetic burden contributes to phenotypic variability and complex neuropathy

PubMed Central

Gonzaga-Jauregui, Claudia; Harel, Tamar; Gambin, Tomasz; Kousi, Maria; Griffin, Laurie B.; Francescatto, Ludmila; Ozes, Burcak; Karaca, Ender; Jhangiani, Shalini; Bainbridge, Matthew N.; Lawson, Kim S.; Pehlivan, Davut; Okamoto, Yuji; Withers, Marjorie; Mancias, Pedro; Slavotinek, Anne; Reitnauer, Pamela J; Goksungur, Meryem T.; Shy, Michael; Crawford, Thomas O.; Koenig, Michel; Willer, Jason; Flores, Brittany N.; Pediaditrakis, Igor; Us, Onder; Wiszniewski, Wojciech; Parman, Yesim; Antonellis, Anthony; Muzny, Donna M.; Katsanis, Nicholas; Battaloglu, Esra; Boerwinkle, Eric; Gibbs, Richard A.; Lupski, James R.

2015-01-01

Charcot-Marie-Tooth (CMT) disease is a clinically and genetically heterogeneous distal symmetric polyneuropathy. Whole-exome sequencing (WES) of 40 individuals from 37 unrelated families with CMT-like peripheral neuropathy refractory to molecular diagnosis identified apparent causal mutations in ~45% (17/37) of families. Three candidate disease genes are proposed, supported by a combination of genetic and in vivo studies. Aggregate analysis of mutation data revealed a significantly increased number of rare variants across 58 neuropathy associated genes in subjects versus controls; confirmed in a second ethnically discrete neuropathy cohort, suggesting mutation burden potentially contributes to phenotypic variability. Neuropathy genes shown to have highly penetrant Mendelizing variants (HMPVs) and implicated by burden in families were shown to interact genetically in a zebrafish assay exacerbating the phenotype established by the suppression of single genes. Our findings suggest that the combinatorial effect of rare variants contributes to disease burden and variable expressivity. PMID:26257172

Key variables analysis of a novel continuous biodrying process for drying mixed sludge.

PubMed

Navaee-Ardeh, Shahram; Bertrand, François; Stuart, Paul R

2010-05-01

A novel continuous biodrying process has been developed whose goal is to increase the dry solids content of the sludge to economic levels rendering it suitable for a safe and economic combustion operation in a biomass boiler. The sludge drying rates are enhanced by the metabolic bioheat produced in the matrix of mixed sludge. The goal of this study was to systematically analyze the continuous biodrying reactor. By performing a variable analysis, it was found that the outlet relative humidity profile was the key variable in the biodrying reactor. The influence of different outlet relative humidity profiles was then evaluated using biodrying efficiency index. It was found that by maintaining the air outlet relative humidity profile at 85/85/96/96% in the four compartments of the reactor, the highest biodrying efficiency index can be achieved, while economic dry solids level (>45%w/w) are guaranteed. Crown Copyright 2009. Published by Elsevier Ltd. All rights reserved.

A variety of variables.

PubMed

Jupiter, Daniel C

2014-01-01

In designing studies and developing plans for analyses, we must consider which tests are appropriate for the types of variables we are using. Here I describe the types of variables available to us, and I briefly consider the appropriate tools to use in their analysis. Copyright © 2014 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Variable Selection in Logistic Regression.

DTIC Science & Technology

1987-06-01

23 %. AUTIOR(.) S. CONTRACT OR GRANT NUMBE Rf.i %Z. D. Bai, P. R. Krishnaiah and . C. Zhao F49620-85- C-0008 " PERFORMING ORGANIZATION NAME AND AOORESS...d I7 IOK-TK- d 7 -I0 7’ VARIABLE SELECTION IN LOGISTIC REGRESSION Z. D. Bai, P. R. Krishnaiah and L. C. Zhao Center for Multivariate Analysis...University of Pittsburgh Center for Multivariate Analysis University of Pittsburgh Y !I VARIABLE SELECTION IN LOGISTIC REGRESSION Z- 0. Bai, P. R. Krishnaiah

Methodological framework for heart rate variability analysis during exercise: application to running and cycling stress testing.

PubMed

Hernando, David; Hernando, Alberto; Casajús, Jose A; Laguna, Pablo; Garatachea, Nuria; Bailón, Raquel

2018-05-01

Standard methodologies of heart rate variability analysis and physiological interpretation as a marker of autonomic nervous system condition have been largely published at rest, but not so much during exercise. A methodological framework for heart rate variability (HRV) analysis during exercise is proposed, which deals with the non-stationary nature of HRV during exercise, includes respiratory information, and identifies and corrects spectral components related to cardiolocomotor coupling (CC). This is applied to 23 male subjects who underwent different tests: maximal and submaximal, running and cycling; where the ECG, respiratory frequency and oxygen consumption were simultaneously recorded. High-frequency (HF) power results largely modified from estimations with the standard fixed band to those obtained with the proposed methodology. For medium and high levels of exercise and recovery, HF power results in a 20 to 40% increase. When cycling, HF power increases around 40% with respect to running, while CC power is around 20% stronger in running.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering

PubMed Central

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor

2015-01-01

Abstract To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice. PMID:25560745

A geostatistical approach to the change-of-support problem and variable-support data fusion in spatial analysis

NASA Astrophysics Data System (ADS)

Wang, Jun; Wang, Yang; Zeng, Hui

2016-01-01

A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.

Planning performance in schizophrenia patients: a meta-analysis of the influence of task difficulty and clinical and sociodemographic variables.

PubMed

Knapp, F; Viechtbauer, W; Leonhart, R; Nitschke, K; Kaller, C P

2017-08-01

Despite a large body of research on planning performance in adult schizophrenia patients, results of individual studies are equivocal, suggesting either no, moderate or severe planning deficits. This meta-analysis therefore aimed to quantify planning deficits in schizophrenia and to examine potential sources of the heterogeneity seen in the literature. The meta-analysis comprised outcomes of planning accuracy of 1377 schizophrenia patients and 1477 healthy controls from 31 different studies which assessed planning performance using tower tasks such as the Tower of London, the Tower of Hanoi and the Stockings of Cambridge. A meta-regression analysis was applied to assess the influence of potential moderator variables (i.e. sociodemographic and clinical variables as well as task difficulty). The findings indeed demonstrated a planning deficit in schizophrenia patients (mean effect size: ; 95% confidence interval 0.56-0.78) that was moderated by task difficulty in terms of the minimum number of moves required for a solution. The results did not reveal any significant relationship between the extent of planning deficits and sociodemographic or clinical variables. The current results provide first meta-analytic evidence for the commonly assumed impairments of planning performance in schizophrenia. Deficits are more likely to become manifest in problem items with higher demands on planning ahead, which may at least partly explain the heterogeneity of previous findings. As only a small fraction of studies reported coherent information on sample characteristics, future meta-analyses would benefit from more systematic reports on those variables.

Analysis of Soccer Players’ Positional Variability During the 2012 UEFA European Championship: A Case Study

PubMed Central

Moura, Felipe Arruda; Santana, Juliana Exel; Vieira, Nathália Arnosti; Santiago, Paulo Roberto Pereira; Cunha, Sergio Augusto

2015-01-01

The purpose of this study was to analyse players’ positional variability during the 2012 UEFA European Championship by applying principal component analysis (PCA) to data gathered from heat maps posted on the UEFA website. We analysed the teams that reached the finals and semi-finals of the competition. The players’ 2D coordinates from each match were obtained by applying an image-processing algorithm to the heat maps. With all the players’ 2D coordinates for each match, we applied PCA to identify the directions of greatest variability. Then, two orthogonal segments were centred on each player’s mean position for all matches. The segments’ directions were driven by the eigenvectors of the PCA, and the length of each segment was defined as one standard deviation around the mean. Finally, an ellipse was circumscribed around both segments. To represent player variability, segment lengths and elliptical areas were analysed. The results demonstrate that Portugal exhibited the lowest variability, followed by Germany, Spain and Italy. Additionally, a graphical representation of every player’s ellipse provided insight into the teams’ organisational features throughout the competition. The presented study provides important information regarding soccer teams’ tactical strategy in high-level championships that allows coaches to better control team organisation on the pitch. PMID:26557206

An evaluation of FIA's stand age variable

Treesearch

John D. Shaw

2015-01-01

The Forest Inventory and Analysis Database (FIADB) includes a large number of measured and computed variables. The definitions of measured variables are usually well-documented in FIA field and database manuals. Some computed variables, such as live basal area of the condition, are equally straightforward. Other computed variables, such as individual tree volume,...

Mobility performance analysis of an innovation lunar rover with diameter-variable wheel

NASA Astrophysics Data System (ADS)

Sun, Gang; Gao, Feng; Sun, Peng; Xu, Guoyan

2007-11-01

To achieve excellent mobility performance, a four-wheel, all-wheel drive lunar rover with diameter-variable wheel was presented, the wheel can be contracted and extended by the motor equipped in the wheel hub, accompanied with wheel diameter varying from 200mm to 390mm. The wheel sinkage and drawbar pull force were predicated with terramechanics formulae and lunar regolith mechanic parameters employed, furthermore, the slope traversability was investigated through quasi-static modeling mechanic analysis, also the obstacle resistance and the maximum negotiable obstacle height for different wheel radius were derived from the equations of static equilibrium of the rover. Analysis results show that for the innovation lunar rover presented, it will bring much better slope traveling stability and obstacle climbing capability than rovers with normal wheels, these will improve the rover mobility performance and stabilize the rover's frame, smooth the motion of sensors.

Finite element analysis to investigate variability of MR elastography in the human thigh.

PubMed

Hollis, L; Barnhill, E; Perrins, M; Kennedy, P; Conlisk, N; Brown, C; Hoskins, P R; Pankaj, P; Roberts, N

2017-11-01

To develop finite element analysis (FEA) of magnetic resonance elastography (MRE) in the human thigh and investigate inter-individual variability of measurement of muscle mechanical properties. Segmentation was performed on MRI datasets of the human thigh from 5 individuals and FEA models consisting of 12 muscles and surrounding tissue created. The same material properties were applied to each tissue type and a previously developed transient FEA method of simulating MRE using Abaqus was performed at 4 frequencies. Synthetic noise was applied to the simulated data at various levels before inversion was performed using the Elastography Software Pipeline. Maps of material properties were created and visually assessed to determine key features. The coefficient of variation (CoV) was used to assess the variability of measurements in each individual muscle and in the groups of muscles across the subjects. Mean measurements for the set of muscles were ranked in size order and compared with the expected ranking. At noise levels of 2% the CoV in measurements of |G * | ranged from 5.3 to 21.9% and from 7.1 to 36.1% for measurements of ϕ in the individual muscles. A positive correlation (R 2 value 0.80) was attained when the expected and measured |G * | ranking were compared, whilst a negative correlation (R 2 value 0.43) was found for ϕ. Created elastograms demonstrated good definition of muscle structure and were robust to noise. Variability of measurements across the 5 subjects was dramatically lower for |G * | than it was for ϕ. This large variability in ϕ measurements was attributed to artefacts. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis and testing of high entrainment single nozzle jet pumps with variable mixing tubes

NASA Technical Reports Server (NTRS)

Hickman, K. E.; Hill, P. G.; Gilbert, G. B.

1972-01-01

An analytical model was developed to predict the performance characteristics of axisymmetric single-nozzle jet pumps with variable area mixing tubes. The primary flow may be subsonic or supersonic. The computer program uses integral techniques to calculate the velocity profiles and the wall static pressures that result from the mixing of the supersonic primary jet and the subsonic secondary flow. An experimental program was conducted to measure mixing tube wall static pressure variations, velocity profiles, and temperature profiles in a variable area mixing tube with a supersonic primary jet. Static pressure variations were measured at four different secondary flow rates. These test results were used to evaluate the analytical model. The analytical results compared well to the experimental data. Therefore, the analysis is believed to be ready for use to relate jet pump performance characteristics to mixing tube design.

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimations

ERIC Educational Resources Information Center

Can, Seda; van de Schoot, Rens; Hox, Joop

2015-01-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation…

Analysis of the Variable Pressure Growth Chamber using the CASE/A simulation package

NASA Technical Reports Server (NTRS)

Mcfadden, Carl D.; Edeen, Marybeth A.

1992-01-01

A computer simulation of the Variable Pressure Growth Chamber (VPGC), located at the NASA Johnson Space Center, has been developed using the Computer Aided Systems Engineering and Analysis (CASE/A) package. The model has been used to perform several analyses of the VPGC. The analyses consisted of a study of the effects of a human metabolic load on the VPGC and a study of two new configurations for the temperature and humidity control (THC) subsystem in the VPGC. The objective of the human load analysis was to study the effects of a human metabolic load on the air revitalization and THC subsystems. This included the effects on the quantity of carbon dioxide injected and oxygen removed from the chamber and the effects of the additional sensible and latent heat loads. The objective of the configuration analysis was to compare the two new THC configurations against the current THC configuration to determine which had the best performance.

Gaia DR2 documentation Chapter 7: Variability

NASA Astrophysics Data System (ADS)

Eyer, L.; Guy, L.; Distefano, E.; Clementini, G.; Mowlavi, N.; Rimoldini, L.; Roelens, M.; Audard, M.; Holl, B.; Lanzafame, A.; Lebzelter, T.; Lecoeur-Taïbi, I.; Molnár, L.; Ripepi, V.; Sarro, L.; Jevardat de Fombelle, G.; Nienartowicz, K.; De Ridder, J.; Juhász, Á.; Molinaro, R.; Plachy, E.; Regibo, S.

2018-04-01

This chapter of the Gaia DR2 documentation describes the models and methods used on the 22 months of data to produce the Gaia variable star results for Gaia DR2. The variability processing and analysis was based mostly on the calibrated G and integrated BP and RP photometry. The variability analysis approach to the Gaia data has been described in Eyer et al. (2017), and the Gaia DR2 results are presented in Holl et al. (2018). Detailed methods on specific topics will be published in a number of separate articles. Variability behaviour in the colour magnitude diagram is presented in Gaia Collaboration et al. (2018c).

Breastfeeding and the risk of childhood asthma: A two-stage instrumental variable analysis to address endogeneity.

PubMed

Sharma, Nivita D

2017-09-01

Several explanations for the inconsistent results on the effects of breastfeeding on childhood asthma have been suggested. The purpose of this study was to investigate one unexplored explanation, which is the presence of a potential endogenous relationship between breastfeeding and childhood asthma. Endogeneity exists when an explanatory variable is correlated with the error term for reasons such as selection bias, reverse causality, and unmeasured confounders. Unadjusted endogeneity will bias the effect of breastfeeding on childhood asthma. To investigate potential endogeneity, a cross-sectional study of breastfeeding practices and incidence of childhood asthma in 87 pediatric patients in Georgia, the USA, was conducted using generalized linear modeling and a two-stage instrumental variable analysis. First, the relationship between breastfeeding and childhood asthma was analyzed without considering endogeneity. Second, tests for presence of endogeneity were performed and having detected endogeneity between breastfeeding and childhood asthma, a two-stage instrumental variable analysis was performed. The first stage of this analysis estimated the duration of breastfeeding and the second-stage estimated the risk of childhood asthma. When endogeneity was not taken into account, duration of breastfeeding was found to significantly increase the risk of childhood asthma (relative risk ratio [RR]=2.020, 95% confidence interval [CI]: [1.143-3.570]). After adjusting for endogeneity, duration of breastfeeding significantly reduced the risk of childhood asthma (RR=0.003, 95% CI: [0.000-0.240]). The findings suggest that researchers should consider evaluating how the presence of endogeneity could affect the relationship between duration of breastfeeding and the risk of childhood asthma. © 2017 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.

Assessing compositional variability through graphical analysis and Bayesian statistical approaches: case studies on transgenic crops.

PubMed

Harrigan, George G; Harrison, Jay M

2012-01-01

New transgenic (GM) crops are subjected to extensive safety assessments that include compositional comparisons with conventional counterparts as a cornerstone of the process. The influence of germplasm, location, environment, and agronomic treatments on compositional variability is, however, often obscured in these pair-wise comparisons. Furthermore, classical statistical significance testing can often provide an incomplete and over-simplified summary of highly responsive variables such as crop composition. In order to more clearly describe the influence of the numerous sources of compositional variation we present an introduction to two alternative but complementary approaches to data analysis and interpretation. These include i) exploratory data analysis (EDA) with its emphasis on visualization and graphics-based approaches and ii) Bayesian statistical methodology that provides easily interpretable and meaningful evaluations of data in terms of probability distributions. The EDA case-studies include analyses of herbicide-tolerant GM soybean and insect-protected GM maize and soybean. Bayesian approaches are presented in an analysis of herbicide-tolerant GM soybean. Advantages of these approaches over classical frequentist significance testing include the more direct interpretation of results in terms of probabilities pertaining to quantities of interest and no confusion over the application of corrections for multiple comparisons. It is concluded that a standardized framework for these methodologies could provide specific advantages through enhanced clarity of presentation and interpretation in comparative assessments of crop composition.

Ideal, nonideal, and no-marker variables: The confirmatory factor analysis (CFA) marker technique works when it matters.

PubMed

Williams, Larry J; O'Boyle, Ernest H

2015-09-01

A persistent concern in the management and applied psychology literature is the effect of common method variance on observed relations among variables. Recent work (i.e., Richardson, Simmering, & Sturman, 2009) evaluated 3 analytical approaches to controlling for common method variance, including the confirmatory factor analysis (CFA) marker technique. Their findings indicated significant problems with this technique, especially with nonideal marker variables (those with theoretical relations with substantive variables). Based on their simulation results, Richardson et al. concluded that not correcting for method variance provides more accurate estimates than using the CFA marker technique. We reexamined the effects of using marker variables in a simulation study and found the degree of error in estimates of a substantive factor correlation was relatively small in most cases, and much smaller than error associated with making no correction. Further, in instances in which the error was large, the correlations between the marker and substantive scales were higher than that found in organizational research with marker variables. We conclude that in most practical settings, the CFA marker technique yields parameter estimates close to their true values, and the criticisms made by Richardson et al. are overstated. (c) 2015 APA, all rights reserved).

Phenology Analysis of Forest Vegetation to Environmental Variables during - and Post-Monsoon Seasons in Western Himalayan Region of India

NASA Astrophysics Data System (ADS)

Khare, S.; Latifi, H.; Ghosh, K.

2016-06-01

To assess the phenological changes in Moist Deciduous Forest (MDF) of western Himalayan region of India, we carried out NDVI time series analysis from 2013 to 2015 using Landsat 8 OLI data. We used the vegetation index differencing method to calculate the change in NDVI (NDVIchange) during pre and post monsoon seasons and these changes were used to assess the phenological behaviour of MDF by taking the effect of a set of environmental variables into account. To understand the effect of environmental variables on change in phenology, we designed a linear regression analysis with sample-based NDVIchange values as the response variable and elevation aspect, and Land Surface Temperature (LST) as explanatory variables. The Landsat-8 derived phenology transition stages were validated by calculating the phenology variation from Nov 2008 to April 2009 using Landsat-7 which has the same spatial resolution as Landsat-8. The Landsat-7 derived NDVI trajectories were plotted in accordance with MODIS derived phenology stages (from Nov 2008 to April 2009) of MDF. Results indicate that the Landsat -8 derived NDVI trajectories describing the phenology variation of MDF during spring, monsoon autumn and winter seasons agreed closely with Landsat-7 and MODIS derived phenology transition from Nov 2008 to April 2009. Furthermore, statistical analysis showed statistically significant correlations (p < 0.05) amongst the environmental variables and the NDVIchange between full greenness and maximum frequency stage of Onset of Greenness (OG) activity.. The major change in NDVI was observed in medium (600 to 650 m) and maximum (650 to 750 m) elevation areas. The change in LST showed also to be highly influential. The results of this study can be used for large scale monitoring of difficult-to-reach mountainous forests, with additional implications in biodiversity assessment. By means of a sufficient amount of available cloud-free imagery, detailed phenological trends across mountainous

Effects of the lateral amplitude and regularity of upper body fluctuation on step time variability evaluated using return map analysis.

PubMed

Chidori, Kazuhiro; Yamamoto, Yuji

2017-01-01

The aim of this study was to evaluate the effects of the lateral amplitude and regularity of upper body fluctuation on step time variability. Return map analysis was used to clarify the relationship between step time variability and a history of falling. Eleven healthy, community-dwelling older adults and twelve younger adults participated in the study. All of the subjects walked 25 m at a comfortable speed. Trunk acceleration was measured using triaxial accelerometers attached to the third lumbar vertebrae (L3) and the seventh cervical vertebrae (C7). The normalized average magnitude of acceleration, the coefficient of determination ($R^2$) of the return map, and the step time variabilities, were calculated. Cluster analysis using the average fluctuation and the regularity of C7 fluctuation identified four walking patterns in the mediolateral (ML) direction. The participants with higher fluctuation and lower regularity showed significantly greater step time variability compared with the others. Additionally, elderly participants who had fallen in the past year had higher amplitude and a lower regularity of fluctuation during walking. In conclusion, by focusing on the time evolution of each step, it is possible to understand the cause of stride and/or step time variability that is associated with a risk of falls.

Effects of the lateral amplitude and regularity of upper body fluctuation on step time variability evaluated using return map analysis

PubMed Central

2017-01-01

The aim of this study was to evaluate the effects of the lateral amplitude and regularity of upper body fluctuation on step time variability. Return map analysis was used to clarify the relationship between step time variability and a history of falling. Eleven healthy, community-dwelling older adults and twelve younger adults participated in the study. All of the subjects walked 25 m at a comfortable speed. Trunk acceleration was measured using triaxial accelerometers attached to the third lumbar vertebrae (L3) and the seventh cervical vertebrae (C7). The normalized average magnitude of acceleration, the coefficient of determination ($R^2$) of the return map, and the step time variabilities, were calculated. Cluster analysis using the average fluctuation and the regularity of C7 fluctuation identified four walking patterns in the mediolateral (ML) direction. The participants with higher fluctuation and lower regularity showed significantly greater step time variability compared with the others. Additionally, elderly participants who had fallen in the past year had higher amplitude and a lower regularity of fluctuation during walking. In conclusion, by focusing on the time evolution of each step, it is possible to understand the cause of stride and/or step time variability that is associated with a risk of falls. PMID:28700633

Analysis of the influence of rainfall variables on urban effluents concentrations and fluxes in wet weather

NASA Astrophysics Data System (ADS)

Gooré Bi, Eustache; Monette, Frédéric; Gasperi, Johnny

2015-04-01

Urban rainfall runoff has been a topic of increasing importance over the past years, a result of both the increase in impervious land area arising from constant urban growth and the effects of climate change on urban drainage. The main goal of the present study is to assess and analyze the correlations between rainfall variables and common indicators of urban water quality, namely event mean concentrations (EMCs) and event fluxes (EFs), in order to identify and explain the impacts of each of the main rainfall variables on the generation process of urban pollutants during wet periods. To perform this analysis, runoff from eight summer rainfall events that resulted in combined sewer overflow (CSO) was sampled simultaneously from two distinct catchment areas in order to quantify discharges at the respective outfalls. Pearson statistical analysis of total suspended solids (TSS), chemical oxygen demand (COD), carbonaceous biochemical oxygen demand at 5 days (CBOD5), total phosphorus (Ptot) and total kedjal nitrogen (N-TKN) showed significant correlations (ρ = 0.05) between dry antecedent time (DAT) and EMCs on one hand, and between total rainfall (TR) and the volume discharged (VD) during EFs, on the other. These results show that individual rainfall variables strongly affect either EMCs or EFs and are good predictors to consider when selecting variables for statistical modeling of urban runoff quality. The results also show that in a combined sewer network, there is a linear relationship between TSS event fluxes and COD, CBOD5, Ptot, and N-TKN event fluxes; this explains 97% of the variability of these pollutants which adsorb onto TSS during wet weather, which therefore act as tracers. Consequently, the technological solution selected for TSS removal will also lead to a reduction of these pollutants. Given the huge volumes involved, urban runoffs contribute substantially to pollutant levels in receiving water bodies, a situation which, in a climate change context, may

A new analysis of heart rate variability in the assessment of fetal parasympathetic activity: An experimental study in a fetal sheep model.

PubMed

Garabedian, C; Champion, C; Servan-Schreiber, E; Butruille, L; Aubry, E; Sharma, D; Logier, R; Deruelle, P; Storme, L; Houfflin-Debarge, V; De Jonckheere, J

2017-01-01

Analysis of heart rate variability (HRV) is a recognized tool in the assessment of autonomic nervous system (ANS) activity. Indeed, both time and spectral analysis techniques enable us to obtain indexes that are related to the way the ANS regulates the heart rate. However, these techniques are limited in terms of the lack of thresholds of the numerical indexes, which is primarily due to high inter-subject variability. We proposed a new fetal HRV analysis method related to the parasympathetic activity of the ANS. The aim of this study was to evaluate the performance of our method compared to commonly used HRV analysis, with regard to i) the ability to detect changes in ANS activity and ii) inter-subject variability. This study was performed in seven sheep fetuses. In order to evaluate the sensitivity and specificity of our index in evaluating parasympathetic activity, we directly administered 2.5 mg intravenous atropine, to inhibit parasympathetic tone, and 5 mg propranolol to block sympathetic activity. Our index, as well as time analysis (root mean square of the successive differences; RMSSD) and spectral analysis (high frequency (HF) and low frequency (LF) spectral components obtained via fast Fourier transform), were measured before and after injection. Inter-subject variability was estimated by the coefficient of variance (%CV). In order to evaluate the ability of HRV parameters to detect fetal parasympathetic decrease, we also estimated the effect size for each HRV parameter before and after injections. As expected, our index, the HF spectral component, and the RMSSD were reduced after the atropine injection. Moreover, our index presented a higher effect size. The %CV was far lower for our index than for RMSSD, HF, and LF. Although LF decreased after propranolol administration, fetal stress index, RMSSD, and HF were not significantly different, confirming the fact that those indexes are specific to the parasympathetic nervous system. In conclusion, our method

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis

PubMed Central

Botai, Joel O.; Rautenbach, Hannes; Ncongwane, Katlego P.; Botai, Christina M.

2017-01-01

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease’s transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998–2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables’ and malaria cases’ time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature (R2 = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72

"USA Today": Comparative Analysis with Two National and Two Los Angeles Daily Newspapers. Research Bulletin.

ERIC Educational Resources Information Center

Ames, Steve; And Others

Sections of the newspaper "USA Today" were compared with corresponding sections of four major newspapers--the "New York Times," the "Wall Street Journal," the "Los Angeles Herald Examiner," and the "Los Angeles Times"--to determine what editorial components made "USA Today" different and…

Regression Analysis of Optical Coherence Tomography Disc Variables for Glaucoma Diagnosis.

PubMed

Richter, Grace M; Zhang, Xinbo; Tan, Ou; Francis, Brian A; Chopra, Vikas; Greenfield, David S; Varma, Rohit; Schuman, Joel S; Huang, David

2016-08-01

To report diagnostic accuracy of optical coherence tomography (OCT) disc variables using both time-domain (TD) and Fourier-domain (FD) OCT, and to improve the use of OCT disc variable measurements for glaucoma diagnosis through regression analyses that adjust for optic disc size and axial length-based magnification error. Observational, cross-sectional. In total, 180 normal eyes of 112 participants and 180 eyes of 138 participants with perimetric glaucoma from the Advanced Imaging for Glaucoma Study. Diagnostic variables evaluated from TD-OCT and FD-OCT were: disc area, rim area, rim volume, optic nerve head volume, vertical cup-to-disc ratio (CDR), and horizontal CDR. These were compared with overall retinal nerve fiber layer thickness and ganglion cell complex. Regression analyses were performed that corrected for optic disc size and axial length. Area-under-receiver-operating curves (AUROC) were used to assess diagnostic accuracy before and after the adjustments. An index based on multiple logistic regression that combined optic disc variables with axial length was also explored with the aim of improving diagnostic accuracy of disc variables. Comparison of diagnostic accuracy of disc variables, as measured by AUROC. The unadjusted disc variables with the highest diagnostic accuracies were: rim volume for TD-OCT (AUROC=0.864) and vertical CDR (AUROC=0.874) for FD-OCT. Magnification correction significantly worsened diagnostic accuracy for rim variables, and while optic disc size adjustments partially restored diagnostic accuracy, the adjusted AUROCs were still lower. Axial length adjustments to disc variables in the form of multiple logistic regression indices led to a slight but insignificant improvement in diagnostic accuracy. Our various regression approaches were not able to significantly improve disc-based OCT glaucoma diagnosis. However, disc rim area and vertical CDR had very high diagnostic accuracy, and these disc variables can serve to complement

Spectral analysis of heart rate variability predicts mortality and instability from vascular injury.

PubMed

Koko, Kiavash R; McCauley, Brian D; Gaughan, John P; Fromer, Marc W; Nolan, Ryan S; Hagaman, Ashleigh L; Brown, Spencer A; Hazelton, Joshua P

2018-04-01

Spectral analysis of continuous blood pressure and heart rate variability provides a quantitative assessment of autonomic response to hemorrhage. This may reveal markers of mortality as well as endpoints of resuscitation. Fourteen male Yorkshire pigs, ranging in weight from 33 to 36 kg, were included in the analysis. All pigs underwent laparotomy and then sustained a standardized retrohepatic inferior vena cava injury. Animals were then allowed to progress to class 3 hemorrhagic shock and where then treated with abdominal sponge packing followed by 6 h of crystalloid resuscitation. If the pigs survived the 6 h resuscitation, they were in the survival (S) group, otherwise they were placed in the nonsurvival (NS) group. Fast Fourier transformation calculations were used to convert the components of blood pressure and heart rate variability into corresponding frequency classifications. Autonomic tones are represented as the following: high frequency (HF) = parasympathetic tone, low frequency (LF) = sympathetic, and very low frequency (VLF) = renin-angiotensin aldosterone system. The relative sympathetic to parasympathetic tone was expressed as LF/HF ratio. Baseline hemodynamic parameters were equal for the S (n = 11) and NS groups. LF/HF was lower at baseline for the NS group but was higher after hemorrhage and the resuscitation period indicative of a predominately parasympathetic response during hemorrhagic shock before mortality. HF signal was lower in the NS group during the resuscitation indicating a relatively lower sympathetic tone during hemorrhagic shock, which may have contributed to mortality. Finally, the NS group had a lower VLF signal at baseline (e.g., [S] 16.3 ± 2.5 versus [NS] 4.6 ± 2.9 P < 0.05,) which was predictive of mortality and hemodynamic instability in response to a similar hemorrhagic injury. An increased LF/HF ratio, indicative of parasympathetic predominance following injury and during resuscitation of hemorrhagic shock

Continuous-variable quantum homomorphic signature

NASA Astrophysics Data System (ADS)

Li, Ke; Shang, Tao; Liu, Jian-wei

2017-10-01

Quantum cryptography is believed to be unconditionally secure because its security is ensured by physical laws rather than computational complexity. According to spectrum characteristic, quantum information can be classified into two categories, namely discrete variables and continuous variables. Continuous-variable quantum protocols have gained much attention for their ability to transmit more information with lower cost. To verify the identities of different data sources in a quantum network, we propose a continuous-variable quantum homomorphic signature scheme. It is based on continuous-variable entanglement swapping and provides additive and subtractive homomorphism. Security analysis shows the proposed scheme is secure against replay, forgery and repudiation. Even under nonideal conditions, it supports effective verification within a certain verification threshold.

Cluster analysis and subgrouping to investigate inter-individual variability to non-invasive brain stimulation: a systematic review.

PubMed

Pellegrini, Michael; Zoghi, Maryam; Jaberzadeh, Shapour

2018-01-12

Cluster analysis and other subgrouping techniques have risen in popularity in recent years in non-invasive brain stimulation research in the attempt to investigate the issue of inter-individual variability - the issue of why some individuals respond, as traditionally expected, to non-invasive brain stimulation protocols and others do not. Cluster analysis and subgrouping techniques have been used to categorise individuals, based on their response patterns, as responder or non-responders. There is, however, a lack of consensus and consistency on the most appropriate technique to use. This systematic review aimed to provide a systematic summary of the cluster analysis and subgrouping techniques used to date and suggest recommendations moving forward. Twenty studies were included that utilised subgrouping techniques, while seven of these additionally utilised cluster analysis techniques. The results of this systematic review appear to indicate that statistical cluster analysis techniques are effective in identifying subgroups of individuals based on response patterns to non-invasive brain stimulation. This systematic review also reports a lack of consensus amongst researchers on the most effective subgrouping technique and the criteria used to determine whether an individual is categorised as a responder or a non-responder. This systematic review provides a step-by-step guide to carrying out statistical cluster analyses and subgrouping techniques to provide a framework for analysis when developing further insights into the contributing factors of inter-individual variability in response to non-invasive brain stimulation.

Spectral analysis of time series of categorical variables in earth sciences

NASA Astrophysics Data System (ADS)

Pardo-Igúzquiza, Eulogio; Rodríguez-Tovar, Francisco J.; Dorador, Javier

2016-10-01

Time series of categorical variables often appear in Earth Science disciplines and there is considerable interest in studying their cyclic behavior. This is true, for example, when the type of facies, petrofabric features, ichnofabrics, fossil assemblages or mineral compositions are measured continuously over a core or throughout a stratigraphic succession. Here we deal with the problem of applying spectral analysis to such sequences. A full indicator approach is proposed to complement the spectral envelope often used in other disciplines. Additionally, a stand-alone computer program is provided for calculating the spectral envelope, in this case implementing the permutation test to assess the statistical significance of the spectral peaks. We studied simulated sequences as well as real data in order to illustrate the methodology.

Understanding north-western Mediterranean climate variability: a multi-proxy and multi-sequence approach based on wavelet analysis.

NASA Astrophysics Data System (ADS)

Azuara, Julien; Lebreton, Vincent; Jalali, Bassem; Sicre, Marie-Alexandrine; Sabatier, Pierre; Dezileau, Laurent; Peyron, Odile; Frigola, Jaime; Combourieu-Nebout, Nathalie

2017-04-01

Forcings and physical mechanisms underlying Holocene climate variability still remain poorly understood. Comparison of different paleoclimatic reconstructions using spectral analysis allows to investigate their common periodicities and helps to understand the causes of past climate changes. Wavelet analysis applied on several proxy time series from the Atlantic domain already revealed the first key-issues on the origin of Holocene climate variability. However the differences in duration, resolution and variance between the time-series are important issues for comparing paleoclimatic sequences in the frequency domain. This work compiles 7 paleoclimatic proxy records from 4 time-series from the north-western Mediterranean all ranging from 7000 to 1000 yrs cal BP: -pollen and clay mineral contents from the lagoonal sediment core PB06 recovered in southern France, -Sea Surface Temperatures (SST) derived from alkenones, concentration of terrestrial alkanes and their average chain length (ACL) from core KSGC-31_GolHo-1B recovered in the Gulf of Lion inner-shelf, - δ18O record from speleothems recovered in the Asiul Cave in north-western Spain, -grain size record from the deep basin sediment drift core MD99-2343 north of Minorca island. A comparison of their frequency content is proposed using wavelet analysis and cluster analysis of wavelet power spectra. Common cyclicities are assessed using cross-wavelet analysis. In addition, a new algorithm is used in order to propagate the age model errors within wavelet power spectra. Results are consistents with a non-stationnary Holocene climate variability. The Halstatt cycles (2000-2500 years) depicted in many proxies (ACL, errestrial alkanes and SSTs) demonstrate solar activity influence in the north-western Mediterranean climate. Cluster analysis shows that pollen and ACL proxies, both indicating changes in aridity, are clearly distinct from other proxies and share significant common periodicities around 1000 and 600 years

Sleep Quality Estimation based on Chaos Analysis for Heart Rate Variability

NASA Astrophysics Data System (ADS)

Fukuda, Toshio; Wakuda, Yuki; Hasegawa, Yasuhisa; Arai, Fumihito; Kawaguchi, Mitsuo; Noda, Akiko

In this paper, we propose an algorithm to estimate sleep quality based on a heart rate variability using chaos analysis. Polysomnography(PSG) is a conventional and reliable system to diagnose sleep disorder and to evaluate its severity and therapeatic effect, by estimating sleep quality based on multiple channels. However, a recording process requires a lot of time and a controlled environment for measurement and then an analyzing process of PSG data is hard work because the huge sensed data should be manually evaluated. On the other hand, it is focused that some people make a mistake or cause an accident due to lost of regular sleep and of homeostasis these days. Therefore a simple home system for checking own sleep is required and then the estimation algorithm for the system should be developed. Therefore we propose an algorithm to estimate sleep quality based only on a heart rate variability which can be measured by a simple sensor such as a pressure sensor and an infrared sensor in an uncontrolled environment, by experimentally finding the relationship between chaos indices and sleep quality. The system including the estimation algorithm can inform patterns and quality of own daily sleep to a user, and then the user can previously arranges his life schedule, pays more attention based on sleep results and consult with a doctor.

Effects of Variable Resistance Training on Maximal Strength: A Meta-Analysis.

PubMed

Soria-Gila, Miguel A; Chirosa, Ignacio J; Bautista, Iker J; Baena, Salvador; Chirosa, Luis J

2015-11-01

Variable resistance training (VRT) methods improve the rate of force development, coordination between antagonist and synergist muscles, the recruitment of motor units, and reduce the drop in force produced in the sticking region. However, the beneficial effects of long-term VRT on maximal strength both in athletes and untrained individuals have been much disputed. The purpose of this study was to compare in a meta-analysis the effects of a long-term (≥7 weeks) VRT program using chains or elastic bands and a similar constant resistance program in both trained adults practicing different sports and untrained individuals. Intervention effect sizes were compared among investigations meeting our selection and inclusion criteria using a random-effects model. The published studies considered were those addressing VRT effects on the 1 repetition maximum. Seven studies involving 235 subjects fulfilled the selection and inclusion criteria. Variable resistance training led to a significantly greater mean strength gain (weighted mean difference: 5.03 kg; 95% confidence interval: 2.26-7.80 kg; Z = 3.55; p < 0.001) than the gain recorded in response to conventional weight training. Long-term VRT training using chains or elastic bands attached to the barbell emerged as an effective evidence-based method of improving maximal strength both in athletes with different sports backgrounds and untrained subjects.

Genetic analysis of glucosinolate variability in broccoli florets using genome-anchored single nucleotide polymorphisms.

PubMed

Brown, Allan F; Yousef, Gad G; Reid, Robert W; Chebrolu, Kranthi K; Thomas, Aswathy; Krueger, Christopher; Jeffery, Elizabeth; Jackson, Eric; Juvik, John A

2015-07-01

The identification of genetic factors influencing the accumulation of individual glucosinolates in broccoli florets provides novel insight into the regulation of glucosinolate levels in Brassica vegetables and will accelerate the development of vegetables with glucosinolate profiles tailored to promote human health. Quantitative trait loci analysis of glucosinolate (GSL) variability was conducted with a B. oleracea (broccoli) mapping population, saturated with single nucleotide polymorphism markers from a high-density array designed for rapeseed (Brassica napus). In 4 years of analysis, 14 QTLs were associated with the accumulation of aliphatic, indolic, or aromatic GSLs in floret tissue. The accumulation of 3-carbon aliphatic GSLs (2-propenyl and 3-methylsulfinylpropyl) was primarily associated with a single QTL on C05, but common regulation of 4-carbon aliphatic GSLs was not observed. A single locus on C09, associated with up to 40 % of the phenotypic variability of 2-hydroxy-3-butenyl GSL over multiple years, was not associated with the variability of precursor compounds. Similarly, QTLs on C02, C04, and C09 were associated with 4-methylsulfinylbutyl GSL concentration over multiple years but were not significantly associated with downstream compounds. Genome-specific SNP markers were used to identify candidate genes that co-localized to marker intervals and previously sequenced Brassica oleracea BAC clones containing known GSL genes (GSL-ALK, GSL-PRO, and GSL-ELONG) were aligned to the genomic sequence, providing support that at least three of our 14 QTLs likely correspond to previously identified GSL loci. The results demonstrate that previously identified loci do not fully explain GSL variation in broccoli. The identification of additional genetic factors influencing the accumulation of GSL in broccoli florets provides novel insight into the regulation of GSL levels in Brassicaceae and will accelerate development of vegetables with modified or enhanced GSL

Suspension system vibration analysis with regard to variable type ability to smooth road irregularities

NASA Astrophysics Data System (ADS)

Rykov, S. P.; Rykova, O. A.; Koval, V. S.; Makhno, D. E.; Fedotov, K. V.

2018-03-01

The paper aims to analyze vibrations of the dynamic system equivalent of the suspension system with regard to tyre ability to smooth road irregularities. The research is based on static dynamics for linear systems of automated control, methods of correlation, spectral and numerical analysis. Input of new data on the smoothing effect of the pneumatic tyre reflecting changes of a contact area between the wheel and road under vibrations of the suspension makes the system non-linear which requires using numerical analysis methods. Taking into account the variable smoothing ability of the tyre when calculating suspension vibrations, one can approximate calculation and experimental results and improve the constant smoothing ability of the tyre.

An analysis of the relationship of seven selected variables to State Board Test Pool Examination performance of the University of Tennessee, Knoxville, College of Nursing.

PubMed

Sharp, T G

1984-02-01

The study was designed to determine whether any one of seven selected variables or a combination of the variables is predictive of performance on the State Board Test Pool Examination. The selected variables studied were: high school grade point average (HSGPA), The University of Tennessee, Knoxville, College of Nursing grade point average (GPA), and American College Test Assessment (ACT) standard scores (English, ENG; mathematics, MA; social studies, SS; natural sciences, NSC; composite, COMP). Data utilized were from graduates of the baccalaureate program of The University of Tennessee, Knoxville, College of Nursing from 1974 through 1979. The sample of 322 was selected from a total population of 572. The Statistical Analysis System (SAS) was designed to accomplish analysis of the predictive relationship of each of the seven selected variables to State Board Test Pool Examination performance (result of pass or fail), a stepwise discriminant analysis was designed for determining the predictive relationship of the strongest combination of the independent variables to overall State Board Test Pool Examination performance (result of pass or fail), and stepwise multiple regression analysis was designed to determine the strongest predictive combination of selected variables for each of the five subexams of the State Board Test Pool Examination. The selected variables were each found to be predictive of SBTPE performance (result of pass or fail). The strongest combination for predicting SBTPE performance (result of pass or fail) was found to be GPA, MA, and NSC.

Functional Analysis of Problem Behavior: A Systematic Approach for Identifying Idiosyncratic Variables

PubMed Central

Roscoe, Eileen M.; Schlichenmeyer, Kevin J.; Dube, William V.

2015-01-01

When inconclusive functional analysis (FA) outcomes occur, a number of modifications have been made to enhance the putative establishing operation or consequence associated with behavioral maintenance. However, a systematic method for identifying relevant events to test during modified FAs has not been evaluated. The purpose of this study was to develop and evaluate a technology for systematically identifying events to test in a modified FA after an initial FA led to inconclusive outcomes. Six individuals whose initial FA showed little or no responding or high levels only in the control condition participated. An indirect assessment (IA) questionnaire developed for identifying idiosyncratic variables was administered, and a descriptive analysis (DA) was conducted. Results from the IA only or a combination of the IA and DA were used to inform modified FA test and control conditions. Conclusive FA outcomes were obtained with five of the six participants during the modified FA phase. PMID:25930176

Time dependent analysis of assay comparability: a novel approach to understand intra- and inter-site variability over time

NASA Astrophysics Data System (ADS)

Winiwarter, Susanne; Middleton, Brian; Jones, Barry; Courtney, Paul; Lindmark, Bo; Page, Ken M.; Clark, Alan; Landqvist, Claire

2015-09-01

We demonstrate here a novel use of statistical tools to study intra- and inter-site assay variability of five early drug metabolism and pharmacokinetics in vitro assays over time. Firstly, a tool for process control is presented. It shows the overall assay variability but allows also the following of changes due to assay adjustments and can additionally highlight other, potentially unexpected variations. Secondly, we define the minimum discriminatory difference/ratio to support projects to understand how experimental values measured at different sites at a given time can be compared. Such discriminatory values are calculated for 3 month periods and followed over time for each assay. Again assay modifications, especially assay harmonization efforts, can be noted. Both the process control tool and the variability estimates are based on the results of control compounds tested every time an assay is run. Variability estimates for a limited set of project compounds were computed as well and found to be comparable. This analysis reinforces the need to consider assay variability in decision making, compound ranking and in silico modeling.

The Deglacial to Holocene Paleoceanography of Bering Strait: Results From the SWERUS-C3 Program

NASA Astrophysics Data System (ADS)

Jakobsson, M.; Anderson, L. G.; Backman, J.; Barrientos, N.; Björk, G. M.; Coxall, H.; Cronin, T. M.; De Boer, A. M.; Gemery, L.; Jerram, K.; Johansson, C.; Kirchner, N.; Mayer, L. A.; Mörth, C. M.; Nilsson, J.; Noormets, R. R. N. N.; O'Regan, M.; Pearce, C.; Semiletov, I. P.; Stranne, C.

2017-12-01

The climate-carbon-cryosphere (C3) interactions in the East Siberian Arctic Ocean and related ocean, river and land areas of the Arctic have been the focus for the SWERUS-C3 Program (Swedish - Russian - US Arctic Ocean Investigation of Climate-Cryosphere-Carbon Interactions). This multi-investigator, multi-disciplinary program was carried out on a two-leg 90-day long expedition in 2014 with Swedish icebreaker Oden. One component of the expedition consisted of geophysical mapping and coring of Herald Canyon, located on the Chukchi Sea shelf north of the Bering Strait in the western Arctic Ocean. Herald Canyon is strategically placed to capture the history of the Pacific-Arctic Ocean connection and related changes in Arctic Ocean paleoceanography. Here we present a summary of key results from analyses of the marine geophysical mapping data and cores collected from Herald Canyon on the shelf and slope that proved to be particularly well suited for paleoceanographic reconstruction. For example, we provide a new age constraint of 11 cal ka BP on sediments from the uppermost slope for the initial flooding of the Bering Land Bridge and reestablishment of the Pacific-Arctic Ocean connection following the last glaciation. This age corresponds to meltwater pulse 1b (MWP1b) known as a post-Younger Dryas warming in many sea level and paleoclimate records. In addition, high late Holocene sedimentation rates that range between about 100 and 300 cm kyr-1, in Herald Canyon permitted paleoceanographic reconstructions of ocean circulation and sea ice cover at centennial scales throughout the late Holocene. Evidence suggests varying influence from inflowing Pacific water into the western Arctic Ocean including some evidence for quasi-cyclic variability in several paleoceanographic parameters, e.g. micropaleontological assemblages, isotope geochemistry and sediment physical properties.

Variability of the western Galician upwelling system (NW Spain) during an intensively sampled annual cycle. An EOF analysis approach

NASA Astrophysics Data System (ADS)

Herrera, J. L.; Rosón, G.; Varela, R. A.; Piedracoba, S.

2008-07-01

The key features of the western Galician shelf hydrography and dynamics are analyzed on a solid statistical and experimental basis. The results allowed us to gather together information dispersed in previous oceanographic works of the region. Empirical orthogonal functions analysis and a canonical correlation analysis were applied to a high-resolution dataset collected from 47 surveys done on a weekly frequency from May 2001 to May 2002. The main results of these analyses are summarized bellow. Salinity, temperature and the meridional component of the residual current are correlated with the relevant local forcings (the meridional coastal wind component and the continental run-off) and with a remote forcing (the meridional temperature gradient at latitude 37°N). About 80% of the salinity and temperature total variability over the shelf, and 37% of the residual meridional current total variability are explained by two EOFs for each variable. Up to 22% of the temperature total variability and 14% of the residual meridional current total variability is devoted to the set up of cross-shore gradients of the thermohaline properties caused by the wind-induced Ekman transport. Up to 11% and 10%, respectively, is related to the variability of the meridional temperature gradient at the Western Iberian Winter Front. About 30% of the temperature total variability can be explained by the development and erosion of the seasonal thermocline and by the seasonal variability of the thermohaline properties of the central waters. This thermocline presented unexpected low salinity values due to the trapping during spring and summer of the high continental inputs from the River Miño recorded in 2001. The low salinity plumes can be traced on the Galician shelf during almost all the annual cycle; they tend to be extended throughout the entire water column under downwelling conditions and concentrate in the surface layer when upwelling favourable winds blow. Our evidences point to the

Variables in psychology: a critique of quantitative psychology.

PubMed

Toomela, Aaro

2008-09-01

Mind is hidden from direct observation; it can be studied only by observing behavior. Variables encode information about behaviors. There is no one-to-one correspondence between behaviors and mental events underlying the behaviors, however. In order to understand mind it would be necessary to understand exactly what information is represented in variables. This aim cannot be reached after variables are already encoded. Therefore, statistical data analysis can be very misleading in studies aimed at understanding mind that underlies behavior. In this article different kinds of information that can be represented in variables are described. It is shown how informational ambiguity of variables leads to problems of theoretically meaningful interpretation of the results of statistical data analysis procedures in terms of hidden mental processes. Reasons are provided why presence of dependence between variables does not imply causal relationship between events represented by variables and absence of dependence between variables cannot rule out the causal dependence of events represented by variables. It is concluded that variable-psychology has a very limited range of application for the development of a theory of mind-psychology.

Analysis of the Relationship Between Climate and NDVI Variability at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fan-Wei; Collatz, G. James; Pinzon, Jorge; Ivanoff, Alvaro

2011-01-01

interannual variability in modeled (CASA) C flux is in part caused by interannual variability in Normalized Difference Vegetation Index (NDVI) Fraction of Photosynthetically Active Radiation (FPAR). This study confirms a mechanism producing variability in modeled NPP: -- NDVI (FPAR) interannual variability is strongly driven by climate; -- The climate driven variability in NDVI (FPAR) can lead to much larger fluctuation in NPP vs. the NPP computed from FPAR climatology

Multivariate analysis of water quality and environmental variables in the Great Barrier Reef catchments

NASA Astrophysics Data System (ADS)

Ryu, D.; Liu, S.; Western, A. W.; Webb, J. A.; Lintern, A.; Leahy, P.; Wilson, P.; Watson, M.; Waters, D.; Bende-Michl, U.

2016-12-01

The Great Barrier Reef (GBR) lagoon has been experiencing significant water quality deterioration due in part to agricultural intensification and urban settlement in adjacent catchments. The degradation of water quality in rivers is caused by land-derived pollutants (i.e. sediment, nutrient and pesticide). A better understanding of dynamics of water quality is essential for land management to improve the GBR ecosystem. However, water quality is also greatly influenced by natural hydrological processes. To assess influencing factors and predict the water quality accurately, selection of the most important predictors of water quality is necessary. In this work, multivariate statistical techniques - cluster analysis (CA), principal component analysis (PCA) and factor analysis (FA) - are used to reduce the complexity derived from the multidimensional water quality monitoring data. Seventeen stations are selected across the GBR catchments, and the event-based measurements of 12 variables monitored during 9 years (2006 - 2014) were analysed by means of CA and PCA/FA. The key findings are: (1) 17 stations can be grouped into two clusters according to the hierarchical CA, and the spatial dissimilarity between these sites is characterised by the different climatic and land use in the GBR catchments. (2) PCA results indicate that the first 3 PCs explain 85% of the total variance, and FA on the entire data set shows that the varifactor (VF) loadings can be used to interpret the sources of spatial variation in water quality on the GBR catchments level. The impact of soil erosion and non-point source of pollutants from agriculture contribution to VF1 and the variability in hydrological conditions and biogeochemical processes can explain the loadings in VF2. (3) FA is also performed on two groups of sites identified in CA individually, to evaluate the underlying sources that are responsible for spatial variability in water quality in the two groups. For the Cluster 1 sites

A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

PubMed

Clark, Renee M; Besterfield-Sacre, Mary E

2009-03-01

We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

Latent structure analysis of the process variables and pharmaceutical responses of an orally disintegrating tablet.

PubMed

Hayashi, Yoshihiro; Oshima, Etsuko; Maeda, Jin; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2012-01-01

A multivariate statistical technique was applied to the design of an orally disintegrating tablet and to clarify the causal correlation among variables of the manufacturing process and pharmaceutical responses. Orally disintegrating tablets (ODTs) composed mainly of mannitol were prepared via the wet-granulation method using crystal transition from the δ to the β form of mannitol. Process parameters (water amounts (X(1)), kneading time (X(2)), compression force (X(3)), and amounts of magnesium stearate (X(4))) were optimized using a nonlinear response surface method (RSM) incorporating a thin plate spline interpolation (RSM-S). The results of a verification study revealed that the experimental responses, such as tensile strength and disintegration time, coincided well with the predictions. A latent structure analysis of the pharmaceutical formulations of the tablet performed using a Bayesian network led to the clear visualization of a causal connection among variables of the manufacturing process and tablet characteristics. The quantity of β-mannitol in the granules (Q(β)) was affected by X(2) and influenced all granule properties. The specific surface area of the granules was affected by X(1) and Q(β) and had an effect on all tablet characteristics. Moreover, the causal relationships among the variables were clarified by inferring conditional probability distributions. These techniques provide a better understanding of the complicated latent structure among variables of the manufacturing process and tablet characteristics.

Comparative glacio-climatological analysis of mass balance variability along the geographical margin of Europe

NASA Astrophysics Data System (ADS)

Lehoczky, Annamária; Kern, Zoltán; Pongrácz, Rita

2014-05-01

Glacio-climatological studies recognise glacier mass balance changes as high-confident climate indicators. The climatic sensitivity of a glacier does not simply depend on regional climate variability but also influenced via large- and mesoscale atmospheric circulation patterns. This study focuses on recent changes in the mass balance using records from three border regions of Europe, and investigates the relationships between the seasonal mass balance components, regional climatic conditions, and distant atmospheric forcing. Since glaciers in different macro-climatological conditions (i.e., mid-latitudes or high-latitudes, dry-continental or maritime regions) may present strongly diverse mass balance characteristics, the three analysed regions were selected from different glacierised macroregions (using the database of the World Glacier Monitoring Service). These regions belong to the Caucasus Mountains (Central Europe macroregion), the Polar Ural (Northern Asia macroregion), and Svalbard (Arctic Islands macroregion). The analysis focuses on winter, summer, and annual mass balance series of eight glaciers. The climatic variables (atmospheric pressure, air temperature, precipitation) and indices of teleconnection patterns (e.g., North Atlantic Oscillation, Pacific Decadal Oscillation) are used from the gridded databases of the University of East Anglia, Climatic Research Unit and the National Oceanic and Atmospheric Administration, National Center for Environmental Prediction. However, the period and length of available mass balance data in the selected regions vary greatly (the first full record is in 1958, Polar Ural; the last is in 2010, Caucasus Mountains), a comparative analysis can be carried out for the period of 1968-1981. Since glaciers from different regions respond to large- and mesoscale climatic forcings differently, and because the mass balance of glaciers within a region often co-vary, our specific objectives are (i) to examine the variability and the

Analysis of long term heart rate variability: methods, 1/f scaling and implications

NASA Technical Reports Server (NTRS)

Saul, J. P.; Albrecht, P.; Berger, R. D.; Cohen, R. J.

1988-01-01

The use of spectral techniques to quantify short term heart rate fluctuations on the order of seconds to minutes has helped define the autonomic contributions to beat-to-beat control of heart rate. We used similar techniques to quantify the entire spectrum (0.00003-1.0 Hz) of heart rate variability during 24 hour ambulatory ECG monitoring. The ECG from standard Holter monitor recordings from normal subjects was sampled with the use of a phase locked loop, and a heart rate time series was constructed at 3 Hz. Frequency analysis of the heart rate signal was performed after a nonlinear filtering algorithm was used to eliminate artifacts. A power spectrum of the entire 24 hour record revealed power that was inversely proportional to frequency, 1/f, over 4 decades from 0.00003 to 0.1 Hz (period approximately 10 hours to 10 seconds). Displaying consecutive spectra calculated at 5 minute intervals revealed marked variability in the peaks at all frequencies throughout the 24 hours, probably accounting for the lack of distinct peaks in the spectra of the entire records.

Can Geostatistical Models Represent Nature's Variability? An Analysis Using Flume Experiments

NASA Astrophysics Data System (ADS)

Scheidt, C.; Fernandes, A. M.; Paola, C.; Caers, J.

2015-12-01

The lack of understanding in the Earth's geological and physical processes governing sediment deposition render subsurface modeling subject to large uncertainty. Geostatistics is often used to model uncertainty because of its capability to stochastically generate spatially varying realizations of the subsurface. These methods can generate a range of realizations of a given pattern - but how representative are these of the full natural variability? And how can we identify the minimum set of images that represent this natural variability? Here we use this minimum set to define the geostatistical prior model: a set of training images that represent the range of patterns generated by autogenic variability in the sedimentary environment under study. The proper definition of the prior model is essential in capturing the variability of the depositional patterns. This work starts with a set of overhead images from an experimental basin that showed ongoing autogenic variability. We use the images to analyze the essential characteristics of this suite of patterns. In particular, our goal is to define a prior model (a minimal set of selected training images) such that geostatistical algorithms, when applied to this set, can reproduce the full measured variability. A necessary prerequisite is to define a measure of variability. In this study, we measure variability using a dissimilarity distance between the images. The distance indicates whether two snapshots contain similar depositional patterns. To reproduce the variability in the images, we apply an MPS algorithm to the set of selected snapshots of the sedimentary basin that serve as training images. The training images are chosen from among the initial set by using the distance measure to ensure that only dissimilar images are chosen. Preliminary investigations show that MPS can reproduce fairly accurately the natural variability of the experimental depositional system. Furthermore, the selected training images provide

Global Association of Air Pollution and Cardiorespiratory Diseases: A Systematic Review, Meta-Analysis, and Investigation of Modifier Variables

PubMed Central

Adams, Matthew D.; Arain, Altaf; Papatheodorou, Stefania; Koutrakis, Petros; Mahmoud, Moataz

2018-01-01

Background. Little is known about the health risks of air pollution and cardiorespiratory diseases, globally, across regions and populations, which may differ because of external factors. Objectives. We systematically reviewed the evidence on the association between air pollution and cardiorespiratory diseases (hospital admissions and mortality), including variability by energy, transportation, socioeconomic status, and air quality. Search Methods. We conducted a literature search (PubMed and Web of Science) for studies published between 2006 and May 11, 2016. Selection Criteria. We included studies if they met all of the following criteria: (1) considered at least 1 of these air pollutants: carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, or particulate matter (PM2.5 or PM10); (2) reported risk for hospital admissions, mortality, or both; (3) presented individual results for respiratory diseases, cardiovascular diseases, or both; (4) considered the age groups younger than 5 years, older than 65 years, or all ages; and (5) did not segregate the analysis by gender. Data Collection and Analysis. We extracted data from each study, including location, health outcome, and risk estimates. We performed a meta-analysis to estimate the overall effect and to account for both within- and between-study heterogeneity. Then, we applied a model selection (least absolute shrinkage and selection operator) to assess the modifier variables, and, lastly, we performed meta-regression analyses to evaluate the modifier variables contributing to heterogeneity among studies. Main Results. We assessed 2183 studies, of which we selected 529 for in-depth review, and 70 articles fulfilled our study inclusion criteria. The 70 studies selected for meta-analysis encompass more than 30 million events across 28 countries. We found positive associations between cardiorespiratory diseases and different air pollutants. For example, when we considered only the association between PM2.5 and

Interacting supernovae and supernova impostors. LSQ13zm: an outburst heralds the death of a massive star

DOE PAGES

Tartaglia, L.; Pastorello, A.; Sullivan, M.; ...

2016-03-23

Here we report photometric and spectroscopic observations of the optical transient LSQ13zm. Historical data reveal the presence of an eruptive episode (that we label as ‘2013a’) followed by a much brighter outburst (‘2013b’) three weeks later, that we argue to be the genuine supernova explosion. This sequence of events closely resemble those observed for SN 2010mc and (in 2012) SN 2009ip. Furthermore, the absolute magnitude reached by LSQ13zm during 2013a (MR = -14.87 ± 0.25 mag) is comparable with those of supernova impostors, while that of the 2013b event (M R = -18.46 ± 0.21 mag) is consistent with thosemore » of interacting supernovae. Our spectra reveal the presence of a dense and structured circumstellar medium, probably produced through numerous pre-supernova mass-loss events. In addition, we find evidence for high-velocity ejecta, with a fraction of gas expelled at more than 20 000 km s -1. The spectra of LSQ13zm show remarkable similarity with those of well-studied core-collapse supernovae. From the analysis of the available photometric and spectroscopic data, we conclude that we first observed the last event of an eruptive sequence from a massive star, likely a Luminous Blue Variable, which a short time later exploded as a core-collapse supernova. Our detailed analysis of archival images suggests that the host galaxy is a star-forming Blue Dwarf Compact Galaxy.« less

Interacting supernovae and supernova impostors. LSQ13zm: an outburst heralds the death of a massive star

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

Tartaglia, L.; Pastorello, A.; Sullivan, M.

Here we report photometric and spectroscopic observations of the optical transient LSQ13zm. Historical data reveal the presence of an eruptive episode (that we label as ‘2013a’) followed by a much brighter outburst (‘2013b’) three weeks later, that we argue to be the genuine supernova explosion. This sequence of events closely resemble those observed for SN 2010mc and (in 2012) SN 2009ip. Furthermore, the absolute magnitude reached by LSQ13zm during 2013a (MR = -14.87 ± 0.25 mag) is comparable with those of supernova impostors, while that of the 2013b event (M R = -18.46 ± 0.21 mag) is consistent with thosemore » of interacting supernovae. Our spectra reveal the presence of a dense and structured circumstellar medium, probably produced through numerous pre-supernova mass-loss events. In addition, we find evidence for high-velocity ejecta, with a fraction of gas expelled at more than 20 000 km s -1. The spectra of LSQ13zm show remarkable similarity with those of well-studied core-collapse supernovae. From the analysis of the available photometric and spectroscopic data, we conclude that we first observed the last event of an eruptive sequence from a massive star, likely a Luminous Blue Variable, which a short time later exploded as a core-collapse supernova. Our detailed analysis of archival images suggests that the host galaxy is a star-forming Blue Dwarf Compact Galaxy.« less

Clustering "N" Objects into "K" Groups under Optimal Scaling of Variables.

ERIC Educational Resources Information Center

van Buuren, Stef; Heiser, Willem J.

1989-01-01

A method based on homogeneity analysis (multiple correspondence analysis or multiple scaling) is proposed to reduce many categorical variables to one variable with "k" categories. The method is a generalization of the sum of squared distances cluster analysis problem to the case of mixed measurement level variables. (SLD)

Temporal analysis of the frequency and duration of low and high streamflow: Years of record needed to characterize streamflow variability

USGS Publications Warehouse

Huh, S.; Dickey, D.A.; Meador, M.R.; Ruhl, K.E.

2005-01-01

A temporal analysis of the number and duration of exceedences of high- and low-flow thresholds was conducted to determine the number of years required to detect a level shift using data from Virginia, North Carolina, and South Carolina. Two methods were used - ordinary least squares assuming a known error variance and generalized least squares without a known error variance. Using ordinary least squares, the mean number of years required to detect a one standard deviation level shift in measures of low-flow variability was 57.2 (28.6 on either side of the break), compared to 40.0 years for measures of high-flow variability. These means become 57.6 and 41.6 when generalized least squares is used. No significant relations between years and elevation or drainage area were detected (P>0.05). Cluster analysis did not suggest geographic patterns in years related to physiography or major hydrologic regions. Referring to the number of observations required to detect a one standard deviation shift as 'characterizing' the variability, it appears that at least 20 years of record on either side of a shift may be necessary to adequately characterize high-flow variability. A longer streamflow record (about 30 years on either side) may be required to characterize low-flow variability. ?? 2005 Elsevier B.V. All rights reserved.

A New Variable Weighting and Selection Procedure for K-Means Cluster Analysis

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

A variance-to-range ratio variable weighting procedure is proposed. We show how this weighting method is theoretically grounded in the inherent variability found in data exhibiting cluster structure. In addition, a variable selection procedure is proposed to operate in conjunction with the variable weighting technique. The performances of these…

Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

NASA Astrophysics Data System (ADS)

Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

2014-10-01

The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure

Clostridium botulinum group I strain genotyping by 15-locus multilocus variable-number tandem-repeat analysis.

PubMed

Fillo, Silvia; Giordani, Francesco; Anniballi, Fabrizio; Gorgé, Olivier; Ramisse, Vincent; Vergnaud, Gilles; Riehm, Julia M; Scholz, Holger C; Splettstoesser, Wolf D; Kieboom, Jasper; Olsen, Jaran-Strand; Fenicia, Lucia; Lista, Florigio

2011-12-01

Clostridium botulinum is a taxonomic designation that encompasses a broad variety of spore-forming, Gram-positive bacteria producing the botulinum neurotoxin (BoNT). C. botulinum is the etiologic agent of botulism, a rare but severe neuroparalytic disease. Fine-resolution genetic characterization of C. botulinum isolates of any BoNT type is relevant for both epidemiological studies and forensic microbiology. A 10-locus multiple-locus variable-number tandem-repeat analysis (MLVA) was previously applied to isolates of C. botulinum type A. The present study includes five additional loci designed to better address proteolytic B and F serotypes. We investigated 79 C. botulinum group I strains isolated from human and food samples in several European countries, including types A (28), B (36), AB (4), and F (11) strains, and 5 nontoxic Clostridium sporogenes. Additional data were deduced from in silico analysis of 10 available fully sequenced genomes. This 15-locus MLVA (MLVA-15) scheme identified 86 distinct genotypes that clustered consistently with the results of amplified fragment length polymorphism (AFLP) and MLVA genotyping in previous reports. An MLVA-7 scheme, a subset of the MLVA-15, performed on a lab-on-a-chip device using a nonfluorescent subset of primers, is also proposed as a first-line assay. The phylogenetic grouping obtained with the MLVA-7 does not differ significantly from that generated by the MLVA-15. To our knowledge, this report is the first to analyze genetic variability among all of the C. botulinum group I serotypes by MLVA. Our data provide new insights into the genetic variability of group I C. botulinum isolates worldwide and demonstrate that this group is genetically highly diverse.

Analysis of contextual variables in the evaluation of child abuse in the pediatric emergency setting.

PubMed

Almeida, Ana Nunes de; Ramos, Vasco; Almeida, Helena Nunes de; Escobar, Carlos Gil; Garcia, Catarina

This article comprises a sample of abuse modalities observed in a pediatric emergency room of a public hospital in the Lisbon metropolitan area and a multifactorial characterization of physical and sexual violence. The objectives are: (1) to discuss the importance of social and family variables in the configuration of both types of violence; (2) to show how physical and sexual violence have subtypes and internal diversity. A statistical analysis was carried out in a database (1063 records of child abuse between 2004 and 2013). A form was applied to cases with suspected abuse, containing data on the child, family, abuse episode, abuser, medical history, and clinical observation. A factorial analysis of multiple correspondence was performed to identify patterns of association between social variables and physical and sexual violence, as well as their internal diversity. The prevalence of abuse in this pediatric emergency room was 0.6%. Physical violence predominated (69.4%), followed by sexual violence (39.3%). Exploratory profiles of these types of violence were constructed. Regarding physical violence, the gender of the abuser was the first differentiating dimension; the victim's gender and age range were the second one. In the case of sexual violence, the age of the abuser and co-residence with him/her comprised the first dimension; the victim's age and gender comprised the second dimension. Patterns of association between victims, family contexts, and abusers were identified. It is necessary to alert clinicians about the importance of social variables in the multiple facets of child abuse. Copyright © 2017 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Use of a prototype pulse oximeter for time series analysis of heart rate variability

NASA Astrophysics Data System (ADS)

González, Erika; López, Jehú; Hautefeuille, Mathieu; Velázquez, Víctor; Del Moral, Jésica

2015-05-01

This work presents the development of a low cost pulse oximeter prototype consisting of pulsed red and infrared commercial LEDs and a broad spectral photodetector used to register time series of heart rate and oxygen saturation of blood. This platform, besides providing these values, like any other pulse oximeter, processes the signals to compute a power spectrum analysis of the patient heart rate variability in real time and, additionally, the device allows access to all raw and analyzed data if databases construction is required or another kind of further analysis is desired. Since the prototype is capable of acquiring data for long periods of time, it is suitable for collecting data in real life activities, enabling the development of future wearable applications.

ARTiiFACT: a tool for heart rate artifact processing and heart rate variability analysis.

PubMed

Kaufmann, Tobias; Sütterlin, Stefan; Schulz, Stefan M; Vögele, Claus

2011-12-01

The importance of appropriate handling of artifacts in interbeat interval (IBI) data must not be underestimated. Even a single artifact may cause unreliable heart rate variability (HRV) results. Thus, a robust artifact detection algorithm and the option for manual intervention by the researcher form key components for confident HRV analysis. Here, we present ARTiiFACT, a software tool for processing electrocardiogram and IBI data. Both automated and manual artifact detection and correction are available in a graphical user interface. In addition, ARTiiFACT includes time- and frequency-based HRV analyses and descriptive statistics, thus offering the basic tools for HRV analysis. Notably, all program steps can be executed separately and allow for data export, thus offering high flexibility and interoperability with a whole range of applications.

A novel variable selection approach that iteratively optimizes variable space using weighted binary matrix sampling.

PubMed

Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao

2014-10-07

In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.

Newborn infant pain assessment using heart rate variability analysis.

PubMed

Faye, Papa M; De Jonckheere, Julien; Logier, Regis; Kuissi, Eliane; Jeanne, Mathieu; Rakza, Thameur; Storme, Laurent

2010-01-01

Systems controlling cardiovascular function are closely coupled with the perception of pain. Heart rate variability (HRV) is a well-established noninvasive measure of cardiac autonomic control. We hypothesized that pain may alter HRV in the newborn infant and that HRV analysis could be used as an indicator of prolonged pain in the newborn infant. To test the hypothesis, we measured the magnitude of the heart rate high-frequency variations using an innovative High Frequency Variability Index (HFVI) in newborn infants at risk of postoperative pain. We investigated newborn infants with a gestational age (GA) more than 34 weeks, and who were admitted after a major surgical procedure. Inclusions ranged from 2 to 72 hours after the surgery. The postoperative pain was scored using EDIN scale (neonatal pain and discomfort scale) at the end of the 2 hours recording period. The infants were separated in: (1) Group "Low EDIN," when EDIN<5; and (2) Group "High EDIN," when EDIN >=5. Predictive positive and negative values of a threshold value of HFVI in assessing pain have been studied. Twenty-eight newborn infants were enrolled in the study (mean GA=37.8+/-1.5 wk) at a median delay between the surgery and the recording of 5 hours. Mean EDIN were 2+/-1 and 7+/-2 in respectively the groups "Low EDIN" and "High EDIN." The 2 groups were similar for GA, basal heart and respiratory rates, SpO2, mean arterial blood pressure, and morphine infusion rate. HFVI was significantly lower in the group "High EDIN" than in the group "Low EDIN" (0.7+/-0.2 vs. 1.2+/-0.3, respectively; P<0.01). An HFVI <0.9 was able to predict an EDIN score >=5, with a sensitivity of 90%, and a specificity of 75%. The results of this study indicate that postoperative pain is associated with a decreased high-frequency HRV in full-term newborn infants. Our findings suggest that HRV could be used as an indicator to assess prolonged pain in the newborn infants.

An analysis of input errors in precipitation-runoff models using regression with errors in the independent variables

USGS Publications Warehouse

Troutman, Brent M.

1982-01-01

Errors in runoff prediction caused by input data errors are analyzed by treating precipitation-runoff models as regression (conditional expectation) models. Independent variables of the regression consist of precipitation and other input measurements; the dependent variable is runoff. In models using erroneous input data, prediction errors are inflated and estimates of expected storm runoff for given observed input variables are biased. This bias in expected runoff estimation results in biased parameter estimates if these parameter estimates are obtained by a least squares fit of predicted to observed runoff values. The problems of error inflation and bias are examined in detail for a simple linear regression of runoff on rainfall and for a nonlinear U.S. Geological Survey precipitation-runoff model. Some implications for flood frequency analysis are considered. A case study using a set of data from Turtle Creek near Dallas, Texas illustrates the problems of model input errors.

Clustering of Variables for Mixed Data

NASA Astrophysics Data System (ADS)

Saracco, J.; Chavent, M.

2016-05-01

This chapter presents clustering of variables which aim is to lump together strongly related variables. The proposed approach works on a mixed data set, i.e. on a data set which contains numerical variables and categorical variables. Two algorithms of clustering of variables are described: a hierarchical clustering and a k-means type clustering. A brief description of PCAmix method (that is a principal component analysis for mixed data) is provided, since the calculus of the synthetic variables summarizing the obtained clusters of variables is based on this multivariate method. Finally, the R packages ClustOfVar and PCAmixdata are illustrated on real mixed data. The PCAmix and ClustOfVar approaches are first used for dimension reduction (step 1) before applying in step 2 a standard clustering method to obtain groups of individuals.

[Inter-and intra-operator variability in the analysis of semen parameters: results from a quality control program].

PubMed

Daoud, Salima; Chakroun-Feki, Nozha; Sellami, Afifa; Ammar-Keskes, Leila; Rebai, Tarek

2016-01-01

Semen analysis is a key part of male infertility investigation. The necessity of quality management implementation in the andrology laboratory has been recognized in order to ensure the reliability of its results. The aim of this study was to evaluate intra- and inter-individual variability in the assessment of semen parameters in our laboratory through a quality control programme. Four participants from the laboratory with different experience levels have participated in this study. Semen samples of varying quality were assessed for sperm motility, concentration and morphology and the results were used to evaluate inter-participant variability. In addition, replicates of each semen sample were analyzed to determine intra-individual variability for semen parameters analysis. The average values of inter-participant coefficients of variation for sperm motility, concentration and morphology were 12.8%, 19.8% and 48.9% respectively. The mean intra-participant coefficients of variation were, respectively, 6.9%, 12.3% and 42.7% for sperm motility, concentration and morphology. Despite some random errors of under- or overestimation, the overall results remained within the limits of acceptability for all participants. Sperm morphology assessment was particularly influenced by the participant's level of experience. The present data emphasize the need for appropriate training of the laboratory staff and for regular participation in internal quality control programmes in order to improve the reliability of laboratory results.

Deciphering Sources of Variability in Clinical Pathology.

PubMed

Tripathi, Niraj K; Everds, Nancy E; Schultze, A Eric; Irizarry, Armando R; Hall, Robert L; Provencher, Anne; Aulbach, Adam

2017-01-01

The objectives of this session were to explore causes of variability in clinical pathology data due to preanalytical and analytical variables as well as study design and other procedures that occur in toxicity testing studies. The presenters highlighted challenges associated with such variability in differentiating test article-related effects from the effects of experimental procedures and its impact on overall data interpretation. These presentations focused on preanalytical and analytical variables and study design-related factors and their influence on clinical pathology data, and the importance of various factors that influence data interpretation including statistical analysis and reference intervals. Overall, these presentations touched upon potential effect of many variables on clinical pathology parameters, including animal physiology, sample collection process, specimen handling and analysis, study design, and some discussion points on how to manage those variables to ensure accurate interpretation of clinical pathology data in toxicity studies. This article is a brief synopsis of presentations given in a session entitled "Deciphering Sources of Variability in Clinical Pathology-It's Not Just about the Numbers" that occurred at the 35th Annual Symposium of the Society of Toxicologic Pathology in San Diego, California.

Variable spectra of active galaxies

NASA Technical Reports Server (NTRS)

Halpern, Jules P.

1988-01-01

The analysis of EXOSAT spectra of active galaxies are presented. The objects examined for X-ray spectral variability were MR 2251-178 and 3C 120. The results of these investigations are described, as well as additional results on X-ray spectral variability related to EXOSAT observations of active galaxies. Additionally, the dipping X-ray source 4U1624-49 was also investigated.

Variable Importance in Multivariate Group Comparisons.

ERIC Educational Resources Information Center

Huberty, Carl J.; Wisenbaker, Joseph M.

1992-01-01

Interpretations of relative variable importance in multivariate analysis of variance are discussed, with attention to (1) latent construct definition; (2) linear discriminant function scores; and (3) grouping variable effects. Two numerical ranking methods are proposed and compared by the bootstrap approach using two real data sets. (SLD)

Spacesuit Glove-Induced Hand Trauma and Analysis of Potentially Related Risk Variables

NASA Technical Reports Server (NTRS)

Charvat, Chacqueline M.; Norcross, Jason; Reid, Christopher R.; McFarland, Shane M.

2015-01-01

Injuries to the hands are common among astronauts who train for extravehicular activity (EVA). When the gloves are pressurized, they restrict movement and create pressure points during tasks, sometimes resulting in pain, muscle fatigue, abrasions, and occasionally more severe injuries such as onycholysis. Glove injuries, both anecdotal and recorded, have been reported during EVA training and flight persistently through NASA's history regardless of mission or glove model. Theories as to causation such as glove-hand fit are common but often lacking in supporting evidence. Previous statistical analysis has evaluated onycholysis in the context of crew anthropometry only. The purpose of this study was to analyze all injuries (as documented in the medical records) and available risk factor variables with the goal to determine engineering and operational controls that may reduce hand injuries due to the EVA glove in the future. A literature review and data mining study were conducted between 2012 and 2014. This study included 179 US NASA crew who trained or completed an EVA between 1981 and 2010 (crossing both Shuttle and ISS eras) and wore either the 4000 Series or Phase VI glove during Extravehicular Mobility Unit (EMU) spacesuit EVA training and flight. All injuries recorded in medical records were analyzed in their association to candidate risk factor variables. Those risk factor variables included demographic characteristics, hand anthropometry, glove fit characteristics, and training/EVA characteristics. Utilizing literature, medical records and anecdotal causation comments recorded in crewmember injury data, investigators were able to identify several risk factors associated with increased risk of glove related injuries. Prime among them were smaller hand anthropometry, duration of individual suited exposures, and improper glove-hand fit as calculated by the difference in the anthropometry middle finger length compared to the baseline EVA glove middle finger length.

Spacesuit Glove-Induced Hand Trauma and Analysis of Potentially Related Risk Variables

NASA Technical Reports Server (NTRS)

McFarland, Shane M.; Reid, Christopher R.; Norcross, Jason; Charvat, Jacqueline M.

2015-01-01

Injuries to the hands are common among astronauts who train for extravehicular activity (EVA). When the gloves are pressurized, they restrict movement and create pressure points during tasks, sometimes resulting in pain, muscle fatigue, abrasions, and occasionally more severe injuries such as onycholysis. Glove injuries, both anecdotal and recorded, have been reported during EVA training and flight persistently through NASA's history regardless of mission or glove model. Theories as to causation such as glove-hand fit are common but often lacking in supporting evidence. Previous statistical analysis has evaluated onycholysis in the context of crew anthropometry only (Opperman et al 2010). The purpose of this study was to analyze all injuries (as documented in the medical records) and available risk factor variables with the goal to determine engineering and operational controls that may reduce hand injuries due to the EVA glove in the future. A literature review and data mining study were conducted between 2012 and 2014. This study included 179 US NASA crew who trained or completed an EVA between 1981 and 2010 (crossing both Shuttle and ISS eras) and wore either the 4000 Series or Phase VI glove during Extravehicular Mobility Unit (EMU) spacesuit EVA training and flight. All injuries recorded in medical records were analyzed in their association to candidate risk factor variables. Those risk factor variables included demographic characteristics, hand anthropometry, glove fit characteristics, and training/EVA characteristics. Utilizing literature, medical records and anecdotal causation comments recorded in crewmember injury data, investigators were able to identify several risk factors associated with increased risk of glove related injuries. Prime among them were smaller hand anthropometry, duration of individual suited exposures, and improper glove-hand fit as calculated by the difference in the anthropometry middle finger length compared to the baseline EVA

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data. Part II: Using Maximum Covariance Analysis to Effectively Compare Spatiotemporal Variability of Satellite and AERONET Measured Aerosol Optical Depth

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.

Processable English: The Theory Behind the PENG System

DTIC Science & Technology

2009-06-01

implicit - is often buried amongst masses of irrelevant data. Heralding from unstructured sources such as natural language documents, email, audio ...estimation and prediction, data-mining, social network analysis, and semantic search and visualisation . This report describes the theoretical

MULTIPLE-LOCUS VARIABLE-NUMBER TANDEM REPEAT ANALYSIS OF BRUCELLA ISOLATES FROM THAILAND.

PubMed

Kumkrong, Khurawan; Chankate, Phanita; Tonyoung, Wittawat; Intarapuk, Apiradee; Kerdsin, Anusak; Kalambaheti, Thareerat

2017-01-01

Brucellosis-induced abortion can result in significant economic loss to farm animals. Brucellosis can be transmitted to humans during slaughter of infected animals or via consumption of contaminated food products. Strain identification of Brucella isolates can reveal the route of transmission. Brucella strains were isolated from vaginal swabs of farm animal, cow milk and from human blood cultures. Multiplex PCR was used to identify Brucella species, and owing to high DNA homology among Brucella isolates, multiple-locus variable-number tandem repeat analysis (MLVA) based on the number of tandem repeats at 16 different genomic loci was used for strain identification. Multiplex PCR categorized the isolates into B. abortus (n = 7), B. melitensis (n = 37), B. suis (n = 3), and 5 of unknown Brucella spp. MLVA-16 clustering analysis differentiated the strains into various genotypes, with Brucella isolates from the same geographic region being closely related, and revealed that the Thai isolates were phylogenetically distinct from those in other countries, including within the Southeast Asian region. Thus, MLVA-16 typing has utility in epidemiological studies.

Stochastic Analysis of the Efficiency of a Wireless Power Transfer System Subject to Antenna Variability and Position Uncertainties

PubMed Central

Rossi, Marco; Stockman, Gert-Jan; Rogier, Hendrik; Vande Ginste, Dries

2016-01-01

The efficiency of a wireless power transfer (WPT) system in the radiative near-field is inevitably affected by the variability in the design parameters of the deployed antennas and by uncertainties in their mutual position. Therefore, we propose a stochastic analysis that combines the generalized polynomial chaos (gPC) theory with an efficient model for the interaction between devices in the radiative near-field. This framework enables us to investigate the impact of random effects on the power transfer efficiency (PTE) of a WPT system. More specifically, the WPT system under study consists of a transmitting horn antenna and a receiving textile antenna operating in the Industrial, Scientific and Medical (ISM) band at 2.45 GHz. First, we model the impact of the textile antenna’s variability on the WPT system. Next, we include the position uncertainties of the antennas in the analysis in order to quantify the overall variations in the PTE. The analysis is carried out by means of polynomial-chaos-based macromodels, whereas a Monte Carlo simulation validates the complete technique. It is shown that the proposed approach is very accurate, more flexible and more efficient than a straightforward Monte Carlo analysis, with demonstrated speedup factors up to 2500. PMID:27447632

Stochastic Analysis of the Efficiency of a Wireless Power Transfer System Subject to Antenna Variability and Position Uncertainties.

PubMed

Rossi, Marco; Stockman, Gert-Jan; Rogier, Hendrik; Vande Ginste, Dries

2016-07-19

The efficiency of a wireless power transfer (WPT) system in the radiative near-field is inevitably affected by the variability in the design parameters of the deployed antennas and by uncertainties in their mutual position. Therefore, we propose a stochastic analysis that combines the generalized polynomial chaos (gPC) theory with an efficient model for the interaction between devices in the radiative near-field. This framework enables us to investigate the impact of random effects on the power transfer efficiency (PTE) of a WPT system. More specifically, the WPT system under study consists of a transmitting horn antenna and a receiving textile antenna operating in the Industrial, Scientific and Medical (ISM) band at 2.45 GHz. First, we model the impact of the textile antenna's variability on the WPT system. Next, we include the position uncertainties of the antennas in the analysis in order to quantify the overall variations in the PTE. The analysis is carried out by means of polynomial-chaos-based macromodels, whereas a Monte Carlo simulation validates the complete technique. It is shown that the proposed approach is very accurate, more flexible and more efficient than a straightforward Monte Carlo analysis, with demonstrated speedup factors up to 2500.

Statistical Assessment of Variability of Terminal Restriction Fragment Length Polymorphism Analysis Applied to Complex Microbial Communities ▿ †

PubMed Central

Rossi, Pierre; Gillet, François; Rohrbach, Emmanuelle; Diaby, Nouhou; Holliger, Christof

2009-01-01

The variability of terminal restriction fragment polymorphism analysis applied to complex microbial communities was assessed statistically. Recent technological improvements were implemented in the successive steps of the procedure, resulting in a standardized procedure which provided a high level of reproducibility. PMID:19749066

Detailed analysis of the microbial population in Malaysian spontaneous cocoa pulp fermentations reveals a core and variable microbiota.

PubMed

Meersman, Esther; Steensels, Jan; Mathawan, Melissa; Wittocx, Pieter-Jan; Saels, Veerle; Struyf, Nore; Bernaert, Herwig; Vrancken, Gino; Verstrepen, Kevin J

2013-01-01

The fermentation of cocoa pulp is one of the few remaining large-scale spontaneous microbial processes in today's food industry. The microbiota involved in cocoa pulp fermentations is complex and variable, which leads to inconsistent production efficiency and cocoa quality. Despite intensive research in the field, a detailed and comprehensive analysis of the microbiota is still lacking, especially for the expanding Asian production region. Here, we report a large-scale, comprehensive analysis of four spontaneous Malaysian cocoa pulp fermentations across two time points in the harvest season and two fermentation methods. Our results show that the cocoa microbiota consists of a "core" and a "variable" part. The bacterial populations show a remarkable consistency, with only two dominant species, Lactobacillus fermentum and Acetobacter pasteurianus. The fungal diversity is much larger, with four dominant species occurring in all fermentations ("core" yeasts), and a large number of yeasts that only occur in lower numbers and specific fermentations ("variable" yeasts). Despite this diversity, a clear pattern emerges, with early dominance of apiculate yeasts and late dominance of Saccharomyces cerevisiae. Our results provide new insights into the microbial diversity in Malaysian cocoa pulp fermentations and pave the way for the selection of starter cultures to increase efficiency and consistency.

Job demands and job strain as risk factors for employee wellbeing in elderly care: an instrumental-variables analysis.

PubMed

Elovainio, Marko; Heponiemi, Tarja; Kuusio, Hannamaria; Jokela, Markus; Aalto, Anna-Mari; Pekkarinen, Laura; Noro, Anja; Finne-Soveri, Harriet; Kivimäki, Mika; Sinervo, Timo

2015-02-01

The association between psychosocial work environment and employee wellbeing has repeatedly been shown. However, as environmental evaluations have typically been self-reported, the observed associations may be attributable to reporting bias. Applying instrumental-variable regression, we used staffing level (the ratio of staff to residents) as an unconfounded instrument for self-reported job demands and job strain to predict various indicators of wellbeing (perceived stress, psychological distress and sleeping problems) among 1525 registered nurses, practical nurses and nursing assistants working in elderly care wards. In ordinary regression, higher self-reported job demands and job strain were associated with increased risk of perceived stress, psychological distress and sleeping problems. The effect estimates for the associations of these psychosocial factors with perceived stress and psychological distress were greater, but less precisely estimated, in an instrumental-variables analysis which took into account only the variation in self-reported job demands and job strain that was explained by staffing level. No association between psychosocial factors and sleeping problems was observed with the instrumental-variable analysis. These results support a causal interpretation of high self-reported job demands and job strain being risk factors for employee wellbeing. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Validation of Heart Rate Monitor Polar RS800 for Heart Rate Variability Analysis During Exercise.

PubMed

Hernando, David; Garatachea, Nuria; Almeida, Rute; Casajús, Jose A; Bailón, Raquel

2018-03-01

Hernando, D, Garatachea, N, Almeida, R, Casajús, JA, and Bailón, R. Validation of heart rate monitor Polar RS800 for heart rate variability analysis during exercise. J Strength Cond Res 32(3): 716-725, 2018-Heart rate variability (HRV) analysis during exercise is an interesting noninvasive tool to measure the cardiovascular response to the stress of exercise. Wearable heart rate monitors are a comfortable option to measure interbeat (RR) intervals while doing physical activities. It is necessary to evaluate the agreement between HRV parameters derived from the RR series recorded by wearable devices and those derived from an electrocardiogram (ECG) during dynamic exercise of low to high intensity. Twenty-three male volunteers performed an exercise stress test on a cycle ergometer. Subjects wore a Polar RS800 device, whereas ECG was also recorded simultaneously to extract the reference RR intervals. A time-frequency spectral analysis was performed to extract the instantaneous mean heart rate (HRM), and the power of low-frequency (PLF) and high-frequency (PHF) components, the latter centered on the respiratory frequency. Analysis was done in intervals of different exercise intensity based on oxygen consumption. Linear correlation, reliability, and agreement were computed in each interval. The agreement between the RR series obtained from the Polar device and from the ECG is high throughout the whole test although the shorter the RR is, the more differences there are. Both methods are interchangeable when analyzing HRV at rest. At high exercise intensity, HRM and PLF still presented a high correlation (ρ > 0.8) and excellent reliability and agreement indices (above 0.9). However, the PHF measurements from the Polar showed reliability and agreement coefficients around 0.5 or lower when the level of the exercise increases (for levels of O2 above 60%).

Temporal Variability in the Deglutition Literature

PubMed Central

Molfenter, Sonja M.; Steele, Catriona M.

2013-01-01

A literature review was conducted on temporal measures of swallowing in healthy individuals with the purpose of determining the degree of variability present in such measures within the literature. A total of 46 studies that met inclusion criteria were reviewed. The definitions and descriptive statistics for all reported temporal parameters were compiled for meta-analysis. In total, 119 different temporal parameters were found in the literature. The three most-frequently occurring durational measures were: UES opening, laryngeal closure and hyoid movement. The three most-frequently occurring interval measures were: stage transition duration, pharyngeal transit time and duration from laryngeal closure to UES opening. Subtle variations in operational definitions across studies were noted, making the comparison of data challenging. Analysis of forest plots compiling descriptive statistical data (means and 95% confidence intervals) across studies revealed differing degrees of variability across durations and intervals. Two parameters (UES opening duration and the laryngeal-closure-to-UES-opening interval) demonstrated the least variability, reflected by small ranges for mean values and tight confidence intervals. Trends emerged for factors of bolus size and participant age for some variables. Other potential sources of variability are discussed. PMID:22366761

Remote Sensing Analysis of Malawi's Agricultural Inputs Subsidy and Climate Variability Impacts on Productivity

NASA Astrophysics Data System (ADS)

Galford, G. L.; Fiske, G. J.; Sedano, F.; Michelson, H.

2016-12-01

Agriculture in sub-Saharan Africa is characterized by smallholder production and low yields ( 1 ton ha-1 year-1 since records began in 1961) for staple food crops such as maize (Zea mays). Many years of low-input farming have depleted much of the region's agricultural land of critical soil carbon and nitrogen, further reducing yield potentials. Malawi is a 98,000 km2 subtropical nation with a short rainy season from November to May, with most rainfall occurring between December and mid-April. This short growing season supports the cultivation of one primary crop, maize. In Malawi, many smallholder farmers face annual nutrient deficits as nutrients removed as grain harvest and residues are beyond replenishment levels. As a result, Malawi has had stagnant maize yields averaging 1.2 ton ha-1 year-1 for decades. After multiple years of drought and widespread hunger in the early 2000s, Malawi introduced an agricultural input support program (fertilizer and seed subsidy) in time for the 2006 harvest that was designed to restore soil nutrients, improve maize production, and decrease dependence on food aid. Malawi's subsidy program targets 50-67% of smallholder farmers who cultivate half a hectare or less, yet collectively supply 80% of the country's maize. The country has achieved significant increases in crop yields (now 2 tons/ha/year) and, as our analysis shows, benefited from a new resilience against drought. We utilized Landsat time series to determine cropland extent from 2000-present and identify areas of marginal and/or intermittent production. We found a strong latitudinal gradient of precipitation variability from north to south in CHIRPS data. We used the precipitation variability to normalize trends in a productivity proxy derived from MODIS EVI. After normalization of productivity to precipitation variability, we found significant productivity trends correlated to subsidy distribution. This work was conducted with Google's Earth Engine, a cloud-based platform

Decoupling Solar Variability and Instrument Trends Using the Multiple Same-Irradiance-Level (MuSIL) Analysis Technique

NASA Astrophysics Data System (ADS)

Woods, Thomas N.; Eparvier, Francis G.; Harder, Jerald; Snow, Martin

2018-05-01

The solar spectral irradiance (SSI) dataset is a key record for studying and understanding the energetics and radiation balance in Earth's environment. Understanding the long-term variations of the SSI over timescales of the 11-year solar activity cycle and longer is critical for many Sun-Earth research topics. Satellite measurements of the SSI have been made since the 1970s, most of them in the ultraviolet, but recently also in the visible and near-infrared. A limiting factor for the accuracy of previous solar variability results is the uncertainties for the instrument degradation corrections, which need fairly large corrections relative to the amount of solar cycle variability at some wavelengths. The primary objective of this investigation has been to separate out solar cycle variability and any residual uncorrected instrumental trends in the SSI measurements from the Solar Radiation and Climate Experiment (SORCE) mission and the Thermosphere, Mesosphere, Ionosphere, Energetic, and Dynamics (TIMED) mission. A new technique called the Multiple Same-Irradiance-Level (MuSIL) analysis has been developed, which examines an SSI time series at different levels of solar activity to provide long-term trends in an SSI record, and the most common result is a downward trend that most likely stems from uncorrected instrument degradation. This technique has been applied to each wavelength in the SSI records from SORCE (2003 - present) and TIMED (2002 - present) to provide new solar cycle variability results between 27 nm and 1600 nm with a resolution of about 1 nm at most wavelengths. This technique, which was validated with the highly accurate total solar irradiance (TSI) record, has an estimated relative uncertainty of about 5% of the measured solar cycle variability. The MuSIL results are further validated with the comparison of the new solar cycle variability results from different solar cycles.

Using asymmetry analysis to reduce normal variability of Spectral Domain Optical Coherence Tomography (SD-OCT) macular thickness

NASA Astrophysics Data System (ADS)

Alluwimi, Muhammed Saad

Purpose: To investigate the use of asymmetry analysis to reduce normal between-subject variability of macular thickness measurements using SD-OCT. Methods: 63 volunteers free of eye disease were recruited: 33 young subjects (ages 21 to 35 years with mean and SD of 25 +/- 1.7), and 30 older subjects (ages 45 to 85 years with mean and SD of 66.7 +/- 9.0). All participants passed a comprehensive ophthalmic examination within the past two years. Macular images were gathered with the Spectralis OCT (V 5.4, Heidelberg Engineering, GmbH). The overlay 8x8 grid was manually centered on the fovea and aligned with the foveal-disc axis, then divided into five zones per hemifield following the method of Um et al (2012 IOVS 53:1139); asymmetry was computed as the difference between superior and inferior zone thicknesses. We assumed that the lowest variation and the highest density of ganglion cells will be found ~3° to 6° from the foveal center, corresponding to zones 1 and 2. For each zone and age group, between-subject standard deviations (SDs) were compared for retinal thickness (RT) versus asymmetry using an F-test. To account for repeated measures, a probability of p < 0.0125 was required for statistical significance. Axial length (AL) and corneal curvature (CC) were measured with an IOLMaster by the same operator and during the same imaging session. Results: For OD, asymmetry analysis reduced between-subject variability in zones 1 and 2 in both groups (F > 3.2, p < 0.001). SD for zone 1 dropped from 12.0 to 3.0 mum in the young group and from 11.7 to 2.6 mum in the older group. SD for zone 2 dropped from 13.6 to 5.3 mum (young) and from 11.1 to 5.8 mum (older). Combining all subjects, neither RT nor asymmetry showed a strong correlation with AL or CC (R2 < 0.01). Analysis for OS yielded the same pattern of results, as did asymmetry analyses between eyes (F > 3.8, p < 0.0001). Conclusions: Asymmetry analysis reduced between-subject variability. These findings demonstrate

[Drug abuse in adolescent offenders: analysis of the psychosocial variables involved].

PubMed

Contreras Martínez, Lourdes; Molina Banqueri, Virginia; Cano Lozano, Ma Carmen

2012-01-01

Research shows that drugs and delinquency are frequently linked, the abuse of various types of substance being a widespread practice among young offenders. At the same time, some psychosocial characteristics are associated with both drug abuse and criminal/antisocial behavior. To help us explore the relationship between young offenders' drug abuse and certain psychosocial variables, we examined closed judicial files on young offenders from the Juvenile Justice Service in Jaen (Spain) corresponding to the period 2001 to 2010. From the contents of these judicial files we analyzed demographic variables such as gender and age, as well as psychosocial variables such as drug abuse, peer group, violent behavior, self-control, tolerance to frustration and attributional style. The results show that most of the young offenders use some type of drug, as well as revealing differential patterns of use according to gender. Also observed is a link between drug abuse and deviant peer group, violent behavior and the above-mentioned psychological variables. Finally, we found some differences in these psychological variables depending on the type of drug used.

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis

NASA Astrophysics Data System (ADS)

Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P < 0.001) in rice yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

Place, Poverty, and Algebra: A Statewide Comparative Spatial Analysis of Variable Relationships

ERIC Educational Resources Information Center

Hogrebe, Mark C.; Tate, William F.

2012-01-01

Place matters in moderating variable relationships between algebra performance and educational variables because there are differences on the socioeconomic (SES) poverty-affluence continuum that shape local contexts. This article examines relationships between variables for school district demographic composition, teaching and financial contexts,…

Advocacy Groups and the Discourse of Teacher Policy Reform: An Analysis of Policy Narratives

ERIC Educational Resources Information Center

Harrison, Christopher

2017-01-01

In recent years, several states have engaged in significant action surrounding a key policy area-- teacher policy reform. In Florida, for example, the passage of Senate Bill (SB) 736, the Student Success Act, heralded substantial shifts in the boundaries defining the profession of teaching in the state. Through SB 736 and its unsuccessful…

Effects of a cognitive dual task on variability and local dynamic stability in sustained repetitive arm movements using principal component analysis: a pilot study.

PubMed

Longo, Alessia; Federolf, Peter; Haid, Thomas; Meulenbroek, Ruud

2018-06-01

In many daily jobs, repetitive arm movements are performed for extended periods of time under continuous cognitive demands. Even highly monotonous tasks exhibit an inherent motor variability and subtle fluctuations in movement stability. Variability and stability are different aspects of system dynamics, whose magnitude may be further affected by a cognitive load. Thus, the aim of the study was to explore and compare the effects of a cognitive dual task on the variability and local dynamic stability in a repetitive bimanual task. Thirteen healthy volunteers performed the repetitive motor task with and without a concurrent cognitive task of counting aloud backwards in multiples of three. Upper-body 3D kinematics were collected and postural reconfigurations-the variability related to the volunteer's postural change-were determined through a principal component analysis-based procedure. Subsequently, the most salient component was selected for the analysis of (1) cycle-to-cycle spatial and temporal variability, and (2) local dynamic stability as reflected by the largest Lyapunov exponent. Finally, end-point variability was evaluated as a control measure. The dual cognitive task proved to increase the temporal variability and reduce the local dynamic stability, marginally decrease endpoint variability, and substantially lower the incidence of postural reconfigurations. Particularly, the latter effect is considered to be relevant for the prevention of work-related musculoskeletal disorders since reduced variability in sustained repetitive tasks might increase the risk of overuse injuries.

Forcing variables in simulation of transpiration of water stressed plants determined by principal component analysis

NASA Astrophysics Data System (ADS)

Durigon, Angelica; Lier, Quirijn de Jong van; Metselaar, Klaas

2016-10-01

To date, measuring plant transpiration at canopy scale is laborious and its estimation by numerical modelling can be used to assess high time frequency data. When using the model by Jacobs (1994) to simulate transpiration of water stressed plants it needs to be reparametrized. We compare the importance of model variables affecting simulated transpiration of water stressed plants. A systematic literature review was performed to recover existing parameterizations to be tested in the model. Data from a field experiment with common bean under full and deficit irrigation were used to correlate estimations to forcing variables applying principal component analysis. New parameterizations resulted in a moderate reduction of prediction errors and in an increase in model performance. Ags model was sensitive to changes in the mesophyll conductance and leaf angle distribution parameterizations, allowing model improvement. Simulated transpiration could be separated in temporal components. Daily, afternoon depression and long-term components for the fully irrigated treatment were more related to atmospheric forcing variables (specific humidity deficit between stomata and air, relative air humidity and canopy temperature). Daily and afternoon depression components for the deficit-irrigated treatment were related to both atmospheric and soil dryness, and long-term component was related to soil dryness.

Bayesian Adaptive Lasso for Ordinal Regression with Latent Variables

ERIC Educational Resources Information Center

Feng, Xiang-Nan; Wu, Hao-Tian; Song, Xin-Yuan

2017-01-01

We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct…

Variable Selection for Regression Models of Percentile Flows

NASA Astrophysics Data System (ADS)

Fouad, G.

2017-12-01

Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high

The Effect of Educational Leadership on Organizational Variables: A Meta-Analysis Study in the Sample of Turkey

ERIC Educational Resources Information Center

Çogaltay, Nazim; Karadag, Engin

2016-01-01

The purpose of this study is to test the effect of educational leadership on some organizational variables using meta-analysis method. In this context, the results of independent researches were merged together and the hypotheses created within the scope of the study were tested. In order to determine the researches to be included in the study,…

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

2017-01-01

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

[Design of a Front-end Device of Heart Rate Variability Analysis System Based on Photoplethysmography].

PubMed

Shi, Lei; Sun, Peng; Pang, Yu; Luo, Zhiyong; Wang, Wei; Wang, Yanxiang

2016-02-01

Heart rate variability (HRV) is the difference between the successive changes in the heartbeat cycle, and it is produced in the autonomic nervous system modulation of the sinus node of the heart. The HRV is a valuable indicator in predicting the sudden cardiac death and arrhythmic events. Traditional analysis of HRV is based on a multielectrocardiogram (ECG), but the ECG signal acquisition is complex, so we have designed an HRV analysis system based on photoplethysmography (PPG). PPG signal is collected by a microcontroller from human's finger, and it is sent to the terminal via USB-Serial module. The terminal software not only collects the data and plot waveforms, but also stores the data for future HRV analysis. The system is small in size, low in power consumption, and easy for operation. It is suitable for daily care no matter whether it is used at home or in a hospital.

Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

NASA Astrophysics Data System (ADS)

Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

2018-02-01

This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

Heart Rate Variability Indexes in Dementia: A Systematic Review with a Quantitative Analysis.

PubMed

da Silva, Vanessa Pereira; Ramalho Oliveira, Bruno Ribeiro; Tavares Mello, Roger Gomes; Moraes, Helena; Deslandes, Andrea Camaz; Laks, Jerson

2018-01-01

Decreased heart rate variability (HRV) indexes indicate low vagal activity and may be associated with development of dementia. The neurodegenerative process is associated with the cardiovascular autonomic control. The aim of this systematic review was to investigate the effect size (ES) magnitude of the HRV indexes in the evaluation of autonomic dysfunction in older persons with dementia. PubMed (Medline), Web of Science, Scopus, Scielo, Lilacs, and APA Psycnet were consulted. Complete original articles published in English or Portuguese, investigating the association between autonomic dysfunction and dementia, using the HRV indexes were included. The search identified 97 potentially relevant articles. After screening the full text, eight articles were included in the qualitative analysis and six were included in the quantitative analysis. Almost all indexes showed a negative ES for all types of dementia and mild cognitive impairment. The most common frequency band of the power spectrum density function was the high frequency, which was reported by six studies. The meta-analysis of high frequency power in Alzheimer's disease group showed high heterogeneity and inconsistent results. The negative effect size suggests an autonomic dysfunction in all types of dementia as well as mild cognitive impairment. However, further analysis is necessary to support these results. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The Second Catalog of Flaring Gamma-Ray Sources from the Fermi All-sky Variability Analysis

NASA Astrophysics Data System (ADS)

Abdollahi, S.; Ackermann, M.; Ajello, M.; Albert, A.; Baldini, L.; Ballet, J.; Barbiellini, G.; Bastieri, D.; Becerra Gonzalez, J.; Bellazzini, R.; Bissaldi, E.; Blandford, R. D.; Bloom, E. D.; Bonino, R.; Bottacini, E.; Bregeon, J.; Bruel, P.; Buehler, R.; Buson, S.; Cameron, R. A.; Caragiulo, M.; Caraveo, P. A.; Cavazzuti, E.; Cecchi, C.; Chekhtman, A.; Cheung, C. C.; Chiaro, G.; Ciprini, S.; Conrad, J.; Costantin, D.; Costanza, F.; Cutini, S.; D'Ammando, F.; de Palma, F.; Desai, A.; Desiante, R.; Digel, S. W.; Di Lalla, N.; Di Mauro, M.; Di Venere, L.; Donaggio, B.; Drell, P. S.; Favuzzi, C.; Fegan, S. J.; Ferrara, E. C.; Focke, W. B.; Franckowiak, A.; Fukazawa, Y.; Funk, S.; Fusco, P.; Gargano, F.; Gasparrini, D.; Giglietto, N.; Giomi, M.; Giordano, F.; Giroletti, M.; Glanzman, T.; Green, D.; Grenier, I. A.; Grove, J. E.; Guillemot, L.; Guiriec, S.; Hays, E.; Horan, D.; Jogler, T.; Jóhannesson, G.; Johnson, A. S.; Kocevski, D.; Kuss, M.; La Mura, G.; Larsson, S.; Latronico, L.; Li, J.; Longo, F.; Loparco, F.; Lovellette, M. N.; Lubrano, P.; Magill, J. D.; Maldera, S.; Manfreda, A.; Mayer, M.; Mazziotta, M. N.; Michelson, P. F.; Mitthumsiri, W.; Mizuno, T.; Monzani, M. E.; Morselli, A.; Moskalenko, I. V.; Negro, M.; Nuss, E.; Ohsugi, T.; Omodei, N.; Orienti, M.; Orlando, E.; Paliya, V. S.; Paneque, D.; Perkins, J. S.; Persic, M.; Pesce-Rollins, M.; Petrosian, V.; Piron, F.; Porter, T. A.; Principe, G.; Rainò, S.; Rando, R.; Razzano, M.; Razzaque, S.; Reimer, A.; Reimer, O.; Sgrò, C.; Simone, D.; Siskind, E. J.; Spada, F.; Spandre, G.; Spinelli, P.; Stawarz, L.; Suson, D. J.; Takahashi, M.; Tanaka, K.; Thayer, J. B.; Thompson, D. J.; Torres, D. F.; Torresi, E.; Tosti, G.; Troja, E.; Vianello, G.; Wood, K. S.

2017-09-01

We present the second catalog of flaring gamma-ray sources (2FAV) detected with the Fermi All-sky Variability Analysis (FAVA), a tool that blindly searches for transients over the entire sky observed by the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope. With respect to the first FAVA catalog, this catalog benefits from a larger data set, the latest LAT data release (Pass 8), as well as from an improved analysis that includes likelihood techniques for a more precise localization of the transients. Applying this analysis to the first 7.4 years of Fermi observations, and in two separate energy bands 0.1-0.8 GeV and 0.8-300 GeV, a total of 4547 flares were detected with significance greater than 6σ (before trials), on the timescale of one week. Through spatial clustering of these flares, 518 variable gamma-ray sources were identified. Based on positional coincidence, likely counterparts have been found for 441 sources, mostly among the blazar class of active galactic nuclei. For 77 2FAV sources, no likely gamma-ray counterpart has been found. For each source in the catalog, we provide the time, location, and spectrum of each flaring episode. Studying the spectra of the flares, we observe a harder-when-brighter behavior for flares associated with blazars, with the exception of BL Lac flares detected in the low-energy band. The photon indexes of the flares are never significantly smaller than 1.5. For a leptonic model, and under the assumption of isotropy, this limit suggests that the spectrum of freshly accelerated electrons is never harder than p˜ 2.

Finite Adaptation and Multistep Moves in the Metropolis-Hastings Algorithm for Variable Selection in Genome-Wide Association Analysis

PubMed Central

Peltola, Tomi; Marttinen, Pekka; Vehtari, Aki

2012-01-01

High-dimensional datasets with large amounts of redundant information are nowadays available for hypothesis-free exploration of scientific questions. A particular case is genome-wide association analysis, where variations in the genome are searched for effects on disease or other traits. Bayesian variable selection has been demonstrated as a possible analysis approach, which can account for the multifactorial nature of the genetic effects in a linear regression model. Yet, the computation presents a challenge and application to large-scale data is not routine. Here, we study aspects of the computation using the Metropolis-Hastings algorithm for the variable selection: finite adaptation of the proposal distributions, multistep moves for changing the inclusion state of multiple variables in a single proposal and multistep move size adaptation. We also experiment with a delayed rejection step for the multistep moves. Results on simulated and real data show increase in the sampling efficiency. We also demonstrate that with application specific proposals, the approach can overcome a specific mixing problem in real data with 3822 individuals and 1,051,811 single nucleotide polymorphisms and uncover a variant pair with synergistic effect on the studied trait. Moreover, we illustrate multimodality in the real dataset related to a restrictive prior distribution on the genetic effect sizes and advocate a more flexible alternative. PMID:23166669

Bayesian Group Bridge for Bi-level Variable Selection.

PubMed

Mallick, Himel; Yi, Nengjun

2017-06-01

A Bayesian bi-level variable selection method (BAGB: Bayesian Analysis of Group Bridge) is developed for regularized regression and classification. This new development is motivated by grouped data, where generic variables can be divided into multiple groups, with variables in the same group being mechanistically related or statistically correlated. As an alternative to frequentist group variable selection methods, BAGB incorporates structural information among predictors through a group-wise shrinkage prior. Posterior computation proceeds via an efficient MCMC algorithm. In addition to the usual ease-of-interpretation of hierarchical linear models, the Bayesian formulation produces valid standard errors, a feature that is notably absent in the frequentist framework. Empirical evidence of the attractiveness of the method is illustrated by extensive Monte Carlo simulations and real data analysis. Finally, several extensions of this new approach are presented, providing a unified framework for bi-level variable selection in general models with flexible penalties.

Variability Extraction and Synthesis via Multi-Resolution Analysis using Distribution Transformer High-Speed Power Data

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

Chamana, Manohar; Mather, Barry A

A library of load variability classes is created to produce scalable synthetic data sets using historical high-speed raw data. These data are collected from distribution monitoring units connected at the secondary side of a distribution transformer. Because of the irregular patterns and large volume of historical high-speed data sets, the utilization of current load characterization and modeling techniques are challenging. Multi-resolution analysis techniques are applied to extract the necessary components and eliminate the unnecessary components from the historical high-speed raw data to create the library of classes, which are then utilized to create new synthetic load data sets. A validationmore » is performed to ensure that the synthesized data sets contain the same variability characteristics as the training data sets. The synthesized data sets are intended to be utilized in quasi-static time-series studies for distribution system planning studies on a granular scale, such as detailed PV interconnection studies.« less

Design study and performance analysis of a high-speed multistage variable-geometry fan for a variable cycle engine

NASA Technical Reports Server (NTRS)

Sullivan, T. J.; Parker, D. E.

1979-01-01

A design technology study was performed to identify a high speed, multistage, variable geometry fan configuration capable of achieving wide flow modulation with near optimum efficiency at the important operating condition. A parametric screening study of the front and rear block fans was conducted in which the influence of major fan design features on weight and efficiency was determined. Key design parameters were varied systematically to determine the fan configuration most suited for a double bypass, variable cycle engine. Two and three stage fans were considered for the front block. A single stage, core driven fan was studied for the rear block. Variable geometry concepts were evaluated to provide near optimum off design performance. A detailed aerodynamic design and a preliminary mechanical design were carried out for the selected fan configuration. Performance predictions were made for the front and rear block fans.

78 FR 12290 - Annual List of Newspapers Used for Publication of Legal Notice of Decisions Appealable Under 36...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-22

... Decisions Durango Herald, published daily in Durango, La Plata County, Colorado. Notice by District Rangers of Availability for Comment and Decisions Durango Herald, published daily in Durango, La Plata County...

Ambulatory ECG and analysis of heart rate variability in Parkinson's disease.

PubMed

Haapaniemi, T H; Pursiainen, V; Korpelainen, J T; Huikuri, H V; Sotaniemi, K A; Myllylä, V V

2001-03-01

Cardiovascular reflex tests have shown both sympathetic and parasympathetic failure in Parkinson's disease. These tests, however, describe the autonomic responses during a restricted time period and have great individual variability, providing a limited view of the autonomic cardiac control mechanisms. Thus, they do not reflect tonic autonomic regulation. The aim was to examine tonic autonomic cardiovascular regulation in untreated patients with Parkinson's disease. 24 Hour ambulatory ECG was recorded in 54 untreated patients with Parkinson's disease and 47 age matched healthy subjects. In addition to the traditional spectral (very low frequency, VLF; low frequency, LF; high frequency, HF) and non-spectral components of heart rate variability, instantaneous beat to beat variability (SD1) and long term continuous variability (SD2) derived from Poincaré plots, and the slope of the power law relation were analysed. All spectral components (p<0.01) and the slope of the power-law relation (p<0.01) were lower in the patients with Parkinson's disease than in the control subjects. The Unified Parkinson's disease rating scale total and motor scores had a negative correlation with VLF and LF power spectrum values and the power law relation slopes. Patients with mild hypokinesia had higher HF values than patients with more severe hypokinesia. Tremor and rigidity were not associated with the HR variability parameters. Parkinson's disease causes dysfunction of the diurnal autonomic cardiovascular regulation as demonstrated by the spectral measures of heart rate variability and the slope of the power law relation. This dysfunction seems to be more profound in patients with more severe Parkinson's disease.

Identification of speech transients using variable frame rate analysis and wavelet packets.

PubMed

Rasetshwane, Daniel M; Boston, J Robert; Li, Ching-Chung

2006-01-01

Speech transients are important cues for identifying and discriminating speech sounds. Yoo et al. and Tantibundhit et al. were successful in identifying speech transients and, emphasizing them, improving the intelligibility of speech in noise. However, their methods are computationally intensive and unsuitable for real-time applications. This paper presents a method to identify and emphasize speech transients that combines subband decomposition by the wavelet packet transform with variable frame rate (VFR) analysis and unvoiced consonant detection. The VFR analysis is applied to each wavelet packet to define a transitivity function that describes the extent to which the wavelet coefficients of that packet are changing. Unvoiced consonant detection is used to identify unvoiced consonant intervals and the transitivity function is amplified during these intervals. The wavelet coefficients are multiplied by the transitivity function for that packet, amplifying the coefficients localized at times when they are changing and attenuating coefficients at times when they are steady. Inverse transform of the modified wavelet packet coefficients produces a signal corresponding to speech transients similar to the transients identified by Yoo et al. and Tantibundhit et al. A preliminary implementation of the algorithm runs more efficiently.

The mortality burden of hourly temperature variability in five capital cities, Australia: Time-series and meta-regression analysis.

PubMed

Cheng, Jian; Xu, Zhiwei; Bambrick, Hilary; Su, Hong; Tong, Shilu; Hu, Wenbiao

2017-12-01

Unstable weather, such as intra- and inter-day temperature variability, can impair the health and shorten the survival time of population around the world. Climate change will cause Earth's surface temperature rise, but has unclear effects on temperature variability, making it urgent to understand the characteristics of the burden of temperature variability on mortality, regionally and nationally. This paper aims to quantify the mortality risk of exposure to short-term temperature variability, estimate the resulting death toll and explore how the strength of temperature variability effects will vary as a function of city-level characteristics. Ten-year (2000-2009) time-series data on temperature and mortality were collected for five largest Australia's cities (Sydney, Melbourne, Brisbane, Perth and Adelaide), collectively registering 708,751 deaths in different climates. Short-term temperature variability was captured and represented as the hourly temperature standard deviation within two days. Three-stage analyses were used to assess the burden of temperature variability on mortality. First, we modelled temperature variability-mortality relation and estimated the relative risk of death for each city, using a time-series quasi-Poisson regression model. Second, we used meta-analysis to pool the city-specific estimates, and meta-regression to explore if some city-level factors will modify the population vulnerability to temperature variability. Finally, we calculated the city-specific deaths attributable to temperature variability, and applied such estimates to the whole of Australia as a reflection of the nation-wide death burden associated with temperature variability. We found evidence of significant associations between temperature variability and mortality in all cities assessed. Deaths associated with each 1°C rise in temperature variability elevated by 0.28% (95% confidence interval (CI): 0.05%, 0.52%) in Melbourne to 1.00% (95%CI: 0.52%, 1.48%) in Brisbane

Multiscale power analysis for heart rate variability

NASA Astrophysics Data System (ADS)

Zeng, Peng; Liu, Hongxing; Ni, Huangjing; Zhou, Jing; Xia, Lan; Ning, Xinbao

2015-06-01

We first introduce multiscale power (MSP) method to assess the power distribution of physiological signals on multiple time scales. Simulation on synthetic data and experiments on heart rate variability (HRV) are tested to support the approach. Results show that both physical and psychological changes influence power distribution significantly. A quantitative parameter, termed power difference (PD), is introduced to evaluate the degree of power distribution alteration. We find that dynamical correlation of HRV will be destroyed completely when PD>0.7.

Analysis on electronic control unit of continuously variable transmission

NASA Astrophysics Data System (ADS)

Cao, Shuanggui

Continuously variable transmission system can ensure that the engine work along the line of best fuel economy, improve fuel economy, save fuel and reduce harmful gas emissions. At the same time, continuously variable transmission allows the vehicle speed is more smooth and improves the ride comfort. Although the CVT technology has made great development, but there are many shortcomings in the CVT. The CVT system of ordinary vehicles now is still low efficiency, poor starting performance, low transmission power, and is not ideal controlling, high cost and other issues. Therefore, many scholars began to study some new type of continuously variable transmission. The transmission system with electronic systems control can achieve automatic control of power transmission, give full play to the characteristics of the engine to achieve optimal control of powertrain, so the vehicle is always traveling around the best condition. Electronic control unit is composed of the core processor, input and output circuit module and other auxiliary circuit module. Input module collects and process many signals sent by sensor and , such as throttle angle, brake signals, engine speed signal, speed signal of input and output shaft of transmission, manual shift signals, mode selection signals, gear position signal and the speed ratio signal, so as to provide its corresponding processing for the controller core.

An Analysis of Basic Construction Variables of Racing Wheelchairs Used in the 1984 International Games for the Disabled.

ERIC Educational Resources Information Center

York, Sherril L.; Kimura, Iris F.

1987-01-01

A photographic analysis of racing wheelchairs used by cerebral palsy class four athletes and amputee athletes at the 1984 International Games for the Disabled was undertaken in order to analyze seven wheelchair construction variables in relation to performance outcome, distance raced, and type of disability of the user. (Author/MT)

Quantum Communication Systems

DTIC Science & Technology

2008-03-15

numbers make the observation of non -Poissonian features easier, which calls for higher pump power and better mode matching of the pump beam , more...heralded two-photon NOON states, we rely on the local photon- bunching effect of two heralded single photons at a beam splitter , as sketched in Fig. 1. Two...heralded single photons are sent to separate input ports of a 50:50 beam splitter (BS1). The photons bunch at the beam splitter , exiting together from

Measuring the environmental effects of organic farming: A meta-analysis of structural variables in empirical research.

PubMed

Lee, Ki Song; Choe, Young Chan; Park, Sung Hee

2015-10-01

This study examined the structural variables affecting the environmental effects of organic farming compared to those of conventional farming. A meta-analysis based on 107 studies and 360 observations published from 1977 to 2012 compared energy efficiency (EE) and greenhouse gas emissions (GHGE) for organic and conventional farming. The meta-analysis systematically analyzed the results of earlier comparative studies and used logistic regression to identify the structural variables that contributed to differences in the effects of organic and conventional farming on the environment. The statistical evidence identified characteristics that differentiated the environmental effects of organic and conventional farming, which is controversial. The results indicated that data sources, sample size and product type significantly affected EE, whereas product type, cropping pattern and measurement unit significantly affected the GHGE of organic farming compared to conventional farming. Superior effects of organic farming on the environment were more likely to appear for larger samples, primary data rather than secondary data, monocropping rather than multicropping, and crops other than fruits and vegetables. The environmental effects of organic farming were not affected by the study period, geographic location, farm size, cropping pattern, or measurement method. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

The effect of heart rate variability biofeedback training on stress and anxiety: a meta-analysis.

PubMed

Goessl, V C; Curtiss, J E; Hofmann, S G

2017-11-01

Some evidence suggests that heart rate variability (HRV) biofeedback might be an effective way to treat anxiety and stress symptoms. To examine the effect of HRV biofeedback on symptoms of anxiety and stress, we conducted a meta-analysis of studies extracted from PubMed, PsycINFO and the Cochrane Library. The search identified 24 studies totaling 484 participants who received HRV biofeedback training for stress and anxiety. We conducted a random-effects meta-analysis. The pre-post within-group effect size (Hedges' g) was 0.81. The between-groups analysis comparing biofeedback to a control condition yielded Hedges' g = 0.83. Moderator analyses revealed that treatment efficacy was not moderated by study year, risk of study bias, percentage of females, number of sessions, or presence of an anxiety disorder. HRV biofeedback training is associated with a large reduction in self-reported stress and anxiety. Although more well-controlled studies are needed, this intervention offers a promising approach for treating stress and anxiety with wearable devices.

Variability of chemical analysis of reinforcing bar produced in Saudi Arabia

NASA Astrophysics Data System (ADS)

Salman, A.; Djavanroodi, F.

2018-04-01

In view of the importance and demanding roles of steel rebar’s in the reinforced concrete structures, accurate information on the properties of the steels is important at the design stage. In the steelmaking process, production variations in chemical composition are unavoidable. The aim of this work is to study the variability of the chemical composition of reinforcing steel produced throughout the Saudi Arabia and asses the quality of steel rebar’s acoording to ASTM A615. 68 samples of ASTM A615 Grade 60 from different manufacturers were collected and tested using the Spectrometer test to obtain Chemical Compositions. EasyFit (5.6) software is utilized to conducted statistical analysis. Chemical compositions distributions and, control charts are generated for the compositions. Results showed that some compositions are above the upper line of the control chart. Finally, the analyses show that less than 3% of the steel failed to meet minimum ASTM standards for chemical composition.

Analysis of the impact path on factors of China's energy-related CO2 emissions: a path analysis with latent variables.

PubMed

Chen, Wenhui; Lei, Yalin

2017-02-01

Identifying the impact path on factors of CO 2 emissions is crucial for the government to take effective measures to reduce carbon emissions. The most existing research focuses on the total influence of factors on CO 2 emissions without differentiating between the direct and indirect influence. Moreover, scholars have addressed the relationships among energy consumption, economic growth, and CO 2 emissions rather than estimating all the causal relationships simultaneously. To fill this research gaps and explore overall driving factors' influence mechanism on CO 2 emissions, this paper utilizes a path analysis model with latent variables (PA-LV) to estimate the direct and indirect effect of factors on China's energy-related carbon emissions and to investigate the causal relationships among variables. Three key findings emanate from the analysis: (1) The change in the economic growth pattern inhibits the growth rate of CO 2 emissions by reducing the energy intensity; (2) adjustment of industrial structure contributes to energy conservation and CO 2 emission reduction by raising the proportion of the tertiary industry; and (3) the growth of CO 2 emissions impacts energy consumption and energy intensity negatively, which results in a negative impact indirectly on itself. To further control CO 2 emissions, the Chinese government should (1) adjust the industrial structure and actively develop its tertiary industry to improve energy efficiency and develop low-carbon economy, (2) optimize population shifts to avoid excessive population growth and reduce energy consumption, and (3) promote urbanization steadily to avoid high energy consumption and low energy efficiency.

Nonlinear analysis of heart rate variability within independent frequency components during the sleep-wake cycle.

PubMed

Vigo, Daniel E; Dominguez, Javier; Guinjoan, Salvador M; Scaramal, Mariano; Ruffa, Eduardo; Solernó, Juan; Siri, Leonardo Nicola; Cardinali, Daniel P

2010-04-19

Heart rate variability (HRV) is a complex signal that results from the contribution of different sources of oscillation related to the autonomic nervous system activity. Although linear analysis of HRV has been applied to sleep studies, the nonlinear dynamics of HRV underlying frequency components during sleep is less known. We conducted a study to evaluate nonlinear HRV within independent frequency components in wake status, slow-wave sleep (SWS, stages III or IV of non-rapid eye movement sleep), and rapid-eye-movement sleep (REM). The sample included 10 healthy adults. Polysomnography was performed to detect sleep stages. HRV was studied globally during each phase and then very low frequency (VLF), low frequency (LF) and high frequency (HF) components were separated by means of the wavelet transform algorithm. HRV nonlinear dynamics was estimated with sample entropy (SampEn). A higher SampEn was found when analyzing global variability (Wake: 1.53+/-0.28, SWS: 1.76+/-0.32, REM: 1.45+/-0.19, p=0.005) and VLF variability (Wake: 0.13+/-0.03, SWS: 0.19+/-0.03, REM: 0.14+/-0.03, p<0.001) at SWS. REM was similar to wake status regarding nonlinear HRV. We propose nonlinear HRV is a useful index of the autonomic activity that characterizes the different sleep-wake cycle stages. 2009 Elsevier B.V. All rights reserved.

Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability.

PubMed

Kim, Hyungjin; Park, Chang Min; Lee, Myunghee; Park, Sang Joon; Song, Yong Sub; Lee, Jong Hyuk; Hwang, Eui Jin; Goo, Jin Mo

2016-01-01

To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed with filtered back projection and commercial iterative reconstruction algorithm (level 3 and 5). Two readers independently segmented the whole tumor volume. Fifteen radiomic features were extracted and compared among reconstruction algorithms. Intra- and inter-reader variability and inter-reconstruction algorithm variability were calculated using coefficients of variation (CVs) and then compared. Among the 15 features, 5 first-order tumor intensity features and 4 gray level co-occurrence matrix (GLCM)-based features showed significant differences (p<0.05) among reconstruction algorithms. As for the variability, effective diameter, sphericity, entropy, and GLCM entropy were the most robust features (CV≤5%). Inter-reader variability was larger than intra-reader or inter-reconstruction algorithm variability in 9 features. However, for entropy, homogeneity, and 4 GLCM-based features, inter-reconstruction algorithm variability was significantly greater than inter-reader variability (p<0.013). Most of the radiomic features were significantly affected by the reconstruction algorithms. Inter-reconstruction algorithm variability was greater than inter-reader variability for entropy, homogeneity, and GLCM-based features.

Baseflow recession analysis in a large shale play: Climate variability and anthropogenic alterations mask effects of hydraulic fracturing

NASA Astrophysics Data System (ADS)

Arciniega-Esparza, Saúl; Breña-Naranjo, Jose Agustín; Hernández-Espriú, Antonio; Pedrozo-Acuña, Adrián; Scanlon, Bridget R.; Nicot, Jean Philippe; Young, Michael H.; Wolaver, Brad D.; Alcocer-Yamanaka, Victor Hugo

2017-10-01

Water resources development and landscape alteration exert marked impacts on water-cycle dynamics, including areas subjected to hydraulic fracturing (HF) for exploitation of unconventional oil and gas resources found in shale or tight sandstones. Here we apply a conceptual framework for linking baseflow analysis to changes in water demands from different sectors (e.g. oil/gas extraction, irrigation, and municipal consumption) and climatic variability in the semiarid Eagle Ford play in Texas, USA. We hypothesize that, in water-limited regions, baseflow (Qb) changes are partly due (along with climate variability) to groundwater abstraction. For a more realistic assessment, the analysis was conducted in two different sets of unregulated catchments, located outside and inside the Eagle Ford play. Three periods were considered in the analysis related to HF activities: pre-development (1980-2000), moderate (2001-2008) and intensive (2009-2015) periods. Results indicate that in the Eagle Ford play region, temporal changes in baseflow cannot be directly related to the increase in hydraulic fracturing. Instead, substantial baseflow declines during the intensive period of hydraulic fracturing represent the aggregated effects from the combination of: (1) a historical exceptional drought during 2011-2012; (2) increased groundwater-based irrigation; and (3) an intensive hydraulic fracturing activity.

Increased Intra-Participant Variability in Children with Autistic Spectrum Disorders: Evidence from Single-Trial Analysis of Evoked EEG

PubMed Central

Milne, Elizabeth

2011-01-01

Intra-participant variability in clinical conditions such as autistic spectrum disorder (ASD) is an important indicator of pathophysiological processing. The data reported here illustrate that trial-by-trial variability can be reliably measured from EEG, and that intra-participant EEG variability is significantly greater in those with ASD than in neuro-typical matched controls. EEG recorded at the scalp is a linear mixture of activity arising from muscle artifacts and numerous concurrent brain processes. To minimize these additional sources of variability, EEG data were subjected to two different methods of spatial filtering. (i) The data were decomposed using infomax independent component analysis, a method of blind source separation which un-mixes the EEG signal into components with maximally independent time-courses, and (ii) a surface Laplacian transform was performed (current source density interpolation) in order to reduce the effects of volume conduction. Data are presented from 13 high functioning adolescents with ASD without co-morbid ADHD, and 12 neuro-typical age-, IQ-, and gender-matched controls. Comparison of variability between the ASD and neuro-typical groups indicated that intra-participant variability of P1 latency and P1 amplitude was greater in the participants with ASD, and inter-trial α-band phase coherence was lower in the participants with ASD. These data support the suggestion that individuals with ASD are less able to synchronize the activity of stimulus-related cell assemblies than neuro-typical individuals, and provide empirical evidence in support of theories of increased neural noise in ASD. PMID:21716921

Redundant variables and Granger causality

NASA Astrophysics Data System (ADS)

Angelini, L.; de Tommaso, M.; Marinazzo, D.; Nitti, L.; Pellicoro, M.; Stramaglia, S.

2010-03-01

We discuss the use of multivariate Granger causality in presence of redundant variables: the application of the standard analysis, in this case, leads to under estimation of causalities. Using the un-normalized version of the causality index, we quantitatively develop the notions of redundancy and synergy in the frame of causality and propose two approaches to group redundant variables: (i) for a given target, the remaining variables are grouped so as to maximize the total causality and (ii) the whole set of variables is partitioned to maximize the sum of the causalities between subsets. We show the application to a real neurological experiment, aiming to a deeper understanding of the physiological basis of abnormal neuronal oscillations in the migraine brain. The outcome by our approach reveals the change in the informational pattern due to repetitive transcranial magnetic stimulations.

Predicting punching acceleration from selected strength and power variables in elite karate athletes: a multiple regression analysis.

PubMed

Loturco, Irineu; Artioli, Guilherme Giannini; Kobal, Ronaldo; Gil, Saulo; Franchini, Emerson

2014-07-01

This study investigated the relationship between punching acceleration and selected strength and power variables in 19 professional karate athletes from the Brazilian National Team (9 men and 10 women; age, 23 ± 3 years; height, 1.71 ± 0.09 m; and body mass [BM], 67.34 ± 13.44 kg). Punching acceleration was assessed under 4 different conditions in a randomized order: (a) fixed distance aiming to attain maximum speed (FS), (b) fixed distance aiming to attain maximum impact (FI), (c) self-selected distance aiming to attain maximum speed, and (d) self-selected distance aiming to attain maximum impact. The selected strength and power variables were as follows: maximal dynamic strength in bench press and squat-machine, squat and countermovement jump height, mean propulsive power in bench throw and jump squat, and mean propulsive velocity in jump squat with 40% of BM. Upper- and lower-body power and maximal dynamic strength variables were positively correlated to punch acceleration in all conditions. Multiple regression analysis also revealed predictive variables: relative mean propulsive power in squat jump (W·kg-1), and maximal dynamic strength 1 repetition maximum in both bench press and squat-machine exercises. An impact-oriented instruction and a self-selected distance to start the movement seem to be crucial to reach the highest acceleration during punching execution. This investigation, while demonstrating strong correlations between punching acceleration and strength-power variables, also provides important information for coaches, especially for designing better training strategies to improve punching speed.

Maximum Likelihood Analysis of Nonlinear Structural Equation Models with Dichotomous Variables

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2005-01-01

In this article, a maximum likelihood approach is developed to analyze structural equation models with dichotomous variables that are common in behavioral, psychological and social research. To assess nonlinear causal effects among the latent variables, the structural equation in the model is defined by a nonlinear function. The basic idea of the…

Design and prototyping of a wristband-type wireless photoplethysmographic device for heart rate variability signal analysis.

PubMed

Ghamari, M; Soltanpur, C; Cabrera, S; Romero, R; Martinek, R; Nazeran, H

2016-08-01

Heart Rate Variability (HRV) signal analysis provides a quantitative marker of the Autonomic Nervous System (ANS) function. A wristband-type wireless photoplethysmographic (PPG) device was custom-designed to collect and analyze the arterial pulse in the wrist. The proposed device is comprised of an optical sensor to monitor arterial pulse, a signal conditioning unit to filter and amplify the analog PPG signal, a microcontroller to digitize the analog PPG signal, and a Bluetooth module to transfer the data to a smart device. This paper proposes a novel model to represent the PPG signal as the summation of two Gaussian functions. The paper concludes with a verification procedure for HRV signal analysis during sedentary activities.

Toward Capturing Momentary Changes of Heart Rate Variability by a Dynamic Analysis Method

PubMed Central

Zhang, Haoshi; Zhu, Mingxing; Zheng, Yue; Li, Guanglin

2015-01-01

The analysis of heart rate variability (HRV) has been performed on long-term electrocardiography (ECG) recordings (12~24 hours) and short-term recordings (2~5 minutes), which may not capture momentary change of HRV. In this study, we present a new method to analyze the momentary HRV (mHRV). The ECG recordings were segmented into a series of overlapped HRV analysis windows with a window length of 5 minutes and different time increments. The performance of the proposed method in delineating the dynamics of momentary HRV measurement was evaluated with four commonly used time courses of HRV measures on both synthetic time series and real ECG recordings from human subjects and dogs. Our results showed that a smaller time increment could capture more dynamical information on transient changes. Considering a too short increment such as 10 s would cause the indented time courses of the four measures, a 1-min time increment (4-min overlapping) was suggested in the analysis of mHRV in the study. ECG recordings from human subjects and dogs were used to further assess the effectiveness of the proposed method. The pilot study demonstrated that the proposed analysis of mHRV could provide more accurate assessment of the dynamical changes in cardiac activity than the conventional measures of HRV (without time overlapping). The proposed method may provide an efficient means in delineating the dynamics of momentary HRV and it would be worthy performing more investigations. PMID:26172953

A Comprehensive Meta-Analysis of Triple P-Positive Parenting Program Using Hierarchical Linear Modeling: Effectiveness and Moderating Variables

ERIC Educational Resources Information Center

Nowak, Christoph; Heinrichs, Nina

2008-01-01

A meta-analysis encompassing all studies evaluating the impact of the Triple P-Positive Parenting Program on parent and child outcome measures was conducted in an effort to identify variables that moderate the program's effectiveness. Hierarchical linear models (HLM) with three levels of data were employed to analyze effect sizes. The results (N =…

Evolution of the genetic variability of eight French dairy cattle breeds assessed by pedigree analysis.

PubMed

Danchin-Burge, C; Leroy, G; Brochard, M; Moureaux, S; Verrier, E

2012-06-01

A pedigree analysis was performed on eight French dairy cattle breeds to assess their change in genetic variability since a first analysis completed in 1996. The Holstein, Normande and Montbéliarde breeds are selected internationally with over hundreds of thousands cows registered in the performance recording system. Three breeds are internationally selected but with limited numbers of cows in France (Brown Swiss, French Simmental and French Red Pied). The last two remaining breeds (Abondance and Tarentaise) are raised at regional level. The effective numbers of ancestors of cows born between 2004 and 2007 varied between 15 (Abondance and Tarentaise) and 51 (French Red Pied). The effective population sizes (classical approach) varied between 53 (Abondance) and 197 (French Red Pied). This article also compares the genetic variability of the ex situ (collections of the French National Cryobank) and in situ populations. The results were commented in regard to the recent history of gene flows in the different breeds as well as the existence of more or less stringent bottlenecks. Our results showed that whatever the size of the breeds, their genetic diversity impoverished quite rapidly since 1996 and they all could be considered as quite poor from a genetic diversity point of view. It shows the need for setting up cryobanks as gene reservoirs as well as sustainable breeding programmes that include loss of genetic diversity as an integrated control parameter. © 2011 Blackwell Verlag GmbH.

A Meta-analysis on Resting State High-frequency Heart Rate Variability in Bulimia Nervosa.

PubMed

Peschel, Stephanie K V; Feeling, Nicole R; Vögele, Claus; Kaess, Michael; Thayer, Julian F; Koenig, Julian

2016-09-01

Autonomic nervous system function is altered in eating disorders. We aimed to quantify differences in resting state vagal activity, indexed by high-frequency heart rate variability comparing patients with bulimia nervosa (BN) and healthy controls. A systematic search of the literature to identify studies eligible for inclusion and meta-analytical methods were applied. Meta-regression was used to identify potential covariates. Eight studies reporting measures of resting high-frequency heart rate variability in individuals with BN (n = 137) and controls (n = 190) were included. Random-effects meta-analysis revealed a sizeable main effect (Z = 2.22, p = .03; Hedge's g = 0.52, 95% CI [0.06;0.98]) indicating higher resting state vagal activity in individuals with BN. Meta-regression showed that body mass index and medication intake are significant covariates. Findings suggest higher vagal activity in BN at rest, particularly in unmedicated samples with lower body mass index. Potential mechanisms underlying these findings and implications for routine clinical care are discussed. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association.

Quality assurance of temporal variability of natural decay chain and neutron induced background for low-level NORM analysis

DOE PAGES

Yoho, Michael; Porterfield, Donivan R.; Landsberger, Sheldon

2015-09-22

In this study, twenty-one high purity germanium (HPGe) background spectra were collected over 2 years at Los Alamos National Laboratory. A quality assurance methodology was developed to monitor spectral background levels from thermal and fast neutron flux levels and naturally occurring radioactive material decay series radionuclides. 238U decay products above 222Rn demonstrated minimal temporal variability beyond that expected from counting statistics. 238U and 232Th progeny below Rn gas displayed at most twice the expected variability. Further, an analysis of the 139 keV 74Ge(n, γ) and 691 keV 72Ge(n, n') spectral features demonstrated temporal stability for both thermal and fastmore » neutron fluxes.« less

Assessing Independent Variables Used in Econometric Modeling Forest Land Use or Land Cover Change: A Meta-Analysis

Treesearch

J Jeuck; F. Cubbage; R. Abt; R. Bardon; J. McCarter; J. Coulston; M. Renkow

2014-01-01

: We conducted a meta-analysis on 64 econometric models from 47 studies predicting forestland conversion to agriculture (F2A), forestland to development (F2D), forestland to non-forested (F2NF) and undeveloped (including forestland) to developed (U2D) land. Over 250 independent econometric variables were identified from 21 F2A models, 21 F2D models, 12 F2NF models, and...

Stochastic time series analysis of fetal heart-rate variability

NASA Astrophysics Data System (ADS)

Shariati, M. A.; Dripps, J. H.

1990-06-01

Fetal Heart Rate(FHR) is one of the important features of fetal biophysical activity and its long term monitoring is used for the antepartum(period of pregnancy before labour) assessment of fetal well being. But as yet no successful method has been proposed to quantitatively represent variety of random non-white patterns seen in FHR. Objective of this paper is to address this issue. In this study the Box-Jenkins method of model identification and diagnostic checking was used on phonocardiographic derived FHR(averaged) time series. Models remained exclusively autoregressive(AR). Kalman filtering in conjunction with maximum likelihood estimation technique forms the parametric estimator. Diagnosrics perfonned on the residuals indicated that a second order model may be adequate in capturing type of variability observed in 1 up to 2 mm data windows of FHR. The scheme may be viewed as a means of data reduction of a highly redundant information source. This allows a much more efficient transmission of FHR information from remote locations to places with facilities and expertise for doser analysis. The extracted parameters is aimed to reflect numerically the important FHR features. These are normally picked up visually by experts for their assessments. As a result long term FHR recorded during antepartum period could then be screened quantitatively for detection of patterns considered normal or abnonnal. 1.

An analysis of effect of land use change on river flow variability

NASA Astrophysics Data System (ADS)

Zhang, Tao; Liu, Yuting; Yang, Xinyue; Wang, Xiang

2018-02-01

Land use scenario analysis, SWAT model, flow characteristic indices and flow variability technology were used to analyze the effect of land use quantity and location change on river flow. Results showed that river flow variation caused by land use change from forest to crop was larger than that caused by land use change from forest to grass; Land use change neither from upstream to downstream nor from downstream to upstream had little effect on annual average discharge and maximum annual average discharge. But it had obvious effect on maximum daily discharge; Land use change which occurred in upstream could lead to producing larger magnitude flood more easily; Land use change from forest to crop or grass could increase the number of large magnitude floods and their total duration. And it also could increase the number of small magnitude floods but decrease their duration.

Permutation entropy analysis of heart rate variability for the assessment of cardiovascular autonomic neuropathy in type 1 diabetes mellitus.

PubMed

Carricarte Naranjo, Claudia; Sanchez-Rodriguez, Lazaro M; Brown Martínez, Marta; Estévez Báez, Mario; Machado García, Andrés

2017-07-01

Heart rate variability (HRV) analysis is a relevant tool for the diagnosis of cardiovascular autonomic neuropathy (CAN). To our knowledge, no previous investigation on CAN has assessed the complexity of HRV from an ordinal perspective. Therefore, the aim of this work is to explore the potential of permutation entropy (PE) analysis of HRV complexity for the assessment of CAN. For this purpose, we performed a short-term PE analysis of HRV in healthy subjects and type 1 diabetes mellitus patients, including patients with CAN. Standard HRV indicators were also calculated in the control group. A discriminant analysis was used to select the variables combination with best discriminative power between control and CAN patients groups, as well as for classifying cases. We found that for some specific temporal scales, PE indicators were significantly lower in CAN patients than those calculated for controls. In such cases, there were ordinal patterns with high probabilities of occurrence, while others were hardly found. We posit this behavior occurs due to a decrease of HRV complexity in the diseased system. Discriminant functions based on PE measures or probabilities of occurrence of ordinal patterns provided an average of 75% and 96% classification accuracy. Correlations of PE and HRV measures showed to depend only on temporal scale, regardless of pattern length. PE analysis at some specific temporal scales, seem to provide additional information to that obtained with traditional HRV methods. We concluded that PE analysis of HRV is a promising method for the assessment of CAN. Copyright © 2017 Elsevier Ltd. All rights reserved.

Learner Variables in Second Language Listening Comprehension: An Exploratory Path Analysis

ERIC Educational Resources Information Center

Vandergrift, Larry; Baker, Susan

2015-01-01

Listening comprehension plays a key role in language acquisition, yet little is known about the variables that contribute to the development of second language (L2) listening ability. This study sought to obtain empirical evidence for the impact of some of the learner variables and the degree to which they might predict success in L2 listening.…

Ambient temperature effect on pulse rate variability as an alternative to heart rate variability in young adult.

PubMed

Shin, Hangsik

2016-12-01

Pulse rate variability (PRV) is a promising physiological and analytic technique used as a substitute for heart rate variability (HRV). PRV is measured by pulse wave from various devices including mobile and wearable devices but HRV is only measured by an electrocardiogram (ECG). The purpose of this study was to evaluate PRV and HRV at various ambient temperatures and elaborate on the interchangeability of PRV and HRV. Twenty-eight healthy young subjects were enrolled in the experiment. We prepared temperature-controlled rooms and recorded the ECG and photoplethysmography (PPG) under temperature-controlled, constant humidity conditions. The rooms were kept at 17, 25, and 38 °C as low, moderate, and high ambient temperature environments, respectively. HRV and PRV were derived from the synchronized ECG and PPG measures and they were studied in time and frequency domain analysis for PRV/HRV ratio and pulse transit time (PTT). Similarity and differences between HRV and PRV were determined by a statistical analysis. PRV/HRV ratio analysis revealed that there was a significant difference between HRV and PRV for a given ambient temperature; this was with short-term variability measures such as SDNN SDSD or RMSSD, and HF-based variables including HF, LF/HF and normalized HF. In our analysis the absolute value of PTT was not significantly influenced by temperature. Standard deviation of PTT, however, showed significant difference not only between low and moderate temperatures but also between low and high temperatures. Our results suggest that ambient temperature induces a significant difference in PRV compared to HRV and that the difference becomes greater at a higher ambient temperature.

A Framework for Categorizing Important Project Variables

NASA Technical Reports Server (NTRS)

Parsons, Vickie S.

2003-01-01

While substantial research has led to theories concerning the variables that affect project success, no universal set of such variables has been acknowledged as the standard. The identification of a specific set of controllable variables is needed to minimize project failure. Much has been hypothesized about the need to match project controls and management processes to individual projects in order to increase the chance for success. However, an accepted taxonomy for facilitating this matching process does not exist. This paper surveyed existing literature on classification of project variables. After an analysis of those proposals, a simplified categorization is offered to encourage further research.

Instrumental variables I: instrumental variables exploit natural variation in nonexperimental data to estimate causal relationships.

PubMed

Rassen, Jeremy A; Brookhart, M Alan; Glynn, Robert J; Mittleman, Murray A; Schneeweiss, Sebastian

2009-12-01

The gold standard of study design for treatment evaluation is widely acknowledged to be the randomized controlled trial (RCT). Trials allow for the estimation of causal effect by randomly assigning participants either to an intervention or comparison group; through the assumption of "exchangeability" between groups, comparing the outcomes will yield an estimate of causal effect. In the many cases where RCTs are impractical or unethical, instrumental variable (IV) analysis offers a nonexperimental alternative based on many of the same principles. IV analysis relies on finding a naturally varying phenomenon, related to treatment but not to outcome except through the effect of treatment itself, and then using this phenomenon as a proxy for the confounded treatment variable. This article demonstrates how IV analysis arises from an analogous but potentially impossible RCT design, and outlines the assumptions necessary for valid estimation. It gives examples of instruments used in clinical epidemiology and concludes with an outline on estimation of effects.