TH-CD-207A-07: Prediction of High Dimensional State Subject to Respiratory Motion: A Manifold Learning Approach

International Nuclear Information System (INIS)

Liu, W; Sawant, A; Ruan, D

2016-01-01

Purpose: The development of high dimensional imaging systems (e.g. volumetric MRI, CBCT, photogrammetry systems) in image-guided radiotherapy provides important pathways to the ultimate goal of real-time volumetric/surface motion monitoring. This study aims to develop a prediction method for the high dimensional state subject to respiratory motion. Compared to conventional linear dimension reduction based approaches, our method utilizes manifold learning to construct a descriptive feature submanifold, where more efficient and accurate prediction can be performed. Methods: We developed a prediction framework for high-dimensional state subject to respiratory motion. The proposed method performs dimension reduction in a nonlinear setting to permit more descriptive features compared to its linear counterparts (e.g., classic PCA). Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where low-dimensional prediction is performed. A fixed-point iterative pre-image estimation method is applied subsequently to recover the predicted value in the original state space. We evaluated and compared the proposed method with PCA-based method on 200 level-set surfaces reconstructed from surface point clouds captured by the VisionRT system. The prediction accuracy was evaluated with respect to root-mean-squared-error (RMSE) for both 200ms and 600ms lookahead lengths. Results: The proposed method outperformed PCA-based approach with statistically higher prediction accuracy. In one-dimensional feature subspace, our method achieved mean prediction accuracy of 0.86mm and 0.89mm for 200ms and 600ms lookahead lengths respectively, compared to 0.95mm and 1.04mm from PCA-based method. The paired t-tests further demonstrated the statistical significance of the superiority of our method, with p-values of 6.33e-3 and 5.78e-5, respectively. Conclusion: The proposed approach benefits from the descriptiveness of a nonlinear manifold and the prediction

Strain dyssynchrony index determined by three-dimensional speckle area tracking can predict response to cardiac resynchronization therapy

Directory of Open Access Journals (Sweden)

Onishi Tetsuari

2011-04-01

Full Text Available Abstract Background We have previously reported strain dyssynchrony index assessed by two-dimensional speckle tracking strain, and a marker of both dyssynchrony and residual myocardial contractility, can predict response to cardiac resynchronization therapy (CRT. A newly developed three-dimensional (3-D speckle tracking system can quantify endocardial area change ratio (area strain, which coupled with the factors of both longitudinal and circumferential strain, from all 16 standard left ventricular (LV segments using complete 3-D pyramidal datasets. Our objective was to test the hypothesis that strain dyssynchrony index using area tracking (ASDI can quantify dyssynchrony and predict response to CRT. Methods We studied 14 heart failure patients with ejection fraction of 27 ± 7% (all≤35% and QRS duration of 172 ± 30 ms (all≥120 ms who underwent CRT. Echocardiography was performed before and 6-month after CRT. ASDI was calculated as the average difference between peak and end-systolic area strain of LV endocardium obtained from 3-D speckle tracking imaging using 16 segments. Conventional dyssynchrony measures were assessed by interventricular mechanical delay, Yu Index, and two-dimensional radial dyssynchrony by speckle-tracking strain. Response was defined as a ≥15% decrease in LV end-systolic volume 6-month after CRT. Results ASDI ≥ 3.8% was the best predictor of response to CRT with a sensitivity of 78%, specificity of 100% and area under the curve (AUC of 0.93 (p Conclusions ASDI can predict responders and LV reverse remodeling following CRT. This novel index using the 3-D speckle tracking system, which shows circumferential and longitudinal LV dyssynchrony and residual endocardial contractility, may thus have clinical significance for CRT patients.

Thermodynamic-based retention time predictions of endogenous steroids in comprehensive two-dimensional gas chromatography.

Science.gov (United States)

Silva, Aline C A; Ebrahimi-Najafadabi, Heshmatollah; McGinitie, Teague M; Casilli, Alessandro; Pereira, Henrique M G; Aquino Neto, Francisco R; Harynuk, James J

2015-05-01

This work evaluates the application of a thermodynamic model to comprehensive two-dimensional gas chromatography (GC × GC) coupled with time-of-flight mass spectrometry for anabolic agent investigation. Doping control deals with hundreds of drugs that are prohibited in sports. Drug discovery in biological matrices is a challenging task that requires powerful tools when one is faced with the rapidly changing designer drug landscape. In this work, a thermodynamic model developed for the prediction of both primary and secondary retention times in GC × GC has been applied to trimethylsilylated hydroxyl (O-TMS)- and methoxime-trimethylsilylated carbonyl (MO-TMS)-derivatized endogenous steroids. This model was previously demonstrated on a pneumatically modulated GC × GC system, and is applied for the first time to a thermally modulated GC × GC system. Preliminary one-dimensional experiments allowed the calculation of thermodynamic parameters (ΔH, ΔS, and ΔC p ) which were successfully applied for the prediction of the analytes' interactions with the stationary phases of both the first-dimension column and the second-dimension column. The model was able to predict both first-dimension and second-dimension retention times with high accuracy compared with the GC × GC experimental measurements. Maximum differences of -8.22 s in the first dimension and 0.4 s in the second dimension were encountered for the O-TMS derivatives of 11β-hydroxyandrosterone and 11-ketoetiocholanolone, respectively. For the MO-TMS derivatives, the largest discrepancies were from testosterone (9.65 ) for the first-dimension retention times and 11-keto-etiocholanolone (0.4 s) for the second-dimension retention times.

A double-pass interferometer for measurement of dimensional changes

International Nuclear Information System (INIS)

Ren, Dongmei; Lawton, K M; Miller, J A

2008-01-01

A double-pass interferometer was developed for measuring dimensional changes of materials in a nanoscale absolute interferometric dilatometer. This interferometer realized the double-ended measurement of a sample using a single-detection double-pass interference system. The nearly balanced design, in which the measurement beam and the reference beam have equal optical path lengths except for the path difference caused by the sample itself, makes this interferometer have high stability, which is verified by the measurement of a quasi-zero-length sample. The preliminary experiments and uncertainty analysis show that this interferometer should be able to measure dimensional changes with characteristic uncertainty at the nanometer level

Flow predictions for MHD channels with an approximation for three-dimensional effects

International Nuclear Information System (INIS)

Blottner, F.G.

1978-01-01

A finite-difference procedure has been formulated for predicting the flow properties across channels. A quasi-two-dimensional approach has been developed which allows the three-dimensional channel effects to be taken into account. Comparison of the numerical solutions with experimental results show that this approach is a reasonable approximation for MHD flow conditions if there is not significant merging of the wall boundary layers. The resulting code provides a technique to obtain the flow details in the symmetry plane of the channel and requires only a small amount of computer time

Drying and control of moisture content and dimensional changes

Science.gov (United States)

Richard Bergman

2010-01-01

The discussion in this chapter is concerned with moisture content determination, recommended moisture content values, drying methods, methods of calculating dimensional changes, design factors affecting such changes in structures, and moisture content control during transit, storage, and construction. Data on green moisture content, fiber saturation point, shrinkage,...

Predicting future changes in Muskegon River Watershed game fish distributions under future land cover alteration and climate change scenarios

Science.gov (United States)

Steen, Paul J.; Wiley, Michael J.; Schaeffer, Jeffrey S.

2010-01-01

Future alterations in land cover and climate are likely to cause substantial changes in the ranges of fish species. Predictive distribution models are an important tool for assessing the probability that these changes will cause increases or decreases in or the extirpation of species. Classification tree models that predict the probability of game fish presence were applied to the streams of the Muskegon River watershed, Michigan. The models were used to study three potential future scenarios: (1) land cover change only, (2) land cover change and a 3°C increase in air temperature by 2100, and (3) land cover change and a 5°C increase in air temperature by 2100. The analysis indicated that the expected change in air temperature and subsequent change in water temperatures would result in the decline of coldwater fish in the Muskegon watershed by the end of the 21st century while cool- and warmwater species would significantly increase their ranges. The greatest decline detected was a 90% reduction in the probability that brook trout Salvelinus fontinalis would occur in Bigelow Creek. The greatest increase was a 276% increase in the probability that northern pike Esox lucius would occur in the Middle Branch River. Changes in land cover are expected to cause large changes in a few fish species, such as walleye Sander vitreus and Chinook salmon Oncorhynchus tshawytscha, but not to drive major changes in species composition. Managers can alter stream environmental conditions to maximize the probability that species will reside in particular stream reaches through application of the classification tree models. Such models represent a good way to predict future changes, as they give quantitative estimates of the n-dimensional niches for particular species.

Dimensional changes of alginate impression by using perforated and non-perforated ring trays

Directory of Open Access Journals (Sweden)

Sumadhi Sastrodihardjo

2010-03-01

Full Text Available Dimensional changes are a common occurrence in impressions, either during or after impression taking. It produces a difference in the dimensions of the object and the model, which leads to the restoration being ill-fitted. Several causal factors have been proposed such as friction between the impression material and the teeth, the bulk of the impression material, the type of impression materials used, the impression technique, the pouring time and many others. The exact causal factor is still unknown and the dimensional change mechanism is still poorly understood. The objective of this research was to investigate the role of the perforation on the ring trays in producing dimensional changes in the impression by using perforated and non-perforated ring trays. Alginate impressions were made on the frustum of cone metal master die with a 7.08 mm base diameter, 7.03 mm top diameter and 9.23 mm height using perforated and non-perforated ring trays with 9.40 mm in diameter and 14.17 mm in height. The dimensional change was determined by comparing the dimension of the dental stone die and its metal master die. The results showed that the percentage of dimensional changes that occurred by using perforated ring tray were (+ 0.56±0.40 on the top area, (- 3.54±2.92 on base area and (+ 1.54±0.83 in height, respectively. As compared to using non-perforated ring trays, the percentage of dimensional changes that occurred were (- 0.49±0.49 on top area, (- 8.76±3.95 on base area and (+ 1.19±0.71 in height, respectively. There was a significant difference in the direction of the dimensional changes on both the top areas, but not in the base areas and height.

Predicting the bounds of large chaotic systems using low-dimensional manifolds.

Directory of Open Access Journals (Sweden)

Asger M Haugaard

Full Text Available Predicting extrema of chaotic systems in high-dimensional phase space remains a challenge. Methods, which give extrema that are valid in the long term, have thus far been restricted to models of only a few variables. Here, a method is presented which treats extrema of chaotic systems as belonging to discretised manifolds of low dimension (low-D embedded in high-dimensional (high-D phase space. As a central feature, the method exploits that strange attractor dimension is generally much smaller than parent system phase space dimension. This is important, since the computational cost associated with discretised manifolds depends exponentially on their dimension. Thus, systems that would otherwise be associated with tremendous computational challenges, can be tackled on a laptop. As a test, bounding manifolds are calculated for high-D modifications of the canonical Duffing system. Parameters can be set such that the bounding manifold displays harmonic behaviour even if the underlying system is chaotic. Thus, solving for one post-transient forcing cycle of the bounding manifold predicts the extrema of the underlying chaotic problem indefinitely.

A phase change processor method for solving a one-dimensional phase change problem with convection boundary

Energy Technology Data Exchange (ETDEWEB)

Halawa, E.; Saman, W.; Bruno, F. [Institute for Sustainable Systems and Technologies, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes SA 5095 (Australia)

2010-08-15

A simple yet accurate iterative method for solving a one-dimensional phase change problem with convection boundary is described. The one-dimensional model takes into account the variation in the wall temperature along the direction of the flow as well as the sensible heat during preheating/pre-cooling of the phase change material (PCM). The mathematical derivation of convective boundary conditions has been integrated into a phase change processor (PCP) algorithm that solves the liquid fraction and temperature of the nodes. The algorithm is based on the heat balance at each node as it undergoes heating or cooling which inevitably involves phase change. The paper presents the model and its experimental validation. (author)

Clinical Prediction Performance of Glaucoma Progression Using a 2-Dimensional Continuous-Time Hidden Markov Model with Structural and Functional Measurements.

Science.gov (United States)

Song, Youngseok; Ishikawa, Hiroshi; Wu, Mengfei; Liu, Yu-Ying; Lucy, Katie A; Lavinsky, Fabio; Liu, Mengling; Wollstein, Gadi; Schuman, Joel S

2018-03-20

Previously, we introduced a state-based 2-dimensional continuous-time hidden Markov model (2D CT HMM) to model the pattern of detected glaucoma changes using structural and functional information simultaneously. The purpose of this study was to evaluate the detected glaucoma change prediction performance of the model in a real clinical setting using a retrospective longitudinal dataset. Longitudinal, retrospective study. One hundred thirty-four eyes from 134 participants diagnosed with glaucoma or as glaucoma suspects (average follow-up, 4.4±1.2 years; average number of visits, 7.1±1.8). A 2D CT HMM model was trained using OCT (Cirrus HD-OCT; Zeiss, Dublin, CA) average circumpapillary retinal nerve fiber layer (cRNFL) thickness and visual field index (VFI) or mean deviation (MD; Humphrey Field Analyzer; Zeiss). The model was trained using a subset of the data (107 of 134 eyes [80%]) including all visits except for the last visit, which was used to test the prediction performance (training set). Additionally, the remaining 27 eyes were used for secondary performance testing as an independent group (validation set). The 2D CT HMM predicts 1 of 4 possible detected state changes based on 1 input state. Prediction accuracy was assessed as the percentage of correct prediction against the patient's actual recorded state. In addition, deviations of the predicted long-term detected change paths from the actual detected change paths were measured. Baseline mean ± standard deviation age was 61.9±11.4 years, VFI was 90.7±17.4, MD was -3.50±6.04 dB, and cRNFL thickness was 74.9±12.2 μm. The accuracy of detected glaucoma change prediction using the training set was comparable with the validation set (57.0% and 68.0%, respectively). Prediction deviation from the actual detected change path showed stability throughout patient follow-up. The 2D CT HMM demonstrated promising prediction performance in detecting glaucoma change performance in a simulated clinical setting

Numerical prediction of augmented turbulent heat transfer in an annular fuel channel with repeated two-dimensional square ribs

International Nuclear Information System (INIS)

Takase, K.

1996-01-01

The square-ribbed fuel rod for high temperature gas-cooled reactors was designed and developed so as to enhance the turbulent heat transfer in comparison with the previous standard fuel rod. The turbulent heat transfer characteristics in an annular fuel channel with repeated two-dimensional square ribs were analysed numerically on a fully developed incompressible flow using the k-ε turbulence model and the two-dimensional axisymmetrical coordinate system. Numerical analyses were carried out under the conditions of Reynolds numbers from 3000 to 20000 and ratios of square-rib pitch to height of 10, 20 and 40 respectively. The predictions of the heat transfer coefficients agreed well within an error of 10% for the square-rib pitch to height ratio of 10, 20% for 20 and 25% for 40 respectively, with the heat transfer empirical correlations obtained from the experimental data due to the simulated square-ribbed fuel rods. Therefore it was found that the effect of heat transfer augmentation due to the square ribs could be predicted by the present numerical simulations and the mechanism could be explained by the change in the turbulence kinematic energy distribution along the flow direction. (orig.)

Reduced-order prediction of rogue waves in two-dimensional deep-water waves

Science.gov (United States)

Sapsis, Themistoklis; Farazmand, Mohammad

2017-11-01

We consider the problem of large wave prediction in two-dimensional water waves. Such waves form due to the synergistic effect of dispersive mixing of smaller wave groups and the action of localized nonlinear wave interactions that leads to focusing. Instead of a direct simulation approach, we rely on the decomposition of the wave field into a discrete set of localized wave groups with optimal length scales and amplitudes. Due to the short-term character of the prediction, these wave groups do not interact and therefore their dynamics can be characterized individually. Using direct numerical simulations of the governing envelope equations we precompute the expected maximum elevation for each of those wave groups. The combination of the wave field decomposition algorithm, which provides information about the statistics of the system, and the precomputed map for the expected wave group elevation, which encodes dynamical information, allows (i) for understanding of how the probability of occurrence of rogue waves changes as the spectrum parameters vary, (ii) the computation of a critical length scale characterizing wave groups with high probability of evolving to rogue waves, and (iii) the formulation of a robust and parsimonious reduced-order prediction scheme for large waves. T.S. has been supported through the ONR Grants N00014-14-1-0520 and N00014-15-1-2381 and the AFOSR Grant FA9550-16-1-0231. M.F. has been supported through the second Grant.

Numerical prediction of turbulent heat transfer augmentation in an annular fuel channel with two-dimensional square ribs

International Nuclear Information System (INIS)

Takase, Kazuyuki

1996-01-01

The square-ribbed fuel rod for high temperature gas-cooled reactors was developed in order to enhance the turbulent heat transfer in comparison with the standard fuel rod. To evaluate the heat transfer performance of the square-ribbed fuel rod, the turbulent heat transfer coefficients in an annular fuel channel with repeated two-dimensional square ribs were analyzed numerically on a fully developed incompressible flow using the k - ε turbulence model and the two-dimensional axisymmetrical coordinate system. Numerical analyses were carried out for a range of Reynolds numbers from 3000 to 20000 and ratios of square-rib pitch to height of 10, 20 and 40, respectively. The predicted values of the heat transfer coefficients agreed within an error of 10% for the square-rib pitch to height ratio of 10, 20% for 20 and 25% for 40, respectively, with the heat transfer empirical correlations obtained from the experimental data. It was concluded by the present study that the effect of the heat transfer augmentation by square ribs could be predicted sufficiently by the present numerical simulations and also a part of its mechanism could be explained by means of the change in the turbulence kinematic energy distribution along the flow direction. (author)

A three-dimensional relaxation model for calculation of atomic mixing and topography changes induces by ion beams

International Nuclear Information System (INIS)

Collins, R.; Perez-Martin, A.M.C.; Dominguez-Vazquez, J.; Jimenez-Rodriguez, J.J.

1994-01-01

A simple model for three-dimensional material relaxation associated with atomic mixing is presented. The relaxation of the solid to accommodate the extra effective displacement volume Ω of an implanted or relocated atom is modelled by treating the surrounding solid as an incompressible medium. This leads to a tractable general formalism which can be used to predict implant distribution and changes in surface topography induced by ion beams, both in monatomic and multicomponent targets. The two-component case is discussed in detail. (orig.)

Predicting persuasion-induced behavior change from the brain.

Science.gov (United States)

Falk, Emily B; Berkman, Elliot T; Mann, Traci; Harrison, Brittany; Lieberman, Matthew D

2010-06-23

Although persuasive messages often alter people's self-reported attitudes and intentions to perform behaviors, these self-reports do not necessarily predict behavior change. We demonstrate that neural responses to persuasive messages can predict variability in behavior change in the subsequent week. Specifically, an a priori region of interest (ROI) in medial prefrontal cortex (MPFC) was reliably associated with behavior change (r = 0.49, p change beyond the variance predicted by self-reported attitudes and intentions. Thus, neural signals can predict behavioral changes that are not predicted from self-reported attitudes and intentions alone. Additionally, this is the first functional magnetic resonance imaging study to demonstrate that a neural signal can predict complex real world behavior days in advance.

Editorial Commentary: Single-Image Slice Magnetic Resonance Imaging Assessments Do Not Predict 3-Dimensional Muscle Volume.

Science.gov (United States)

Brand, Jefferson C

2016-01-01

No single-image magnetic resonance imaging (MRI) assessment-Goutallier classification, Fuchs classification, or cross-sectional area-is predictive of whole-muscle volume or fatty atrophy of the supraspinatus or infraspinatus. Rather, 3-dimensional MRI measurement of whole-muscle volume and fat-free muscle volume is required and is associated with shoulder strength, which is clinically relevant. Three-dimensional MRI may represent a new gold standard for assessment of the rotator cuff musculature using imaging and may help to predict the feasibility of repair of a rotator cuff tear as well as the postoperative outcome. Unfortunately, 3-dimensional MRI assessment of muscle volume is labor intensive and is not widely available for clinical use. Copyright © 2016 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Predicting transition in two- and three-dimensional separated flows

International Nuclear Information System (INIS)

Cutrone, L.; De Palma, P.; Pascazio, G.; Napolitano, M.

2008-01-01

This paper is concerned with the numerical prediction of two- and three-dimensional transitional separated flows of turbomachinery interest. The recently proposed single-point transition model based on the use of a laminar kinetic energy transport equation is considered, insofar as it does not require to evaluate any integral parameter, such as boundary-layer thickness, and is thus directly applicable to three-dimensional flows. A well established model, combining a transition-onset correlation with an intermittency transport equation, is also used for comparison. Both models are implemented within a Reynolds-averaged Navier-Stokes solver employing a low-Reynolds-number k-ω turbulence model. The performance of the transition models have been evaluated and tested versus well-documented incompressible flows past a flat plate with semi-circular leading edge, namely: tests T3L2, T3L3, T3L5, and T3LA1 of ERCOFTAC, with different Reynolds numbers and free-stream conditions, the last one being characterized by a non-zero pressure gradient. In all computations, the first model has proven as adequate as or superior to the second one and has been then applied with success to two more complex test cases, for which detailed experimental data are available in the literature, namely: the two- and three-dimensional flows through the T106 linear turbine cascade

Three-dimensional transient cooling simulations of a portable electronic device using PCM (phase change materials) in multi-fin heat sink

International Nuclear Information System (INIS)

Wang, Yi-Hsien; Yang, Yue-Tzu

2011-01-01

Transient three-dimensional heat transfer numerical simulations were conducted to investigate a hybrid PCM (phase change materials) based multi-fin heat sink. Numerical computation was conducted with different amounts of fins (0 fin, 3 fins and 6 fins), various heating power level (2 W, 3 W and 4 W), different orientation tests (vertical/horizontal/slanted), and charge and discharge modes. Calculating time step (0.03 s, 0.05 s, and 0.07 s) size was discussed for transient accuracy as well. The theoretical model developed is validated by comparing numerical predictions with the available experimental data in the literature. The results showed that the transient surface temperatures are predicted with a maximum discrepancy within 10.2%. The operation temperature can be controlled well by the attendance of phase change material and the longer melting time can be conducted by using a multi-fin hybrid heat sink respectively. -- Highlights: → Electronic device cooling use phase change materials. → N-eicosane is adapted as phase change materials. → Present surface transient temperatures prediction error is within 10.2%. → Hybrid PCM-heat sink system provides stable operation temperature. → Orientation effects show independent on the phase change performance.

Performance of a process-based hydrodynamic model in predicting shoreline change

Science.gov (United States)

Safak, I.; Warner, J. C.; List, J. H.

2012-12-01

Shoreline change is controlled by a complex combination of processes that include waves, currents, sediment characteristics and availability, geologic framework, human interventions, and sea level rise. A comprehensive data set of shoreline position (14 shorelines between 1978-2002) along the continuous and relatively non-interrupted North Carolina Coast from Oregon Inlet to Cape Hatteras (65 km) reveals a spatial pattern of alternating erosion and accretion, with an erosional average shoreline change rate of -1.6 m/yr and up to -8 m/yr in some locations. This data set gives a unique opportunity to study long-term shoreline change in an area hit by frequent storm events while relatively uninfluenced by human interventions and the effects of tidal inlets. Accurate predictions of long-term shoreline change may require a model that accurately resolves surf zone processes and sediment transport patterns. Conventional methods for predicting shoreline change such as one-line models and regression of shoreline positions have been designed for computational efficiency. These methods, however, not only have several underlying restrictions (validity for small angle of wave approach, assuming bottom contours and shoreline to be parallel, depth of closure, etc.) but also their empirical estimates of sediment transport rates in the surf zone have been shown to vary greatly from the calculations of process-based hydrodynamic models. We focus on hind-casting long-term shoreline change using components of the process-based, three-dimensional coupled-ocean-atmosphere-wave-sediment transport modeling system (COAWST). COAWST is forced with historical predictions of atmospheric and oceanographic data from public-domain global models. Through a method of coupled concurrent grid-refinement approach in COAWST, the finest grid with resolution of O(10 m) that covers the surf zone along the section of interest is forced at its spatial boundaries with waves and currents computed on the grids

Verification of a 1-dimensional model for predicting shallow infiltration at Yucca Mountain

International Nuclear Information System (INIS)

Hevesi, J.A.; Flint, A.L.; Flint, L.E.

1994-01-01

A characterization of net infiltration rates is needed for site-scale evaluation of groundwater flow at Yucca Mountain, Nevada. Shallow infiltration caused by precipitation may be a potential source of net infiltration. A 1-dimensional finite difference model of shallow infiltration with a moisture-dependant evapotranspiration function and a hypothetical root-zone was calibrated and verified using measured water content profiles, measured precipitation, and estimated potential evapotranspiration. Monthly water content profiles obtained from January 1990 through October 1993 were measured by geophysical logging of 3 boreholes located in the alluvium channel of Pagany Wash on Yucca Mountain. The profiles indicated seasonal wetting and drying of the alluvium in response to winter season precipitation and summer season evapotranspiration above a depth of 2.5 meters. A gradual drying trend below a depth of 2.5 meters was interpreted as long-term redistribution and/or evapotranspiration following a deep infiltration event caused by runoff in Pagany Wash during 1984. An initial model, calibrated using the 1990 to 1 992 record, did not provide a satisfactory prediction of water content profiles measured in 1993 following a relatively wet winter season. A re-calibrated model using a modified, seasonally-dependent evapotranspiration function provided an improved fit to the total record. The new model provided a satisfactory verification using water content changes measured at a distance of 6 meters from the calibration site, but was less satisfactory in predicting changes at a distance of 18 meters

Verification of a 1-dimensional model for predicting shallow infiltration at Yucca Mountain

International Nuclear Information System (INIS)

Hevesi, J.; Flint, A.L.; Flint, L.E.

1994-01-01

A characterization of net infiltration rates is needed for site-scale evaluation of groundwater flow at Yucca Mountain, Nevada. Shallow infiltration caused by precipitation may be a potential source of net infiltration. A 1-dimensional finite difference model of shallow infiltration with a moisture-dependent evapotranspiration function and a hypothetical root-zone was calibrated and verified using measured water content profiles, measured precipitation, and estimated potential evapotranspiration. Monthly water content profiles obtained from January 1990 through October 1993 were measured by geophysical logging of 3 boreholes located in the alluvium channel of Pagany Wash on Yucca Mountain. The profiles indicated seasonal wetting and drying of the alluvium in response to winter season precipitation and summer season evapotranspiration above a depth of 2.5 meters. A gradual drying trend below a depth of 2.5 meters was interpreted as long-term redistribution and/or evapotranspiration following a deep infiltration event caused by runoff in Pagany Wash during 1984. An initial model, calibrated using the 1990 to 1992 record, did not provide a satisfactory prediction of water content profiles measured in 1993 following a relatively wet winter season. A re-calibrated model using a modified, seasonally-dependent evapotranspiration function provided an improved fit to the total record. The new model provided a satisfactory verification using water content changes measured at a distance of 6 meters from the calibration site, but was less satisfactory in predicting changes at a distance of 18 meters

Three-dimensional protein structure prediction: Methods and computational strategies.

Science.gov (United States)

Dorn, Márcio; E Silva, Mariel Barbachan; Buriol, Luciana S; Lamb, Luis C

2014-10-12

A long standing problem in structural bioinformatics is to determine the three-dimensional (3-D) structure of a protein when only a sequence of amino acid residues is given. Many computational methodologies and algorithms have been proposed as a solution to the 3-D Protein Structure Prediction (3-D-PSP) problem. These methods can be divided in four main classes: (a) first principle methods without database information; (b) first principle methods with database information; (c) fold recognition and threading methods; and (d) comparative modeling methods and sequence alignment strategies. Deterministic computational techniques, optimization techniques, data mining and machine learning approaches are typically used in the construction of computational solutions for the PSP problem. Our main goal with this work is to review the methods and computational strategies that are currently used in 3-D protein prediction. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting Persuasion-Induced Behavior Change from the Brain

Science.gov (United States)

Falk, Emily B.; Berkman, Elliot T.; Mann, Traci; Harrison, Brittany; Lieberman, Matthew D.

2011-01-01

Although persuasive messages often alter people’s self-reported attitudes and intentions to perform behaviors, these self-reports do not necessarily predict behavior change. We demonstrate that neural responses to persuasive messages can predict variability in behavior change in the subsequent week. Specifically, an a priori region of interest (ROI) in medial prefrontal cortex (MPFC) was reliably associated with behavior change (r = 0.49, p < 0.05). Additionally, an iterative cross-validation approach using activity in this MPFC ROI predicted an average 23% of the variance in behavior change beyond the variance predicted by self-reported attitudes and intentions. Thus, neural signals can predict behavioral changes that are not predicted from self-reported attitudes and intentions alone. Additionally, this is the first functional magnetic resonance imaging study to demonstrate that a neural signal can predict complex real world behavior days in advance. PMID:20573889

Revealing skill of the MiKlip decadal prediction system by three-dimensional probabilistic evaluation

Directory of Open Access Journals (Sweden)

Sophie Stolzenberger

2016-12-01

Full Text Available Decadal climate predictions and their verification are part of ongoing research. This article studies different methods applied to decadal hindcasts of three-dimensional atmospheric variables to evaluate the MiKlip (Mittelfristige Klimaprognosen prediction system. Variables such as upper air temperature are tight to the core of the prediction system and hence help to reveal its power and deficiencies. The verification uses both, necessary and sufficient probabilistic measures. We analyze annual and multi-year averages of air temperature and geopotential height and the parametrized quantity net water flux at the ocean surface, the so-called freshwater flux, also known as E‑P (evaporation minus precipitation, as an important variable for atmosphere-ocean coupling. The model data stem from various versions of the MiKlip prediction system and constitute different sets of ensemble hindcasts covering 1979–2012. The results reveal that the freshwater flux is far more sensitive to model deficiencies than the basic dynamical variables and the predictability decays much earlier with prediction lead time. Initializing the atmospheric component is more important for the predictability than the difference in resolution between two model versions. The combined initialization of atmosphere and ocean has the effect of increasing the predictability in the inner tropics from 1 to 2 years compared to the ocean only initialization. For prediction year 7–10, the hindcasts are still closer to each other than to the uninitialized historical runs indicating that the prediction system is still influenced by the initial conditions. The skill for prediction year 7–10 is, however, only marginally larger than the skill of the uninitialized ensemble. The three-dimensional skill analysis reveals a clear indication of a mid-tropospheric temperature error developing in the tropical Pacific area.

Analytical approach for predicting three-dimensional tire-pavement contact load

CSIR Research Space (South Africa)

Hernandez, JA

2014-12-01

Full Text Available stream_source_info De Beer1_2014.pdf.txt stream_content_type text/plain stream_size 38657 Content-Encoding UTF-8 stream_name De Beer1_2014.pdf.txt Content-Type text/plain; charset=UTF-8 75 Transportation Research Record... by measuring the applied forces in each perpendicular direction (15). Analytical Approach for Predicting Three-Dimensional Tire–Pavement Contact Load Jaime A. Hernandez, Angeli Gamez, Imad L. Al-Qadi, and Morris De Beer J. A. Hernandez, A. Gamez, and I. L...

Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

Science.gov (United States)

Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

2015-04-01

This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

Three-dimensional computed tomographic volumetry precisely predicts the postoperative pulmonary function.

Science.gov (United States)

Kobayashi, Keisuke; Saeki, Yusuke; Kitazawa, Shinsuke; Kobayashi, Naohiro; Kikuchi, Shinji; Goto, Yukinobu; Sakai, Mitsuaki; Sato, Yukio

2017-11-01

It is important to accurately predict the patient's postoperative pulmonary function. The aim of this study was to compare the accuracy of predictions of the postoperative residual pulmonary function obtained with three-dimensional computed tomographic (3D-CT) volumetry with that of predictions obtained with the conventional segment-counting method. Fifty-three patients scheduled to undergo lung cancer resection, pulmonary function tests, and computed tomography were enrolled in this study. The postoperative residual pulmonary function was predicted based on the segment-counting and 3D-CT volumetry methods. The predicted postoperative values were compared with the results of postoperative pulmonary function tests. Regarding the linear correlation coefficients between the predicted postoperative values and the measured values, those obtained using the 3D-CT volumetry method tended to be higher than those acquired using the segment-counting method. In addition, the variations between the predicted and measured values were smaller with the 3D-CT volumetry method than with the segment-counting method. These results were more obvious in COPD patients than in non-COPD patients. Our findings suggested that the 3D-CT volumetry was able to predict the residual pulmonary function more accurately than the segment-counting method, especially in patients with COPD. This method might lead to the selection of appropriate candidates for surgery among patients with a marginal pulmonary function.

Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression

International Nuclear Information System (INIS)

Riaz, Nadeem; Wiersma, Rodney; Mao Weihua; Xing Lei; Shanker, Piyush; Gudmundsson, Olafur; Widrow, Bernard

2009-01-01

Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

Climate Change as a Predictable Surprise

International Nuclear Information System (INIS)

Bazerman, M.H.

2006-01-01

In this article, I analyze climate change as a 'predictable surprise', an event that leads an organization or nation to react with surprise, despite the fact that the information necessary to anticipate the event and its consequences was available (Bazerman and Watkins, 2004). I then assess the cognitive, organizational, and political reasons why society fails to implement wise strategies to prevent predictable surprises generally and climate change specifically. Finally, I conclude with an outline of a set of response strategies to overcome barriers to change

AucPR: an AUC-based approach using penalized regression for disease prediction with high-dimensional omics data.

Science.gov (United States)

Yu, Wenbao; Park, Taesung

2014-01-01

It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on the area under the receiver operating characteristic curve (AUC) have been proposed. Existing works based on AUC in a high-dimensional context depend mainly on a non-parametric, smooth approximation of AUC, with no work using a parametric AUC-based approach, for high-dimensional data. We propose an AUC-based approach using penalized regression (AucPR), which is a parametric method used for obtaining a linear combination for maximizing the AUC. To obtain the AUC maximizer in a high-dimensional context, we transform a classical parametric AUC maximizer, which is used in a low-dimensional context, into a regression framework and thus, apply the penalization regression approach directly. Two kinds of penalization, lasso and elastic net, are considered. The parametric approach can avoid some of the difficulties of a conventional non-parametric AUC-based approach, such as the lack of an appropriate concave objective function and a prudent choice of the smoothing parameter. We apply the proposed AucPR for gene selection and classification using four real microarray and synthetic data. Through numerical studies, AucPR is shown to perform better than the penalized logistic regression and the nonparametric AUC-based method, in the sense of AUC and sensitivity for a given specificity, particularly when there are many correlated genes. We propose a powerful parametric and easily-implementable linear classifier AucPR, for gene selection and disease prediction for high-dimensional data. AucPR is recommended for its good prediction performance. Beside gene expression microarray data, AucPR can be applied to other types of high-dimensional omics data, such as miRNA and protein data.

Reconstruction 3-dimensional image from 2-dimensional image of status optical coherence tomography (OCT) for analysis of changes in retinal thickness

Energy Technology Data Exchange (ETDEWEB)

Arinilhaq,; Widita, Rena [Department of Physics, Nuclear Physics and Biophysics Research Group, Institut Teknologi Bandung (Indonesia)

2014-09-30

Optical Coherence Tomography is often used in medical image acquisition to diagnose that change due easy to use and low price. Unfortunately, this type of examination produces a two-dimensional retinal image of the point of acquisition. Therefore, this study developed a method that combines and reconstruct 2-dimensional retinal images into three-dimensional images to display volumetric macular accurately. The system is built with three main stages: data acquisition, data extraction and 3-dimensional reconstruction. At data acquisition step, Optical Coherence Tomography produced six *.jpg images of each patient were further extracted with MATLAB 2010a software into six one-dimensional arrays. The six arrays are combined into a 3-dimensional matrix using a kriging interpolation method with SURFER9 resulting 3-dimensional graphics of macula. Finally, system provides three-dimensional color graphs based on the data distribution normal macula. The reconstruction system which has been designed produces three-dimensional images with size of 481 × 481 × h (retinal thickness) pixels.

Separation prediction in two dimensional boundary layer flows using artificial neural networks

International Nuclear Information System (INIS)

Sabetghadam, F.; Ghomi, H.A.

2003-01-01

In this article, the ability of artificial neural networks in prediction of separation in steady two dimensional boundary layer flows is studied. Data for network training is extracted from numerical solution of an ODE obtained from Von Karman integral equation with approximate one parameter Pohlhousen velocity profile. As an appropriate neural network, a two layer radial basis generalized regression artificial neural network is used. The results shows good agreements between the overall behavior of the flow fields predicted by the artificial neural network and the actual flow fields for some cases. The method easily can be extended to unsteady separation and turbulent as well as compressible boundary layer flows. (author)

Irradiation-induced dimensional changes of fuel compacts and graphite sleeves of OGL-1 fuel assemblies

International Nuclear Information System (INIS)

Hayashi, Kimio; Minato, Kazuo; Kobayashi, Fumiaki; Tobita, Tsutomu; Kikuchi, Teruo; Kurobane, Shiro; Adachi, Mamoru; Fukuda, Kousaku

1988-06-01

Experimental data are summarized on irradiation-induced dimensional changes of fuel compacts and graphite sleeves of the first to ninth OGL-1 fuel assemblies. The range of fast-neutron fluence is up to 4 x 10 24 n/m 2 (E > 0.18 MeV); and that of irradiation temperature is 900 - 1400 deg C for fuel compacts and 800 - 1050 deg C for graphite sleeves. The dimensional change of the fuel compacts was shrinkage under these test conditions, and the shrinkage fraction increased almost linearly with fast-neutron fluence. The shrinkage fraction of the fuel compacts was larger by 20 % in the axial direction than in the radial direction. Influence of the irradiation temperature on the dimensional-change behavior of the fuel compacts was not observed clearly; presumably the influence was hidden by scatter of the data because of low level of the fast-neutron fluence and the resultant small dimensional changes. (author)

Are abrupt climate changes predictable?

Science.gov (United States)

Ditlevsen, Peter

2013-04-01

It is taken for granted that the limited predictability in the initial value problem, the weather prediction, and the predictability of the statistics are two distinct problems. Lorenz (1975) dubbed this predictability of the first and the second kind respectively. Predictability of the first kind in a chaotic dynamical system is limited due to the well-known critical dependence on initial conditions. Predictability of the second kind is possible in an ergodic system, where either the dynamics is known and the phase space attractor can be characterized by simulation or the system can be observed for such long times that the statistics can be obtained from temporal averaging, assuming that the attractor does not change in time. For the climate system the distinction between predictability of the first and the second kind is fuzzy. This difficulty in distinction between predictability of the first and of the second kind is related to the lack of scale separation between fast and slow components of the climate system. The non-linear nature of the problem furthermore opens the possibility of multiple attractors, or multiple quasi-steady states. As the ice-core records show, the climate has been jumping between different quasi-stationary climates, stadials and interstadials through the Dansgaard-Oechger events. Such a jump happens very fast when a critical tipping point has been reached. The question is: Can such a tipping point be predicted? This is a new kind of predictability: the third kind. If the tipping point is reached through a bifurcation, where the stability of the system is governed by some control parameter, changing in a predictable way to a critical value, the tipping is predictable. If the sudden jump occurs because internal chaotic fluctuations, noise, push the system across a barrier, the tipping is as unpredictable as the triggering noise. In order to hint at an answer to this question, a careful analysis of the high temporal resolution NGRIP isotope

Prediction of DVH parameter changes due to setup errors for breast cancer treatment based on 2D portal dosimetry

International Nuclear Information System (INIS)

Nijsten, S. M. J. J. G.; Elmpt, W. J. C. van; Mijnheer, B. J.; Minken, A. W. H.; Persoon, L. C. G. G.; Lambin, P.; Dekker, A. L. A. J.

2009-01-01

Electronic portal imaging devices (EPIDs) are increasingly used for portal dosimetry applications. In our department, EPIDs are clinically used for two-dimensional (2D) transit dosimetry. Predicted and measured portal dose images are compared to detect dose delivery errors caused for instance by setup errors or organ motion. The aim of this work is to develop a model to predict dose-volume histogram (DVH) changes due to setup errors during breast cancer treatment using 2D transit dosimetry. First, correlations between DVH parameter changes and 2D gamma parameters are investigated for different simulated setup errors, which are described by a binomial logistic regression model. The model calculates the probability that a DVH parameter changes more than a specific tolerance level and uses several gamma evaluation parameters for the planning target volume (PTV) projection in the EPID plane as input. Second, the predictive model is applied to clinically measured portal images. Predicted DVH parameter changes are compared to calculated DVH parameter changes using the measured setup error resulting from a dosimetric registration procedure. Statistical accuracy is investigated by using receiver operating characteristic (ROC) curves and values for the area under the curve (AUC), sensitivity, specificity, positive and negative predictive values. Changes in the mean PTV dose larger than 5%, and changes in V 90 and V 95 larger than 10% are accurately predicted based on a set of 2D gamma parameters. Most pronounced changes in the three DVH parameters are found for setup errors in the lateral-medial direction. AUC, sensitivity, specificity, and negative predictive values were between 85% and 100% while the positive predictive values were lower but still higher than 54%. Clinical predictive value is decreased due to the occurrence of patient rotations or breast deformations during treatment, but the overall reliability of the predictive model remains high. Based on our

Study of dimensional changes during redox cycling of oxygen carrier materials for chemical looping combustion

NARCIS (Netherlands)

Fossdal, A.; Darell, O.; Lambert, A.; Schols, E.; Comte, E.; Leenman, R.N.; Blom, R.

2015-01-01

Dimensional and phase changes of four candidate oxygen carrier materials for chemical looping combustion are investigated by dilatometry and high-temperature X-ray diffraction during four redox cycles. NiO/Ni2AlO4 does not exhibit significant dimensional changes during cycling, and it is shown that

Are Some Semantic Changes Predictable?

DEFF Research Database (Denmark)

Schousboe, Steen

2010-01-01

  Historical linguistics is traditionally concerned with phonology and syntax. With the exception of grammaticalization - the development of auxiliary verbs, the syntactic rather than localistic use of prepositions, etc. - semantic change has usually not been described as a result of regular...... developments, but only as specific meaning changes in individual words. This paper will suggest some regularities in semantic change, regularities which, like sound laws, have predictive power and can be tested against recorded languages....

Maximal locality and predictive power in higher-dimensional, compactified field theories

International Nuclear Information System (INIS)

Kubo, Jisuke; Nunami, Masanori

2004-01-01

To realize maximal locality in a trivial field theory, we maximize the ultraviolet cutoff of the theory by fine tuning the infrared values of the parameters. This optimization procedure is applied to the scalar theory in D + 1 dimensional (D ≥ 4) with one extra dimension compactified on a circle of radius R. The optimized, infrared values of the parameters are then compared with the corresponding ones of the uncompactified theory in D dimensions, which is assumed to be the low-energy effective theory. We find that these values approximately agree with each other as long as R -1 > approx sM is satisfied, where s ≅ 10, 50, 50, 100 for D = 4,5,6,7, and M is a typical scale of the D-dimensional theory. This result supports the previously made claim that the maximization of the ultraviolet cutoff in a nonrenormalizable field theory can give the theory more predictive power. (author)

Effect of immersion disinfection of alginate impressions in sodium hypochlorite solution on the dimensional changes of stone models.

Science.gov (United States)

Hiraguchi, Hisako; Kaketani, Masahiro; Hirose, Hideharu; Yoneyama, Takayuki

2012-01-01

This study investigated the effect of the immersion of alginate impressions in 0.5% sodium hypochlorite solution for 15 min on the dimensional changes of stone models designed to simulate a sectional form of a residual ridge. Five brands of alginate impression materials, which underwent various dimensional changes in water, were used. A stone model made with an impression that had not been immersed was prepared as a control. The immersion of two brands of alginate impressions that underwent small dimensional changes in water did not lead to serious deformation of the stone models, and the differences in the dimensional changes between the stone models produced with disinfected impressions and those of the control were less than 15 µm. In contrast, the immersions of three brands of alginate impressions that underwent comparatively large dimensional changes in water caused deformation of the stone models.

The validation and assessment of machine learning: a game of prediction from high-dimensional data

DEFF Research Database (Denmark)

Pers, Tune Hannes; Albrechtsen, A; Holst, C

2009-01-01

In applied statistics, tools from machine learning are popular for analyzing complex and high-dimensional data. However, few theoretical results are available that could guide to the appropriate machine learning tool in a new application. Initial development of an overall strategy thus often...... the ideas, the game is applied to data from the Nugenob Study where the aim is to predict the fat oxidation capacity based on conventional factors and high-dimensional metabolomics data. Three players have chosen to use support vector machines, LASSO, and random forests, respectively....

Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression.

Science.gov (United States)

Kim, Soyeon; Baladandayuthapani, Veerabhadran; Lee, J Jack

2017-06-01

In personalized medicine, biomarkers are used to select therapies with the highest likelihood of success based on an individual patient's biomarker/genomic profile. Two goals are to choose important biomarkers that accurately predict treatment outcomes and to cull unimportant biomarkers to reduce the cost of biological and clinical verifications. These goals are challenging due to the high dimensionality of genomic data. Variable selection methods based on penalized regression (e.g., the lasso and elastic net) have yielded promising results. However, selecting the right amount of penalization is critical to simultaneously achieving these two goals. Standard approaches based on cross-validation (CV) typically provide high prediction accuracy with high true positive rates but at the cost of too many false positives. Alternatively, stability selection (SS) controls the number of false positives, but at the cost of yielding too few true positives. To circumvent these issues, we propose prediction-oriented marker selection (PROMISE), which combines SS with CV to conflate the advantages of both methods. Our application of PROMISE with the lasso and elastic net in data analysis shows that, compared to CV, PROMISE produces sparse solutions, few false positives, and small type I + type II error, and maintains good prediction accuracy, with a marginal decrease in the true positive rates. Compared to SS, PROMISE offers better prediction accuracy and true positive rates. In summary, PROMISE can be applied in many fields to select regularization parameters when the goals are to minimize false positives and maximize prediction accuracy.

Dimensional analysis and prediction of dielectrophoretic crossover frequency of spherical particles

Directory of Open Access Journals (Sweden)

Che-Kai Yeh

2017-06-01

Full Text Available The manipulation of biological cells and micrometer-scale particles using dielectrophoresis (DEP is an indispensable technique for lab-on-a-chip systems for many biological and colloidal science applications. However, existing models, including the dipole model and numerical simulations based on Maxwell stress tensor (MST, cannot achieve high accuracy and high computation efficiency at the same time. The dipole model is widely used and provides adequate predictions on the crossover frequency of submicron particles, but cannot predict the crossover frequency for larger particles accurately; on the other hand, the MST method offers high accuracy for a wide variety of particle sizes and shapes, but is time-consuming and may lack predictive understanding of the interplay between key parameters. Here we present a mathematical model, using dimensional analysis and the Buckingham pi theorem, that permits high accuracy and efficiency in predicting the crossover frequency of spherical particles. The curve fitting and calculation are performed using commercial packages OriginLab and MATLAB, respectively. In addition, through this model we also can predict the conditions in which no crossover frequency exists. Also, we propose a pair of dimensionless parameters, forming a functional relation, that provide physical insights into the dependency of the crossover frequency on five key parameters. The model is verified under several scenarios using comprehensive MST simulations by COMSOL Multiphysics software (COMSOL, Inc. and some published experimental data.

Dimensional Changes of Nb$_{3}$Sn Rutherford Cables During Heat Treatment

CERN Document Server

Rochepault, E; Ambrosio, G; Anerella, M; Ballarino, A; Bonasia, A; Bordini, B; Cheng, D; Dietderich, D R; Felice, H; Garcia Fajardo, L; Ghosh, A; Holik, E F; Izquierdo Bermudez, S; Perez, J C; Pong, I; Schmalzle, J; Yu, M

2016-01-01

In high field magnet applications, Nb$_{3}$Sn coils undergo a heat treatment step after winding. During this stage, coils radially expand and longitudinally contract due to the Nb$_{3}$Sn phase change. In order to prevent residual strain from altering superconducting performances, the tooling must provide the adequate space for these dimensional changes. The aim of this paper is to understand the behavior of cable dimensions during heat treatment and to provide estimates of the space to be accommodated in the tooling for coil expansion and contraction. This paper summarizes measurements of dimensional changes on strands, single Rutherford cables, cable stacks, and coils performed between 2013 and 2015. These samples and coils have been performed within a collaboration between CERN and the U.S. LHC Accelerator Research Program to develop Nb$_{3}$Sn quadrupole magnets for the HiLumi LHC. The results are also compared with other high field magnet projects.

High-order accurate numerical algorithm for three-dimensional transport prediction

Energy Technology Data Exchange (ETDEWEB)

Pepper, D W [Savannah River Lab., Aiken, SC; Baker, A J

1980-01-01

The numerical solution of the three-dimensional pollutant transport equation is obtained with the method of fractional steps; advection is solved by the method of moments and diffusion by cubic splines. Topography and variable mesh spacing are accounted for with coordinate transformations. First estimate wind fields are obtained by interpolation to grid points surrounding specific data locations. Numerical results agree with results obtained from analytical Gaussian plume relations for ideal conditions. The numerical model is used to simulate the transport of tritium released from the Savannah River Plant on 2 May 1974. Predicted ground level air concentration 56 km from the release point is within 38% of the experimentally measured value.

Three-dimensional evaluation of changes in lip position from before to after orthodontic appliance removal.

Science.gov (United States)

Eidson, Lindsey; Cevidanes, Lucia H S; de Paula, Leonardo Koerich; Hershey, H Garland; Welch, Gregory; Rossouw, P Emile

2012-09-01

Our objectives were to develop a reproducible method of superimposing 3-dimensional images for measuring soft-tissue changes over time and to use this method to document changes in lip position after the removal of orthodontic appliances. Three-dimensional photographs of 50 subjects were made in repose and maximum intercuspation before and after orthodontic appliance removal with a stereo camera. For reliability assessment, 2 photographs were repeated for 15 patients. The images were registered on stable areas, and surface-to-surface measurements were made for defined landmarks. Mean changes were below the level of clinical significance (set at 1.5 mm). However, 51% and 18% of the subjects experienced changes greater than 1.5 mm at the commissures and lower lips, respectively. The use of serial 3-dimensional photographs is a reliable method of documenting soft-tissue changes. Soft-tissue changes after appliance removal are not clinically significant; however, there is great individual variability. Copyright © 2012 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Predicting incentives to change among adolescents with substance abuse disorder.

Science.gov (United States)

Breda, Carolyn; Heflinger, Craig Anne

2004-05-01

While interest in understanding the incentives to change among individuals with substance abuse disorders is growing, little is known about incentives among adolescents with substance abuse disorders who are participating in formal services. The present research assesses the degree and nature of motivation and treatment readiness among adolescents admitted to substance abuse services, and whether such factors vary across significant subgroups of youth based on their social, legal, or clinical profiles. Data are based on interviews with 249 youth between 12 and 18 years of age who have been admitted to either inpatient, residential, or outpatient substance abuse treatment. Measures are adapted from an instrument developed to assess multiple domains of motivation to change (e.g., intrinsic and extrinsic motivation, treatment readiness). Results suggest that the incentive to change among adolescents with substance-abusing behavior is modest at best, regardless of dimension. Nonetheless, ethnicity, type of substance use, and psychopathology significantly predict incentives to change, though the predictors depend on which dimension is considered. The most robust predictor of incentives is the severity of negative consequences associated with youth's substance use--the greater the severity, the greater the incentives. Findings underscore the need to examine the utility and dimensionality of incentive for treatment planning, while at the same time, they identify factors that treatment planners can consider as they seek ways to enhance incentives and help adolescents with substance use disorders attain positive outcomes.

"You've Changed": Low Self-Concept Clarity Predicts Lack of Support for Partner Change.

Science.gov (United States)

Emery, Lydia F; Gardner, Wendi L; Finkel, Eli J; Carswell, Kathleen L

2018-03-01

People often pursue self-change, and having a romantic partner who supports these changes increases relationship satisfaction. However, most existing research focuses only on the experience of the person who is changing. What predicts whether people support their partner's change? People with low self-concept clarity resist self-change, so we hypothesized that they would be unsupportive of their partner's changes. People with low self-concept clarity did not support their partner's change (Study 1a), because they thought they would have to change, too (Study 1b). Low self-concept clarity predicted failing to support a partner's change, but not vice versa (Studies 2 and 3), and only for larger changes (Study 3). Not supporting a partner's change predicted decreases in relationship quality for both members of the couple (Studies 2 and 3). This research underscores the role of partners in self-change, suggesting that failing to support a partner's change may stem from self-concept confusion.

Global vegetation change predicted by the modified Budyko model

Energy Technology Data Exchange (ETDEWEB)

Monserud, R.A.; Tchebakova, N.M.; Leemans, R. (US Department of Agriculture, Moscow, ID (United States). Intermountain Research Station, Forest Service)

1993-09-01

A modified Budyko global vegetation model is used to predict changes in global vegetation patterns resulting from climate change (CO[sub 2] doubling). Vegetation patterns are predicted using a model based on a dryness index and potential evaporation determined by solving radiation balance equations. Climate change scenarios are derived from predictions from four General Circulation Models (GCM's) of the atmosphere (GFDL, GISS, OSU, and UKMO). All four GCM scenarios show similar trends in vegetation shifts and in areas that remain stable, although the UKMO scenario predicts greater warming than the others. Climate change maps produced by all four GCM scenarios show good agreement with the current climate vegetation map for the globe as a whole, although over half of the vegetation classes show only poor to fair agreement. The most stable areas are Desert and Ice/Polar Desert. Because most of the predicted warming is concentrated in the Boreal and Temperate zones, vegetation there is predicted to undergo the greatest change. Most vegetation classes in the Subtropics and Tropics are predicted to expand. Any shift in the Tropics favouring either Forest over Savanna, or vice versa, will be determined by the magnitude of the increased precipitation accompanying global warming. Although the model predicts equilibrium conditions to which many plant species cannot adjust (through migration or microevolution) in the 50-100 y needed for CO[sub 2] doubling, it is not clear if projected global warming will result in drastic or benign vegetation change. 72 refs., 3 figs., 3 tabs.

The IEA Annex 20 Two-Dimensional Benchmark Test for CFD Predictions

DEFF Research Database (Denmark)

Nielsen, Peter V.; Rong, Li; Cortes, Ines Olmedo

2010-01-01

predictions both for isothermal flow and for nonisothermal flow. The benchmark is defined on a web page, which also shows about 50 different benchmark tests with studies of e.g. grid dependence, numerical schemes, different source codes, different turbulence models, RANS or LES, different turbulence levels...... in a supply opening, study of local emission and study of airborne chemical reactions. Therefore the web page is also a collection of information which describes the importance of the different elements of a CFD procedure. The benchmark is originally developed for test of two-dimensional flow, but the paper...

AucPR: An AUC-based approach using penalized regression for disease prediction with high-dimensional omics data

OpenAIRE

Yu, Wenbao; Park, Taesung

2014-01-01

Motivation It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on the area under the receiver operating characteristic curve (AUC) have been proposed. Existing works based on AUC in a high-dimensional context depend mainly on a non-parametric, smooth approximation of AUC, with no work using a parametric AUC-based approach, for high-dimensional data. Results We propose an AUC-based approach u...

Validation of a zero-dimensional model for prediction of NOx and engine performance for electronically controlled marine two-stroke diesel engines

DEFF Research Database (Denmark)

Scappin, Fabio; Stefansson, Sigurður H.; Haglind, Fredrik

2012-01-01

The aim of this paper is to derive a methodology suitable for energy system analysis for predicting the performance and NOx emissions of marine low speed diesel engines. The paper describes a zero-dimensional model, evaluating the engine performance by means of an energy balance and a two zone...... experimental data from two MAN B&W engines; one case being data subject to engine parameter changes corresponding to simulating an electronically controlled engine; the second case providing data covering almost all model input and output parameters. The first case of validation suggests that the model can...

Dimensional crossover in fragmentation

Science.gov (United States)

Sotolongo-Costa, Oscar; Rodriguez, Arezky H.; Rodgers, G. J.

2000-11-01

Experiments in which thick clay plates and glass rods are fractured have revealed different behavior of fragment mass distribution function in the small and large fragment regions. In this paper we explain this behavior using non-extensive Tsallis statistics and show how the crossover between the two regions is caused by the change in the fragments’ dimensionality during the fracture process. We obtain a physical criterion for the position of this crossover and an expression for the change in the power-law exponent between the small and large fragment regions. These predictions are in good agreement with the experiments on thick clay plates.

Casting dimensional control and fatigue life prediction for permanent mold casting dies. Technical progress report, September 29, 1993-- September 30, 1994

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-11-01

First year efforts as part of a three year program to address metal casting dimensional control and fatigue life prediction for permanent mold casting dies are described. Procedures have been developed and implemented to collect dimensional variability data from production steel castings. The influence of process variation and casting geometry variables on dimensional tolerances have been investigated. Preliminary results have shown that these factors have a significant influence on dimensional variability, although this variability is considerably less than the variability indicated in current tolerance standards. Gage repeatability and reproducibility testing must precede dimensional studies to insure that measurement system errors are acceptably small. Also initial efforts leading to the development and validation of a CAD/CAE model to predict the thermal fatigue life of permanent molds for aluminum castings are described. An appropriate thermomechanical property database for metal, mold and coating materials has been constructed. A finite element model has been developed to simulate the mold temperature distribution during repeated casting cycles. Initial validation trials have indicated the validity of the temperature distribution model developed.

Prediction of body lipid change in pregnancy and lactation.

Science.gov (United States)

Friggens, N C; Ingvartsen, K L; Emmans, G C

2004-04-01

A simple method to predict the genetically driven pattern of body lipid change through pregnancy and lactation in dairy cattle is proposed. The rationale and evidence for genetically driven body lipid change have their basis in evolutionary considerations and in the homeorhetic changes in lipid metabolism through the reproductive cycle. The inputs required to predict body lipid change are body lipid mass at calving (kg) and the date of conception (days in milk). Body lipid mass can be derived from body condition score and live weight. A key assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between calving and a genetically determined time in lactation (T') at which a particular level of body lipid (L') is sought. A second assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between T' and the next calving. The resulting model was evaluated using 2 sets of data. The first was from Holstein cows with 3 different levels of body fatness at calving. The second was from Jersey cows in first, second, and third parity. The model was found to reproduce the observed patterns of change in body lipid reserves through lactation in both data sets. The average error of prediction was low, less than the variation normally associated with the recording of condition score, and was similar for the 2 data sets. When the model was applied using the initially suggested parameter values derived from the literature the average error of prediction was 0.185 units of condition score (+/- 0.086 SD). After minor adjustments to the parameter values, the average error of prediction was 0.118 units of condition score (+/- 0.070 SD). The assumptions on which the model is based were sufficient to predict the changes in body lipid of both Holstein and Jersey cows under different nutritional conditions and parities. Thus, the model presented here shows that it is possible to predict genetically driven curves of body

Integration of meanline and one-dimensional methods for prediction of pulsating performance of a turbocharger turbine

International Nuclear Information System (INIS)

Chiong, M.S.; Rajoo, S.; Romagnoli, A.; Costall, A.W.; Martinez-Botas, R.F.

2014-01-01

Highlights: • Unsteady turbine performance prediction by integrating the 1-D and meanline models. • The optimum discretization length/diameter ratio is identified. • No improvement is gained by increasing the number of rotor entries. • The predicted instantaneous mass flow and output power are analysed in detail. - Abstract: Stringent emission regulations are driving engine manufacturers to increase investment into enabling technologies to achieve better specific fuel consumption, thermal efficiency and most importantly carbon reduction. Engine downsizing is seen as a key enabler to successfully achieve all of these requirements. Boosting through turbocharging is widely regarded as one of the most promising technologies for engine downsizing. However, the wide range of engine speeds and loads requires enhanced quality of engine-turbocharger matching, compared to the conventional approach which considers only the full load condition. Thus, development of computational models capable of predicting the unsteady behaviour of a turbocharger turbine is crucial to the overall matching process. A purely one-dimensional (1D) turbine model is capable of good unsteady swallowing capacity predictions, however it has not been fully exploited to predict instantaneous turbine power. On the contrary, meanline models (zero-dimensional) are regarded as a good tool to determine turbine efficiency in steady state but they do not include any information about the pressure wave action occurring within the turbine. This paper explores an alternative methodology to predict instantaneous turbine power and swallowing capacity by integrating one-dimensional and meanline models. A single entry mixed-flow turbine is modelled using a 1D gas dynamic code to solve the unsteady flow state in the volute, consequently used as the input for a meanline model to evaluate the instantaneous turbine power. The key in the effectiveness of this methodology relies on the synchronisation of the flow

Relationship between efficiency and predictability in stock price change

Science.gov (United States)

Eom, Cheoljun; Oh, Gabjin; Jung, Woo-Sung

2008-09-01

In this study, we evaluate the relationship between efficiency and predictability in the stock market. The efficiency, which is the issue addressed by the weak-form efficient market hypothesis, is calculated using the Hurst exponent and the approximate entropy (ApEn). The predictability corresponds to the hit-rate; this is the rate of consistency between the direction of the actual price change and that of the predicted price change, as calculated via the nearest neighbor prediction method. We determine that the Hurst exponent and the ApEn value are negatively correlated. However, predictability is positively correlated with the Hurst exponent.

Fuzzy Regression Prediction and Application Based on Multi-Dimensional Factors of Freight Volume

Science.gov (United States)

Xiao, Mengting; Li, Cheng

2018-01-01

Based on the reality of the development of air cargo, the multi-dimensional fuzzy regression method is used to determine the influencing factors, and the three most important influencing factors of GDP, total fixed assets investment and regular flight route mileage are determined. The system’s viewpoints and analogy methods, the use of fuzzy numbers and multiple regression methods to predict the civil aviation cargo volume. In comparison with the 13th Five-Year Plan for China’s Civil Aviation Development (2016-2020), it is proved that this method can effectively improve the accuracy of forecasting and reduce the risk of forecasting. It is proved that this model predicts civil aviation freight volume of the feasibility, has a high practical significance and practical operation.

Short-Term Predictive Validity of Cluster Analytic and Dimensional Classification of Child Behavioral Adjustment in School

Science.gov (United States)

Kim, Sangwon; Kamphaus, Randy W.; Baker, Jean A.

2006-01-01

A constructive debate over the classification of child psychopathology can be stimulated by investigating the validity of different classification approaches. We examined and compared the short-term predictive validity of cluster analytic and dimensional classifications of child behavioral adjustment in school using the Behavior Assessment System…

Hemp yarn reinforced composites – III. Moisture content and dimensional changes

DEFF Research Database (Denmark)

Madsen, Bo; Hoffmeyer, Preben; Lilholt, Hans

2012-01-01

Based on a comprehensive set of experimental data it is demonstrated that the moisture properties of aligned hemp fibre yarn/thermoplastic matrix composites are showing low moisture sorption capacity and low dimensional changes. Using a reference humidity of 65% RH, and a common span of ambient...

Dimensional Stability of Color-Changing Irreversible Hydrocolloids after Disinfection

Directory of Open Access Journals (Sweden)

Khaledi AAR

2015-03-01

Full Text Available Statement of Problem: Disinfection of dental impressions is a weak point in the dental hygiene chain. In addition, dental office personnel and dental technicians are endangered by cross-contamination. Objectives: This study aimed to investigate the dimensional stability of two color-changing irreversible hydrocolloid materials (IH after disinfection with glutaraldehyde. Materials and Methods: In this in vitro study, impressions were made of a master maxillary arch containing three reference inserts on the occlucal surface of the left and right maxillary second molars and in the incisal surface of the maxillary central incisors. Two types of color-changing irreversible hydrocolloid (tetrachrom, cavex were used. Glutaraldehyde 2% was used in two methods of spraying and immersion to disinfect the impressions. The control group was not disinfected. Casts were made of type IV gypsum. The linear dimensional change of the stone casts was measured with a profile projector. For statistical analysis, Kruskall-Wallis and Mann-Witney tests were used (α=0.05. Results: By immersion method, the casts fabricated from tetrachrom were 0.36% larger in the anteroposterior (AP and 0.05% smaller in cross arch (CA dimensions; however, the casts prepared after spraying of tetrachrom were 0.44% larger in the AP and 0.10% smaller in CA dimensions. The casts made from Cavex were 0.05% smaller in the AP and 0.02% smaller in CA dimensions after spraying and 0.01% smaller in the AP and 0.003% smaller in CA dimensions after immersion. Generally there were not significant differences in AP and CA dimensions of the experimental groups compared to the control (p > 0.05. Conclusions: Disinfection of the tested color-changing irreversible hydrocolloids by glutaraldahyde 2% did not compromise the accuracy of the obtained casts.

Predicting typhoon-induced storm surge tide with a two-dimensional hydrodynamic model and artificial neural network model

Science.gov (United States)

Chen, W.-B.; Liu, W.-C.; Hsu, M.-H.

2012-12-01

Precise predictions of storm surges during typhoon events have the necessity for disaster prevention in coastal seas. This paper explores an artificial neural network (ANN) model, including the back propagation neural network (BPNN) and adaptive neuro-fuzzy inference system (ANFIS) algorithms used to correct poor calculations with a two-dimensional hydrodynamic model in predicting storm surge height during typhoon events. The two-dimensional model has a fine horizontal resolution and considers the interaction between storm surges and astronomical tides, which can be applied for describing the complicated physical properties of storm surges along the east coast of Taiwan. The model is driven by the tidal elevation at the open boundaries using a global ocean tidal model and is forced by the meteorological conditions using a cyclone model. The simulated results of the hydrodynamic model indicate that this model fails to predict storm surge height during the model calibration and verification phases as typhoons approached the east coast of Taiwan. The BPNN model can reproduce the astronomical tide level but fails to modify the prediction of the storm surge tide level. The ANFIS model satisfactorily predicts both the astronomical tide level and the storm surge height during the training and verification phases and exhibits the lowest values of mean absolute error and root-mean-square error compared to the simulated results at the different stations using the hydrodynamic model and the BPNN model. Comparison results showed that the ANFIS techniques could be successfully applied in predicting water levels along the east coastal of Taiwan during typhoon events.

Changes in Pilot Behavior with Predictive System Status Information

Science.gov (United States)

Trujillo, Anna C.

1998-01-01

Research has shown a strong pilot preference for predictive information of aircraft system status in the flight deck. However, changes in pilot behavior associated with using this predictive information have not been ascertained. The study described here quantified these changes using three types of predictive information (none, whether a parameter was changing abnormally, and the time for a parameter to reach an alert range) and three initial time intervals until a parameter alert range was reached (ITIs) (1 minute, 5 minutes, and 15 minutes). With predictive information, subjects accomplished most of their tasks before an alert occurred. Subjects organized the time they did their tasks by locus-of-control with no predictive information and for the 1-minute ITI, and by aviatenavigate-communicate for the time for a parameter to reach an alert range and the 15-minute conditions. Overall, predictive information and the longer ITIs moved subjects to performing tasks before the alert actually occurred and had them more mission oriented as indicated by their tasks grouping of aviate-navigate-communicate.

Applicability of one-dimensional mechanistic post-dryout prediction model

International Nuclear Information System (INIS)

Jeong, Hae Yong; No Hee Cheon

1996-01-01

Through the analysis of many experimental post-dryout data, it is shown that the most probable flow regime near dryout or quench front is not annular flow but churn-turbulent flow when the mass flux is low. A correlation describing the initial droplet size just after the CHF position at low mass flux is low. A correlation describing the initial droplet size just after the CHF position at low mass flux is suggested through regression analysis. In the post-dryout region at low pressure and low flow, it is found that the suggested one-dimensional mechanistic model is not applicable when the vapor superficial velocity is very low, i. e., when the flow is bubbly or slug flow regime. This is explained by the change of main entrainment mechanism with the change of flow regime. Therefore, the suggested correlation is valid only in the churn-turbulent flow regime (j * g = 0.5 ∼ 4.5)

The validation and assessment of machine learning: a game of prediction from high-dimensional data.

Directory of Open Access Journals (Sweden)

Tune H Pers

Full Text Available In applied statistics, tools from machine learning are popular for analyzing complex and high-dimensional data. However, few theoretical results are available that could guide to the appropriate machine learning tool in a new application. Initial development of an overall strategy thus often implies that multiple methods are tested and compared on the same set of data. This is particularly difficult in situations that are prone to over-fitting where the number of subjects is low compared to the number of potential predictors. The article presents a game which provides some grounds for conducting a fair model comparison. Each player selects a modeling strategy for predicting individual response from potential predictors. A strictly proper scoring rule, bootstrap cross-validation, and a set of rules are used to make the results obtained with different strategies comparable. To illustrate the ideas, the game is applied to data from the Nugenob Study where the aim is to predict the fat oxidation capacity based on conventional factors and high-dimensional metabolomics data. Three players have chosen to use support vector machines, LASSO, and random forests, respectively.

A multi-dimensional assessment of urban vulnerability to climate change in Sub-Saharan Africa

DEFF Research Database (Denmark)

Herslund, Lise Byskov; Jalyer, Fatameh; Jean-Baptiste, Nathalie

2016-01-01

In this paper, we develop and apply a multi-dimensional vulnerability assessment framework for understanding the impacts of climate change-induced hazards in Sub- Saharan African cities. The research was carried out within the European/African FP7 project CLimate change and Urban Vulnerability...... in Africa, which investigated climate change-induced risks, assessed vulnerability and proposed policy initiatives in five African cities. Dar es Salaam (Tanzania) was used as a main case with a particular focus on urban flooding. The multi-dimensional assessment covered the physical, institutional...... encroachment on green and flood-prone land). Scenario modeling suggests that vulnerability will continue to increase strongly due to the expected loss of agricultural land at the urban fringes and loss of green space within the city. However, weak institutional commitment and capacity limit the potential...

Climate modelling, uncertainty and responses to predictions of change

International Nuclear Information System (INIS)

Henderson-Sellers, A.

1996-01-01

Article 4.1(F) of the Framework Convention on Climate Change commits all parties to take climate change considerations into account, to the extent feasible, in relevant social, economic and environmental policies and actions and to employ methods such as impact assessments to minimize adverse effects of climate change. This could be achieved by, inter alia, incorporating climate change risk assessment into development planning processes, i.e. relating climatic change to issues of habitability and sustainability. Adaptation is an ubiquitous and beneficial natural and human strategy. Future adaptation (adjustment) to climate is inevitable at the least to decrease the vulnerability to current climatic impacts. An urgent issue is the mismatch between the predictions of global climatic change and the need for information on local to regional change in order to develop adaptation strategies. Mitigation efforts are essential since the more successful mitigation activities are, the less need there will be for adaptation responses. And, mitigation responses can be global (e.g. a uniform percentage reduction in greenhouse gas emissions) while adaptation responses will be local to regional in character and therefore depend upon confident predictions of regional climatic change. The dilemma facing policymakers is that scientists have considerable confidence in likely global climatic changes but virtually zero confidence in regional changes. Mitigation and adaptation strategies relevant to climatic change can most usefully be developed in the context of sound understanding of climate, especially the near-surface continental climate, permitting discussion of societally relevant issues. But, climate models can't yet deliver this type of regionally and locationally specific prediction and some aspects of current research even seem to indicate increased uncertainty. These topics are explored in this paper using the specific example of the prediction of land-surface climate changes

Validation of Molecular Dynamics Simulations for Prediction of Three-Dimensional Structures of Small Proteins.

Science.gov (United States)

Kato, Koichi; Nakayoshi, Tomoki; Fukuyoshi, Shuichi; Kurimoto, Eiji; Oda, Akifumi

2017-10-12

Although various higher-order protein structure prediction methods have been developed, almost all of them were developed based on the three-dimensional (3D) structure information of known proteins. Here we predicted the short protein structures by molecular dynamics (MD) simulations in which only Newton's equations of motion were used and 3D structural information of known proteins was not required. To evaluate the ability of MD simulationto predict protein structures, we calculated seven short test protein (10-46 residues) in the denatured state and compared their predicted and experimental structures. The predicted structure for Trp-cage (20 residues) was close to the experimental structure by 200-ns MD simulation. For proteins shorter or longer than Trp-cage, root-mean square deviation values were larger than those for Trp-cage. However, secondary structures could be reproduced by MD simulations for proteins with 10-34 residues. Simulations by replica exchange MD were performed, but the results were similar to those from normal MD simulations. These results suggest that normal MD simulations can roughly predict short protein structures and 200-ns simulations are frequently sufficient for estimating the secondary structures of protein (approximately 20 residues). Structural prediction method using only fundamental physical laws are useful for investigating non-natural proteins, such as primitive proteins and artificial proteins for peptide-based drug delivery systems.

A GIS tool for two-dimensional glacier-terminus change tracking

Science.gov (United States)

Urbanski, Jacek Andrzej

2018-02-01

This paper presents a Glacier Termini Tracking (GTT) toolbox for the two-dimensional analysis of glacier-terminus position changes. The input consists of a vector layer with several termini lines relating to the same glacier at different times. The output layers allow analyses to be conducted of glacier-terminus retreats, changes in retreats over time and along the ice face, and glacier-terminus fluctuations over time. The application of three tools from the toolbox is demonstrated via the analysis of eight glacier-terminus retreats and fluctuations at the Hornsund fjord in south Svalbard. It is proposed that this toolbox may also be useful in the study of other line features that change over time, like coastlines and rivers. The toolbox has been coded in Python and runs via ArcGIS.

Tag gas burnup based on three-dimensional FTR analysis

International Nuclear Information System (INIS)

Kidman, R.B.

1976-01-01

Flux spectra from a three-dimensional diffusion theory analysis of the Fast Test Reactor (FTR) are used to predict gas tag ratio changes, as a function of exposure, for each FTR fuel and absorber subassembly plenum. These flux spectra are also used to predict Xe-125 equilibrium activities in absorber plena in order to assess the feasibility of using Xe-125 gamma rays to detect and distinguish control rod failures from fuel rod failures. Worst case tag burnup changes are used in conjunction with burnup and mass spectrometer uncertainties to establish the minimum spacing of tags which allows the tags to be unambiguously identified

Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms

Science.gov (United States)

Jian, Jhih-Wei; Elumalai, Pavadai; Pitti, Thejkiran; Wu, Chih Yuan; Tsai, Keng-Chang; Chang, Jeng-Yih; Peng, Hung-Pin; Yang, An-Suei

2016-01-01

Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites. PMID:27513851

Prediction of optimal deployment projection for transcatheter aortic valve replacement: angiographic 3-dimensional reconstruction of the aortic root versus multidetector computed tomography.

Science.gov (United States)

Binder, Ronald K; Leipsic, Jonathon; Wood, David; Moore, Teri; Toggweiler, Stefan; Willson, Alex; Gurvitch, Ronen; Freeman, Melanie; Webb, John G

2012-04-01

Identifying the optimal fluoroscopic projection of the aortic valve is important for successful transcatheter aortic valve replacement (TAVR). Various imaging modalities, including multidetector computed tomography (MDCT), have been proposed for prediction of the optimal deployment projection. We evaluated a method that provides 3-dimensional angiographic reconstructions (3DA) of the aortic root for prediction of the optimal deployment angle and compared it with MDCT. Forty patients undergoing transfemoral TAVR at St Paul's Hospital, Vancouver, Canada, were evaluated. All underwent preimplant 3DA and 68% underwent preimplant MDCT. Three-dimensional angiographic reconstructions were generated from images of a C-arm rotational aortic root angiogram during breath-hold, rapid ventricular pacing, and injection of 32 mL contrast medium at 8 mL/s. Two independent operators prospectively predicted perpendicular valve projections. The implant angle was chosen at the discretion of the physician performing TAVR. The angles from 3DA, from MDCT, the implant angle, and the postdeployment perpendicular prosthesis view were compared. The shortest distance from the postdeployment perpendicular prosthesis projection to the regression line of predicted perpendicular projections was calculated. All but 1 patient had adequate image quality for reproducible angle predictions. There was a significant correlation between 3DA and MDCT for prediction of perpendicular valve projections (r=0.682, Pregression line of predicted angles to the postdeployment prosthesis view was 5.1±4.6° for 3DA and 7.9±4.9° for MDCT (P=0.01). Three-dimensional angiographic reconstructions and MDCT are safe, practical, and accurate imaging modalities for identifying the optimal perpendicular valve deployment projection during TAVR.

Density prediction and dimensionality reduction of mid-term electricity demand in China: A new semiparametric-based additive model

International Nuclear Information System (INIS)

Shao, Zhen; Yang, Shan-Lin; Gao, Fei

2014-01-01

Highlights: • A new stationary time series smoothing-based semiparametric model is established. • A novel semiparametric additive model based on piecewise smooth is proposed. • We model the uncertainty of data distribution for mid-term electricity forecasting. • We provide efficient long horizon simulation and extraction for external variables. • We provide stable and accurate density predictions for mid-term electricity demand. - Abstract: Accurate mid-term electricity demand forecasting is critical for efficient electric planning, budgeting and operating decisions. Mid-term electricity demand forecasting is notoriously complicated, since the demand is subject to a range of external drivers, such as climate change, economic development, which will exhibit monthly, seasonal, and annual complex variations. Conventional models are based on the assumption that original data is stable and normally distributed, which is generally insignificant in explaining actual demand pattern. This paper proposes a new semiparametric additive model that, in addition to considering the uncertainty of the data distribution, includes practical discussions covering the applications of the external variables. To effectively detach the multi-dimensional volatility of mid-term demand, a novel piecewise smooth method which allows reduction of the data dimensionality is developed. Besides, a semi-parametric procedure that makes use of bootstrap algorithm for density forecast and model estimation is presented. Two typical cases in China are presented to verify the effectiveness of the proposed methodology. The results suggest that both meteorological and economic variables play a critical role in mid-term electricity consumption prediction in China, while the extracted economic factor is adequate to reveal the potentially complex relationship between electricity consumption and economic fluctuation. Overall, the proposed model can be easily applied to mid-term demand forecasting, and

Statistical Mechanics of the Geometric Control of Flow Topology in Two-Dimensional Turbulence

Science.gov (United States)

Nadiga, Balasubramanya; Loxley, Peter

2013-04-01

We apply the principle of maximum entropy to two dimensional turbulence in a new fashion to predict the effect of geometry on flow topology. We consider two prototypical regimes of turbulence that lead to frequently observed self-organized coherent structures. Our theory predicts bistable behavior that exhibits hysteresis and large abrupt changes in flow topology in one regime; the other regime is predicted to exhibit monstable behavior with a continuous change of flow topology. The predictions are confirmed in fully nonlinear numerical simulations of the two-dimensional Navier-Stokes equation. These results suggest an explanation of the low frequency regime transitions that have been observed in the non-equilibrium setting of this problem. Following further development in the non-equilibrium context, we expect that insights developed in this problem should be useful in developing a better understanding of the phenomenon of low frequency regime transitions that is a pervasive feature of the weather and climate systems. Familiar occurrences of this phenomenon---wherein extreme and abrupt qualitative changes occur, seemingly randomly, after very long periods of apparent stability---include blocking in the extra-tropical winter atmosphere, the bimodality of the Kuroshio extension system, the Dansgaard-Oeschger events, and the glacial-interglacial transitions.

Application of General Regression Neural Network to the Prediction of LOD Change

Science.gov (United States)

Zhang, Xiao-Hong; Wang, Qi-Jie; Zhu, Jian-Jun; Zhang, Hao

2012-01-01

Traditional methods for predicting the change in length of day (LOD change) are mainly based on some linear models, such as the least square model and autoregression model, etc. However, the LOD change comprises complicated non-linear factors and the prediction effect of the linear models is always not so ideal. Thus, a kind of non-linear neural network — general regression neural network (GRNN) model is tried to make the prediction of the LOD change and the result is compared with the predicted results obtained by taking advantage of the BP (back propagation) neural network model and other models. The comparison result shows that the application of the GRNN to the prediction of the LOD change is highly effective and feasible.

Regime shifts limit the predictability of land-system change

DEFF Research Database (Denmark)

Müller, Daniel; Sun, Zhanli; Vongvisouk, Thoumthone

2014-01-01

Payment schemes for ecosystem services such as Reducing Emissions from Deforestation and forest Degradation (REDD) rely on the prediction of ‘business-as-usual’ scenarios to ensure that emission reductions from carbon credits are additional. However, land systems often undergo periods of nonlinear...... and abrupt change that invalidate predictions calibrated on past trends. Rapid land-system change can occur when critical thresholds in broad-scale underlying drivers such as commodity prices and climate conditions are crossed or when sudden events such as political change or natural disasters punctuate long...

Climate-Induced Boreal Forest Change: Predictions versus Current Observations

Science.gov (United States)

Soja, Amber J.; Tchebakova, Nadezda M.; French, Nancy H. F.; Flannigan, Michael D.; Shugart, Herman H.; Stocks, Brian J.; Sukhinin, Anatoly I.; Parfenova, E. I.; Chapin, F. Stuart, III; Stackhouse, Paul W., Jr.

2007-01-01

For about three decades, there have been many predictions of the potential ecological response in boreal regions to the currently warmer conditions. In essence, a widespread, naturally occurring experiment has been conducted over time. In this paper, we describe previously modeled predictions of ecological change in boreal Alaska, Canada and Russia, and then we investigate potential evidence of current climate-induced change. For instance, ecological models have suggested that warming will induce the northern and upslope migration of the treeline and an alteration in the current mosaic structure of boreal forests. We present evidence of the migration of keystone ecosystems in the upland and lowland treeline of mountainous regions across southern Siberia. Ecological models have also predicted a moisture-stress-related dieback in white spruce trees in Alaska, and current investigations show that as temperatures increase, white spruce tree growth is declining. Additionally, it was suggested that increases in infestation and wildfire disturbance would be catalysts that precipitate the alteration of the current mosaic forest composition. In Siberia, five of the last seven years have resulted in extreme fire seasons, and extreme fire years have also been more frequent in both Alaska and Canada. In addition, Alaska has experienced extreme and geographically expansive multi-year outbreaks of the spruce beetle, which had been previously limited by the cold, moist environment. We suggest that there is substantial evidence throughout the circumboreal region to conclude that the biosphere within the boreal terrestrial environment has already responded to the transient effects of climate change. Additionally, temperature increases and warming-induced change are progressing faster than had been predicted in some regions, suggesting a potential non-linear rapid response to changes in climate, as opposed to the predicted slow linear response to climate change.

Observations on dimensional changes of sized canvas based on glue temperature

DEFF Research Database (Denmark)

Krarup Andersen, Cecil

2008-01-01

The aim of this study was to explore dimensional changes caused by water on sized canvas. Samples of new linen canvas were mounted on a rig for biaxial tensioning, holding a constant stress of 100 N/m in both weave directions. The samples were then sized with respectively warm fluent glue (45 °C......) or a cold gel (20 °C), both consisting of a 5 percent sheepskin glue extracted from parchment clippings. The warm glue was absorbed into the canvas structure, whereas the cold gel mostly stayed as a discrete layer on the canvas. Twice the amount of glue was therefore needed for the warm sizing. When...... of size layers during application is important to the dimensional reaction of a canvas painting that is exposed to water....

Can we predict the response of large sand bed rivers to changes in flow and sediment supply? The case of the Missouri River.

Science.gov (United States)

Viparelli, E.; Blum, M. D.

2015-12-01

In the past century engineering projects and changes in land use significantly modified the hydrology and the sediment supply of large sand bed rivers all over the world. Field studies documented the river responses to the imposed changes, which can be summarized as adjustments in channel geometry, slope, and/or characteristics of the bed material. Further, one-, two- and three-dimensional river morphodynamic models were used to predict the fluvial system response to the imposed changes at time scales ranging from few months up to several decades. Notwithstading this previous research effort, the spatial and temporal scales of river adjustment, as well as quantitative predictions of the river responses, are still a matter of debate due to the difficulties associated with the interpretation of limited field datasets and with the large scale sediment transport modeling. Here we present the preliminary results of a study of the Missouri River response to the construction of dams, i.e. reduction in flood flow and sediment supply. In particular, we first compare the numerical results of a one-dimensional model of river morphodynamics for large, low slope sand bed rivers with field data to validate the model. The validated model is then used to constrain the spatial and temporal scales of the river adjustment, i.e. bed degradation in the Missouri River case. In other words, our numerical work focuses on how the magnitude and speed of the wave of channel bed degradation changes in time and space for the Missouri River case and how these scales change for different values of the ratio between pre- and pos-dam flow rates, and pre- and post-dam sediment loads.

Contextual remapping in visual search after predictable target-location changes.

Science.gov (United States)

Conci, Markus; Sun, Luning; Müller, Hermann J

2011-07-01

Invariant spatial context can facilitate visual search. For instance, detection of a target is faster if it is presented within a repeatedly encountered, as compared to a novel, layout of nontargets, demonstrating a role of contextual learning for attentional guidance ('contextual cueing'). Here, we investigated how context-based learning adapts to target location (and identity) changes. Three experiments were performed in which, in an initial learning phase, observers learned to associate a given context with a given target location. A subsequent test phase then introduced identity and/or location changes to the target. The results showed that contextual cueing could not compensate for target changes that were not 'predictable' (i.e. learnable). However, for predictable changes, contextual cueing remained effective even immediately after the change. These findings demonstrate that contextual cueing is adaptive to predictable target location changes. Under these conditions, learned contextual associations can be effectively 'remapped' to accommodate new task requirements.

Deformation behaviors of three-dimensional graphene honeycombs under out-of-plane compression: Atomistic simulations and predictive modeling

Science.gov (United States)

Meng, Fanchao; Chen, Cheng; Hu, Dianyin; Song, Jun

2017-12-01

Combining atomistic simulations and continuum modeling, a comprehensive study of the out-of-plane compressive deformation behaviors of equilateral three-dimensional (3D) graphene honeycombs was performed. It was demonstrated that under out-of-plane compression, the honeycomb exhibits two critical deformation events, i.e., elastic mechanical instability (including elastic buckling and structural transformation) and inelastic structural collapse. The above events were shown to be strongly dependent on the honeycomb cell size and affected by the local atomic bonding at the cell junction. By treating the 3D graphene honeycomb as a continuum cellular solid, and accounting for the structural heterogeneity and constraint at the junction, a set of analytical models were developed to accurately predict the threshold stresses corresponding to the onset of those deformation events. The present study elucidates key structure-property relationships of 3D graphene honeycombs under out-of-plane compression, and provides a comprehensive theoretical framework to predictively analyze their deformation responses, and more generally, offers critical new knowledge for the rational bottom-up design of 3D networks of two-dimensional nanomaterials.

Predicting Immediate Belief Change and Adherence to Argument Claims.

Science.gov (United States)

Hample, Dale

1978-01-01

Discusses the probative potential of evidence in argument, and evaluates the importance of evidence in predicting belief change. Predicts adherence to argument claims and confirms the traditionally recognized importance of evidence to persuasion. (JMF)

Three dimensional assessment of condylar surface changes and remodeling after orthognathic surgery

International Nuclear Information System (INIS)

Lee, Jung Hye; Lee, Jin Woo; Huh, Kyung Hoe; Yi, Won Jin; Heo, Min Suk; Lee, Sam Sun; Choi, Soon Chul; Shin, Jae Myung

2016-01-01

This study was performed to evaluate condylar surface changes and remodeling after orthognathic surgery using three-dimensional computed tomography (3D CT) imaging, including comparisons between the right and left sides and between the sexes. Forty patients (20 males and 20 females) who underwent multi-detector CT examinations before and after surgery were selected. Three-dimensional images comprising thousands of points on the condylar surface were obtained before and after surgery. For the quantitative assessment of condylar surface changes, point-to-point (preoperative-to-postoperative) distances were calculated using D processing software. These point-to-point distances were converted to a color map. In order to evaluate the types of condylar remodeling, the condylar head was divided into six areas (anteromedial, anteromiddle, anterolateral, posteromedial, posteromiddle, and posterolateral areas) and each area was classified into three types of condylar remodeling (bone formation, no change, and bone resorption) based on the color map. Additionally, comparative analyses were performed between the right and left sides and according to sex. The mean of the average point-to-point distances on condylar surface was 0.11±0.03 mm. Bone resorption occurred more frequently than other types of condylar remodeling, especially in the lateral areas. However, bone formation in the anteromedial area was particularly prominent. No significant difference was found between the right and left condyles, but condylar surface changes in males were significantly larger than in females. This study revealed that condylar remodeling exhibited a tendency towards bone resorption, especially in the lateral areas. Condylar surface changes occurred, but were small

Three dimensional assessment of condylar surface changes and remodeling after orthognathic surgery

Energy Technology Data Exchange (ETDEWEB)

Lee, Jung Hye; Lee, Jin Woo; Huh, Kyung Hoe; Yi, Won Jin; Heo, Min Suk; Lee, Sam Sun; Choi, Soon Chul [Dental Research Institute, Seoul National University, Seoul (Korea, Republic of); Shin, Jae Myung [Dept. of Oral and Maxillofacial Surgery, Ilsan Paik Hospital, Inje University College of Medicine, Goyang (Korea, Republic of)

2016-03-15

This study was performed to evaluate condylar surface changes and remodeling after orthognathic surgery using three-dimensional computed tomography (3D CT) imaging, including comparisons between the right and left sides and between the sexes. Forty patients (20 males and 20 females) who underwent multi-detector CT examinations before and after surgery were selected. Three-dimensional images comprising thousands of points on the condylar surface were obtained before and after surgery. For the quantitative assessment of condylar surface changes, point-to-point (preoperative-to-postoperative) distances were calculated using D processing software. These point-to-point distances were converted to a color map. In order to evaluate the types of condylar remodeling, the condylar head was divided into six areas (anteromedial, anteromiddle, anterolateral, posteromedial, posteromiddle, and posterolateral areas) and each area was classified into three types of condylar remodeling (bone formation, no change, and bone resorption) based on the color map. Additionally, comparative analyses were performed between the right and left sides and according to sex. The mean of the average point-to-point distances on condylar surface was 0.11±0.03 mm. Bone resorption occurred more frequently than other types of condylar remodeling, especially in the lateral areas. However, bone formation in the anteromedial area was particularly prominent. No significant difference was found between the right and left condyles, but condylar surface changes in males were significantly larger than in females. This study revealed that condylar remodeling exhibited a tendency towards bone resorption, especially in the lateral areas. Condylar surface changes occurred, but were small.

Predicting Wetland Distribution Changes under Climate Change and Human Activities in a Mid- and High-Latitude Region

Directory of Open Access Journals (Sweden)

Dandan Zhao

2018-03-01

Full Text Available Wetlands in the mid- and high-latitudes are particularly vulnerable to environmental changes and have declined dramatically in recent decades. Climate change and human activities are arguably the most important factors driving wetland distribution changes which will have important implications for wetland ecological functions and services. We analyzed the importance of driving variables for wetland distribution and investigated the relative importance of climatic factors and human activity factors in driving historical wetland distribution changes. We predicted wetland distribution changes under climate change and human activities over the 21st century using the Random Forest model in a mid- and high-latitude region of Northeast China. Climate change scenarios included three Representative Concentration Pathways (RCPs based on five general circulation models (GCMs downloaded from the Coupled Model Intercomparison Project, Phase 5 (CMIP5. The three scenarios (RCP 2.6, RCP 4.5, and RCP 8.5 predicted radiative forcing to peak at 2.6, 4.5, and 8.5 W/m2 by the 2100s, respectively. Our results showed that the variables with high importance scores were agricultural population proportion, warmness index, distance to water body, coldness index, and annual mean precipitation; climatic variables were given higher importance scores than human activity variables on average. Average predicted wetland area among three emission scenarios were 340,000 ha, 123,000 ha, and 113,000 ha for the 2040s, 2070s, and 2100s, respectively. Average change percent in predicted wetland area among three periods was greatest under the RCP 8.5 emission scenario followed by RCP 4.5 and RCP 2.6 emission scenarios, which were 78%, 64%, and 55%, respectively. Losses in predicted wetland distribution were generally around agricultural lands and expanded continually from the north to the whole region over time, while the gains were mostly associated with grasslands and water in the

The relationship between the changes in three-dimensional facial morphology and mandibular movement after orthognathic surgery.

Science.gov (United States)

Kim, Dae-Seung; Huh, Kyung-Hoe; Lee, Sam-Sun; Heo, Min-Suk; Choi, Soon-Chul; Hwang, Soon-Jung; Yi, Won-Jin

2013-10-01

The purpose of this study was to investigate the relationship between changes in three-dimensional (3D) facial morphology and mandibular movement after orthognathic surgery. We hypothesized that facial morphology changes after orthognathic surgery exert effects on 3D mandibular movement. We conducted a prospective follow-up study of patients who had undergone orthognathic surgical procedures. Three-dimensional facial morphological values were measured from facial CT images before and three months after orthognathic surgery. Three-dimensional maximum mandibular opening (MMO) values of four points (bilateral condylions, infradentale, and pogonion) were also measured using a mandibular movement tracking and simulation system. The predictor variables were changes in morphological parameters divided into two groups (deviated side (DS) or contralateral side (CS) groups), and the outcome variables were changes in the MMO at four points. We evaluated 21 subjects who had undergone orthognathic surgical procedures. Alterations in the TFH (total facial height), LFH (lower facial height), CS MBL (mandibular body length), and DS RL (ramus length) were negatively correlated with changes in bilateral condylar movement. The UFH, DS MBL and CS ML (mandibular length) showed correlations with infradentale movement. The CS ML, DS ML, MBL, UFH, and SNB were correlated with pogonion movement. The height of the face is most likely to affect post-operative mandibular movement, and is negatively correlated with movement changes in the condyles, infradentale and pogonion. The changes in CS morphological parameters are more correlated with mandibular movement changes than the DS. The changes in CS MBL and bilateral RL were negatively correlated with condylar movement changes, while the bilateral MBL and CS ML were positively correlated with changes in infradentale and pogonion. Copyright © 2013 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights

Local Fitness Landscapes Predict Yeast Evolutionary Dynamics in Directionally Changing Environments.

Science.gov (United States)

Gorter, Florien A; Aarts, Mark G M; Zwaan, Bas J; de Visser, J Arjan G M

2018-01-01

The fitness landscape is a concept that is widely used for understanding and predicting evolutionary adaptation. The topography of the fitness landscape depends critically on the environment, with potentially far-reaching consequences for evolution under changing conditions. However, few studies have assessed directly how empirical fitness landscapes change across conditions, or validated the predicted consequences of such change. We previously evolved replicate yeast populations in the presence of either gradually increasing, or constant high, concentrations of the heavy metals cadmium (Cd), nickel (Ni), and zinc (Zn), and analyzed their phenotypic and genomic changes. Here, we reconstructed the local fitness landscapes underlying adaptation to each metal by deleting all repeatedly mutated genes both by themselves and in combination. Fitness assays revealed that the height, and/or shape, of each local fitness landscape changed considerably across metal concentrations, with distinct qualitative differences between unconditionally (Cd) and conditionally toxic metals (Ni and Zn). This change in topography had particularly crucial consequences in the case of Ni, where a substantial part of the individual mutational fitness effects changed in sign across concentrations. Based on the Ni landscape analyses, we made several predictions about which mutations had been selected when during the evolution experiment. Deep sequencing of population samples from different time points generally confirmed these predictions, demonstrating the power of landscape reconstruction analyses for understanding and ultimately predicting evolutionary dynamics, even under complex scenarios of environmental change. Copyright © 2018 by the Genetics Society of America.

Predicting postoperative haemoglobin changes after burn surgery

African Journals Online (AJOL)

Burn surgery is associated with significant peri-operative haemoglobin. (Hb) changes. ... operative factors predictive of an Hb <7 g/dL on the first day after surgery, which were ..... clinical judgement, taking into consideration the risk associated.

Neural activity predicts attitude change in cognitive dissonance.

Science.gov (United States)

van Veen, Vincent; Krug, Marie K; Schooler, Jonathan W; Carter, Cameron S

2009-11-01

When our actions conflict with our prior attitudes, we often change our attitudes to be more consistent with our actions. This phenomenon, known as cognitive dissonance, is considered to be one of the most influential theories in psychology. However, the neural basis of this phenomenon is unknown. Using a Solomon four-group design, we scanned participants with functional MRI while they argued that the uncomfortable scanner environment was nevertheless a pleasant experience. We found that cognitive dissonance engaged the dorsal anterior cingulate cortex and anterior insula; furthermore, we found that the activation of these regions tightly predicted participants' subsequent attitude change. These effects were not observed in a control group. Our findings elucidate the neural representation of cognitive dissonance, and support the role of the anterior cingulate cortex in detecting cognitive conflict and the neural prediction of attitude change.

Empirical analysis of change metrics for software fault prediction

NARCIS (Netherlands)

Choudhary, Garvit Rajesh; Kumar, Sandeep; Kumar, Kuldeep; Mishra, Alok; Catal, Cagatay

2018-01-01

A quality assurance activity, known as software fault prediction, can reduce development costs and improve software quality. The objective of this study is to investigate change metrics in conjunction with code metrics to improve the performance of fault prediction models. Experimental studies are

Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis.

Science.gov (United States)

Masso, Majid; Vaisman, Iosif I

2008-09-15

Accurate predictive models for the impact of single amino acid substitutions on protein stability provide insight into protein structure and function. Such models are also valuable for the design and engineering of new proteins. Previously described methods have utilized properties of protein sequence or structure to predict the free energy change of mutants due to thermal (DeltaDeltaG) and denaturant (DeltaDeltaG(H2O)) denaturations, as well as mutant thermal stability (DeltaT(m)), through the application of either computational energy-based approaches or machine learning techniques. However, accuracy associated with applying these methods separately is frequently far from optimal. We detail a computational mutagenesis technique based on a four-body, knowledge-based, statistical contact potential. For any mutation due to a single amino acid replacement in a protein, the method provides an empirical normalized measure of the ensuing environmental perturbation occurring at every residue position. A feature vector is generated for the mutant by considering perturbations at the mutated position and it's ordered six nearest neighbors in the 3-dimensional (3D) protein structure. These predictors of stability change are evaluated by applying machine learning tools to large training sets of mutants derived from diverse proteins that have been experimentally studied and described. Predictive models based on our combined approach are either comparable to, or in many cases significantly outperform, previously published results. A web server with supporting documentation is available at http://proteins.gmu.edu/automute.

Stock price change rate prediction by utilizing social network activities.

Science.gov (United States)

Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

Stock Price Change Rate Prediction by Utilizing Social Network Activities

Directory of Open Access Journals (Sweden)

Shangkun Deng

2014-01-01

Full Text Available Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL and genetic algorithm (GA. MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

Supporting change processes in design: Complexity, prediction and reliability

Energy Technology Data Exchange (ETDEWEB)

Eckert, Claudia M. [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: cme26@cam.ac.uk; Keller, Rene [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: rk313@cam.ac.uk; Earl, Chris [Open University, Department of Design and Innovation, Walton Hall, Milton Keynes MK7 6AA (United Kingdom)]. E-mail: C.F.Earl@open.ac.uk; Clarkson, P. John [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: pjc10@cam.ac.uk

2006-12-15

Change to existing products is fundamental to design processes. New products are often designed through change or modification to existing products. Specific parts or subsystems are changed to similar ones whilst others are directly reused. Design by modification applies particularly to safety critical products where the reuse of existing working parts and subsystems can reduce cost and risk. However change is rarely a matter of just reusing or modifying parts. Changing one part can propagate through the entire design leading to costly rework or jeopardising the integrity of the whole product. This paper characterises product change based on studies in the aerospace and automotive industry and introduces tools to aid designers in understanding the potential effects of change. Two ways of supporting designers are described: probabilistic prediction of the effects of change and visualisation of change propagation through product connectivities. Change propagation has uncertainties which are amplified by the choices designers make in practice as they implement change. Change prediction and visualisation is discussed with reference to complexity in three areas of product development: the structural backcloth of connectivities in the existing product (and its processes), the descriptions of the product used in design and the actions taken to carry out changes.

Predicting vulnerabilities of North American shorebirds to climate change.

Directory of Open Access Journals (Sweden)

Hector Galbraith

Full Text Available Despite an increase in conservation efforts for shorebirds, there are widespread declines of many species of North American shorebirds. We wanted to know whether these declines would be exacerbated by climate change, and whether relatively secure species might become at-risk species. Virtually all of the shorebird species breeding in the USA and Canada are migratory, which means climate change could affect extinction risk via changes on the breeding, wintering, and/or migratory refueling grounds, and that ecological synchronicities could be disrupted at multiple sites. To predict the effects of climate change on shorebird extinction risks, we created a categorical risk model complementary to that used by Partners-in-Flight and the U.S. Shorebird Conservation Plan. The model is based on anticipated changes in breeding, migration, and wintering habitat, degree of dependence on ecological synchronicities, migration distance, and degree of specialization on breeding, migration, or wintering habitat. We evaluated 49 species, and for 3 species we evaluated 2 distinct populations each, and found that 47 (90% taxa are predicted to experience an increase in risk of extinction. No species was reclassified into a lower-risk category, although 6 species had at least one risk factor decrease in association with climate change. The number of species that changed risk categories in our assessment is sensitive to how much of an effect of climate change is required to cause the shift, but even at its least sensitive, 20 species were at the highest risk category for extinction. Based on our results it appears that shorebirds are likely to be highly vulnerable to climate change. Finally, we discuss both how our approach can be integrated with existing risk assessments and potential future directions for predicting change in extinction risk due to climate change.

Pyridine-induced Dimensionality Change in Hybrid Perovskite Nanocrystals

KAUST Repository

Ahmed, Ghada H.; Yin, Jun; Bose, Riya; Sinatra, Lutfan; Alarousu, Erkki; Yengel, Emre; AlYami, Noktan; Saidaminov, Makhsud I.; Zhang, Yuhai; Hedhili, Mohamed N.; Bakr, Osman; Bredas, Jean-Luc; Mohammed, Omar F.

2017-01-01

of pyridine during the synthesis of methylammonium lead bromide (MAPbBr) perovskite nanocrystals can transform three-dimensional (3D) cubes into two-dimensional (2D) nanostructures. Density functional theory (DFT) calculations show that pyridine preferentially

Three-dimensional prediction of the human eyeball and canthi for craniofacial reconstruction using cone-beam computed tomography.

Science.gov (United States)

Kim, Sang-Rok; Lee, Kyung-Min; Cho, Jin-Hyoung; Hwang, Hyeon-Shik

2016-04-01

An anatomical relationship between the hard and soft tissues of the face is mandatory for facial reconstruction. The purpose of this study was to investigate the positions of the eyeball and canthi three-dimensionally from the relationships between the facial hard and soft tissues using cone-beam computed tomography (CBCT). CBCT scan data of 100 living subjects were used to obtain the measurements of facial hard and soft tissues. Stepwise multiple regression analyses were carried out using the hard tissue measurements in the orbit, nasal bone, nasal cavity and maxillary canine to predict the most probable positions of the eyeball and canthi within the orbit. Orbital width, orbital height, and orbital depth were strong predictors of the eyeball and canthi position. Intercanine width was also a predictor of the mediolateral position of the eyeball. Statistically significant regression models for the positions of the eyeball and canthi could be derived from the measurements of orbit and maxillary canine. These results suggest that CBCT data can be useful in predicting the positions of the eyeball and canthi three-dimensionally. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Predicting Peri-Device Leakage of Left Atrial Appendage Device Closure Using Novel Three-Dimensional Geometric CT Analysis.

Science.gov (United States)

Chung, Hyemoon; Jeon, Byunghwan; Chang, Hyuk-Jae; Han, Dongjin; Shim, Hackjoon; Cho, In Jeong; Shim, Chi Young; Hong, Geu-Ru; Kim, Jung-Sun; Jang, Yangsoo; Chung, Namsik

2015-12-01

After left atrial appendage (LAA) device closure, peri-device leakage into the LAA persists due to incomplete occlusion. We hypothesized that pre-procedural three-dimensional (3D) geometric analysis of the interatrial septum (IAS) and LAA orifice can predict this leakage. We investigated the predictive parameters of LAA device closure obtained from baseline cardiac computerized tomography (CT) using a novel 3D analysis system. We conducted a retrospective study of 22 patients who underwent LAA device closure. We defined peri-device leakage as the presence of a Doppler signal inside the LAA after device deployment (group 2, n = 5) compared with patients without peri-device leakage (group 1, n = 17). Conventional parameters were measured by cardiac CT. Angles θ and φ were defined between the IAS plane and the line, linking the LAA orifice center and foramen ovale. Group 2 exhibited significantly better left atrial (LA) function than group 1 (p = 0.031). Pre-procedural θ was also larger in this group (41.9° vs. 52.3°, p = 0.019). The LAA cauliflower-type morphology was more common in group 2. Overall, the patients' LA reserve significantly decreased after the procedure (21.7 mm(3) vs. 17.8 mm(3), p = 0.035). However, we observed no significant interval changes in pre- and post-procedural values of θ and φ in either group (all p > 0.05). Angles between the IAS and LAA orifice might be a novel anatomical parameter for predicting peri-device leakage after LAA device closure. In addition, 3D CT analysis of the LA and LAA orifice could be used to identify clinically favorable candidates for LAA device closure.

Tuning spin transport across two-dimensional organometallic junctions

Science.gov (United States)

Liu, Shuanglong; Wang, Yun-Peng; Li, Xiangguo; Fry, James N.; Cheng, Hai-Ping

2018-01-01

We study via first-principles modeling and simulation two-dimensional spintronic junctions made of metal-organic frameworks consisting of two Mn-phthalocyanine ferromagnetic metal leads and semiconducting Ni-phthalocyanine channels of various lengths. These systems exhibit a large tunneling magnetoresistance ratio; the transmission functions of such junctions can be tuned using gate voltage by three orders of magnitude. We find that the origin of this drastic change lies in the orbital alignment and hybridization between the leads and the center electronic states. With physical insight into the observed on-off phenomenon, we predict a gate-controlled spin current switch based on two-dimensional crystallines and offer general guidelines for designing spin junctions using 2D materials.

An overview of techniques for linking high-dimensional molecular data to time-to-event endpoints by risk prediction models.

Science.gov (United States)

Binder, Harald; Porzelius, Christine; Schumacher, Martin

2011-03-01

Analysis of molecular data promises identification of biomarkers for improving prognostic models, thus potentially enabling better patient management. For identifying such biomarkers, risk prediction models can be employed that link high-dimensional molecular covariate data to a clinical endpoint. In low-dimensional settings, a multitude of statistical techniques already exists for building such models, e.g. allowing for variable selection or for quantifying the added value of a new biomarker. We provide an overview of techniques for regularized estimation that transfer this toward high-dimensional settings, with a focus on models for time-to-event endpoints. Techniques for incorporating specific covariate structure are discussed, as well as techniques for dealing with more complex endpoints. Employing gene expression data from patients with diffuse large B-cell lymphoma, some typical modeling issues from low-dimensional settings are illustrated in a high-dimensional application. First, the performance of classical stepwise regression is compared to stage-wise regression, as implemented by a component-wise likelihood-based boosting approach. A second issues arises, when artificially transforming the response into a binary variable. The effects of the resulting loss of efficiency and potential bias in a high-dimensional setting are illustrated, and a link to competing risks models is provided. Finally, we discuss conditions for adequately quantifying the added value of high-dimensional gene expression measurements, both at the stage of model fitting and when performing evaluation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A New Model for Birth Weight Prediction Using 2- and 3-Dimensional Ultrasonography by Principal Component Analysis: A Chinese Population Study.

Science.gov (United States)

Liao, Shuxin; Wang, Yunfang; Xiao, Shufang; Deng, Xujie; Fang, Bimei; Yang, Fang

2018-03-30

To establish a new model for birth weight prediction using 2- and 3-dimensional ultrasonography (US) by principal component analysis (PCA). Two- and 3-dimensional US was prospectively performed in women with normal singleton pregnancies within 7 days before delivery (37-41 weeks' gestation). The participants were divided into a development group (n = 600) and a validation group (n = 597). Principal component analysis and stepwise linear regression analysis were used to develop a new prediction model. The new model's accuracy in predicting fetal birth weight was confirmed by the validation group through comparisons with previously published formulas. A total of 1197 cases were recruited in this study. All interclass and intraclass correlation coefficients of US measurements were greater than 0.75. Two principal components (PCs) were considered primary in determining estimated fetal birth weight, which were derived from 9 US measurements. Stepwise linear regression analysis showed a positive association between birth weight and PC1 and PC2. In the development group, our model had a small mean percentage error (mean ± SD, 3.661% ± 3.161%). At least a 47.558% decrease in the mean percentage error and a 57.421% decrease in the standard deviation of the new model compared with previously published formulas were noted. The results were similar to those in the validation group, and the new model covered 100% of birth weights within 10% of actual birth weights. The birth weight prediction model based on 2- and 3-dimensional US by PCA could help improve the precision of estimated fetal birth weight. © 2018 by the American Institute of Ultrasound in Medicine.

Predicted Mobility Edges in One-Dimensional Incommensurate Optical Lattices: An Exactly Solvable Model of Anderson Localization

International Nuclear Information System (INIS)

Biddle, J.; Das Sarma, S.

2010-01-01

Localization properties of noninteracting quantum particles in one-dimensional incommensurate lattices are investigated with an exponential short-range hopping that is beyond the minimal nearest-neighbor tight-binding model. Energy dependent mobility edges are analytically predicted in this model and verified with numerical calculations. The results are then mapped to the continuum Schroedinger equation, and an approximate analytical expression for the localization phase diagram and the energy dependent mobility edges in the ground band is obtained.

A 2.5-dimensional method for the prediction of structure-borne low-frequency noise from concrete rail transit bridges.

Science.gov (United States)

Li, Qi; Song, Xiaodong; Wu, Dingjun

2014-05-01

Predicting structure-borne noise from bridges subjected to moving trains using the three-dimensional (3D) boundary element method (BEM) is a time consuming process. This paper presents a two-and-a-half dimensional (2.5D) BEM-based procedure for simulating bridge-borne low-frequency noise with higher efficiency, yet no loss of accuracy. The two-dimensional (2D) BEM of a bridge with a constant cross section along the track direction is adopted to calculate the spatial modal acoustic transfer vectors (MATVs) of the bridge using the space-wave number transforms of its 3D modal shapes. The MATVs calculated using the 2.5D method are then validated by those computed using the 3D BEM. The bridge-borne noise is finally obtained through the MATVs and modal coordinate responses of the bridge, considering time-varying vehicle-track-bridge dynamic interaction. The presented procedure is applied to predict the sound pressure radiating from a U-shaped concrete bridge, and the computed results are compared with those obtained from field tests on Shanghai rail transit line 8. The numerical results match well with the measured results in both time and frequency domains at near-field points. Nevertheless, the computed results are smaller than the measured ones for far-field points, mainly due to the sound radiation from adjacent spans neglected in the current model.

Prediction of inorganic superconductors with quasi-one-dimensional crystal structure

International Nuclear Information System (INIS)

Volkova, L M; Marinin, D V

2013-01-01

Models of superconductors having a quasi-one-dimensional crystal structure based on the convoluted into a tube Ginzburg sandwich, which comprises a layered dielectric–metal–dielectric structure, have been suggested. The critical crystal chemistry parameters of the Ginzburg sandwich determining the possibility of the emergence of superconductivity and the T c value in layered high-T c cuprates, which could have the same functions in quasi-one-dimensional fragments (sandwich-type tubes), have been examined. The crystal structures of known low-temperature superconductors, in which one can mark out similar quasi-one-dimensional fragments, have been analyzed. Five compounds with quasi-one-dimensional structures, which can be considered as potential parents of new superconductor families, possibly with high transition temperatures, have been suggested. The methods of doping and modification of these compounds are provided. (paper)

Dimensional response of CANDU fuel to power changes

Energy Technology Data Exchange (ETDEWEB)

Fehrenbach, P J [Fuel Engineering Branch, Chalk River Nuclear Laboratories, Atomic Energy of Canada Limited, Chalk River, ON (Canada); Hastings, I J; Morel, P A; Sage, R D; Smith, A D [Fuel Materials Branch, Chalk River Nuclear Laboratories, Atomic Energy of Canada Limited, Chalk River, ON (Canada)

1983-06-01

The introduction of CANLUB-coated fuel cladding, modified fuel management schemes, and revisions to the sequence of control rod movements, have eliminated power ramping fuel failures in CANDU power reactors. However, an irradiation program continues at Chalk River Nuclear Laboratories to determine the effect of various design and operating parameters on the dimensional response of UO{sub 2} fuel elements to power changes, over a range of conditions outside those normally experienced by CANDU power reactor fuel. We have investigated the effect of power changes on element diameter for UO{sub 2} fuel with starting densities of 10.6 and 10.8 Mg/m{sup 3} clad in 0.4 mm thick Zircaloy, at burnups from 0 to 100 MW.h/kg U. Element diameter measurements were obtained at power using an In-Reactor Diameter Measuring Rig (IRDMR). Rates of power change over the range 0.0005 to 0.03 kW.m{sup -1}.s{sup -1} were achieved by a combination of reactor power control and use of a Helium-3 power cycling facility. Total diameter increases in unirradiated elements were about 1% at pellet interface locations for both fuel densities during the initial power increase to 60 kW/m. Diameter changes during subsequent power cycles of these elements from 55 to 100% maximum power were significantly larger for the higher density fuel, ranging from 0.3 to 0.5% compared to less than 0.1% for the standard density (10.6 Mg/m{sup 3}) fuel. In elements pre-irradiated at 27 kW/m to burnups of about 100 MW.h/kg U prior to power ramping, the diameter increases measured after ramping to 55 kW/m also varied with starting fuel density. Diameter changes at pellet interface locations were about 0.9% and 0.6% for higher density and standard density fuel respectively. (author)

Novel Radiobiological Gamma Index for Evaluation of 3-Dimensional Predicted Dose Distribution

Energy Technology Data Exchange (ETDEWEB)

Sumida, Iori, E-mail: sumida@radonc.med.osaka-u.ac.jp [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Yamaguchi, Hajime; Kizaki, Hisao; Aboshi, Keiko; Tsujii, Mari; Yoshikawa, Nobuhiko; Yamada, Yuji [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan); Suzuki, Osamu; Seo, Yuji [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Isohashi, Fumiaki [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan); Yoshioka, Yasuo [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Ogawa, Kazuhiko [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan)

2015-07-15

Purpose: To propose a gamma index-based dose evaluation index that integrates the radiobiological parameters of tumor control (TCP) and normal tissue complication probabilities (NTCP). Methods and Materials: Fifteen prostate and head and neck (H&N) cancer patients received intensity modulated radiation therapy. Before treatment, patient-specific quality assurance was conducted via beam-by-beam analysis, and beam-specific dose error distributions were generated. The predicted 3-dimensional (3D) dose distribution was calculated by back-projection of relative dose error distribution per beam. A 3D gamma analysis of different organs (prostate: clinical [CTV] and planned target volumes [PTV], rectum, bladder, femoral heads; H&N: gross tumor volume [GTV], CTV, spinal cord, brain stem, both parotids) was performed using predicted and planned dose distributions under 2%/2 mm tolerance and physical gamma passing rate was calculated. TCP and NTCP values were calculated for voxels with physical gamma indices (PGI) >1. We propose a new radiobiological gamma index (RGI) to quantify the radiobiological effects of TCP and NTCP and calculate radiobiological gamma passing rates. Results: The mean RGI gamma passing rates for prostate cases were significantly different compared with those of PGI (P<.03–.001). The mean RGI gamma passing rates for H&N cases (except for GTV) were significantly different compared with those of PGI (P<.001). Differences in gamma passing rates between PGI and RGI were due to dose differences between the planned and predicted dose distributions. Radiobiological gamma distribution was visualized to identify areas where the dose was radiobiologically important. Conclusions: RGI was proposed to integrate radiobiological effects into PGI. This index would assist physicians and medical physicists not only in physical evaluations of treatment delivery accuracy, but also in clinical evaluations of predicted dose distribution.

Prediction of axial limit capacity of stone columns using dimensional analysis

Science.gov (United States)

Nazaruddin A., T.; Mohamed, Zainab; Mohd Azizul, L.; Hafez M., A.

2017-08-01

Stone column is the most favorable method used by engineers in designing work for stabilization of soft ground for road embankment, and foundation for liquid structure. Easy installation and cheaper cost are among the factors that make stone column more preferable than other method. Furthermore, stone column also can acts as vertical drain to increase the rate of consolidation during preloading stage before construction work started. According to previous studied there are several parameters that influence the capacity of stone column. Among of them are angle friction of among the stones, arrangement of column (two pattern arrangement most applied triangular and square), spacing center to center between columns, shear strength of soil, and physical size of column (diameter and length). Dimensional analysis method (Buckingham-Pi Theorem) has used to carry out the new formula for prediction of load capacity stone columns. Experimental data from two previous studies was used for analysis of study.

An analytical one-dimensional model for predicting waste package performance

International Nuclear Information System (INIS)

Relyea, J.F.; Wood, M.I.

1984-01-01

A method for allocating waste package performance requirements among waste package components with regard to radionuclide isolation has been developed. Modification or change in this approach can be expected as the understanding of radionuclide behavior in the waste package improves. Thus, the performance requirements derived in this document are preliminary and subject to change. However, this kind of analysis is a useful starting point. It has also proved useful for identifying a small group of radionuclides which should be emphasized in a laboratory experimental program designed to characterize the behavior of specific radionuclides in the waste package environment. A simple one-dimensional, two media transport model has been derived and used to calculate radionuclide transport from the waste form-packing material interface of the waste package into the host rock. Cumulative release over 10,000 years, maximum yearly releases and release rates at the packing material-host rock interface were evaluated on a radionuclide-by radionuclide basis. The major parameters controlling radionuclide release were found to be: radionuclide solubility, porosity of the rock, isotopic ratio of the radionuclide and surface area of the waste form-packing material interface. 15 refs., 2 figs., 16 tabs

Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

Science.gov (United States)

Li, Zhijin; Chao, Yi; Li, P. Peggy

2012-01-01

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

Two- and three-dimensional accuracy of dental impression materials: effects of storage time and moisture contamination.

Science.gov (United States)

Chandran, Deepa T; Jagger, Daryll C; Jagger, Robert G; Barbour, Michele E

2010-01-01

Dental impression materials are used to create an inverse replica of the dental hard and soft tissues, and are used in processes such as the fabrication of crowns and bridges. The accuracy and dimensional stability of impression materials are of paramount importance to the accuracy of fit of the resultant prosthesis. Conventional methods for assessing the dimensional stability of impression materials are two-dimensional (2D), and assess shrinkage or expansion between selected fixed points on the impression. In this study, dimensional changes in four impression materials were assessed using an established 2D and an experimental three-dimensional (3D) technique. The former involved measurement of the distance between reference points on the impression; the latter a contact scanning method for producing a computer map of the impression surface showing localised expansion, contraction and warpage. Dimensional changes were assessed as a function of storage times and moisture contamination comparable to that found in clinical situations. It was evident that dimensional changes observed using the 3D technique were not always apparent using the 2D technique, and that the former offers certain advantages in terms of assessing dimensional accuracy and predictability of impression methods. There are, however, drawbacks associated with 3D techniques such as the more time-consuming nature of the data acquisition and difficulty in statistically analysing the data.

Predicting tropospheric ozone and hydroxyl radical in a global, three-dimensional, chemistry, transport, and deposition model

Energy Technology Data Exchange (ETDEWEB)

Atherton, C.S.

1995-01-05

Two of the most important chemically reactive tropospheric gases are ozone (O{sub 3}) and the hydroxyl radical (OH). Although ozone in the stratosphere is a necessary protector against the sun`s radiation, tropospheric ozone is actually a pollutant which damages materials and vegetation, acts as a respiratory irritant, and is a greenhouse gas. One of the two main sources of ozone in the troposphere is photochemical production. The photochemistry is initiated when hydrocarbons and carbon monoxide (CO) react with nitrogen oxides (NO{sub x} = NO + NO{sub 2}) in the presence of sunlight. Reaction with the hydroxyl radical, OH, is the main sink for many tropospheric gases. The hydroxyl radical is highly reactive and has a lifetime on the order of seconds. Its formation is initiated by the photolysis of tropospheric ozone. Tropospheric chemistry involves a complex, non-linear set of chemical reactions between atmospheric species that vary substantially in time and space. To model these and other species on a global scale requires the use of a global, three-dimensional chemistry, transport, and deposition (CTD) model. In this work, I developed two such three dimensional CTD models. The first model incorporated the chemistry necessary to model tropospheric ozone production from the reactions of nitrogen oxides with carbon monoxide (CO) and methane (CH{sub 4}). The second also included longer-lived alkane species and the biogenic hydrocarbon isoprene, which is emitted by growing plants and trees. The models` ability to predict a number of key variables (including the concentration of O{sub 3}, OH, and other species) were evaluated. Then, several scenarios were simulated to understand the change in the chemistry of the troposphere since preindustrial times and the role of anthropogenic NO{sub x} on present day conditions.

Development of migration prediction system (MIGSTEM) for cationic species of radionuclides through soil layers

International Nuclear Information System (INIS)

Ohnuki, Toshihiko; Takebe, Shinichi; Yamamoto, Tadatoshi

1989-01-01

The migration prediction system (MIGSTEM) has been developed for estimating the migration of cationic species of radionuclides through soil layers systematically. The MIGSTEM consists of the migration experiments, the one-dimensional fitting code (inverse analysis code) for determining retardation factor and dispersivity (migration factors) and the three-dimensional differential code (prediction code) for estimating the migration of the radionuclides. The migration experiments are carried out for obtaining the concentration profiles of the radionuclides in unsaturated and saturated soil layers. Using the inverse analysis code, the migration factors are obtained at one time by fitting the concentration profiles calculated to those observed. The prediction code can give the contours of concentration and the one-dimensional concentration profiles at selected time, as well as the changing in the concentration at a selected position with time. The validity of the MIGSTEM was obtained by the benchmark test on the prediction and inverse analysis codes. The MIGSTEM was applied to estimate the migration of Sr 2+ through the sandy soil. (author)

Redox transitions in strontium vanadates: Electrical conductivity and dimensional changes

International Nuclear Information System (INIS)

Macías, J.; Yaremchenko, A.A.; Frade, J.R.

2014-01-01

Highlights: • Electrical conductivity and thermal expansion of strontium vanadates are measured. • Conductivity of SrVO 3−δ is 10 6 –10 8 times higher compared to Sr 2 V 2 O 7 and Sr 3 V 2 O 8 . • Sr 2 V 2 O 7 transforms on reduction to SrVO 3−δ via (5Sr 3 V 2 O 8 + SrV 6 O 11 ) intermediate. • This process is kinetically stagnated due to good redox stability of Sr 3 V 2 O 8 . • Large volume changes on Sr 2 V 2 O 7 ↔ SrVO 3 transformation are confirmed by dilatometry. - Abstract: The reversibility of redox-induced phase transformations and accompanying electrical conductivity and dimensional changes in perovskite-type SrVO 3−δ , a parent material for a family of potential solid oxide fuel cell anode materials, were evaluated employing X-ray diffraction, thermal analysis, dilatometry and electrical measurements. At 873–1273 K, the electrical conductivity of SrVO 3−δ is metallic-like and 6–8 orders of magnitude higher compared to semiconducting V 5+ -based strontium pyrovanadate Sr 2 V 2 O 7 and strontium orthovanadate Sr 3 V 2 O 8 existing under oxidizing conditions. SrVO 3−δ is easily oxidized to a pyrovanadate phase at atmospheric oxygen pressure. Inverse reduction in 10%H 2 –90%N 2 atmosphere occurs in two steps through (5Sr 3 V 2 O 8 + SrV 6 O 11 ) intermediate. As Sr 3 V 2 O 8 is relatively stable even under reducing conditions, the perovskite phase and its high level of electrical conductivity cannot be recovered completely in a reasonable time span at temperatures ⩽1273 K. Dilatometric studies confirmed that SrVO 3 ↔ Sr 2 V 2 O 7 redox transformation is accompanied with significant dimensional changes. Their extent depends on the degree of phase conversion and, apparently, on microstructural features

Comparison of zero-dimensional and one-dimensional thermonuclear burn computations for the reversed-field pinch reactor (RFPR)

International Nuclear Information System (INIS)

Nebel, R.A.; Hagenson, R.L.; Moses, R.W.; Krakowski, R.A.

1980-01-01

Conceptual fusion reactor designs of the Reversed-Field Pinch Reactor (RFPR) have been based on profile-averaged zero-dimensional (point) plasma models. The plasma response/performance that has been predicted by the point plasma model is re-examined by a comprehensive one-dimensional (radial) burn code that has been developed and parametrically evaluated for the RFPR. Agreement is good between the zero-dimensional and one-dimensional models, giving more confidence in the RFPR design point reported previously from the zero-dimensional analysis

The direct field boundary impedance of two-dimensional periodic structures with application to high frequency vibration prediction.

Science.gov (United States)

Langley, Robin S; Cotoni, Vincent

2010-04-01

Large sections of many types of engineering construction can be considered to constitute a two-dimensional periodic structure, with examples ranging from an orthogonally stiffened shell to a honeycomb sandwich panel. In this paper, a method is presented for computing the boundary (or edge) impedance of a semi-infinite two-dimensional periodic structure, a quantity which is referred to as the direct field boundary impedance matrix. This terminology arises from the fact that none of the waves generated at the boundary (the direct field) are reflected back to the boundary in a semi-infinite system. The direct field impedance matrix can be used to calculate elastic wave transmission coefficients, and also to calculate the coupling loss factors (CLFs), which are required by the statistical energy analysis (SEA) approach to predicting high frequency vibration levels in built-up systems. The calculation of the relevant CLFs enables a two-dimensional periodic region of a structure to be modeled very efficiently as a single subsystem within SEA, and also within related methods, such as a recently developed hybrid approach, which couples the finite element method with SEA. The analysis is illustrated by various numerical examples involving stiffened plate structures.

Prediction of optimal deployment projection for transcatheter aortic valve replacement: angiographic 3-dimensional reconstruction of the aortic root versus multidetector computed tomography.

OpenAIRE

Binder Ronald K; Leipsic Jonathon; Wood David; Moore Teri; Toggweiler Stefan; Willson Alex; Gurvitch Ronen; Freeman Melanie; Webb John G

2012-01-01

BACKGROUND Identifying the optimal fluoroscopic projection of the aortic valve is important for successful transcatheter aortic valve replacement (TAVR). Various imaging modalities including multidetector computed tomography (MDCT) have been proposed for prediction of the optimal deployment projection. We evaluated a method that provides 3 dimensional angiographic reconstructions (3DA) of the aortic root for prediction of the optimal deployment angle and compared it with MDCT. METHODS AND RES...

Pyridine-induced Dimensionality Change in Hybrid Perovskite Nanocrystals

KAUST Repository

Ahmed, Ghada H.

2017-05-02

Engineering the surface energy through careful manipulation of the surface chemistry is a convenient approach to control quantum confinement and structure dimensionality during nanocrystal growth. Here, we demonstrate that the introduction of pyridine during the synthesis of methylammonium lead bromide (MAPbBr) perovskite nanocrystals can transform three-dimensional (3D) cubes into two-dimensional (2D) nanostructures. Density functional theory (DFT) calculations show that pyridine preferentially binds to Pb atoms terminating the surface, driving the selective 2D growth of the nanostructures. These 2D nanostructures exhibit strong quantum confinement effects, high photoluminescence quantum yields in the visible spectral range, and efficient charge transfer to molecular acceptors. These qualities indicate the suitability of the synthesized 2D nanostructures for a wide range of optoelectronic applications.

Environmental, Transient, Three-Dimensional, Hydrothermal, Mass Transport Code - FLESCOT

Energy Technology Data Exchange (ETDEWEB)

Onishi, Yasuo [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bao, Jie [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Glass, Kevin A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Eyler, L. L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Okumura, Masahiko [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-03-28

The purpose of the project was to modify and apply the transient, three-dimensional FLESCOT code to be able to effectively simulate cesium behavior in Fukushima lakes/dam reservoirs, river mouths, and coastal areas. The ultimate objective of the FLESCOT simulation is to predict future changes of cesium accumulation in Fukushima area reservoirs and costal water. These evaluation results will assist ongoing and future environmental remediation activities and policies in a systematic and comprehensive manner.

Rotary engine performance limits predicted by a zero-dimensional model

Science.gov (United States)

Bartrand, Timothy A.; Willis, Edward A.

1992-01-01

A parametric study was performed to determine the performance limits of a rotary combustion engine. This study shows how well increasing the combustion rate, insulating, and turbocharging increase brake power and decrease fuel consumption. Several generalizations can be made from the findings. First, it was shown that the fastest combustion rate is not necessarily the best combustion rate. Second, several engine insulation schemes were employed for a turbocharged engine. Performance improved only for a highly insulated engine. Finally, the variability of turbocompounding and the influence of exhaust port shape were calculated. Rotary engines performance was predicted by an improved zero-dimensional computer model based on a model developed at the Massachusetts Institute of Technology in the 1980's. Independent variables in the study include turbocharging, manifold pressures, wall thermal properties, leakage area, and exhaust port geometry. Additions to the computer programs since its results were last published include turbocharging, manifold modeling, and improved friction power loss calculation. The baseline engine for this study is a single rotor 650 cc direct-injection stratified-charge engine with aluminum housings and a stainless steel rotor. Engine maps are provided for the baseline and turbocharged versions of the engine.

Changes in Predictive Task Switching with Age and with Cognitive Load.

Science.gov (United States)

Levy-Tzedek, Shelly

2017-01-01

Predictive control of movement is more efficient than feedback-based control, and is an important skill in everyday life. We tested whether the ability to predictively control movements of the upper arm is affected by age and by cognitive load. A total of 63 participants were tested in two experiments. In both experiments participants were seated, and controlled a cursor on a computer screen by flexing and extending their dominant arm. In Experiment 1, 20 young adults and 20 older adults were asked to continuously change the frequency of their horizontal arm movements, with the goal of inducing an abrupt switch between discrete movements (at low frequencies) and rhythmic movements (at high frequencies). We tested whether that change was performed based on a feed-forward (predictive) or on a feedback (reactive) control. In Experiment 2, 23 young adults performed the same task, while being exposed to a cognitive load half of the time via a serial subtraction task. We found that both aging and cognitive load diminished, on average, the ability of participants to predictively control their movements. Five older adults and one young adult under a cognitive load were not able to perform the switch between rhythmic and discrete movement (or vice versa). In Experiment 1, 40% of the older participants were able to predictively control their movements, compared with 70% in the young group. In Experiment 2, 48% of the participants were able to predictively control their movements with a cognitively loading task, compared with 70% in the no-load condition. The ability to predictively change a motor plan in anticipation of upcoming changes may be an important component in performing everyday functions, such as safe driving and avoiding falls.

Prediction of three-dimensional arm trajectories based on ECoG signals recorded from human sensorimotor cortex.

Directory of Open Access Journals (Sweden)

Yasuhiko Nakanishi

Full Text Available Brain-machine interface techniques have been applied in a number of studies to control neuromotor prostheses and for neurorehabilitation in the hopes of providing a means to restore lost motor function. Electrocorticography (ECoG has seen recent use in this regard because it offers a higher spatiotemporal resolution than non-invasive EEG and is less invasive than intracortical microelectrodes. Although several studies have already succeeded in the inference of computer cursor trajectories and finger flexions using human ECoG signals, precise three-dimensional (3D trajectory reconstruction for a human limb from ECoG has not yet been achieved. In this study, we predicted 3D arm trajectories in time series from ECoG signals in humans using a novel preprocessing method and a sparse linear regression. Average Pearson's correlation coefficients and normalized root-mean-square errors between predicted and actual trajectories were 0.44~0.73 and 0.18~0.42, respectively, confirming the feasibility of predicting 3D arm trajectories from ECoG. We foresee this method contributing to future advancements in neuroprosthesis and neurorehabilitation technology.

A novel two-dimensional liquid chromatographic system for the online toxicity prediction of pharmaceuticals and related substances

Energy Technology Data Exchange (ETDEWEB)

Li, Jian; Xu, Li [Tongji School of Pharmacy, Huazhong University of Science and Technology, Wuhan 430030 (China); Shi, Zhi-guo, E-mail: shizg@whu.edu.cn [Department of Chemistry, Wuhan University, Wuhan 430072 (China); Hu, Min [Hubei Instrument for Food and Drug Control, Wuhan (China)

2015-08-15

Highlights: • A novel two-dimensional liquid chromatographic system was developed. • The 1st dimension was ODS to separate components in the sample. • The 2nd dimension was biopartitioning micellar chromatography to predict toxicity. • The system was used to screen toxicity of pharmaceuticals and related substances. • It was promising for fast online toxicity screening of complex sample in one step. - Abstract: In this study, a novel two-dimensional liquid chromatographic (2D-LC) system was developed for simultaneous separation and toxicity prediction of pharmaceutical and its related substances. A conventional ODS column was used on the 1st-D to separate the sample; while, bio-partitioning micellar chromatography served as the 2nd-D to predict toxicity of the components. The established system was tested for the toxicity of ibuprofen and its impurities with known toxicity. With only one injection, ibuprofen and its impurities were separated on the 1st-D; and LC50 values of individual impurity were obtained based on the quantitative retention–activity relationships, which agreed well with the reported data. Furthermore, LC50 values of photolysis transformation products (TPs) of carprofen, ketoprofen and diclofenac acid (as unknown compounds) were screened in this 2D-LC system, which could be an indicator of the toxicity of these TPs and was meaningful for the environmental monitoring and drinking water treatment. The established 2D-LC system was cost-effective, time-saving and reliable, and was promising for fast online screening of toxicity of known and unknown analytes in the complex sample in a single step. It may find applications in environment, pharmaceutical and food, etc.

A novel two-dimensional liquid chromatographic system for the online toxicity prediction of pharmaceuticals and related substances

International Nuclear Information System (INIS)

Li, Jian; Xu, Li; Shi, Zhi-guo; Hu, Min

2015-01-01

Highlights: • A novel two-dimensional liquid chromatographic system was developed. • The 1st dimension was ODS to separate components in the sample. • The 2nd dimension was biopartitioning micellar chromatography to predict toxicity. • The system was used to screen toxicity of pharmaceuticals and related substances. • It was promising for fast online toxicity screening of complex sample in one step. - Abstract: In this study, a novel two-dimensional liquid chromatographic (2D-LC) system was developed for simultaneous separation and toxicity prediction of pharmaceutical and its related substances. A conventional ODS column was used on the 1st-D to separate the sample; while, bio-partitioning micellar chromatography served as the 2nd-D to predict toxicity of the components. The established system was tested for the toxicity of ibuprofen and its impurities with known toxicity. With only one injection, ibuprofen and its impurities were separated on the 1st-D; and LC50 values of individual impurity were obtained based on the quantitative retention–activity relationships, which agreed well with the reported data. Furthermore, LC50 values of photolysis transformation products (TPs) of carprofen, ketoprofen and diclofenac acid (as unknown compounds) were screened in this 2D-LC system, which could be an indicator of the toxicity of these TPs and was meaningful for the environmental monitoring and drinking water treatment. The established 2D-LC system was cost-effective, time-saving and reliable, and was promising for fast online screening of toxicity of known and unknown analytes in the complex sample in a single step. It may find applications in environment, pharmaceutical and food, etc

Ab Initio Prediction of Piezoelectricity in Two-Dimensional Materials.

Science.gov (United States)

Blonsky, Michael N; Zhuang, Houlong L; Singh, Arunima K; Hennig, Richard G

2015-10-27

Two-dimensional (2D) materials present many unique materials concepts, including material properties that sometimes differ dramatically from those of their bulk counterparts. One of these properties, piezoelectricity, is important for micro- and nanoelectromechanical systems applications. Using symmetry analysis, we determine the independent piezoelectric coefficients for four groups of predicted and synthesized 2D materials. We calculate with density-functional perturbation theory the stiffness and piezoelectric tensors of these materials. We determine the in-plane piezoelectric coefficient d11 for 37 materials within the families of 2D metal dichalcogenides, metal oxides, and III-V semiconductor materials. A majority of the structures, including CrSe2, CrTe2, CaO, CdO, ZnO, and InN, have d11 coefficients greater than 5 pm/V, a typical value for bulk piezoelectric materials. Our symmetry analysis shows that buckled 2D materials exhibit an out-of-plane coefficient d31. We find that d31 for 8 III-V semiconductors ranges from 0.02 to 0.6 pm/V. From statistical analysis, we identify correlations between the piezoelectric coefficients and the electronic and structural properties of the 2D materials that elucidate the origin of the piezoelectricity. Among the 37 2D materials, CdO, ZnO, and CrTe2 stand out for their combination of large piezoelectric coefficient and low formation energy and are recommended for experimental exploration.

Change in avian abundance predicted from regional forest inventory data

Science.gov (United States)

Twedt, Daniel J.; Tirpak, John M.; Jones-Farrand, D. Todd; Thompson, Frank R.; Uihlein, William B.; Fitzgerald, Jane A.

2010-01-01

An inability to predict population response to future habitat projections is a shortcoming in bird conservation planning. We sought to predict avian response to projections of future forest conditions that were developed from nationwide forest surveys within the Forest Inventory and Analysis (FIA) program. To accomplish this, we evaluated the historical relationship between silvicolous bird populations and FIA-derived forest conditions within 25 ecoregions that comprise the southeastern United States. We aggregated forest area by forest ownership, forest type, and tree size-class categories in county-based ecoregions for 5 time periods spanning 1963-2008. We assessed the relationship of forest data with contemporaneous indices of abundance for 24 silvicolous bird species that were obtained from Breeding Bird Surveys. Relationships between bird abundance and forest inventory data for 18 species were deemed sufficient as predictive models. We used these empirically derived relationships between regional forest conditions and bird populations to predict relative changes in abundance of these species within ecoregions that are anticipated to coincide with projected changes in forest variables through 2040. Predicted abundances of these 18 species are expected to remain relatively stable in over a quarter (27%) of the ecoregions. However, change in forest area and redistribution of forest types will likely result in changed abundance of some species within many ecosystems. For example, abundances of 11 species, including pine warbler (Dendroica pinus), brown-headed nuthatch (Sitta pusilla), and chuckwills- widow (Caprimulgus carolinensis), are projected to increase within more ecoregions than ecoregions where they will decrease. For 6 other species, such as blue-winged warbler (Vermivora pinus), Carolina wren (Thryothorus ludovicianus), and indigo bunting (Passerina cyanea), we projected abundances will decrease within more ecoregions than ecoregions where they will

Changing predictions, stable recognition: Children's representations of downward incline motion.

Science.gov (United States)

Hast, Michael; Howe, Christine

2017-11-01

Various studies to-date have demonstrated children hold ill-conceived expressed beliefs about the physical world such as that one ball will fall faster than another because it is heavier. At the same time, they also demonstrate accurate recognition of dynamic events. How these representations relate is still unresolved. This study examined 5- to 11-year-olds' (N = 130) predictions and recognition of motion down inclines. Predictions were typically in error, matching previous work, but children largely recognized correct events as correct and rejected incorrect ones. The results also demonstrate while predictions change with increasing age, recognition shows signs of stability. The findings provide further support for a hybrid model of object representations and argue in favour of stable core cognition existing alongside developmental changes. Statement of contribution What is already known on this subject? Children's predictions of physical events show limitations in accuracy Their recognition of such events suggests children may use different knowledge sources in their reasoning What the present study adds? Predictions fluctuate more strongly than recognition, suggesting stable core cognition But recognition also shows some fluctuation, arguing for a hybrid model of knowledge representation. © 2017 The British Psychological Society.

Prediction of Land Use Change Based on Markov and GM(1,1 Models

Directory of Open Access Journals (Sweden)

SUN Yi-yang

2016-05-01

Full Text Available In order to explore the law of land use change in Laiwu City, Markov and GM(1,1 were respectively employed in the prediction of land use change in Laiwu from 2015 to 2050, after which the results were analyzed and discussed. The results showed that:(1The variational trends of all kinds of land use change predicted by the two models were consistent and the goodness of fit of the predictive value in corresponding years in the near future was high, illustrating that the predicted results in the near future were credible and the trend predicted in mid long term could be used as reference. (2The cultivated land would remanin almost no change from 2015 to 2020, and then gradually decreaseed in a small range from 2020 to 2050. The garden, the woodland, the grassland always reducing and the decreare range of the grassland was the largest. The urban village and industrial and mining land, the transportation land would be continuously increased and the range of urban village and industrial and mining land was the largest. The water and water conservancy facilities land and the other land would be always reduced in a very small range. It could be concluded that the results predicted by the two models in the near future were credible and could provide scientific basis for land use planning of Laiwu, while the method could provide reference for the prediction of land use change.

"Engage" therapy: Prediction of change of late-life major depression.

Science.gov (United States)

Alexopoulos, George S; O'Neil, Robert; Banerjee, Samprit; Raue, Patrick J; Victoria, Lindsay W; Bress, Jennifer N; Pollari, Cristina; Arean, Patricia A

2017-10-15

Engage grew out of the need for streamlined psychotherapies that can be accurately used by community therapists in late-life depression. Engage was based on the view that dysfunction of reward networks is the principal mechanism mediating depressive symptoms. Accordingly, Engage uses "reward exposure" (exposure to meaningful activities) and assumes that repeated activation of reward networks will normalize these systems. This study examined whether change in a behavioral activation scale, an index of reward system function, predicts change in depressive symptomatology. The participants (N = 48) were older adults with major depression treated with 9 weekly sessions of Engage and assessed 27 weeks after treatment. Depression was assessed with the 24-item Hamilton Depression Rating Scale (HAM-D) and behavioral activation with the four subscales of Behavioral Activation for Depression Scale (activation, avoidance/rumination, work impairment, social impairment) at baseline, 6 weeks (mid-treatment), 9 weeks (end of treatment), and 36 weeks. Change only in the Activation subscale during successive periods of assessment predicted depression severity (HAM-D) at the end of each period (F 1, 47 = 21.05, psocial support. Change in behavioral activation predicts improvement of depressive symptoms and signs in depressed older adults treated with Engage. Copyright © 2017. Published by Elsevier B.V.

Controlled test for predictive power of Lyapunov exponents: their inability to predict epileptic seizures.

Science.gov (United States)

Lai, Ying-Cheng; Harrison, Mary Ann F; Frei, Mark G; Osorio, Ivan

2004-09-01

Lyapunov exponents are a set of fundamental dynamical invariants characterizing a system's sensitive dependence on initial conditions. For more than a decade, it has been claimed that the exponents computed from electroencephalogram (EEG) or electrocorticogram (ECoG) signals can be used for prediction of epileptic seizures minutes or even tens of minutes in advance. The purpose of this paper is to examine the predictive power of Lyapunov exponents. Three approaches are employed. (1) We present qualitative arguments suggesting that the Lyapunov exponents generally are not useful for seizure prediction. (2) We construct a two-dimensional, nonstationary chaotic map with a parameter slowly varying in a range containing a crisis, and test whether this critical event can be predicted by monitoring the evolution of finite-time Lyapunov exponents. This can thus be regarded as a "control test" for the claimed predictive power of the exponents for seizure. We find that two major obstacles arise in this application: statistical fluctuations of the Lyapunov exponents due to finite time computation and noise from the time series. We show that increasing the amount of data in a moving window will not improve the exponents' detective power for characteristic system changes, and that the presence of small noise can ruin completely the predictive power of the exponents. (3) We report negative results obtained from ECoG signals recorded from patients with epilepsy. All these indicate firmly that, the use of Lyapunov exponents for seizure prediction is practically impossible as the brain dynamical system generating the ECoG signals is more complicated than low-dimensional chaotic systems, and is noisy. Copyright 2004 American Institute of Physics

Three-Dimensional Simulation of Ultrasound-Induced Microalgal Cell Disruption.

Science.gov (United States)

Wang, M; Yuan, W; Hale, Andy

2016-03-01

The three-dimensional distribution (x, y, and z) of ultrasound-induced microalgal cell disruption in a sonochemical reactor was predicted by solving the Helmholtz equation using a three-dimensional acoustic module in the COMSOL Multiphysics software. The simulated local ultrasound pressure at any given location (x, y, and z) was found to correlate with cell disruption of a freshwater alga, Scenedesmus dimorphus, represented by the change of algal cell particle/debris concentration, chlorophyll-a fluorescence density (CAFD), and Nile red stained lipid fluorescence density (LFD), which was also validated by the model reaction of potassium iodide oxidation (the Weissler reaction). Furthermore, the effect of ultrasound power intensity and processing duration on algal cell disruption was examined to address the limitation of the model.

Prognostic value of three-dimensional ultrasound for fetal hydronephrosis

Science.gov (United States)

WANG, JUNMEI; YING, WEIWEN; TANG, DAXING; YANG, LIMING; LIU, DONGSHENG; LIU, YUANHUI; PAN, JIAOE; XIE, XING

2015-01-01

The present study evaluated the prognostic value of three-dimensional ultrasound for fetal hydronephrosis. Pregnant females with fetal hydronephrosis were enrolled and a novel three-dimensional ultrasound indicator, renal parenchymal volume/kidney volume, was introduced to predict the postnatal prognosis of fetal hydronephrosis in comparison with commonly used ultrasound indicators. All ultrasound indicators of fetal hydronephrosis could predict whether postnatal surgery was required for fetal hydronephrosis; however, the predictive performance of renal parenchymal volume/kidney volume measurements as an individual indicator was the highest. In conclusion, ultrasound is important in predicting whether postnatal surgery is required for fetal hydronephrosis, and the three-dimensional ultrasound indicator renal parenchymal volume/kidney volume has a high predictive performance. Furthermore, the majority of cases of fetal hydronephrosis spontaneously regress subsequent to birth, and the regression time is closely associated with ultrasound indicators. PMID:25667626

Predicting Climate Change Impacts to the Canadian Boreal Forest

Directory of Open Access Journals (Sweden)

Trisalyn A. Nelson

2014-03-01

Full Text Available Climate change is expected to alter temperature, precipitation, and seasonality with potentially acute impacts on Canada’s boreal. In this research we predicted future spatial distributions of biodiversity in Canada’s boreal for 2020, 2050, and 2080 using indirect indicators derived from remote sensing and based on vegetation productivity. Vegetation productivity indices, representing annual amounts and variability of greenness, have been shown to relate to tree and wildlife richness in Canada’s boreal. Relationships between historical satellite-derived productivity and climate data were applied to modelled scenarios of future climate to predict and map potential future vegetation productivity for 592 regions across Canada. Results indicated that the pattern of vegetation productivity will become more homogenous, particularly west of Hudson Bay. We expect climate change to impact biodiversity along north/south gradients and by 2080 vegetation distributions will be dominated by processes of seasonality in the north and a combination of cumulative greenness and minimum cover in the south. The Hudson Plains, which host the world’s largest and most contiguous wetland, are predicted to experience less seasonality and more greenness. The spatial distribution of predicted trends in vegetation productivity was emphasized over absolute values, in order to support regional biodiversity assessments and conservation planning.

A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

Directory of Open Access Journals (Sweden)

M Irfan Ashraf

Full Text Available Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model. Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2 5-year(-1 and volume: 0.0008 m(3 5-year(-1. Model variability described by root mean squared error (RMSE in basal area prediction was 40.53 cm(2 5-year(-1 and 0.0393 m(3 5-year(-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence

A Multi-layer Hybrid Framework for Dimensional Emotion Classification

NARCIS (Netherlands)

Nicolaou, Mihalis A.; Gunes, Hatice; Pantic, Maja

2011-01-01

This paper investigates dimensional emotion prediction and classification from naturalistic facial expressions. Similarly to many pattern recognition problems, dimensional emotion classification requires generating multi-dimensional outputs. To date, classification for valence and arousal dimensions

Catchment coevolution: A useful framework for improving predictions of hydrological change?

Science.gov (United States)

Troch, Peter A.

2017-04-01

The notion that landscape features have co-evolved over time is well known in the Earth sciences. Hydrologists have recently called for a more rigorous connection between emerging spatial patterns of landscape features and the hydrological response of catchments, and have termed this concept catchment coevolution. In this presentation we present a general framework of catchment coevolution that could improve predictions of hydrologic change. We first present empirical evidence of the interaction and feedback of landscape evolution and changes in hydrological response. From this review it is clear that the independent drivers of catchment coevolution are climate, geology, and tectonics. We identify common currency that allows comparing the levels of activity of these independent drivers, such that, at least conceptually, we can quantify the rate of evolution or aging. Knowing the hydrologic age of a catchment by itself is not very meaningful without linking age to hydrologic response. Two avenues of investigation have been used to understand the relationship between (differences in) age and hydrological response: (i) one that is based on relating present landscape features to runoff processes that are hypothesized to be responsible for the current fingerprints in the landscape; and (ii) one that takes advantage of an experimental design known as space-for-time substitution. Both methods have yielded significant insights in the hydrologic response of landscapes with different histories. If we want to make accurate predictions of hydrologic change, we will also need to be able to predict how the catchment will further coevolve in association with changes in the activity levels of the drivers (e.g., climate). There is ample evidence in the literature that suggests that whole-system prediction of catchment coevolution is, at least in principle, plausible. With this imperative we outline a research agenda that implements the concepts of catchment coevolution for building

Multi-perspective views of students’ difficulties with one-dimensional vector and two-dimensional vector

Science.gov (United States)

Fauzi, Ahmad; Ratna Kawuri, Kunthi; Pratiwi, Retno

2017-01-01

Researchers of students’ conceptual change usually collects data from written tests and interviews. Moreover, reports of conceptual change often simply refer to changes in concepts, such as on a test, without any identification of the learning processes that have taken place. Research has shown that students have difficulties with vectors in university introductory physics courses and high school physics courses. In this study, we intended to explore students’ understanding of one-dimensional and two-dimensional vector in multi perspective views. In this research, we explore students’ understanding through test perspective and interviews perspective. Our research study adopted the mixed-methodology design. The participants of this research were sixty students of third semester of physics education department. The data of this research were collected by testand interviews. In this study, we divided the students’ understanding of one-dimensional vector and two-dimensional vector in two categories, namely vector skills of the addition of one-dimensionaland two-dimensional vector and the relation between vector skills and conceptual understanding. From the investigation, only 44% of students provided correct answer for vector skills of the addition of one-dimensional and two-dimensional vector and only 27% students provided correct answer for the relation between vector skills and conceptual understanding.

Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions.

Science.gov (United States)

Fox, Naomi J; Marion, Glenn; Davidson, Ross S; White, Piran C L; Hutchings, Michael R

2012-03-06

Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed.

Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions

Directory of Open Access Journals (Sweden)

Ross S. Davidson

2012-03-01

Full Text Available Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed.

Interrelated Dimensional Chains in Predicting Accuracy of Turbine Wheel Assembly Parameters

Science.gov (United States)

Yanyukina, M. V.; Bolotov, M. A.; Ruzanov, N. V.

2018-03-01

The working capacity of any device primarily depends on the assembly accuracy which, in its turn, is determined by the quality of each part manufactured, i.e., the degree of conformity between final geometrical parameters and the set ones. However, the assembly accuracy depends not only on a qualitative manufacturing process but also on the assembly process correctness. In this connection, there were preliminary calculations of assembly stages in terms of conformity to real geometrical parameters with their permissible values. This task is performed by means of the calculation of dimensional chains. The calculation of interrelated dimensional chains in the aircraft industry requires particular attention. The article considers the issues of dimensional chain calculation modelling by the example of the turbine wheel assembly process. The authors described the solution algorithm in terms of mathematical statistics implemented in Matlab. The paper demonstrated the results of a dimensional chain calculation for a turbine wheel in relation to the draw of turbine blades to the shroud ring diameter. Besides, the article provides the information on the influence of a geometrical parameter tolerance for the dimensional chain link elements on a closing one.

Three dimensional force prediction in a model linear brushless dc motor

Energy Technology Data Exchange (ETDEWEB)

Moghani, J.S.; Eastham, J.F.; Akmese, R.; Hill-Cottingham, R.J. (Univ. of Bath (United Kingdom). School of Electronic and Electric Engineering)

1994-11-01

Practical results are presented for the three axes forces produced on the primary of a linear brushless dc machine which is supplied from a three-phase delta-modulated inverter. Conditions of both lateral alignment and lateral displacement are considered. Finite element analysis using both two and three dimensional modeling is compared with the practical results. It is shown that a modified two dimensional model is adequate, where it can be used, in the aligned position and that the full three dimensional method gives good results when the machine is axially misaligned.

Three dimensional illustrating - three-dimensional vision and deception of sensibility

Directory of Open Access Journals (Sweden)

Anita Gánóczy

2009-03-01

Full Text Available The wide-spread digital photography and computer use gave the opportunity for everyone to make three-dimensional pictures and to make them public. The new opportunities with three-dimensional techniques give chance for the birth of new artistic photographs. We present in detail the biological roots of three-dimensional visualization, the phenomena of movement parallax, which can be used efficiently in making three-dimensional graphics, the Zöllner- and Corridor-illusion. There are present in this paper the visual elements, which contribute to define a plane two-dimensional image in three-dimension: coherent lines, the covering, the measurement changes, the relative altitude state, the abatement of detail profusion, the shadings and the perspective effects of colors.

Prediction of permeability changes in an excavation response zone

International Nuclear Information System (INIS)

Kinoshita, Naoto; Ishii, Takashi; Kuroda, Hidetaka; Tada, Hiroyuki

1992-01-01

In geologic disposal of radioactive wastes, stress changes due to cavern excavation may expand the existing fractures and create possible bypasses for groundwater. This paper proposes a simple method for predicting permeability changes in the excavation response zones. Numerical analyses using this method predict that the response zones created by cavern excavation would differ greatly in thickness and permeability depending on the depth of the cavern site and the initial in-situ stress, that when the cavern site is deeper, response zones would expand more and permeability would increases more, and that if the ratio of horizontal to vertical in-situ stress is small, extensive permeable zones at the crown and the bottom would occur, whereas if the ratio is large, extensive permeable zones would occur in the side walls. (orig.)

Two-dimensional global longitudinal strain is superior to left ventricular ejection fraction in prediction of outcome in patients with left-sided infective endocarditis

DEFF Research Database (Denmark)

Lauridsen, Trine Kiilerich; Alhede, Christina; Crowley, Anna Lisa

2018-01-01

BACKGROUND: Impaired cardiac function is the main predictor of poor outcome in infective endocarditis (IE). Global longitudinal strain (GLS) derived from two-dimensional strain echocardiography has proven superior in prediction of long-term outcome as compared to left ventricular ejection fraction...

Thermal and hydrologic responses to climate change predict marked alterations in boreal stream invertebrate assemblages.

Science.gov (United States)

Mustonen, Kaisa-Riikka; Mykrä, Heikki; Marttila, Hannu; Sarremejane, Romain; Veijalainen, Noora; Sippel, Kalle; Muotka, Timo; Hawkins, Charles P

2018-06-01

Air temperature at the northernmost latitudes is predicted to increase steeply and precipitation to become more variable by the end of the 21st century, resulting in altered thermal and hydrological regimes. We applied five climate scenarios to predict the future (2070-2100) benthic macroinvertebrate assemblages at 239 near-pristine sites across Finland (ca. 1200 km latitudinal span). We used a multitaxon distribution model with air temperature and modeled daily flow as predictors. As expected, projected air temperature increased the most in northernmost Finland. Predicted taxonomic richness also increased the most in northern Finland, congruent with the predicted northwards shift of many species' distributions. Compositional changes were predicted to be high even without changes in richness, suggesting that species replacement may be the main mechanism causing climate-induced changes in macroinvertebrate assemblages. Northern streams were predicted to lose much of the seasonality of their flow regimes, causing potentially marked changes in stream benthic assemblages. Sites with the highest loss of seasonality were predicted to support future assemblages that deviate most in compositional similarity from the present-day assemblages. Macroinvertebrate assemblages were also predicted to change more in headwaters than in larger streams, as headwaters were particularly sensitive to changes in flow patterns. Our results emphasize the importance of focusing protection and mitigation on headwater streams with high-flow seasonality because of their vulnerability to climate change. © 2018 John Wiley & Sons Ltd.

Predictive factors of gastroduodenal toxicity in cirrhotic patients after three-dimensional conformal radiotherapy for hepatocellular carcinoma

International Nuclear Information System (INIS)

Kim, Haeyoung; Lim, Do Hoon; Paik, Seung Woon; Yoo, Byung Chul; Koh, Kwang Gheol; Lee, Joon Hyoek; Choi, Moon Seok; Park, Won; Park, Hee Chul; Huh, Seung Jae; Choi, Doo Ho; Ahn, Yong Chan

2009-01-01

Background and purpose: To identify predictive factors for the development of gastroduodenal toxicity (GDT) in cirrhotic patients treated with three-dimensional conformal radiotherapy (3D-CRT) for hepatocellular carcinoma (HCC). Materials and methods: We retrospectively analyzed dose-volume histograms (DVHs) and clinical records of 73 cirrhotic patients treated with 3D-CRT for HCC. The median radiation dose was 36 Gy (range, 30-54 Gy) with a daily dose of 3 Gy. The grade of GDT was defined by the Common Toxicity Criteria Version 2. The predictive factors of grade 3 GDT were identified. Results: Grade 3 GDT was found in 9 patients. Patient's age and the percentage of gastroduodenal volume receiving more than 35 Gy (V 35 ) significantly affected the development of grade 3 GDT. Patients over 50 years of age developed grade 3 GDT more frequently than patients under 50 years of age. The risk of grade 3 GDT grew exponentially as V 35 increased. The 1-year actuarial rate of grade 3 GDT in patients with V 35 35 ≥5% (4% vs. 48%, p 35 were the most predictive factors for the development of grade 3 GDT in patients treated with RT.

An Improved Optimal Slip Ratio Prediction considering Tyre Inflation Pressure Changes

Directory of Open Access Journals (Sweden)

Guoxing Li

2015-01-01

Full Text Available The prediction of optimal slip ratio is crucial to vehicle control systems. Many studies have verified there is a definitive impact of tyre pressure change on the optimal slip ratio. However, the existing method of optimal slip ratio prediction has not taken into account the influence of tyre pressure changes. By introducing a second-order factor, an improved optimal slip ratio prediction considering tyre inflation pressure is proposed in this paper. In order to verify and evaluate the performance of the improved prediction, a cosimulation platform is developed by using MATLAB/Simulink and CarSim software packages, achieving a comprehensive simulation study of vehicle braking performance cooperated with an ABS controller. The simulation results show that the braking distances and braking time under different tyre pressures and initial braking speeds are effectively shortened with the improved prediction of optimal slip ratio. When the tyre pressure is slightly lower than the nominal pressure, the difference of braking performances between original optimal slip ratio and improved optimal slip ratio is the most obvious.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters

Science.gov (United States)

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, D.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

Predictive capabilities of a two-dimensional model in the ground water transport of radionuclides

International Nuclear Information System (INIS)

Gureghian, A.B.; Beskid, N.J.; Marmer, G.J.

1978-01-01

The discharge of low-level radioactive waste into tailings ponds is a potential source of ground water contamination. The estimation of the radiological hazards related to the ground water transport of radionuclides from tailings retention systems depends on reasonably accurate estimates of the movement of both water and solute. A two-dimensional mathematical model having predictive capability for ground water flow and solute transport has been developed. The flow equation has been solved under steady-state conditions and the mass transport equation under transient conditions. The simultaneous solution of both equations is achieved through the finite element technique using isoparametric elements, based on the Galerkin formulation. However, in contrast to the flow equation solution, the weighting functions used in the solution of the mass transport equation have a non-symmetric form. The predictive capability of the model is demonstrated using an idealized case based on analyses of field data obtained from the sites of operating uranium mills. The pH of the solution, which regulates the variation of the distribution coefficient (K/sub d/) in a particular site, appears to be the most important factor in the assessment of the rate of migration of the elements considered herein

Three-dimensional dental arch changes of patients submitted to orthodontic-surgical treatment for correction of Class II malocclusion

OpenAIRE

Peixoto,Adriano Porto; Pinto,Ary dos Santos; Garib,Daniela Gamba; Gonçalves,João Roberto

2014-01-01

INTRODUCTION: This study assessed the three-dimensional changes in the dental arch of patients submitted to orthodontic-surgical treatment for correction of Class II malocclusions at three different periods. METHODS: Landmarks previously identified on upper and lower dental casts were digitized on a three-dimensional digitizer MicroScribe-3DX and stored in Excel worksheets in order to assess the width, length and depth of patient's dental arches. RESULTS: During orthodontic preparation, the m...

On dimensional reduction over coset spaces

International Nuclear Information System (INIS)

Kapetanakis, D.; Zoupanos, G.

1990-01-01

Gauge theories defined in higher dimensions can be dimensionally reduced over coset spaces giving definite predictions for the resulting four-dimensional theory. We present the most interesting features of these theories as well as an attempt to construct a model with realistic low energy behaviour within this framework. (author)

A two-dimensional matrix correction for off-axis portal dose prediction errors

International Nuclear Information System (INIS)

Bailey, Daniel W.; Kumaraswamy, Lalith; Bakhtiari, Mohammad; Podgorsak, Matthew B.

2013-01-01

Purpose: This study presents a follow-up to a modified calibration procedure for portal dosimetry published by Bailey et al. [“An effective correction algorithm for off-axis portal dosimetry errors,” Med. Phys. 36, 4089–4094 (2009)]. A commercial portal dose prediction system exhibits disagreement of up to 15% (calibrated units) between measured and predicted images as off-axis distance increases. The previous modified calibration procedure accounts for these off-axis effects in most regions of the detecting surface, but is limited by the simplistic assumption of radial symmetry. Methods: We find that a two-dimensional (2D) matrix correction, applied to each calibrated image, accounts for off-axis prediction errors in all regions of the detecting surface, including those still problematic after the radial correction is performed. The correction matrix is calculated by quantitative comparison of predicted and measured images that span the entire detecting surface. The correction matrix was verified for dose-linearity, and its effectiveness was verified on a number of test fields. The 2D correction was employed to retrospectively examine 22 off-axis, asymmetric electronic-compensation breast fields, five intensity-modulated brain fields (moderate-high modulation) manipulated for far off-axis delivery, and 29 intensity-modulated clinical fields of varying complexity in the central portion of the detecting surface. Results: Employing the matrix correction to the off-axis test fields and clinical fields, predicted vs measured portal dose agreement improves by up to 15%, producing up to 10% better agreement than the radial correction in some areas of the detecting surface. Gamma evaluation analyses (3 mm, 3% global, 10% dose threshold) of predicted vs measured portal dose images demonstrate pass rate improvement of up to 75% with the matrix correction, producing pass rates that are up to 30% higher than those resulting from the radial correction technique alone. As

Neural response to pictorial health warning labels can predict smoking behavioral change.

Science.gov (United States)

Riddle, Philip J; Newman-Norlund, Roger D; Baer, Jessica; Thrasher, James F

2016-11-01

In order to improve our understanding of how pictorial health warning labels (HWLs) influence smoking behavior, we examined whether brain activity helps to explain smoking behavior above and beyond self-reported effectiveness of HWLs. We measured the neural response in the ventromedial prefrontal cortex (vmPFC) and the amygdala while adult smokers viewed HWLs. Two weeks later, participants' self-reported smoking behavior and biomarkers of smoking behavior were reassessed. We compared multiple models predicting change in self-reported smoking behavior (cigarettes per day [CPD]) and change in a biomarkers of smoke exposure (expired carbon monoxide [CO]). Brain activity in the vmPFC and amygdala not only predicted changes in CO, but also accounted for outcome variance above and beyond self-report data. Neural data were most useful in predicting behavioral change as quantified by the objective biomarker (CO). This pattern of activity was significantly modulated by individuals' intention to quit. The finding that both cognitive (vmPFC) and affective (amygdala) brain areas contributed to these models supports the idea that smokers respond to HWLs in a cognitive-affective manner. Based on our findings, researchers may wish to consider using neural data from both cognitive and affective networks when attempting to predict behavioral change in certain populations (e.g. cigarette smokers). © The Author (2016). Published by Oxford University Press.

Prediction of equibiaxial loading stress in collagen-based extracellular matrix using a three-dimensional unit cell model.

Science.gov (United States)

Susilo, Monica E; Bell, Brett J; Roeder, Blayne A; Voytik-Harbin, Sherry L; Kokini, Klod; Nauman, Eric A

2013-03-01

Mechanical signals are important factors in determining cell fate. Therefore, insights as to how mechanical signals are transferred between the cell and its surrounding three-dimensional collagen fibril network will provide a basis for designing the optimum extracellular matrix (ECM) microenvironment for tissue regeneration. Previously we described a cellular solid model to predict fibril microstructure-mechanical relationships of reconstituted collagen matrices due to unidirectional loads (Acta Biomater 2010;6:1471-86). The model consisted of representative volume elements made up of an interconnected network of flexible struts. The present study extends this work by adapting the model to account for microstructural anisotropy of the collagen fibrils and a biaxial loading environment. The model was calibrated based on uniaxial tensile data and used to predict the equibiaxial tensile stress-stretch relationship. Modifications to the model significantly improved its predictive capacity for equibiaxial loading data. With a comparable fibril length (model 5.9-8μm, measured 7.5μm) and appropriate fibril anisotropy the anisotropic model provides a better representation of the collagen fibril microstructure. Such models are important tools for tissue engineering because they facilitate prediction of microstructure-mechanical relationships for collagen matrices over a wide range of microstructures and provide a framework for predicting cell-ECM interactions. Copyright © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

An Extended Assessment of Fluid Flow Models for the Prediction of Two-Dimensional Steady-State Airfoil Aerodynamics

Directory of Open Access Journals (Sweden)

José F. Herbert-Acero

2015-01-01

Full Text Available This work presents the analysis, application, and comparison of thirteen fluid flow models in the prediction of two-dimensional airfoil aerodynamics, considering laminar and turbulent subsonic inflow conditions. Diverse sensitivity analyses of different free parameters (e.g., the domain topology and its discretization, the flow model, and the solution method together with its convergence mechanisms revealed important effects on the simulations’ outcomes. The NACA 4412 airfoil was considered throughout the work and the computational predictions were compared with experiments conducted under a wide range of Reynolds numbers (7e5≤Re≤9e6 and angles-of-attack (-10°≤α≤20°. Improvements both in modeling accuracy and processing time were achieved by considering the RS LP-S and the Transition SST turbulence models, and by considering finite volume-based solution methods with preconditioned systems, respectively. The RS LP-S model provided the best lift force predictions due to the adequate modeling of the micro and macro anisotropic turbulence at the airfoil’s surface and at the nearby flow field, which in turn allowed the adequate prediction of stall conditions. The Transition-SST model provided the best drag force predictions due to adequate modeling of the laminar-to-turbulent flow transition and the surface shear stresses. Conclusions, recommendations, and a comprehensive research agenda are presented based on validated computational results.

Understanding, Predicting, and Preventing Life Changing and Life Threatening Health Changes among Aging Veterans and Civilians with Spinal Cord Injury

Science.gov (United States)

2017-10-01

AWARD NUMBER: W81XWH-16-1-0629 TITLE: Understanding, Predicting, and Preventing Life -Changing and Life -Threatening Health Changes among Aging...Annual 3. DATES COVERED 30 Sep 2016 - 29 Sep 2017 4. TITLE AND SUBTITLE Understanding, Predicting, and Preventing Life -Changing and Life ... hope of preventing them. Our purpose is to better understand the how and why of the development of negative health spirals and how they may best be

An investigation on the effects of different polymerization techniques on dimensional changes ofAcropars, an Iranian autopolymerizing acrylic resin

Directory of Open Access Journals (Sweden)

Ebadian B

2004-02-01

Full Text Available Iranian product, Acropars autopolymerizing acrylic resin is nowadays widely used in"ndental prostheses. Dimensional change is a common problem among Iranian made acrylic resins in making"ncustom trays and record bases, seems to be more than the similar foreign products. In order to achieve a"ntechnique for making a record base with minimum dimensional changes, more research is necessary."nPurpose: The aim of the present study was to determine a curing technique for Iranian autopolymerizing"nacrylic resins leading to the least polymerization shrinkage and the most adaptation between record bases and"nstone casts."nMaterials and Methods: In this experimental study, 40 stone casts were divided into four 10- member group."nFor each group, polymerization shrinkage was determined at three points with one of the following"ntechniques: Bench curing, Curing under a coat of petroleum jelly , Curing in a monomer saturated"natmosphere, Curing in boiled water. Adaptation between bases and stone casts were measured at three points"n(the right and left crests of the ridge and the midpalatal region with a light-measuring microscope. To analyze"nthe data, Variance analysis was used."nResults: The monomer atmosphere technique showed the minimum dimensional changes and the samples in"nboiled water group had the maximum dimensional changes. No statistical differences were observed between"nother groups."nConclusion: More adaptation between record bases and stone casts was observed in monomer atmosphere"npolymerization technique. The differences between bench curing and curing under a coat of petroleum jelly"ntechniques with this method were not statistically significant. Therefore, it is suggested for making base"nrecords with maximum adaptation.

Numerical Simulation of Three-Dimensional Flow Through Full Passage and Performance Prediction of Nuclear Reactor Coolant Pump

International Nuclear Information System (INIS)

Li Ying; Zhou Wenxia; Zhang Jige; Wang Dezhong

2009-01-01

In order to achieve the level of self-design and domestic manufacture of the reactor coolant pump (nuclear main pump), the software FLUENT was used to simulate the three-dimensional flow through full passage of one nuclear main pump basing on RNG κ-ε turbulence model and SIMPLE algorithm. The distribution of pressure and velocity of the flow in the impeller's surface was analyzed in different working conditions. Moreover, the performance of the pump was predicted based on the simulation results. The results show that the distributions of pressure and velocity are reasonable in both the working and back face of the blade in the steady working condition. The pressure of the flow is increased from the inlet to the outlet of the pump, and shows the maximal value in the impeller region. Comparatively satisfactory efficiency and head value were obtained in the condition of the pump design. The shaft power of the nuclear main pump is gradually increased with the increase of the flow flux. These results are helpful in understanding the change of the internal flow field in the nuclear main pump, which is of some importance for the pre-exploration and theoretical research on the domestic manufacture of the nuclear main pump. (authors)

Heat transfer of phase-change materials in two-dimensional cylindrical coordinates

Science.gov (United States)

Labdon, M. B.; Guceri, S. I.

1981-01-01

Two-dimensional phase-change problem is numerically solved in cylindrical coordinates (r and z) by utilizing two Taylor series expansions for the temperature distributions in the neighborhood of the interface location. These two expansions form two polynomials in r and z directions. For the regions sufficiently away from the interface the temperature field equations are numerically solved in the usual way and the results are coupled with the polynomials. The main advantages of this efficient approach include ability to accept arbitrarily time dependent boundary conditions of all types and arbitrarily specified initial temperature distributions. A modified approach using a single Taylor series expansion in two variables is also suggested.

THE EFFECTS OF GLYCOL METHACRYLATE AS A DEHYDRATING AGENT ON THE DIMENSIONAL CHANGES OF LIVER-TISSUE

NARCIS (Netherlands)

GERRITS, PO; HOROBIN, RW; STOKROOS, [No Value

The dimensional changes of liver sections during the course of processing with glycol methacrylate (GMA) or with ethanol are described. Tissue processing with ethanol served as a control. During prolonged processing steps (24 h each), linear shrinkage of tissue specimens dehydrated with GMA at room

Woody plants and the prediction of climate-change impacts on bird diversity

DEFF Research Database (Denmark)

Kissling, W. Daniel; Field, R.; Korntheuer, H.

2010-01-01

Current methods of assessing climate-induced shifts of species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. Here, we used species-richness data from 1005 breeding bird and 1417 woody plant...... species in Kenya and employed model-averaged coefficients from regression models and median climatic forecasts assembled across 15 climate-change scenarios to predict bird species richness under climate change. Forecasts assuming an instantaneous response of woody plants and birds to climate change...... suggested increases in future bird species richness across most of Kenya whereas forecasts assuming strongly lagged woody plant responses to climate change indicated a reversed trend, i.e. reduced bird species richness. Uncertainties in predictions of future bird species richness were geographically...

Inter-decadal change in potential predictability of the East Asian summer monsoon

Science.gov (United States)

Li, Jiao; Ding, Ruiqiang; Wu, Zhiwei; Zhong, Quanjia; Li, Baosheng; Li, Jianping

2018-05-01

The significant inter-decadal change in potential predictability of the East Asian summer monsoon (EASM) has been investigated using the signal-to-noise ratio method. The relatively low potential predictability appears from the early 1950s through the late 1970s and during the early 2000s, whereas the potential predictability is relatively high from the early 1980s through the late 1990s. The inter-decadal change in potential predictability of the EASM can be attributed mainly to variations in the external signal of the EASM. The latter is mostly caused by the El Niño-Southern Oscillation (ENSO) inter-decadal variability. As a major external signal of the EASM, the ENSO inter-decadal variability experiences phase transitions from negative to positive phases in the late 1970s, and to negative phases in the late 1990s. Additionally, ENSO is generally strong (weak) during a positive (negative) phase of the ENSO inter-decadal variability. The strong ENSO is expected to have a greater influence on the EASM, and vice versa. As a result, the potential predictability of the EASM tends to be high (low) during a positive (negative) phase of the ENSO inter-decadal variability. Furthermore, a suite of Pacific Pacemaker experiments suggests that the ENSO inter-decadal variability may be a key pacemaker of the inter-decadal change in potential predictability of the EASM.

HESS Opinions: Hydrologic predictions in a changing environment: behavioral modeling

Directory of Open Access Journals (Sweden)

S. J. Schymanski

2011-02-01

Full Text Available Most hydrological models are valid at most only in a few places and cannot be reasonably transferred to other places or to far distant time periods. Transfer in space is difficult because the models are conditioned on past observations at particular places to define parameter values and unobservable processes that are needed to fully characterize the structure and functioning of the landscape. Transfer in time has to deal with the likely temporal changes to both parameters and processes under future changed conditions. This remains an important obstacle to addressing some of the most urgent prediction questions in hydrology, such as prediction in ungauged basins and prediction under global change. In this paper, we propose a new approach to catchment hydrological modeling, based on universal principles that do not change in time and that remain valid across many places. The key to this framework, which we call behavioral modeling, is to assume that there are universal and time-invariant organizing principles that can be used to identify the most appropriate model structure (including parameter values and responses for a given ecosystem at a given moment in time. These organizing principles may be derived from fundamental physical or biological laws, or from empirical laws that have been demonstrated to be time-invariant and to hold at many places and scales. Much fundamental research remains to be undertaken to help discover these organizing principles on the basis of exploration of observed patterns of landscape structure and hydrological behavior and their interpretation as legacy effects of past co-evolution of climate, soils, topography, vegetation and humans. Our hope is that the new behavioral modeling framework will be a step forward towards a new vision for hydrology where models are capable of more confidently predicting the behavior of catchments beyond what has been observed or experienced before.

Validation of a zero-dimensional model for prediction of NOx and engine performance for electronically controlled marine two-stroke diesel engines

International Nuclear Information System (INIS)

Scappin, Fabio; Stefansson, Sigurður H.; Haglind, Fredrik; Andreasen, Anders; Larsen, Ulrik

2012-01-01

The aim of this paper is to derive a methodology suitable for energy system analysis for predicting the performance and NO x emissions of marine low speed diesel engines. The paper describes a zero-dimensional model, evaluating the engine performance by means of an energy balance and a two zone combustion model using ideal gas law equations over a complete crank cycle. The combustion process is divided into intervals, and the product composition and flame temperature are calculated in each interval. The NO x emissions are predicted using the extended Zeldovich mechanism. The model is validated using experimental data from two MAN B and W engines; one case being data subject to engine parameter changes corresponding to simulating an electronically controlled engine; the second case providing data covering almost all model input and output parameters. The first case of validation suggests that the model can predict specific fuel oil consumption and NO x emissions within the 95% confidence intervals given by the experimental measurements. The second validation confirms the capability of the model to match measured engine output parameters based on measured engine input parameters with a maximum 5% deviation. - Highlights: ► A fast realistic model of a marine two-stroke low speed diesel engine was derived. ► The model is fast and accurate enough for future complex energy systems analysis. ► The effects of engine tuning were validated with experimental tests. ► The model was validated while constrained by experimental input and output data.

Do symptom-specific stages of change predict eating disorder treatment outcome?

Science.gov (United States)

Ackard, Diann M; Cronemeyer, Catherine L; Richter, Sara; Egan, Amber

2015-03-01

Interview methods to assess stages of change (SOC) in eating disorders (ED) indicate that SOC are positively correlated with symptom improvement over time. However, interviews require significant time and staff training and global measures of SOC do not capture varying levels of motivation across ED symptoms. This study used a self-report, ED symptom-specific SOC measure to determine prevalence of stages across symptoms and identify if SOC predict treatment outcome. Participants [N = 182; age 13-58 years; 92% Caucasian; 96% female; average BMI 21.7 (SD = 5.9); 50% ED not otherwise specified (EDNOS), 30.8% bulimia nervosa (BN), 19.2% anorexia nervosa (AN)] seeking ED treatment at a diverse-milieu multi-disciplinary facility in the United States completed stages of change, behavioral (ED symptom use and frequency) and psychological (ED concerns, anxiety, depression) measures at intake assessment and at 3, 6 and 12 months thereafter. Descriptive summaries were generated using ANOVA or Kruskal-Wallis (continuous) and χ (2) (categorical) tests. Repeated measures linear regression models with autoregressive correlation structure predicted treatment outcome. At intake assessment, 53.3% of AN, 34.0% of BN and 18.1% of EDNOS patients were in Preparation/Action. Readiness to change specific symptoms was highest for binge-eating (57.8%) and vomiting (56.5%). Frequency of fasting and restricting behaviors, and scores on all eating disorder and psychological measures improved over time regardless of SOC at intake assessment. Symptom-specific SOC did not predict reductions in ED symptom frequency. Overall SOC predicted neither improvement in Eating Disorder Examination Questionnaire (EDE-Q) scores nor reduction in depression or trait anxiety; however, higher overall SOC predicted lower state anxiety across follow-up. Readiness to change ED behaviors varies considerably. Most patients reduced eating disorder behaviors and increased psychological functioning regardless of stages

The effect of disinfection of alginate impressions with 35% beetle juice spray on stone model linear dimensional changes

Directory of Open Access Journals (Sweden)

Anggra Yudha Ramadianto

2007-07-01

Full Text Available Dimensional stability of alginate impression is very important for treatment in dentistry. This study was to find the effect of the beetle juice spray procedure on alginate impression on gypsum model linear dimensional changes. This experimental study used 25 samples, divided into 5 groups. The first group, as control, were the alginate impressions filled with dental stone immediately after forming. The other four groups were the alginate impressions gel spray each 1,2,3, and 4 times with 35% beetle juice and then filled with dental stone. Dimensional changes were measured in the lower part of the plaster model from buccal-lingual and mesial-distal direction and also measured in the outer distance between the upper part of the stone model by using Mitutoyo digital micrometre and profile projector scaled 0,001 mm. The results of mesial-distal diameter average of the control group and group 2,3,4, and 5 were 9.909 mm, 9.852 mm, 9.845 mm, 9.824 mm, and 9.754 mm. Meanwhile, the results of buccal-lingual diameter average were 9.847 mm, 9.841 mm, 9.826 mm, 9.776 mm, and 9.729 mm. The results of the outer distance between the upper part of the stone model were 31.739 mm, 31.689 mm, 31.682 mm, 31.670 mm, and 31.670 mm. The data of this study was evaluated statistically based on the variant analysis. The conclusion of this study was statistically, there was no significant effect on gypsum model linear dimensional changes obtained from alginate impressions sprayed with 35% beetle juice.

SU-F-J-219: Predicting Ventilation Change Due to Radiation Therapy: Dependency On Pre-RT Ventilation and Effort Correction

Energy Technology Data Exchange (ETDEWEB)

Patton, T; Du, K; Bayouth, J [University of Wisconsin, Madison, WI (United States); Christensen, G; Reinhardt, J [University of Iowa, Iowa City, IA (United States)

2016-06-15

Purpose: Ventilation change caused by radiation therapy (RT) can be predicted using four-dimensional computed tomography (4DCT) and image registration. This study tested the dependency of predicted post-RT ventilation on effort correction and pre-RT lung function. Methods: Pre-RT and 3 month post-RT 4DCT images were obtained for 13 patients. The 4DCT images were used to create ventilation maps using a deformable image registration based Jacobian expansion calculation. The post-RT ventilation maps were predicted in four different ways using the dose delivered, pre-RT ventilation, and effort correction. The pre-RT ventilation and effort correction were toggled to determine dependency. The four different predicted ventilation maps were compared to the post-RT ventilation map calculated from image registration to establish the best prediction method. Gamma pass rates were used to compare the different maps with the criteria of 2mm distance-to-agreement and 6% ventilation difference. Paired t-tests of gamma pass rates were used to determine significant differences between the maps. Additional gamma pass rates were calculated using only voxels receiving over 20 Gy. Results: The predicted post-RT ventilation maps were in agreement with the actual post-RT maps in the following percentage of voxels averaged over all subjects: 71% with pre-RT ventilation and effort correction, 69% with no pre-RT ventilation and effort correction, 60% with pre-RT ventilation and no effort correction, and 58% with no pre-RT ventilation and no effort correction. When analyzing only voxels receiving over 20 Gy, the gamma pass rates were respectively 74%, 69%, 65%, and 55%. The prediction including both pre- RT ventilation and effort correction was the only prediction with significant improvement over using no prediction (p<0.02). Conclusion: Post-RT ventilation is best predicted using both pre-RT ventilation and effort correction. This is the only prediction that provided a significant

Assessment of bracket surface morphology and dimensional change

Directory of Open Access Journals (Sweden)

Pillai Devu Radhakrishnan

2017-01-01

Full Text Available Objective: The objective of this study was to compare the surface morphology and dimensional stability of the bracket slot at the onset of treatment and after 12 months of intraoral exposure. The study also compared the amount of calcium at the bracket base which indicates enamel loss among the three orthodontic brackets following debonding after 12 months of intraoral exposure. Materials and Methods: The sample consisted of 60 (0.022” MBT canine brackets. They were divided into three groups: self-ligating, ceramic bracket with metal slot, and stainless steel (SS brackets. The slot dimensions, micromorphologic characteristics of as-received and retrieved brackets were measured with a stereomicroscope and scanning electron microscope (SEM, respectively. The amount of calcium at the bracket base which indicates enamel damage was quantified using energy-dispersive X-ray spectrometry (EDX. Results: The results showed statistically significant alterations (P < 0.05 in the right vertical dimension, internal tie wing width (cervical, right and left depth of the slot (Kruskal–Wallis test. Multiple comparison using Mann–Whitney test showed that ceramic brackets underwent (P < 0.05 minimal alterations in the right vertical dimension, internal tie wing width (cervical, right and left depth of the slot (0.01 mm, −0.003 mm, 0.006 mm, −0.002 mm, respectively when compared with the changes seen in SS and self-ligating brackets. SEM analysis revealed an increase in the surface roughness of ceramic with metal slot brackets and self-ligating bracket showed the least irregularity. The presence of calcium was noted on all evaluated brackets under EDX, but ceramic with metal slot brackets showed a significantly greater amount of enamel loss (P = 0.001. Conclusion: Ceramic brackets were found to be dimensionally stable when compared to SS and self-ligating. Self-ligating bracket showed minimal surface irregularity. Ceramic with metal slot brackets showed a

Predicting hydrological response to forest changes by simple statistical models: the selection of the best indicator of forest changes with a hydrological perspective

Science.gov (United States)

Ning, D.; Zhang, M.; Ren, S.; Hou, Y.; Yu, L.; Meng, Z.

2017-01-01

Forest plays an important role in hydrological cycle, and forest changes will inevitably affect runoff across multiple spatial scales. The selection of a suitable indicator for forest changes is essential for predicting forest-related hydrological response. This study used the Meijiang River, one of the headwaters of the Poyang Lake as an example to identify the best indicator of forest changes for predicting forest change-induced hydrological responses. Correlation analysis was conducted first to detect the relationships between monthly runoff and its predictive variables including antecedent monthly precipitation and indicators for forest changes (forest coverage, vegetation indices including EVI, NDVI, and NDWI), and by use of the identified predictive variables that were most correlated with monthly runoff, multiple linear regression models were then developed. The model with best performance identified in this study included two independent variables -antecedent monthly precipitation and NDWI. It indicates that NDWI is the best indicator of forest change in hydrological prediction while forest coverage, the most commonly used indicator of forest change is insignificantly related to monthly runoff. This highlights the use of vegetation index such as NDWI to indicate forest changes in hydrological studies. This study will provide us with an efficient way to quantify the hydrological impact of large-scale forest changes in the Meijiang River watershed, which is crucial for downstream water resource management and ecological protection in the Poyang Lake basin.

Generalized perturbation theory using two-dimensional, discrete ordinates transport theory

International Nuclear Information System (INIS)

Childs, R.L.

1979-01-01

Perturbation theory for changes in linear and bilinear functionals of the forward and adjoint fluxes in a critical reactor has been implemented using two-dimensional discrete ordinates transport theory. The computer program DOT IV was modified to calculate the generalized functions Λ and Λ*. Demonstration calculations were performed for changes in a reaction-rate ratio and a reactivity worth caused by system perturbations. The perturbation theory predictions agreed with direct calculations to within about 2%. A method has been developed for calculating higher lambda eigenvalues and eigenfunctions using techniques similar to those developed for generalized functions. Demonstration calculations have been performed to obtain these eigenfunctions

Predicting Effects of Water Regime Changes on Waterbirds: Insights from Staging Swans

NARCIS (Netherlands)

Nolet, Bart A.; Gyimesi, Abel; Krimpen, Van Roderick R.D.; Boer, de Fred; Stillman, Richard A.; Green, Andy J.

2016-01-01

Predicting the environmental impact of a proposed development is notoriously difficult,
especially when future conditions fall outside the current range of conditions. Individualbased
approaches have been developed and applied to predict the impact of environmental
changes on wintering

Predicting effects of water regime changes on waterbirds : insights from staging swans

NARCIS (Netherlands)

Nolet, B.A.; Gyimesi, A.; van Krimpen, R.R.D.; de Boer, W.F.; Stillman, R.A.

2016-01-01

Predicting the environmental impact of a proposed development is notoriously difficult, especially when future conditions fall outside the current range of conditions. Individual-based approaches have been developed and applied to predict the impact of environmental changes on wintering and staging

Can tail damage outbreaks in the pig be predicted by behavioural change?

DEFF Research Database (Denmark)

Larsen, Mona Lilian Vestbjerg; Andersen, Heidi Mai-Lis; Pedersen, Lene Juul

2016-01-01

preventive methods. One strategy is the surveillance of the pigs' behaviour for known preceding indicators of tail damage, which makes it possible to predict a tail damage outbreak and prevent it in proper time. This review discusses the existing literature on behavioural changes observed prior to a tail...... damage outbreak. Behaviours found to change prior to an outbreak include increased activity level, increased performance of enrichment object manipulation, and a changed proportion of tail posture with more tails between the legs. Monitoring these types of behaviours is also discussed for the purpose......, starting with the description of the temporal development of the predictive behaviour in relation to tail damage outbreaks...

Prediction of Tubal Ectopic Pregnancy Using Offline Analysis of 3-Dimensional Transvaginal Ultrasonographic Data Sets: An Interobserver and Diagnostic Accuracy Study.

Science.gov (United States)

Infante, Fernando; Espada Vaquero, Mercedes; Bignardi, Tommaso; Lu, Chuan; Testa, Antonia C; Fauchon, David; Epstein, Elisabeth; Leone, Francesco P G; Van den Bosch, Thierry; Martins, Wellington P; Condous, George

2017-12-08

To assess interobserver reproducibility in detecting tubal ectopic pregnancies by reading data sets from 3-dimensional (3D) transvaginal ultrasonography (TVUS) and comparing it with real-time 2-dimensional (2D) TVUS. Images were initially classified as showing pregnancies of unknown location or tubal ectopic pregnancies on real time 2D TVUS by an experienced sonologist, who acquired 5 3D volumes. Data sets were analyzed offline by 5 observers who had to classify each case as ectopic pregnancy or pregnancy of unknown location. The interobserver reproducibility was evaluated by the Fleiss κ statistic. The performance of each observer in predicting ectopic pregnancies was compared to that of the experienced sonologist. Women were followed until they were reclassified as follows: (1) failed pregnancy of unknown location; (2) intrauterine pregnancy; (3) ectopic pregnancy; or (4) persistent pregnancy of unknown location. Sixty-one women were included. The agreement between reading offline 3D data sets and the first real-time 2D TVUS was very good (80%-82%; κ = 0.89). The overall interobserver agreement among observers reading offline 3D data sets was moderate (κ = 0.52). The diagnostic performance of experienced observers reading offline 3D data sets had accuracy of 78.3% to 85.0%, sensitivity of 66.7% to 81.3%, specificity of 79.5% to 88.4%, positive predictive value of 57.1% to 72.2%, and negative predictive value of 87.5% to 91.3%, compared to the experienced sonologist's real-time 2D TVUS: accuracy of 94.5%, sensitivity of 94.4%, specificity of 94.5%, positive predictive value of 85.0%, and negative predictive value of 98.1%. The diagnostic accuracy of 3D TVUS by reading offline data sets for predicting ectopic pregnancies is dependent on experience. Reading only static 3D data sets without clinical information does not match the diagnostic performance of real time 2D TVUS combined with clinical information obtained during the scan. © 2017 by the American

A low-dimensional tool for predicting force decomposition coefficients for varying inflow conditions

KAUST Repository

Ghommem, Mehdi

2013-01-01

We develop a low-dimensional tool to predict the effects of unsteadiness in the inflow on force coefficients acting on a circular cylinder using proper orthogonal decomposition (POD) modes from steady flow simulations. The approach is based on combining POD and linear stochastic estimator (LSE) techniques. We use POD to derive a reduced-order model (ROM) to reconstruct the velocity field. To overcome the difficulty of developing a ROM using Poisson\\'s equation, we relate the pressure field to the velocity field through a mapping function based on LSE. The use of this approach to derive force decomposition coefficients (FDCs) under unsteady mean flow from basis functions of the steady flow is illustrated. For both steady and unsteady cases, the final outcome is a representation of the lift and drag coefficients in terms of velocity and pressure temporal coefficients. Such a representation could serve as the basis for implementing control strategies or conducting uncertainty quantification. Copyright © 2013 Inderscience Enterprises Ltd.

A low-dimensional tool for predicting force decomposition coefficients for varying inflow conditions

KAUST Repository

Ghommem, Mehdi; Akhtar, Imran; Hajj, M. R.

2013-01-01

We develop a low-dimensional tool to predict the effects of unsteadiness in the inflow on force coefficients acting on a circular cylinder using proper orthogonal decomposition (POD) modes from steady flow simulations. The approach is based on combining POD and linear stochastic estimator (LSE) techniques. We use POD to derive a reduced-order model (ROM) to reconstruct the velocity field. To overcome the difficulty of developing a ROM using Poisson's equation, we relate the pressure field to the velocity field through a mapping function based on LSE. The use of this approach to derive force decomposition coefficients (FDCs) under unsteady mean flow from basis functions of the steady flow is illustrated. For both steady and unsteady cases, the final outcome is a representation of the lift and drag coefficients in terms of velocity and pressure temporal coefficients. Such a representation could serve as the basis for implementing control strategies or conducting uncertainty quantification. Copyright © 2013 Inderscience Enterprises Ltd.

Prediction of residual lung function after lung surgery, and examination of blood perfusion in the pre- and postoperative lung using three-dimensional SPECT

Energy Technology Data Exchange (ETDEWEB)

Shimatani, Shinji [Toho Univ., Tokyo (Japan). School of Medicine

2001-01-01

In order to predict postoperative pulmonary function after lung surgery, preoperative {sup 99m}Tc-macroaggregated albumin (MAA) lung perfusion scans with single-photon emission computed tomography (SPECT) were performed. Spirometry was also performed before and 4-6 months after surgery in 40 patients. In addition, changes in blood perfusion in the pre- and postoperative lung were examined by postoperative lung perfusion scans in 18 of the 40 patients. We measured the three-dimensional (3-D) imaging volume of the operative and contralateral lungs using the volumes rendering method at blood perfusion thresholds of 20, 50 and 75%, utilizing {sup 99m}Tc-MAA lung perfusion, and predicted pulmonary function by means of the measured volumes. We examined the correlation between predicted and the measured values of postoperative pulmonary function, forced vital capacity (FVC) and forced expiratory volume in one second (FEV{sub 1.0}). The correlation between FEV{sub 1.0} predicted by SPECT (threshold 50%) and measured postoperative lung function resembled that between lung function predicted by the standard planar method and measured FEV{sub 1.0} in the lobectomy group. We then examined the ratios of both pre- and postoperative blood perfusion volumes obtained using 3-D imaging at lung perfusion threshold ranges of 10% each (PV20-29, PV30-39) to pre- and postoperative total perfusion (PV20-100). In the lobectomy group, the postoperative PV20-29/PV20-100 value was significantly higher for the operative side lung than the preoperative PV20-29/PV20-100 value, and the postoperative PV50-59, 60-69, 70-79, 80-89 and 90-100/PV20-100 values were significantly lower than the respective preoperative values. However, in the contralateral lung, the respective pre- and postoperative PV/PV20-100 values were almost identical. These findings suggest that the rate of low blood perfusion increased while the rate of middle to high perfusion decreased in the lobectomy group in the operative

Early changes in socioeconomic status do not predict changes in body mass in the first decade of life.

Science.gov (United States)

Starkey, Leighann; Revenson, Tracey A

2015-04-01

Many studies link childhood socioeconomic status (SES) to body mass index (BMI), but few account for the impact of socioeconomic mobility throughout the lifespan. This study aims to investigate the impact of socioeconomic mobility on changes in BMI in childhood. Analyses tested whether [1] socioeconomic status influences BMI, [2] changes in socioeconomic status impact changes in BMI, and [3] timing of socioeconomic status mobility impacts BMI. Secondary data spanning birth to age 9 were analyzed. SES and BMI were investigated with gender, birth weight, maternal race/ethnicity, and maternal nativity as covariates. Autoregressive structural equation modeling and latent growth modeling were used. Socioeconomic status in the first year of life predicted body mass index. Child covariates were consistently associated with body mass index. Rate of change in socioeconomic status did not predict change in body mass index. The findings suggest that early socioeconomic status may most influence body mass in later childhood.

Turbulence prediction in two-dimensional bundle flows using large eddy simulation

Energy Technology Data Exchange (ETDEWEB)

Ibrahim, W.A.; Hassan, Y.A. [Texas A& M Univ., College Station, TX (United States)

1995-09-01

Turbulent flow is characterized by random fluctuations in the fluid velocity and by intense mixing of the fluid. Due to velocity fluctuations, a wide range of eddies exists in the flow field. Because these eddies carry mass, momentum, and energy, this enhanced mixing can sometimes lead to serious problems, such as tube vibrations in many engineering systems that include fluid-tube bundle combinations. Nuclear fuel bundles and PWR steam generators are existing examples in nuclear power plants. Fluid-induced vibration problems are often discovered during the operation of such systems because some of the fluid-tube interaction characteristics are not fully understood. Large Eddy Simulation, incorporated in a three dimensional computer code, became one of the promising techniques to estimate flow turbulence, predict and prevent of long-term tube fretting affecting PWR steam generators. the present turbulence investigations is a step towards more understanding of fluid-tube interaction characteristics by comparing the tube bundles with various pitch-to-diameter ratios were performed. Power spectral densities were used for comparison with experimental data. Correlations, calculations of different length scales in the flow domain and other important turbulent-related parameters were calculated. Finally, important characteristics of turbulent flow field were presented with the aid of flow visualization with tracers impeded in the flow field.

Influence of chemical treatments on moisture-induced dimensional change and elastic modulus of earlywood and latewood

Science.gov (United States)

Robert J. Moon; Joseph Wells; David E. Kretschmann; James Evans; Alex C. Wiedenhoeft; Charles R. Frihart

2010-01-01

To better understand the performance of bonded, coated, and modified wood, knowledge of how these processes alter the dimensional change and mechanical properties of wood at a given moisture content (MC) are important. These localized influences on earlywood (EW) and latewood (LW) properties are not well understood. In the present study, the influence of chemical...

Regression models for predicting peak and continuous three-dimensional spinal loads during symmetric and asymmetric lifting tasks.

Science.gov (United States)

Fathallah, F A; Marras, W S; Parnianpour, M

1999-09-01

Most biomechanical assessments of spinal loading during industrial work have focused on estimating peak spinal compressive forces under static and sagittally symmetric conditions. The main objective of this study was to explore the potential of feasibly predicting three-dimensional (3D) spinal loading in industry from various combinations of trunk kinematics, kinetics, and subject-load characteristics. The study used spinal loading, predicted by a validated electromyography-assisted model, from 11 male participants who performed a series of symmetric and asymmetric lifts. Three classes of models were developed: (a) models using workplace, subject, and trunk motion parameters as independent variables (kinematic models); (b) models using workplace, subject, and measured moments variables (kinetic models); and (c) models incorporating workplace, subject, trunk motion, and measured moments variables (combined models). The results showed that peak 3D spinal loading during symmetric and asymmetric lifting were predicted equally well using all three types of regression models. Continuous 3D loading was predicted best using the combined models. When the use of such models is infeasible, the kinematic models can provide adequate predictions. Finally, lateral shear forces (peak and continuous) were consistently underestimated using all three types of models. The study demonstrated the feasibility of predicting 3D loads on the spine under specific symmetric and asymmetric lifting tasks without the need for collecting EMG information. However, further validation and development of the models should be conducted to assess and extend their applicability to lifting conditions other than those presented in this study. Actual or potential applications of this research include exposure assessment in epidemiological studies, ergonomic intervention, and laboratory task assessment.

Revised predictive equations for salt intrusion modelling in estuaries

NARCIS (Netherlands)

Gisen, J.I.A.; Savenije, H.H.G.; Nijzink, R.C.

2015-01-01

For one-dimensional salt intrusion models to be predictive, we need predictive equations to link model parameters to observable hydraulic and geometric variables. The one-dimensional model of Savenije (1993b) made use of predictive equations for the Van der Burgh coefficient $K$ and the dispersion

Application of a two-dimensional model for predicting the pressure-flow and compression properties during column packing scale-up.

Science.gov (United States)

McCue, Justin T; Cecchini, Douglas; Chu, Cathy; Liu, Wei-Han; Spann, Andrew

2007-03-23

A two-dimensional model was formulated to describe the pressure-flow behavior of compressible stationary phases for protein chromatography at different temperatures and column scales. The model was based on the assumption of elastic deformation of the solid phase and steady-state Darcy flow. Using a single fitted value for the empirical modulus parameters, the model was applied to describe the pressure-flow behavior of several adsorbents packed using both fluid flow and mechanical compression. Simulations were in agreement with experimental data and accurately predicted the pressure-flow and compression behavior of three adsorbents over a range of column scales and operating temperatures. Use of the described theoretical model potentially improves the accuracy of the column scale-up process, allowing the use of limited laboratory scale data to predict column performance in large scale applications.

Medium- and Long-term Prediction of LOD Change with the Leap-step Autoregressive Model

Science.gov (United States)

Liu, Q. B.; Wang, Q. J.; Lei, M. F.

2015-09-01

It is known that the accuracies of medium- and long-term prediction of changes of length of day (LOD) based on the combined least-square and autoregressive (LS+AR) decrease gradually. The leap-step autoregressive (LSAR) model is more accurate and stable in medium- and long-term prediction, therefore it is used to forecast the LOD changes in this work. Then the LOD series from EOP 08 C04 provided by IERS (International Earth Rotation and Reference Systems Service) is used to compare the effectiveness of the LSAR and traditional AR methods. The predicted series resulted from the two models show that the prediction accuracy with the LSAR model is better than that from AR model in medium- and long-term prediction.

LSD-induced entropic brain activity predicts subsequent personality change.

Science.gov (United States)

Lebedev, A V; Kaelen, M; Lövdén, M; Nilsson, J; Feilding, A; Nutt, D J; Carhart-Harris, R L

2016-09-01

Personality is known to be relatively stable throughout adulthood. Nevertheless, it has been shown that major life events with high personal significance, including experiences engendered by psychedelic drugs, can have an enduring impact on some core facets of personality. In the present, balanced-order, placebo-controlled study, we investigated biological predictors of post-lysergic acid diethylamide (LSD) changes in personality. Nineteen healthy adults underwent resting state functional MRI scans under LSD (75µg, I.V.) and placebo (saline I.V.). The Revised NEO Personality Inventory (NEO-PI-R) was completed at screening and 2 weeks after LSD/placebo. Scanning sessions consisted of three 7.5-min eyes-closed resting-state scans, one of which involved music listening. A standardized preprocessing pipeline was used to extract measures of sample entropy, which characterizes the predictability of an fMRI time-series. Mixed-effects models were used to evaluate drug-induced shifts in brain entropy and their relationship with the observed increases in the personality trait openness at the 2-week follow-up. Overall, LSD had a pronounced global effect on brain entropy, increasing it in both sensory and hierarchically higher networks across multiple time scales. These shifts predicted enduring increases in trait openness. Moreover, the predictive power of the entropy increases was greatest for the music-listening scans and when "ego-dissolution" was reported during the acute experience. These results shed new light on how LSD-induced shifts in brain dynamics and concomitant subjective experience can be predictive of lasting changes in personality. Hum Brain Mapp 37:3203-3213, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Nasal changes after orthognathic surgery for patients with prognathism and Class III malocclusion: analysis using three-dimensional photogrammetry.

Science.gov (United States)

Worasakwutiphong, Saran; Chuang, Ya-Fang; Chang, Hsin-Wen; Lin, Hsiu-Hsia; Lin, Pei-Ju; Lo, Lun-Jou

2015-02-01

Orthognathic surgery alters the position of maxilla and mandible, and consequently changes the nasal shape. The nasal change remains a concern to Asian patients. The aim of this study was to measure the nasal changes using a novel three-dimensional photographic imaging method. A total of 38 patients with Class III malocclusion and prognathism were enrolled. All patients underwent two-jaw surgery with the standard technique. A nasal alar cinching suture was included at the end of procedure. Facial landmarks and nasal morphology were defined and measured from pre- and postoperative three-dimensional photographic images. Intra-rater errors on landmark identification were controlled. Patient's reports of perceptual nasal changes were recorded. The average width of the alar base and subalare remained similar after surgery. Alar width was increased by 0.74 mm. Nasal height and length remained the same. Nasolabial angle increased significantly. The area of nostril show revealed a significant increase and was correlated with a decrease of columella inclination. Nasal tip projection decreased significantly, by 1.99 mm. Preoperative nasal morphology was different between patients with and without cleft lip/palate, but most nasal changes were concordant. In the self-perception, 37% of patients reported improved nasal appearance, 58% reported no change, and 5% were not satisfied with the nasal changes. After the surgery, characteristic nasal changes occurred with an increase of nasolabial angle and nostril show, but a preserved nasal width. The majority of patients did not perceive adverse nasal changes. Copyright © 2014. Published by Elsevier B.V.

Prediction methods and databases within chemoinformatics

DEFF Research Database (Denmark)

Jónsdóttir, Svava Osk; Jørgensen, Flemming Steen; Brunak, Søren

2005-01-01

MOTIVATION: To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS: We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information...... about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability...

Three-dimensional dental arch changes of patients submitted to orthodontic-surgical treatment for correction of Class II malocclusion.

Science.gov (United States)

Peixoto, Adriano Porto; dos Santos Pinto, Ary; Garib, Daniela Gamba; Gonçalves, João Roberto

2014-01-01

This study assessed the three-dimensional changes in the dental arch of patients submitted to orthodontic-surgical treatment for correction of Class II malocclusions at three different periods. Landmarks previously identified on upper and lower dental casts were digitized on a three-dimensional digitizer MicroScribe-3DX and stored in Excel worksheets in order to assess the width, length and depth of patient's dental arches. During orthodontic preparation, the maxillary and mandibular transverse dimensions measured at the premolar regions were increased and maintained throughout the follow-up period. Intercanine width was increased only in the upper arch during orthodontic preparation. Maxillary arch length was reduced during orthodontic finalization, only. Upper and lower arch depths were stable in the study periods. Differences between changes in centroid and gingival points suggested that upper and lower premolars buccaly proclined during the pre-surgical period. Maxillary and mandibular dental arches presented transverse expansion at premolar regions during preoperative orthodontic preparation, with a tendency towards buccal tipping. The transverse dimensions were not altered after surgery. No sagittal or vertical changes were observed during the follow-up periods.

National Scale Prediction of Soil Carbon Sequestration under Scenarios of Climate Change

Science.gov (United States)

Izaurralde, R. C.; Thomson, A. M.; Potter, S. R.; Atwood, J. D.; Williams, J. R.

2006-12-01

Carbon sequestration in agricultural soils is gaining momentum as a tool to mitigate the rate of increase of atmospheric CO2. Researchers from the Pacific Northwest National Laboratory, Texas A&M University, and USDA-NRCS used the EPIC model to develop national-scale predictions of soil carbon sequestration with adoption of no till (NT) under scenarios of climate change. In its current form, the EPIC model simulates soil C changes resulting from heterotrophic respiration and wind / water erosion. Representative modeling units were created to capture the climate, soil, and management variability at the 8-digit hydrologic unit (USGS classification) watershed scale. The soils selected represented at least 70% of the variability within each watershed. This resulted in 7,540 representative modeling units for 1,412 watersheds. Each watershed was assigned a major crop system: corn, soybean, spring wheat, winter wheat, cotton, hay, alfalfa, corn-soybean rotation or wheat-fallow rotation based on information from the National Resource Inventory. Each representative farm was simulated with conventional tillage and no tillage, and with and without irrigation. Climate change scenarios for two future periods (2015-2045 and 2045-2075) were selected from GCM model runs using the IPCC SRES scenarios of A2 and B2 from the UK Hadley Center (HadCM3) and US DOE PCM (PCM) models. Changes in mean and standard deviation of monthly temperature and precipitation were extracted from gridded files and applied to baseline climate (1960-1990) for each of the 1,412 modeled watersheds. Modeled crop yields were validated against historical USDA NASS county yields (1960-1990). The HadCM3 model predicted the most severe changes in climate parameters. Overall, there would be little difference between the A2 and B2 scenarios. Carbon offsets were calculated as the difference in soil C change between conventional and no till. Overall, C offsets during the first 30-y period (513 Tg C) are predicted to

[Effects of sampling plot number on tree species distribution prediction under climate change].

Science.gov (United States)

Liang, Yu; He, Hong-Shi; Wu, Zhi-Wei; Li, Xiao-Na; Luo, Xu

2013-05-01

Based on the neutral landscapes under different degrees of landscape fragmentation, this paper studied the effects of sampling plot number on the prediction of tree species distribution at landscape scale under climate change. The tree species distribution was predicted by the coupled modeling approach which linked an ecosystem process model with a forest landscape model, and three contingent scenarios and one reference scenario of sampling plot numbers were assumed. The differences between the three scenarios and the reference scenario under different degrees of landscape fragmentation were tested. The results indicated that the effects of sampling plot number on the prediction of tree species distribution depended on the tree species life history attributes. For the generalist species, the prediction of their distribution at landscape scale needed more plots. Except for the extreme specialist, landscape fragmentation degree also affected the effects of sampling plot number on the prediction. With the increase of simulation period, the effects of sampling plot number on the prediction of tree species distribution at landscape scale could be changed. For generalist species, more plots are needed for the long-term simulation.

Stimuli reduce the dimensionality of cortical activity

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Luca eMazzucato

2016-02-01

Full Text Available The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models.

Stimuli Reduce the Dimensionality of Cortical Activity.

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Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models.

Gaussian Process Regression for WDM System Performance Prediction

DEFF Research Database (Denmark)

Wass, Jesper; Thrane, Jakob; Piels, Molly

2017-01-01

Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data.......Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data....

Predicting short-term weight loss using four leading health behavior change theories

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Barata José T

2007-04-01

Full Text Available Abstract Background This study was conceived to analyze how exercise and weight management psychosocial variables, derived from several health behavior change theories, predict weight change in a short-term intervention. The theories under analysis were the Social Cognitive Theory, the Transtheoretical Model, the Theory of Planned Behavior, and Self-Determination Theory. Methods Subjects were 142 overweight and obese women (BMI = 30.2 ± 3.7 kg/m2; age = 38.3 ± 5.8y, participating in a 16-week University-based weight control program. Body weight and a comprehensive psychometric battery were assessed at baseline and at program's end. Results Weight decreased significantly (-3.6 ± 3.4%, p Conclusion The present models were able to predict 20–30% of variance in short-term weight loss and changes in weight management self-efficacy accounted for a large share of the predictive power. As expected from previous studies, exercise variables were only moderately associated with short-term outcomes; they are expected to play a larger explanatory role in longer-term results.

Hemostatic system changes predictive value in patients with ischemic brain disorders

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Raičević Ranko

2002-01-01

Full Text Available The aim of this research was to determine the importance of tracking the dynamics of changes of the hemostatic system factors (aggregation of thrombocytes, D-dimer, PAI-1, antithrombin III, protein C and protein S, factor VII and factor VIII, fibrin degradation products, euglobulin test and the activated partial thromboplastin time – aPTPV in relation to the level of the severity of ischemic brain disorders (IBD and the level of neurological and functional deficiency in the beginning of IBD manifestation from 7 to 10 days, 19 to 21 day, and after 3 to 6 months. The research results confirmed significant predictive value of changes of hemostatic system with the predomination of procoagulant factors, together with the insufficiency of fibrinolysis. Concerning the IBD severity and it's outcome, the significant predictive value was shown in the higher levels of PAI-1 and the lower level of antithrombin III, and borderline significant value was shown in the accelerated aggregation of thrombocytes and the increased concentration of D-dimer. It could be concluded that the tracking of the dynamics of changes in parameters of hemostatic system proved to be an easily accessible method with the significant predictive value regarding the development of more severe. IBD cases and the outcome of the disease itself.

The anatomy of the aging face: volume loss and changes in 3-dimensional topography.

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Coleman, Sydney R; Grover, Rajiv

2006-01-01

Facial aging reflects the dynamic, cumulative effects of time on the skin, soft tissues, and deep structural components of the face, and is a complex synergy of skin textural changes and loss of facial volume. Many of the facial manifestations of aging reflect the combined effects of gravity, progressive bone resorption, decreased tissue elasticity, and redistribution of subcutaneous fullness. A convenient method for assessing the morphological effects of aging is to divide the face into the upper third (forehead and brows), middle third (midface and nose), and lower third (chin, jawline, and neck). The midface is an important factor in facial aesthetics because perceptions of facial attractiveness are largely founded on the synergy of the eyes, nose, lips, and cheek bones (central facial triangle). For aesthetic purposes, this area should be considered from a 3-dimensional rather than a 2-dimensional perspective, and restoration of a youthful 3-dimensional facial topography should be regarded as the primary goal in facial rejuvenation. Recent years have seen a significant increase in the number of nonsurgical procedures performed for facial rejuvenation. Patients seeking alternatives to surgical procedures include those who require restoration of lost facial volume, those who wish to enhance normal facial features, and those who want to correct facial asymmetry. Important factors in selecting a nonsurgical treatment option include the advantages of an immediate cosmetic result and a short recovery time.

One-Dimensional Modelling of Internal Ballistics

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Monreal-González, G.; Otón-Martínez, R. A.; Velasco, F. J. S.; García-Cascáles, J. R.; Ramírez-Fernández, F. J.

2017-10-01

A one-dimensional model is introduced in this paper for problems of internal ballistics involving solid propellant combustion. First, the work presents the physical approach and equations adopted. Closure relationships accounting for the physical phenomena taking place during combustion (interfacial friction, interfacial heat transfer, combustion) are deeply discussed. Secondly, the numerical method proposed is presented. Finally, numerical results provided by this code (UXGun) are compared with results of experimental tests and with the outcome from a well-known zero-dimensional code. The model provides successful results in firing tests of artillery guns, predicting with good accuracy the maximum pressure in the chamber and muzzle velocity what highlights its capabilities as prediction/design tool for internal ballistics.

Early prediction of tumor recurrence based on CT texture changes after stereotactic ablative radiotherapy (SABR) for lung cancer

International Nuclear Information System (INIS)

Mattonen, Sarah A.; Palma, David A.; Haasbeek, Cornelis J. A.; Senan, Suresh; Ward, Aaron D.

2014-01-01

Purpose: Benign computed tomography (CT) changes due to radiation induced lung injury (RILI) are common following stereotactic ablative radiotherapy (SABR) and can be difficult to differentiate from tumor recurrence. The authors measured the ability of CT image texture analysis, compared to more traditional measures of response, to predict eventual cancer recurrence based on CT images acquired within 5 months of treatment. Methods: A total of 24 lesions from 22 patients treated with SABR were selected for this study: 13 with moderate to severe benign RILI, and 11 with recurrence. Three-dimensional (3D) consolidative and ground-glass opacity (GGO) changes were manually delineated on all follow-up CT scans. Two size measures of the consolidation regions (longest axial diameter and 3D volume) and nine appearance features of the GGO were calculated: 2 first-order features [mean density and standard deviation of density (first-order texture)], and 7 second-order texture features [energy, entropy, correlation, inverse difference moment (IDM), inertia, cluster shade, and cluster prominence]. For comparison, the corresponding response evaluation criteria in solid tumors measures were also taken for the consolidation regions. Prediction accuracy was determined using the area under the receiver operating characteristic curve (AUC) and two-fold cross validation (CV). Results: For this analysis, 46 diagnostic CT scans scheduled for approximately 3 and 6 months post-treatment were binned based on their recorded scan dates into 2–5 month and 5–8 month follow-up time ranges. At 2–5 months post-treatment, first-order texture, energy, and entropy provided AUCs of 0.79–0.81 using a linear classifier. On two-fold CV, first-order texture yielded 73% accuracy versus 76%–77% with the second-order features. The size measures of the consolidative region, longest axial diameter and 3D volume, gave two-fold CV accuracies of 60% and 57%, and AUCs of 0.72 and 0.65, respectively

THE PROCESS OF CHANGE - PREDICTION OF SPORT ACHIEVEMENTS HISTORICAL TENDENCY

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Izenedin Mehmeti

2015-05-01

Full Text Available The aim of this paper is to summarize the different standpoints and different approaches in regard to the sport performance preparation and achievement prediction. Sports researchers are concerned more directly with learning about scientific sports prediction. Their involvement in the sport sciences focuses on understanding how sports organized and how changes in that organization might influence sports experiences for both athletes and coaches. The goal of these scholars is often to improve sport experiences and performance prediction for current participants and make sport participation more attractive and accessible for those who do not currently play sports, prospective athletes. They also may want to help athletes improve their performance, help coaches work effectively with athletes and win more games. Sports researchers intention is also to assist and help sport organizations grow and operate more efficiently and profitably, and improve sport achievement prediction.

Fourth-dimensional changes in nasolabial dimensions following rotation-advancement repair of unilateral cleft lip.

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Mulliken, John B; LaBrie, Richard A

2012-02-01

Repair of unilateral cleft lip requires three-dimensional craftsmanship and understanding four-dimensional changes. Ninety-nine children with unilateral complete or incomplete cleft lip were measured by direct anthropometry following rotation-advancement repair (intraoperatively) and again in childhood. Changes in heminasal width, labial height, and labial width were analyzed and compared measures depending on whether the cleft was incomplete/complete or involved left/right side. Average heminasal width (sn-al) was set 1 mm less on the cleft side and measured only 0.7 mm less at 6 years. Labial height (sn-cphi) was slightly greater on the cleft side at repair and matched the noncleft side at follow-up. Vertical dimension (sbal-cphi) was slightly less at operation; the percent change was the same on both sides. Transverse labial width (cphi-ch) was set short on the cleft side and lengthened disproportionately, resulting in less than 1 mm difference at 6 years. All anthropometric dimensions grew less in complete cleft lips compared with incomplete forms; however, only labial height and width were significantly different. There were no disparities in nasolabial growth between left- and right-sided cleft lips. Cleft side alar base drifts laterally and should be positioned slightly more medial and secured to nasalis or periosteum. Growth in labial height lags and, therefore, the repaired side should be equal to or slightly greater than on the normal side, particularly in a complete labial cleft. Transverse labial width grows more on the cleft side; thus, lateral Cupid's bow peak point can be marked closer to the commissure to match the labial height on the noncleft side. Therapeutic, IV.

TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

Science.gov (United States)

2017-01-01

Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969

Cognitive biases to healthy and unhealthy food words predict change in BMI.

Science.gov (United States)

Calitri, Raff; Pothos, Emmanuel M; Tapper, Katy; Brunstrom, Jeffrey M; Rogers, Peter J

2010-12-01

The current study explored the predictive value of cognitive biases to food cues (assessed by emotional Stroop and dot probe tasks) on weight change over a 1-year period. This was a longitudinal study with undergraduate students (N = 102) living in shared student accommodation. After controlling for the effects of variables associated with weight (e.g., physical activity, stress, restrained eating, external eating, and emotional eating), no effects of cognitive bias were found with the dot probe. However, for the emotional Stroop, cognitive bias to unhealthy foods predicted an increase in BMI whereas cognitive bias to healthy foods was associated with a decrease in BMI. Results parallel findings in substance abuse research; cognitive biases appear to predict behavior change. Accordingly, future research should consider strategies for attentional retraining, encouraging individuals to reorient attention away from unhealthy eating cues.

Neural Networks for protein Structure Prediction

DEFF Research Database (Denmark)

Bohr, Henrik

1998-01-01

This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones...

Medium- and Long-term Prediction of LOD Change by the Leap-step Autoregressive Model

Science.gov (United States)

Wang, Qijie

2015-08-01

The accuracy of medium- and long-term prediction of length of day (LOD) change base on combined least-square and autoregressive (LS+AR) deteriorates gradually. Leap-step autoregressive (LSAR) model can significantly reduce the edge effect of the observation sequence. Especially, LSAR model greatly improves the resolution of signals’ low-frequency components. Therefore, it can improve the efficiency of prediction. In this work, LSAR is used to forecast the LOD change. The LOD series from EOP 08 C04 provided by IERS is modeled by both the LSAR and AR models. The results of the two models are analyzed and compared. When the prediction length is between 10-30 days, the accuracy improvement is less than 10%. When the prediction length amounts to above 30 day, the accuracy improved obviously, with the maximum being around 19%. The results show that the LSAR model has higher prediction accuracy and stability in medium- and long-term prediction.

Adaptation, plasticity, and extinction in a changing environment: towards a predictive theory.

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Luis-Miguel Chevin

2010-04-01

Full Text Available Many species are experiencing sustained environmental change mainly due to human activities. The unusual rate and extent of anthropogenic alterations of the environment may exceed the capacity of developmental, genetic, and demographic mechanisms that populations have evolved to deal with environmental change. To begin to understand the limits to population persistence, we present a simple evolutionary model for the critical rate of environmental change beyond which a population must decline and go extinct. We use this model to highlight the major determinants of extinction risk in a changing environment, and identify research needs for improved predictions based on projected changes in environmental variables. Two key parameters relating the environment to population biology have not yet received sufficient attention. Phenotypic plasticity, the direct influence of environment on the development of individual phenotypes, is increasingly considered an important component of phenotypic change in the wild and should be incorporated in models of population persistence. Environmental sensitivity of selection, the change in the optimum phenotype with the environment, still crucially needs empirical assessment. We use environmental tolerance curves and other examples of ecological and evolutionary responses to climate change to illustrate how these mechanistic approaches can be developed for predictive purposes.

Three-dimensional turbulent swirling flow in a cylinder: Experiments and computations

International Nuclear Information System (INIS)

Gupta, Amit; Kumar, Ranganathan

2007-01-01

Dynamics of the three-dimensional flow in a cyclone with tangential inlet and tangential exit were studied using particle tracking velocimetry (PTV) and a three-dimensional computational model. The PTV technique is described in this paper and appears to be well suited for the current flow situation. The flow was helical in nature and a secondary recirculating flow was observed and well predicted by computations using the RNG k-ε turbulence model. The secondary flow was characterized by a single vortex which circulated around the axis and occupied a large fraction of the cylinder diameter. The locus of the vortex center meandered around the cylinder axis, making one complete revolution for a cylinder aspect ratio of 2. Tangential velocities from both experiments and computations were compared and found to be in good agreement. The general structure of the flow does not vary significantly as the Reynolds number is increased. However, slight changes in all components of velocity and pressure were seen as the inlet velocity is increased. By increasing the inlet aspect ratio it was observed that the vortex meandering changed significantly

Three-dimensional turbulent swirling flow in a cylinder: Experiments and computations

Energy Technology Data Exchange (ETDEWEB)

Gupta, Amit [Department of Mechanical, Materials and Aerospace Engineering, University of Central Florida, Orlando, FL 32816 (United States); Kumar, Ranganathan [Department of Mechanical, Materials and Aerospace Engineering, University of Central Florida, Orlando, FL 32816 (United States)]. E-mail: rnkumar@mail.ucf.edu

2007-04-15

Dynamics of the three-dimensional flow in a cyclone with tangential inlet and tangential exit were studied using particle tracking velocimetry (PTV) and a three-dimensional computational model. The PTV technique is described in this paper and appears to be well suited for the current flow situation. The flow was helical in nature and a secondary recirculating flow was observed and well predicted by computations using the RNG k-{epsilon} turbulence model. The secondary flow was characterized by a single vortex which circulated around the axis and occupied a large fraction of the cylinder diameter. The locus of the vortex center meandered around the cylinder axis, making one complete revolution for a cylinder aspect ratio of 2. Tangential velocities from both experiments and computations were compared and found to be in good agreement. The general structure of the flow does not vary significantly as the Reynolds number is increased. However, slight changes in all components of velocity and pressure were seen as the inlet velocity is increased. By increasing the inlet aspect ratio it was observed that the vortex meandering changed significantly.

Predicting drought propagation within peat layers using a three dimensionally explicit voxel based model

Science.gov (United States)

Condro, A. A.; Pawitan, H.; Risdiyanto, I.

2018-05-01

Peatlands are very vulnerable to widespread fires during dry seasons, due to availability of aboveground fuel biomass on the surface and belowground fuel biomass on the sub-surface. Hence, understanding drought propagation occurring within peat layers is crucial with regards to disaster mitigation activities on peatlands. Using a three dimensionally explicit voxel-based model of peatland hydrology, this study predicted drought propagation time lags into sub-surface peat layers after drought events occurrence on the surface of about 1 month during La-Nina and 2.5 months during El-Nino. The study was carried out on a high-conservation-value area of oil palm plantation in West Kalimantan. Validity of the model was evaluated and its applicability for disaster mitigation was discussed. The animations of simulated voxels are available at: goo.gl/HDRMYN (El-Nino 2015 episode) and goo.gl/g1sXPl (La-Nina 2016 episode). The model is available at: goo.gl/RiuMQz.

Structural integrity of frontostriatal connections predicts longitudinal changes in self-esteem.

Science.gov (United States)

Chavez, Robert S; Heatherton, Todd F

2017-06-01

Diverse neurological and psychiatric conditions are marked by a diminished sense of positive self-regard, and reductions in self-esteem are associated with risk for these disorders. Recent evidence has shown that the connectivity of frontostriatal circuitry reflects individual differences in self-esteem. However, it remains an open question as to whether the integrity of these connections can predict self-esteem changes over larger timescales. Using diffusion magnetic resonance imaging and probabilistic tractography, we demonstrate that the integrity of white matter pathways linking the medial prefrontal cortex to the ventral striatum predicts changes in self-esteem 8 months after initial scanning in a sample of 30 young adults. Individuals with greater integrity of this pathway during the scanning session at Time 1 showed increased levels of self-esteem at follow-up, whereas individuals with lower integrity showed stifled or decreased levels of self-esteem. These results provide evidence that frontostriatal white matter integrity predicts the trajectory of self-esteem development in early adulthood, which may contribute to blunted levels of positive self-regard seen in multiple psychiatric conditions, including depression and anxiety.

Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression.

Directory of Open Access Journals (Sweden)

Kosuke Yoshida

Full Text Available In diagnostic applications of statistical machine learning methods to brain imaging data, common problems include data high-dimensionality and co-linearity, which often cause over-fitting and instability. To overcome these problems, we applied partial least squares (PLS regression to resting-state functional magnetic resonance imaging (rs-fMRI data, creating a low-dimensional representation that relates symptoms to brain activity and that predicts clinical measures. Our experimental results, based upon data from clinically depressed patients and healthy controls, demonstrated that PLS and its kernel variants provided significantly better prediction of clinical measures than ordinary linear regression. Subsequent classification using predicted clinical scores distinguished depressed patients from healthy controls with 80% accuracy. Moreover, loading vectors for latent variables enabled us to identify brain regions relevant to depression, including the default mode network, the right superior frontal gyrus, and the superior motor area.

Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.

Science.gov (United States)

Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C

2016-01-01

Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.

Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

Science.gov (United States)

Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

2013-11-01

The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

Using Flow Characteristics in Three-Dimensional Power Doppler Ultrasound Imaging to Predict Complete Responses in Patients Undergoing Neoadjuvant Chemotherapy.

Science.gov (United States)

Shia, Wei-Chung; Huang, Yu-Len; Wu, Hwa-Koon; Chen, Dar-Ren

2017-05-01

Strategies are needed for the identification of a poor response to treatment and determination of appropriate chemotherapy strategies for patients in the early stages of neoadjuvant chemotherapy for breast cancer. We hypothesize that power Doppler ultrasound imaging can provide useful information on predicting response to neoadjuvant chemotherapy. The solid directional flow of vessels in breast tumors was used as a marker of pathologic complete responses (pCR) in patients undergoing neoadjuvant chemotherapy. Thirty-one breast cancer patients who received neoadjuvant chemotherapy and had tumors of 2 to 5 cm were recruited. Three-dimensional power Doppler ultrasound with high-definition flow imaging technology was used to acquire the indices of tumor blood flow/volume, and the chemotherapy response prediction was established, followed by support vector machine classification. The accuracy of pCR prediction before the first chemotherapy treatment was 83.87% (area under the ROC curve [AUC] = 0.6957). After the second chemotherapy treatment, the accuracy of was 87.9% (AUC = 0.756). Trend analysis showed that good and poor responders exhibited different trends in vascular flow during chemotherapy. This preliminary study demonstrates the feasibility of using the vascular flow in breast tumors to predict chemotherapeutic efficacy. © 2017 by the American Institute of Ultrasound in Medicine.

Are climate-related changes to the character of global-mean precipitation predictable?

International Nuclear Information System (INIS)

Stephens, Graeme L; Hu, Yongxiang

2010-01-01

The physical basis for the change in global-mean precipitation projected to occur with the warming associated with increased greenhouse gases is discussed. The expected increases to column water vapor W control the rate of increase of global precipitation accumulation through its affect on the planet's energy balance. The key role played by changes to downward longwave radiation controlled by this changing water vapor is emphasized. The basic properties of molecular absorption by water vapor dictate that the fractional rate of increase of global-mean precipitation must be significantly less that the fractional rate of increase in water vapor and it is further argued that this reduced rate of precipitation increase implies that the timescale for water re-cycling is increased in the global mean. This further implies less frequent precipitation over a fixed period of time, and the intensity of these less frequent precipitating events must subsequently increase in the mean to realize the increased global accumulation. These changes to the character of global-mean precipitation, predictable consequences of equally predictable changes to W, apply only to the global-mean state and not to the regional or local scale changes in precipitation.

Healthy work revisited: do changes in time strain predict well-being?

Science.gov (United States)

Moen, Phyllis; Kelly, Erin L; Lam, Jack

2013-04-01

Building on Karasek and Theorell (R. Karasek & T. Theorell, 1990, Healthy work: Stress, productivity, and the reconstruction of working life, New York, NY: Basic Books), we theorized and tested the relationship between time strain (work-time demands and control) and seven self-reported health outcomes. We drew on survey data from 550 employees fielded before and 6 months after the implementation of an organizational intervention, the results only work environment (ROWE) in a white-collar organization. Cross-sectional (wave 1) models showed psychological time demands and time control measures were related to health outcomes in expected directions. The ROWE intervention did not predict changes in psychological time demands by wave 2, but did predict increased time control (a sense of time adequacy and schedule control). Statistical models revealed increases in psychological time demands and time adequacy predicted changes in positive (energy, mastery, psychological well-being, self-assessed health) and negative (emotional exhaustion, somatic symptoms, psychological distress) outcomes in expected directions, net of job and home demands and covariates. This study demonstrates the value of including time strain in investigations of the health effects of job conditions. Results encourage longitudinal models of change in psychological time demands as well as time control, along with the development and testing of interventions aimed at reducing time strain in different populations of workers.

Sexual selection predicts advancement of avian spring migration in response to climate change

DEFF Research Database (Denmark)

Spottiswoode, Claire N; Tøttrup, Anders P; Coppack, Timothy

2006-01-01

Global warming has led to earlier spring arrival of migratory birds, but the extent of this advancement varies greatly among species, and it remains uncertain to what degree these changes are phenotypically plastic responses or microevolutionary adaptations to changing environmental conditions. We...... suggest that sexual selection could help to understand this variation, since early spring arrival of males is favoured by female choice. Climate change could weaken the strength of natural selection opposing sexual selection for early migration, which would predict greatest advancement in species...... in the timing of first-arriving individuals, suggesting that selection has not only acted on protandrous males. These results suggest that sexual selection may have an impact on the responses of organisms to climate change, and knowledge of a species' mating system might help to inform attempts at predicting...

Three-dimensional fuel pin model validation by prediction of hydrogen distribution in cladding and comparison with experiment

Energy Technology Data Exchange (ETDEWEB)

Aly, A. [North Carolina State Univ., Raleigh, NC (United States); Avramova, Maria [North Carolina State Univ., Raleigh, NC (United States); Ivanov, Kostadin [Pennsylvania State Univ., University Park, PA (United States); Motta, Arthur [Pennsylvania State Univ., University Park, PA (United States); Lacroix, E. [Pennsylvania State Univ., University Park, PA (United States); Manera, Annalisa [Univ. of Michigan, Ann Arbor, MI (United States); Walter, D. [Univ. of Michigan, Ann Arbor, MI (United States); Williamson, R. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Gamble, K. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2017-10-29

To correctly describe and predict this hydrogen distribution there is a need for multi-physics coupling to provide accurate three-dimensional azimuthal, radial, and axial temperature distributions in the cladding. Coupled high-fidelity reactor-physics codes with a sub-channel code as well as with a computational fluid dynamics (CFD) tool have been used to calculate detailed temperature distributions. These high-fidelity coupled neutronics/thermal-hydraulics code systems are coupled further with the fuel-performance BISON code with a kernel (module) for hydrogen. Both hydrogen migration and precipitation/dissolution are included in the model. Results from this multi-physics analysis is validated utilizing calculations of hydrogen distribution using models informed by data from hydrogen experiments and PIE data.

Three-dimensional dental arch changes of patients submitted to orthodontic-surgical treatment for correction of Class II malocclusion

Directory of Open Access Journals (Sweden)

Adriano Porto Peixoto

2014-08-01

Full Text Available INTRODUCTION: This study assessed the three-dimensional changes in the dental arch of patients submitted to orthodontic-surgical treatment for correction of Class II malocclusions at three different periods. METHODS: Landmarks previously identified on upper and lower dental casts were digitized on a three-dimensional digitizer MicroScribe-3DX and stored in Excel worksheets in order to assess the width, length and depth of patient's dental arches. RESULTS: During orthodontic preparation, the maxillary and mandibular transverse dimensions measured at the premolar regions were increased and maintained throughout the follow-up period. Intercanine width was increased only in the upper arch during orthodontic preparation. Maxillary arch length was reduced during orthodontic finalization, only. Upper and lower arch depths were stable in the study periods. Differences between centroid and gingival changes suggested that upper and lower arch premolars buccaly proclined during the pre-surgical period. CONCLUSIONS: Maxillary and mandibular dental arches presented transverse expansion at premolar regions during preoperative orthodontic preparation, with a tendency towards buccal tipping. The transverse dimensions were not altered after surgery. No sagittal or vertical changes were observed during the follow-up periods.

A linear regression model for predicting PNW estuarine temperatures in a changing climate

Science.gov (United States)

Pacific Northwest coastal regions, estuaries, and associated ecosystems are vulnerable to the potential effects of climate change, especially to changes in nearshore water temperature. While predictive climate models simulate future air temperatures, no such projections exist for...

Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.

Science.gov (United States)

Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J

2018-01-01

Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.

Predictive rhythmic tapping to isochronous and tempo changing metronomes in the nonhuman primate.

Science.gov (United States)

Gámez, Jorge; Yc, Karyna; Ayala, Yaneri A; Dotov, Dobromir; Prado, Luis; Merchant, Hugo

2018-04-30

Beat entrainment is the ability to entrain one's movements to a perceived periodic stimulus, such as a metronome or a pulse in music. Humans have a capacity to predictively respond to a periodic pulse and to dynamically adjust their movement timing to match the varying music tempos. Previous studies have shown that monkeys share some of the human capabilities for rhythmic entrainment, such as tapping regularly at the period of isochronous stimuli. However, it is still unknown whether monkeys can predictively entrain to dynamic tempo changes like humans. To address this question, we trained monkeys in three tapping tasks and compared their rhythmic entrainment abilities with those of humans. We found that, when immediate feedback about the timing of each movement is provided, monkeys can predictively entrain to an isochronous beat, generating tapping movements in anticipation of the metronome pulse. This ability also generalized to a novel untrained tempo. Notably, macaques can modify their tapping tempo by predicting the beat changes of accelerating and decelerating visual metronomes in a manner similar to humans. Our findings support the notion that nonhuman primates share with humans the ability of temporal anticipation during tapping to isochronous and smoothly changing sequences of stimuli. © 2018 New York Academy of Sciences.

Stages of Change or Changes of Stage? Predicting Transitions in Transtheoretical Model Stages in Relation to Healthy Food Choice

Science.gov (United States)

Armitage, Christopher J.; Sheeran, Paschal; Conner, Mark; Arden, Madelynne A.

2004-01-01

Relatively little research has examined factors that account for transitions between transtheoretical model (TTM) stages of change. The present study (N=787) used sociodemographic, TTM, and theory of planned behavior (TPB) variables, as well as theory-driven interventions to predict changes in stage. Longitudinal analyses revealed that…

Predictive Roles of Three-Dimensional Psychological Pain, Psychache, and Depression in Suicidal Ideation among Chinese College Students

Directory of Open Access Journals (Sweden)

Huanhuan Li

2017-09-01

Full Text Available How to develop an effective screening instrument for predicting suicide risk is an important issue in suicidal research. The aim of the present research was to explore the predictive roles of three screening measures in the evaluation of preexisting suicide risk factors in a sample of undergraduate students. We assessed 1,061 students using the Beck depression and suicidal ideation scales (BDI-I (BSI, the Psychache Scale (PAS, and the three-dimensional Psychological Pain Scale (TDPPS. Simultaneous multivariate regression analysis showed that the predictive values of pain avoidance scores and BDI scores for suicidal ideation were more significant than that of the PAS scores. Subsequently, 42 patients with major depressive disorder (MDD, 39 students with subthreshold depression (SD, and 18 healthy controls were voluntarily recruited. Students with SD were divided into high suicidal ideation (HSI-SD and low suicidal ideation (LSI-SD groups. Pain avoidance scores and BDI scores differed significantly among the MDD, HSI-SD, LSI-SD, and healthy control groups. Pain avoidance and BSI scores were significantly higher in the MDD and HSI-SD groups than those in the LSI-SD and healthy control groups. However, no significant difference was observed in BDI scores between the HSI-SD and LSI-SD groups. Pain avoidance and depression, rather than psychache, may be promising predictors of suicidal ideation in a Chinese young adult population.

prediction of the impacts of climate changes on the stream flow

African Journals Online (AJOL)

HOD

Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on Ajali River watershed ... Climate is the synthesis of atmospheric conditions characteristic of a .... generator available in the SWAT model.

Prediction of three-dimensional femoral offset from AP pelvis radiographs in primary hip osteoarthritis

Energy Technology Data Exchange (ETDEWEB)

Merle, C., E-mail: christian.merle@med.uni-heidelberg.de [Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford (United Kingdom); Department of Orthopaedic and Trauma Surgery, University Hospital Heidelberg (Germany); Waldstein, W., E-mail: wwaldstein@gmail.com [Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford (United Kingdom); Department of Orthopaedic and Trauma Surgery, University Hospital Heidelberg (Germany); Pegg, E.C., E-mail: elise.pegg@ndorms.ox.ac.uk [Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford (United Kingdom); Streit, M.R., E-mail: marcus.streit@med.uni-heidelberg.de [Department of Orthopaedic and Trauma Surgery, University Hospital Heidelberg (Germany); Gotterbarm, T., E-mail: tobias.gotterbarm@med.uni-heidelberg.de [Department of Orthopaedic and Trauma Surgery, University Hospital Heidelberg (Germany); Aldinger, P.R., E-mail: peter.aldinger@diak-stuttgart.de [Department of Orthopaedic Surgery, Paulinenhilfe, Diakonieklinikum, Stuttgart (Germany); Murray, D.W., E-mail: david.murray@ndorms.ox.ac.uk [Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford (United Kingdom); Gill, H.S., E-mail: r.gill@bath.ac.uk [Department of Mechanical Engineering, University of Bath (United Kingdom)

2013-08-15

Background: In pre-operative planning for total hip arthroplasty (THA), femoral offset (FO) is frequently underestimated on AP pelvis radiographs as a result of inaccurate patient positioning, imprecise magnification, and radiographic beam divergence. The aim of the present study was to evaluate the accuracy and reliability of predicting three-dimensional (3-D) FO from standardised AP pelvis radiographs. Methods: In a retrospective cohort study, pre-operative AP pelvis radiographs, AP hip radiographs and CT scans of a consecutive series of 345 patients (345 hips, 146 males, 199 females, mean age 60 (range: 40–79) years, mean body-mass-index 27 (range: 19–57) kg/m{sup 2}) with primary end-stage hip OA were reviewed. Patients were positioned according to a standardised protocol and all images were calibrated. Using validated custom programmes, FO was measured on corresponding radiographs and CT scans. Measurement reliability was evaluated using intra-class-correlation-coefficients. To predict 3-D FO from AP pelvis measurements and to assess the accuracy compared to CT, the entire cohort was randomly split into subgroups A and B. Gender specific regression equations were derived from group A (245 patients) and the accuracy of prediction was evaluated in group B (100 patients) using Bland–Altman plots. Results: In the entire cohort, mean FO was 39.2 mm (95%CI: 38.5–40.0 mm) on AP pelvis radiographs, 44.1 mm (95%CI: 43.4–44.9 mm) on AP hip radiographs and 44.6 mm (95%CI: 44.0–45.2 mm) on CT scans. In group B, we observed no significant difference between gender specific predicted FO (males: 48.0 mm, 95%CI: 47.1–48.8 mm; females: 42.0 mm, 95%CI: 41.1–42.8 mm) and FO as measured on CT (males: 47.7 mm, 95%CI: 46.1–49.4 mm, p = 0.689; females: 41.6 mm, 95%CI: 40.3–43.0 mm, p = 0.607). Conclusions: The present study suggests that FO can be accurately and reliably predicted from AP pelvis radiographs in patients with primary end-stage hip osteoarthritis

Within-person changes in salivary testosterone and physical characteristics of puberty predict boys' daily affect.

Science.gov (United States)

Klipker, Kathrin; Wrzus, Cornelia; Rauers, Antje; Boker, Steven M; Riediger, Michaela

2017-09-01

Recent investigations highlighted the role of within-person pubertal changes for adolescents' behavior. Yet, little is known about effects on adolescents' daily affect, particularly regarding the hormonal changes underlying physical changes during puberty. In a study with 148 boys aged 10 to 20years, we tested whether within-person physical and hormonal changes over eight months predicted everyday affect fluctuations, measured with experience sampling. As expected, greater within-person changes in testosterone (but not in dehydroepiandrosterone) were associated with higher affect fluctuations in daily life. Additionally, greater physical changes predicted higher affect fluctuations for individuals in the beginning of puberty. The findings demonstrate the relevance of physical and hormonal changes in boys' affective (in)stability. Copyright © 2017 Elsevier Inc. All rights reserved.

Cross-modal prediction changes the timing of conscious access during the motion-induced blindness.

Science.gov (United States)

Chang, Acer Y C; Kanai, Ryota; Seth, Anil K

2015-01-01

Despite accumulating evidence that perceptual predictions influence perceptual content, the relations between these predictions and conscious contents remain unclear, especially for cross-modal predictions. We examined whether predictions of visual events by auditory cues can facilitate conscious access to the visual stimuli. We trained participants to learn associations between auditory cues and colour changes. We then asked whether congruency between auditory cues and target colours would speed access to consciousness. We did this by rendering a visual target subjectively invisible using motion-induced blindness and then gradually changing its colour while presenting congruent or incongruent auditory cues. Results showed that the visual target gained access to consciousness faster in congruent than in incongruent trials; control experiments excluded potentially confounding effects of attention and motor response. The expectation effect was gradually established over blocks suggesting a role for extensive training. Overall, our findings show that predictions learned through cross-modal training can facilitate conscious access to visual stimuli. Copyright © 2014 Elsevier Inc. All rights reserved.

Climatic associations of British species distributions show good transferability in time but low predictive accuracy for range change.

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Giovanni Rapacciuolo

Full Text Available Conservation planners often wish to predict how species distributions will change in response to environmental changes. Species distribution models (SDMs are the primary tool for making such predictions. Many methods are widely used; however, they all make simplifying assumptions, and predictions can therefore be subject to high uncertainty. With global change well underway, field records of observed range shifts are increasingly being used for testing SDM transferability. We used an unprecedented distribution dataset documenting recent range changes of British vascular plants, birds, and butterflies to test whether correlative SDMs based on climate change provide useful approximations of potential distribution shifts. We modelled past species distributions from climate using nine single techniques and a consensus approach, and projected the geographical extent of these models to a more recent time period based on climate change; we then compared model predictions with recent observed distributions in order to estimate the temporal transferability and prediction accuracy of our models. We also evaluated the relative effect of methodological and taxonomic variation on the performance of SDMs. Models showed good transferability in time when assessed using widespread metrics of accuracy. However, models had low accuracy to predict where occupancy status changed between time periods, especially for declining species. Model performance varied greatly among species within major taxa, but there was also considerable variation among modelling frameworks. Past climatic associations of British species distributions retain a high explanatory power when transferred to recent time--due to their accuracy to predict large areas retained by species--but fail to capture relevant predictors of change. We strongly emphasize the need for caution when using SDMs to predict shifts in species distributions: high explanatory power on temporally-independent records

The role of 3-dimensional sonography and virtual sonographic ...

African Journals Online (AJOL)

A.M. Tawfeek

2017-12-06

Dec 6, 2017 ... 85.7%; positive predictive values were 96.5%; negative predictive value were 85.7%. .... dence of urinary tract injury or infection; suspicious lesions or ..... dimensional ultrasound in the pediatric urinary tract: pictorial demon-.

Predictive Manufacturing: A Classification Strategy to Predict Product Failures

DEFF Research Database (Denmark)

Khan, Abdul Rauf; Schiøler, Henrik; Kulahci, Murat

2018-01-01

manufacturing analytics model that employs a big data approach to predicting product failures; third, we illustrate the issue of high dimensionality, along with statistically redundant information; and, finally, our proposed method will be compared against the well-known classification methods (SVM, K......-nearest neighbor, artificial neural networks). The results from real data show that our predictive manufacturing analytics approach, using genetic algorithms and Voronoi tessellations, is capable of predicting product failure with reasonable accuracy. The potential application of this method contributes...... to accurately predicting product failures, which would enable manufacturers to reduce production costs without compromising product quality....

One-dimensional versus two-dimensional electronic states in vicinal surfaces

International Nuclear Information System (INIS)

Ortega, J E; Ruiz-Oses, M; Cordon, J; Mugarza, A; Kuntze, J; Schiller, F

2005-01-01

Vicinal surfaces with periodic arrays of steps are among the simplest lateral nanostructures. In particular, noble metal surfaces vicinal to the (1 1 1) plane are excellent test systems to explore the basic electronic properties in one-dimensional superlattices by means of angular photoemission. These surfaces are characterized by strong emissions from free-electron-like surface states that scatter at step edges. Thereby, the two-dimensional surface state displays superlattice band folding and, depending on the step lattice constant d, it splits into one-dimensional quantum well levels. Here we use high-resolution, angle-resolved photoemission to analyse surface states in a variety of samples, in trying to illustrate the changes in surface state bands as a function of d

Dimensional control of die castings

Science.gov (United States)

Karve, Aniruddha Ajit

The demand for net shape die castings, which require little or no machining, is steadily increasing. Stringent customer requirements are forcing die casters to deliver high quality castings in increasingly short lead times. Dimensional conformance to customer specifications is an inherent part of die casting quality. The dimensional attributes of a die casting are essentially dependent upon many factors--the quality of the die and the degree of control over the process variables being the two major sources of dimensional error in die castings. This study focused on investigating the nature and the causes of dimensional error in die castings. The two major components of dimensional error i.e., dimensional variability and die allowance were studied. The major effort of this study was to qualitatively and quantitatively study the effects of casting geometry and process variables on die casting dimensional variability and die allowance. This was accomplished by detailed dimensional data collection at production die casting sites. Robust feature characterization schemes were developed to describe complex casting geometry in quantitative terms. Empirical modeling was utilized to quantify the effects of the casting variables on dimensional variability and die allowance for die casting features. A number of casting geometry and process variables were found to affect dimensional variability in die castings. The dimensional variability was evaluated by comparisons with current published dimensional tolerance standards. The casting geometry was found to play a significant role in influencing the die allowance of the features measured. The predictive models developed for dimensional variability and die allowance were evaluated to test their effectiveness. Finally, the relative impact of all the components of dimensional error in die castings was put into perspective, and general guidelines for effective dimensional control in the die casting plant were laid out. The results of

Analysis of changes in gingival contour from three-dimensional co-ordinate data in subjects with drug-induced gingival overgrowth.

Science.gov (United States)

Thomason, J M; Ellis, J S; Jovanovski, V; Corson, M; Lynch, E; Seymour, R A

2005-10-01

This aim of this study was to develop and assess a technique that could be used to assess accurately the gingival volume changes seen in drug-induced gingival overgrowth by the analysis of data obtained from an entire gingival surface by means of three-dimensional imaging. Stone dental models of patients before and after gingivectomy procedures were digitized with a laser scanner and then regenerated as computer models constructed from the acquired three-dimensional co-ordinate data. A comparison of superposed "before" and "after" surfaces was undertaken to assess and accurately quantify changes in gingival contour. The mean vertical tissue reduction varied from 1.58 to 2.56 mm in the four study subjects and individual differences are shown. The maximum thickness of removed buccal gingival overgrowth was found to range between 1.20 and 3.40 mm. The volume of tissue removed from each inter-dental papilla ranged from 4.2 to 46.1 mm3 and the mean volume of the papilla removed from each subject+/-SD values was 24.8+/-13.1 mm3. This method will measure changes in gingival tissues to within 60 microm in one plane, making it ideal for the assessment of longitudinal changes in gingival contour as seen in the development of gingival overgrowth, its recurrence after surgery or the changes in volume brought about by surgery.

Protein-protein interaction site predictions with three-dimensional probability distributions of interacting atoms on protein surfaces.

Directory of Open Access Journals (Sweden)

Ching-Tai Chen

Full Text Available Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins and were tested on an independent dataset (consisting of 142 proteins. The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted

Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

Science.gov (United States)

Chen, Ching-Tai; Peng, Hung-Pin; Jian, Jhih-Wei; Tsai, Keng-Chang; Chang, Jeng-Yih; Yang, Ei-Wen; Chen, Jun-Bo; Ho, Shinn-Ying; Hsu, Wen-Lian; Yang, An-Suei

2012-01-01

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with

Performance prediction of centrifugal compressor impellers using quasi-three-dimensional analysis

International Nuclear Information System (INIS)

Ahn, S. J.; Kim, K. Y.; Oh, H. W.

2001-01-01

This-paper presents analysis of the flows through three different types of radial compressor by using quasi-three-dimensional analysis method. The method obtains two-dimensional solution for velocity distribution on meridional plane, and then calculates approximately the static pressure distributions on blade surfaces. Finite difference method is used for the solutions of governing equations. The compressors have low level compression-ratio and 12 straight radial blades with no sweepback. The results are compared with experimental data and the results of inviscid analysis with finite element method. It can be concluded that the agreement is good for the cases where viscous effects are not dominant

Changing currents: a strategy for understanding and predicting the changing ocean circulation.

Science.gov (United States)

Bryden, Harry L; Robinson, Carol; Griffiths, Gwyn

2012-12-13

Within the context of UK marine science, we project a strategy for ocean circulation research over the next 20 years. We recommend a focus on three types of research: (i) sustained observations of the varying and evolving ocean circulation, (ii) careful analysis and interpretation of the observed climate changes for comparison with climate model projections, and (iii) the design and execution of focused field experiments to understand ocean processes that are not resolved in coupled climate models so as to be able to embed these processes realistically in the models. Within UK-sustained observations, we emphasize smart, cost-effective design of the observational network to extract maximum information from limited field resources. We encourage the incorporation of new sensors and new energy sources within the operational environment of UK-sustained observational programmes to bridge the gap that normally separates laboratory prototype from operational instrument. For interpreting the climate-change records obtained through a variety of national and international sustained observational programmes, creative and dedicated UK scientists should lead efforts to extract the meaningful signals and patterns of climate change and to interpret them so as to project future changes. For the process studies, individual scientists will need to work together in team environments to combine observational and process modelling results into effective improvements in the coupled climate models that will lead to more accurate climate predictions.

Assessment of Soft Tissue Changes by Cephalometry and Two-Dimensional Photogrammetry in Bilateral Sagittal Split Ramus Osteotomy Cases

Directory of Open Access Journals (Sweden)

Jan Rustemeyer

2011-07-01

Full Text Available Objectives: We aimed to compare the standard methods of cephalometry and two-dimensional photogrammetry, to evaluate the reliability and accuracy of both methods.Material and Methods: Twenty-six patients (mean age 25.5, standard deviation (SD 5.2 years with Class II relationship and 23 patients with Class III relationship (mean age 26.4, SD 4.7 years who had undergone bilateral sagittal split ramus osteotomy were selected, with a median follow-up of 8 months between pre- and postsurgical evaluation. Pre- and postsurgical cephalograms and lateral photograms were traced and changes were recorded.Results: Pre- and postsurgical measurements of hard tissue angles and distances revealed higher correlations with cephalometrically performed soft tissue measurements of facial convexity (Class II: N-PG, r = - 0.50, P = 0.047; Class III: ANB, r = 0.73, P = 0.005; NaPg , r = 0.71, P = 0.007; and labiomental angle (Class II: SNB, r = 0.72, P = 0.002; ANB, r = - 0.72, P = 0.002; N-B, r = - 0.68, P = 0.004; ANS-Gn, r = 0.71, P = 0.002; Class III: ANS-Gn, r = 0.65, P = 0.043 compared with two-dimensional photogrammetry. However, two-dimensional photogrammetry revealed higher correlation between lower lip length and cephalometrically assessed angular hard tissue changes (Class II: SNB, r = 0.98, P = 0.007; N-B, r = 0.89, P = 0.037; N-Pg, r = 0.90, P = 0.033; Class III: SNB, r = - 0.54, P = 0.060; NAPg, r = - 0.65, P = 0.041; N-Pg, r = 0.58, P = 0.039.Conclusions: Our findings suggest that cephalometry and two-dimensional photogrammetry offer the possibility to complement one another.

Assessment of Soft Tissue Changes by Cephalometry and Two-Dimensional Photogrammetry in Bilateral Sagittal Split Ramus Osteotomy Cases

Science.gov (United States)

Martin, Alice

2011-01-01

ABSTRACT Objectives We aimed to compare the standard methods of cephalometry and two-dimensional photogrammetry, to evaluate the reliability and accuracy of both methods. Material and Methods Twenty-six patients (mean age 25.5, standard deviation (SD) 5.2 years) with Class II relationship and 23 patients with Class III relationship (mean age 26.4, SD 4.7 years) who had undergone bilateral sagittal split ramus osteotomy were selected, with a median follow-up of 8 months between pre- and postsurgical evaluation. Pre- and postsurgical cephalograms and lateral photograms were traced and changes were recorded. Results Pre- and postsurgical measurements of hard tissue angles and distances revealed higher correlations with cephalometrically performed soft tissue measurements of facial convexity (Class II: N-PG, r = - 0.50, P = 0.047; Class III: ANB, r = 0.73, P = 0.005; NaPg , r = 0.71, P = 0.007;) and labiomental angle (Class II: SNB, r = 0.72, P = 0.002; ANB, r = - 0.72, P = 0.002; N-B, r = - 0.68, P = 0.004; ANS-Gn, r = 0.71, P = 0.002; Class III: ANS-Gn, r = 0.65, P = 0.043) compared with two-dimensional photogrammetry. However, two-dimensional photogrammetry revealed higher correlation between lower lip length and cephalometrically assessed angular hard tissue changes (Class II: SNB, r = 0.98, P = 0.007; N-B, r = 0.89, P = 0.037; N-Pg, r = 0.90, P = 0.033; Class III: SNB, r = - 0.54, P = 0.060; NAPg, r = - 0.65, P = 0.041; N-Pg, r = 0.58, P = 0.039). Conclusions Our findings suggest that cephalometry and two-dimensional photogrammetry offer the possibility to complement one another. PMID:24421994

Vfold: a web server for RNA structure and folding thermodynamics prediction.

Science.gov (United States)

Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2014-01-01

The ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies. The Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization. The Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at "http://rna.physics.missouri.edu".

Life history and spatial traits predict extinction risk due to climate change

Science.gov (United States)

Pearson, Richard G.; Stanton, Jessica C.; Shoemaker, Kevin T.; Aiello-Lammens, Matthew E.; Ersts, Peter J.; Horning, Ned; Fordham, Damien A.; Raxworthy, Christopher J.; Ryu, Hae Yeong; McNees, Jason; Akçakaya, H. Reşit

2014-03-01

There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate. Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change based on the expectation that established assessments such as the IUCN Red List need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened, no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.

Dynamic colloidal assembly pathways via low dimensional models

Energy Technology Data Exchange (ETDEWEB)

Yang, Yuguang; Bevan, Michael A., E-mail: mabevan@jhu.edu [Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218 (United States); Thyagarajan, Raghuram; Ford, David M. [Chemical Engineering, University of Massachusetts, Amherst, Massachusetts 01003 (United States)

2016-05-28

Here we construct a low-dimensional Smoluchowski model for electric field mediated colloidal crystallization using Brownian dynamic simulations, which were previously matched to experiments. Diffusion mapping is used to infer dimensionality and confirm the use of two order parameters, one for degree of condensation and one for global crystallinity. Free energy and diffusivity landscapes are obtained as the coefficients of a low-dimensional Smoluchowski equation to capture the thermodynamics and kinetics of microstructure evolution. The resulting low-dimensional model quantitatively captures the dynamics of different assembly pathways between fluid, polycrystal, and single crystals states, in agreement with the full N-dimensional data as characterized by first passage time distributions. Numerical solution of the low-dimensional Smoluchowski equation reveals statistical properties of the dynamic evolution of states vs. applied field amplitude and system size. The low-dimensional Smoluchowski equation and associated landscapes calculated here can serve as models for predictive control of electric field mediated assembly of colloidal ensembles into two-dimensional crystalline objects.

Improving predictive capabilities of environmental change with GLOBE data

Science.gov (United States)

Robin, Jessica Hill

This dissertation addresses two applications of Normalized Difference Vegetation Index (NDVI) essential for predicting environmental changes. The first study focuses on whether NDVI can improve model simulations of evapotranspiration for temperate Northern (>35°) regions. The second study focuses on whether NDVI can detect phenological changes in start of season (SOS) for high Northern (>60°) environments. The overall objectives of this research were to (1) develop a methodology for utilizing GLOBE data in NDVI research; and (2) provide a critical analysis of NDVI as a long-term monitoring tool for environmental change. GLOBE is an international partnership network of K-12 students, teachers, and scientists working together to study and understand the global environment. The first study utilized data collected by one GLOBE school in Greenville, Pennsylvania and the second utilized phenology observations made by GLOBE students in Alaska. Results from the first study showed NDVI could predict transpiration periods for environments like Greenville, Pennsylvania. In phenological terms, these environments have three distinct periods (QI, QII, and QIII). QI reflects onset of the growing season (mid March--mid May) when vegetation is greening up (NDVI 0.60). Results from the second study showed that a climate threshold of 153 +/- 22 growing degree days was a better predictor of SOS for Fairbanks than a NDVI threshold applied to temporal AVHRR and MODIS datasets. Accumulated growing degree days captured the interannual variability of SOS better than the NDVI threshold and most closely resembled actual SOS observations made by GLOBE students. Overall, biweekly composites and effects of clouds, snow, and conifers limit the ability of NDVI to monitor phenological changes in Alaska. Both studies did show that GLOBE data provides an important source of input and validation information for NDVI research.

Probing temperature-driven flow lines in a gated two-dimensional electron gas with tunable spin-splitting

International Nuclear Information System (INIS)

Wang, Yi-Ting; Huang, C F; Chen, Wei-Jen; Chang, Y H; Liang, C-T; Kim, Gil-Ho; Lo, Shun-Tsung; Nicholls, J T; Lin, Li-Hung; Ritchie, D A; Dolan, B P

2012-01-01

We study the temperature flow of conductivities in a gated GaAs two-dimensional electron gas (2DEG) containing self-assembled InAs dots and compare the results with recent theoretical predictions. By changing the gate voltage, we are able to tune the 2DEG density and thus vary disorder and spin-splitting. Data for both the spin-resolved and spin-degenerate phase transitions are presented, the former collapsing to the latter with decreasing gate voltage and/or decreasing spin-splitting. The experimental results support a recent theory, based on modular symmetry, which predicts how the critical Hall conductivity varies with spin-splitting.

Can phenological models predict tree phenology accurately under climate change conditions?

Science.gov (United States)

Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

2014-05-01

The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

Improving sub-pixel imperviousness change prediction by ensembling heterogeneous non-linear regression models

Science.gov (United States)

Drzewiecki, Wojciech

2016-12-01

In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels) was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques. The results proved that in case of sub-pixel evaluation the most accurate prediction of change may not necessarily be based on the most accurate individual assessments. When single methods are considered, based on obtained results Cubist algorithm may be advised for Landsat based mapping of imperviousness for single dates. However, Random Forest may be endorsed when the most reliable evaluation of imperviousness change is the primary goal. It gave lower accuracies for individual assessments, but better prediction of change due to more correlated errors of individual predictions. Heterogeneous model ensembles performed for individual time points assessments at least as well as the best individual models. In case of imperviousness change assessment the ensembles always outperformed single model approaches. It means that it is possible to improve the accuracy of sub-pixel imperviousness change assessment using ensembles of heterogeneous non-linear regression models.

Quantitative prediction of respiratory tidal volume based on the external torso volume change: a potential volumetric surrogate

International Nuclear Information System (INIS)

Li Guang; Arora, Naveen C; Xie Huchen; Ning, Holly; Citrin, Deborah; Kaushal, Aradhana; Zach, Leor; Camphausen, Kevin; Miller, Robert W; Lu Wei; Low, Daniel

2009-01-01

An external respiratory surrogate that not only highly correlates with but also quantitatively predicts internal tidal volume should be useful in guiding four-dimensional computed tomography (4DCT), as well as 4D radiation therapy (4DRT). A volumetric surrogate should have advantages over external fiducial point(s) for monitoring respiration-induced motion of the torso, which deforms in synchronization with a patient-specific breathing pattern. This study establishes a linear relationship between the external torso volume change (TVC) and lung air volume change (AVC) by validating a proposed volume conservation hypothesis (TVC = AVC) throughout the respiratory cycle using 4DCT and spirometry. Fourteen patients' torso 4DCT images and corresponding spirometric tidal volumes were acquired to examine this hypothesis. The 4DCT images were acquired using dual surrogates in cine mode and amplitude-based binning in 12 respiratory stages, minimizing residual motion artifacts. Torso and lung volumes were calculated using threshold-based segmentation algorithms and volume changes were calculated relative to the full-exhalation stage. The TVC and AVC, as functions of respiratory stages, were compared, showing a high correlation (r = 0.992 ± 0.005, p 2 = 0.980) without phase shift. The AVC was also compared to the spirometric tidal volumes, showing a similar linearity (slope = 1.030 ± 0.092, R 2 = 0.947). In contrast, the thoracic and abdominal heights measured from 4DCT showed relatively low correlation (0.28 ± 0.44 and 0.82 ± 0.30, respectively) and location-dependent phase shifts. This novel approach establishes the foundation for developing an external volumetric respiratory surrogate.

Three-dimensional effects of curved plasma actuators in quiescent air

International Nuclear Information System (INIS)

Wang Chincheng; Durscher, Ryan; Roy, Subrata

2011-01-01

This paper presents results on a new class of curved plasma actuators for the inducement of three-dimensional vortical structures. The nature of the fluid flow inducement on a flat plate, in quiescent conditions, due to four different shapes of dielectric barrier discharge (DBD) plasma actuators is numerically investigated. The three-dimensional plasma kinetic equations are solved using our in-house, finite element based, multiscale ionized gas (MIG) flow code. Numerical results show electron temperature and three dimensional plasma force vectors for four shapes, which include linear, triangular, serpentine, and square actuators. Three-dimensional effects such as pinching and spreading the neighboring fluid are observed for serpentine and square actuators. The mechanisms of vorticity generation for DBD actuators are discussed. Also the influence of geometric wavelength (λ) and amplitude (Λ) of the serpentine and square actuators on vectored thrust inducement is predicted. This results in these actuators producing significantly better flow mixing downstream as compared to the standard linear actuator. Increasing the wavelengths of serpentine and square actuators in the spanwise direction is shown to enhance the pinching effect giving a much higher vertical velocity. On the contrary, changing the amplitude of the curved actuator varies the streamwise velocity significantly influencing the near wall jet. Experimental data for a serpentine actuator are also reported for validation purpose.

An Application to the Prediction of LOD Change Based on General Regression Neural Network

Science.gov (United States)

Zhang, X. H.; Wang, Q. J.; Zhu, J. J.; Zhang, H.

2011-07-01

Traditional prediction of the LOD (length of day) change was based on linear models, such as the least square model and the autoregressive technique, etc. Due to the complex non-linear features of the LOD variation, the performances of the linear model predictors are not fully satisfactory. This paper applies a non-linear neural network - general regression neural network (GRNN) model to forecast the LOD change, and the results are analyzed and compared with those obtained with the back propagation neural network and other models. The comparison shows that the performance of the GRNN model in the prediction of the LOD change is efficient and feasible.

Predicting Subtype Selectivity for Adenosine Receptor Ligands with Three-Dimensional Biologically Relevant Spectrum (BRS-3D)

Science.gov (United States)

He, Song-Bing; Ben Hu; Kuang, Zheng-Kun; Wang, Dong; Kong, De-Xin

2016-11-01

Adenosine receptors (ARs) are potential therapeutic targets for Parkinson’s disease, diabetes, pain, stroke and cancers. Prediction of subtype selectivity is therefore important from both therapeutic and mechanistic perspectives. In this paper, we introduced a shape similarity profile as molecular descriptor, namely three-dimensional biologically relevant spectrum (BRS-3D), for AR selectivity prediction. Pairwise regression and discrimination models were built with the support vector machine methods. The average determination coefficient (r2) of the regression models was 0.664 (for test sets). The 2B-3 (A2B vs A3) model performed best with q2 = 0.769 for training sets (10-fold cross-validation), and r2 = 0.766, RMSE = 0.828 for test sets. The models’ robustness and stability were validated with 100 times resampling and 500 times Y-randomization. We compared the performance of BRS-3D with 3D descriptors calculated by MOE. BRS-3D performed as good as, or better than, MOE 3D descriptors. The performances of the discrimination models were also encouraging, with average accuracy (ACC) 0.912 and MCC 0.792 (test set). The 2A-3 (A2A vs A3) selectivity discrimination model (ACC = 0.882 and MCC = 0.715 for test set) outperformed an earlier reported one (ACC = 0.784). These results demonstrated that, through multiple conformation encoding, BRS-3D can be used as an effective molecular descriptor for AR subtype selectivity prediction.

Two-dimensional liquid chromatography

DEFF Research Database (Denmark)

Græsbøll, Rune

-dimensional separation space. Optimization of gradients in online RP×RP is more difficult than in normal HPLC as a result of the increased number of parameters and their influence on each other. Modeling the coverage of the compounds across the two-dimensional chromatogram as a result of a change in gradients could...... be used for optimization purposes, and reduce the time spend on optimization. In this thesis (chapter 6), and manuscript B, a measure of the coverage of the compounds in the twodimensional separation space is defined. It is then shown that this measure can be modeled for changes in the gradient in both...

Three-dimensional analysis of craniofacial bones using three-dimensional computer tomography

Energy Technology Data Exchange (ETDEWEB)

Ono, Ichiro; Ohura, Takehiko; Kimura, Chu (Hokkaido Univ., Sapporo (Japan). School of Medicine) (and others)

1989-08-01

Three-dimensional computer tomography (3DCT) was performed in patients with various diseases to visualize stereoscopically the deformity of the craniofacial bones. The data obtained were analyzed by the 3DCT analyzing system. A new coordinate system was established using the median sagittal plane of the face (a plane passing through sella, nasion and basion) on the three-dimensional image. Three-dimensional profilograms were prepared for detailed analysis of the deformation of craniofacial bones for cleft lip and palate, mandibular prognathia and hemifacial microsomia. For patients, asymmetry in the frontal view and twist-formed complicated deformities were observed, as well as deformity of profiles in the anteroposterior and up-and-down directions. A newly developed technique allows three-dimensional visualization of changes in craniofacial deformity. It would aid in determining surgical strategy, including crani-facial surgery and maxillo-facial surgery, and in evaluating surgical outcome. (N.K.).

Three-dimensional analysis of craniofacial bones using three-dimensional computer tomography

International Nuclear Information System (INIS)

Ono, Ichiro; Ohura, Takehiko; Kimura, Chu

1989-01-01

Three-dimensional computer tomography (3DCT) was performed in patients with various diseases to visualize stereoscopically the deformity of the craniofacial bones. The data obtained were analyzed by the 3DCT analyzing system. A new coordinate system was established using the median sagittal plane of the face (a plane passing through sella, nasion and basion) on the three-dimensional image. Three-dimensional profilograms were prepared for detailed analysis of the deformation of craniofacial bones for cleft lip and palate, mandibular prognathia and hemifacial microsomia. For patients, asymmetry in the frontal view and twist-formed complicated deformities were observed, as well as deformity of profiles in the anteroposterior and up-and-down directions. A newly developed technique allows three-dimensional visualization of changes in craniofacial deformity. It would aid in determining surgical strategy, including crani-facial surgery and maxillo-facial surgery, and in evaluating surgical outcome. (N.K.)

Prediction of knock limited operating conditions of a natural gas engine

International Nuclear Information System (INIS)

Soylu, Seref

2005-01-01

Computer models of engine processes are valuable tools for predicting and analyzing engine performance and allow exploration of many engine design alternatives in an inexpensive fashion. In the present work, a zero-dimensional, two zone thermodynamic model was used to determine the knock limited operating conditions of a natural gas engine. Experimentally based burning rate models were used for flame initiation and propagation calculations. A knock model was incorporated with the zero-dimensional model. Comparison of the measured and calculated cylinder pressure data indicated that the model is able to match the measured cylinder pressure data with less than 8% error in magnitudes if the computations are started at the experimental spark timing. The knock predictions agreed with the measurements also. With the established knock model, it is possible not only to investigate whether knock is observed with changing operating and design parameters, but also to evaluate their effects on the maximum possible knock intensity

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

Energy Technology Data Exchange (ETDEWEB)

Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)

2015-01-15

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming.

Science.gov (United States)

Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

International Nuclear Information System (INIS)

Hirata, Yoshito; Aihara, Kazuyuki; Suzuki, Hideyuki; Shiro, Masanori; Takahashi, Nozomu; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data

Social Networking Site Use Predicts Changes in Young Adults’ Psychological Adjustment

Science.gov (United States)

Szwedo, David E.; Mikami, Amori Yee; Allen, Joseph P.

2012-01-01

This study examined youths’ friendships and posted pictures on social networking sites as predictors of changes in their adjustment over time. Observational, self-report, and peer report data were obtained from a community sample of 89 young adults interviewed at age 21 and again at age 22. Findings were consistent with a leveling effect for online friendships, predicting decreases in internalizing symptoms for youth with lower initial levels of social acceptance, but increases in symptoms for youth with higher initial levels over the following year. Across the entire sample, deviant behavior in posted photos predicted increases in young adults’ problematic alcohol use over time. The importance of considering the interplay between online and offline social factors for predicting adjustment is discussed. PMID:23109797

Prediction of the microsurgical window for skull-base tumors by advanced three-dimensional multi-fusion volumetric imaging

International Nuclear Information System (INIS)

Oishi, Makoto; Fukuda, Masafumi; Saito, Akihiko; Hiraishi, Tetsuya; Fujii, Yukihiko; Ishida, Go

2011-01-01

The surgery of skull base tumors (SBTs) is difficult due to the complex and narrow surgical window that is restricted by the cranium and important structures. The utility of three-dimensional multi-fusion volumetric imaging (3-D MFVI) for visualizing the predicted window for SBTs was evaluated. Presurgical simulation using 3-D MFVI was performed in 32 patients with SBTs. Imaging data were collected from computed tomography, magnetic resonance imaging, and digital subtraction angiography. Skull data was processed to imitate actual bone resection and integrated with various structures extracted from appropriate imaging modalities by image-analyzing software. The simulated views were compared with the views obtained during surgery. All craniotomies and bone resections except opening of the acoustic canal in 2 patients were performed as simulated. The simulated window allowed observation of the expected microsurgical anatomies including tumors, vasculatures, and cranial nerves, through the predicted operative window. We could not achieve the planned tumor removal in only 3 patients. 3-D MFVI afforded high quality images of the relevant microsurgical anatomies during the surgery of SBTs. The intraoperative deja-vu effect of the simulation increased the confidence of the surgeon in the planned surgical procedures. (author)

Monitoring beach changes using GPS surveying techniques

Science.gov (United States)

Morton, Robert; Leach, Mark P.; Paine, Jeffrey G.; Cardoza, Michael A.

1993-01-01

A need exists for frequent and prompt updating of shoreline positions, rates of shoreline movement, and volumetric nearshore changes. To effectively monitor and predict these beach changes, accurate measurements of beach morphology incorporating both shore-parallel and shore-normal transects are required. Although it is possible to monitor beach dynamics using land-based surveying methods, it is generally not practical to collect data of sufficient density and resolution to satisfy a three-dimensional beach-change model of long segments of the coast. The challenge to coastal scientists is to devise new beach monitoring methods that address these needs and are rapid, reliable, relatively inexpensive, and maintain or improve measurement accuracy.

A predictive framework to understand forest responses to global change.

Science.gov (United States)

McMahon, Sean M; Dietze, Michael C; Hersh, Michelle H; Moran, Emily V; Clark, James S

2009-04-01

Forests are one of Earth's critical biomes. They have been shown to respond strongly to many of the drivers that are predicted to change natural systems over this century, including climate, introduced species, and other anthropogenic influences. Predicting how different tree species might respond to this complex of forces remains a daunting challenge for forest ecologists. Yet shifts in species composition and abundance can radically influence hydrological and atmospheric systems, plant and animal ranges, and human populations, making this challenge an important one to address. Forest ecologists have gathered a great deal of data over the past decades and are now using novel quantitative and computational tools to translate those data into predictions about the fate of forests. Here, after a brief review of the threats to forests over the next century, one of the more promising approaches to making ecological predictions is described: using hierarchical Bayesian methods to model forest demography and simulating future forests from those models. This approach captures complex processes, such as seed dispersal and mortality, and incorporates uncertainty due to unknown mechanisms, data problems, and parameter uncertainty. After describing the approach, an example by simulating drought for a southeastern forest is offered. Finally, there is a discussion of how this approach and others need to be cast within a framework of prediction that strives to answer the important questions posed to environmental scientists, but does so with a respect for the challenges inherent in predicting the future of a complex biological system.

Half-metallic ferromagnetism prediction in MoS2-based two-dimensional superlattice from first-principles

Science.gov (United States)

Wen, Yan-Ni; Gao, Peng-Fei; Xia, Ming-Gang; Zhang, Sheng-Li

2018-03-01

Half-metallic ferromagnetism (HMFM) has great potential application in spin filter. However, it is extremely rare, especially in two-dimensional (2D) materials. At present, 2D materials have drawn international interest in spintronic devices. Here, we use ab initio density functional theory (DFT) calculations to study the structural stability and electrical and magnetic properties of the MoS2-based 2D superlattice formed by inserting graphene hexagonal ring in 6 × 6 × 1 MoS2 supercell. Two kinds of structures with hexagonal carbon ring were predicted with structural stability and were shown HMFM. The two structures combine the spin transport capacity of graphene with the magnetism of the defective 2D MoS2. And they have strong covalent bonding between the C and S or Mo atoms near the interface. This work is very useful to help us to design reasonable MoS2-based spin filter.

Analysis of Phenix End-of-Life asymmetry test with multi-dimensional pool modeling of MARS-LMR code

International Nuclear Information System (INIS)

Jeong, H.-Y.; Ha, K.-S.; Choi, C.-W.; Park, M.-G.

2015-01-01

Highlights: • Pool behaviors under asymmetrical condition in an SFR were evaluated with MARS-LMR. • The Phenix asymmetry test was analyzed one-dimensionally and multi-dimensionally. • One-dimensional modeling has limitation to predict the cold pool temperature. • Multi-dimensional modeling shows improved prediction of stratification and mixing. - Abstract: The understanding of complicated pool behaviors and its modeling is essential for the design and safety analysis of a pool-type Sodium-cooled Fast Reactor. One of the remarkable recent efforts on the study of pool thermal–hydraulic behaviors is the asymmetrical test performed as a part of Phenix End-of-Life tests by the CEA. To evaluate the performance of MARS-LMR code, which is a key system analysis tool for the design of an SFR in Korea, in the prediction of thermal hydraulic behaviors during an asymmetrical condition, the Phenix asymmetry test is analyzed with MARS-LMR in the present study. Pool regions are modeled with two different approaches, one-dimensional modeling and multi-dimensional one, and the prediction results are analyzed to identify the appropriateness of each modeling method. The prediction with one-dimensional pool modeling shows a large deviation from the measured data at the early stage of the test, which suggests limitations to describe the complicated thermal–hydraulic phenomena. When the pool regions are modeled multi-dimensionally, the prediction gives improved results quite a bit. This improvement is explained by the enhanced modeling of pool mixing with the multi-dimensional modeling. On the basis of the results from the present study, it is concluded that an accurate modeling of pool thermal–hydraulics is a prerequisite for the evaluation of design performance and safety margin quantification in the future SFR developments

Predicting Mood Changes in Bipolar Disorder through Heartbeat Nonlinear Dynamics.

Science.gov (United States)

Valenza, Gaetano; Nardelli, Mimma; Lanata', Antonio; Gentili, Claudio; Bertschy, Gilles; Kosel, Markus; Scilingo, Enzo Pasquale

2016-04-20

Bipolar Disorder (BD) is characterized by an alternation of mood states from depression to (hypo)mania. Mixed states, i.e., a combination of depression and mania symptoms at the same time, can also be present. The diagnosis of this disorder in the current clinical practice is based only on subjective interviews and questionnaires, while no reliable objective psychophysiological markers are available. Furthermore, there are no biological markers predicting BD outcomes, or providing information about the future clinical course of the phenomenon. To overcome this limitation, here we propose a methodology predicting mood changes in BD using heartbeat nonlinear dynamics exclusively, derived from the ECG. Mood changes are here intended as transitioning between two mental states: euthymic state (EUT), i.e., the good affective balance, and non-euthymic (non-EUT) states. Heart Rate Variability (HRV) series from 14 bipolar spectrum patients (age: 33.439.76, age range: 23-54; 6 females) involved in the European project PSYCHE, undergoing whole night ECG monitoring were analyzed. Data were gathered from a wearable system comprised of a comfortable t-shirt with integrated fabric electrodes and sensors able to acquire ECGs. Each patient was monitored twice a week, for 14 weeks, being able to perform normal (unstructured) activities. From each acquisition, the longest artifact-free segment of heartbeat dynamics was selected for further analyses. Sub-segments of 5 minutes of this segment were used to estimate trends of HRV linear and nonlinear dynamics. Considering data from a current observation at day t0, and past observations at days (t1, t2,...,), personalized prediction accuracies in forecasting a mood state (EUT/non-EUT) at day t+1 were 69% on average, reaching values as high as 83.3%. This approach opens to the possibility of predicting mood states in bipolar patients through heartbeat nonlinear dynamics exclusively.

Serial Changes in 3-Dimensional Supraspinatus Muscle Volume After Rotator Cuff Repair.

Science.gov (United States)

Chung, Seok Won; Oh, Kyung-Soo; Moon, Sung Gyu; Kim, Na Ra; Lee, Ji Whan; Shim, Eungjune; Park, Sehyung; Kim, Youngjun

2017-08-01

There is considerable debate on the recovery of rotator cuff muscle atrophy after rotator cuff repair. To evaluate the serial changes in supraspinatus muscle volume after rotator cuff repair by using semiautomatic segmentation software and to determine the relationship with functional outcomes. Case series; Level of evidence, 4. Seventy-four patients (mean age, 62.8 ± 8.8 years) who underwent arthroscopic rotator cuff repair and obtained 3 consecutive (preoperatively, immediately postoperatively, and later postoperatively [≥1 year postoperatively]) magnetic resonance imaging (MRI) scans having complete Y-views were included. We generated a 3-dimensional (3D) reconstructed model of the supraspinatus muscle by using in-house semiautomatic segmentation software (ITK-SNAP) and calculated both the 2-dimensional (2D) cross-sectional area and 3D volume of the muscle in 3 different views (Y-view, 1 cm medial to the Y-view [Y+1 view], and 2 cm medial to the Y-view [Y+2 view]) at the 3 time points. The area and volume changes at each time point were evaluated according to repair integrity. Later postoperative volumes were compared with immediately postoperative volumes, and their relationship with various clinical factors and the effect of higher volume increases on range of motion, muscle power, and visual analog scale pain and American Shoulder and Elbow Surgeons scores were evaluated. The interrater reliabilities were excellent for all measurements. Areas and volumes increased immediately postoperatively as compared with preoperatively; however, only volumes on the Y+1 view and Y+2 view significantly increased later postoperatively as compared with immediately postoperatively ( P < .05). There were 9 patients with healing failure, and area and volume changes were significantly less later postoperatively compared with immediately postoperatively at all measurement points in these patients ( P < .05). After omitting the patients with healing failure, volume increases

Variable importance and prediction methods for longitudinal problems with missing variables.

Directory of Open Access Journals (Sweden)

Iván Díaz

Full Text Available We present prediction and variable importance (VIM methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patients, a field in which current medical practice involves rules of thumb and scoring methods that only use a few variables and ignore the dynamic and high-dimensional nature of trauma recovery. Well-principled prediction and VIM methods can provide a tool to make care decisions informed by the high-dimensional patient's physiological and clinical history. Our VIM parameters are analogous to slope coefficients in adjusted regressions, but are not dependent on a specific statistical model, nor require a certain functional form of the prediction regression to be estimated. In addition, they can be causally interpreted under causal and statistical assumptions as the expected outcome under time-specific clinical interventions, related to changes in the mean of the outcome if each individual experiences a specified change in the variable (keeping other variables in the model fixed. Better yet, the targeted MLE used is doubly robust and locally efficient. Because the proposed VIM does not constrain the prediction model fit, we use a very flexible ensemble learner (the SuperLearner, which returns a linear combination of a list of user-given algorithms. Not only is such a prediction algorithm intuitive appealing, it has theoretical justification as being asymptotically equivalent to the oracle selector. The results of the analysis show effects whose size and significance would have been not been found using a parametric approach (such as stepwise regression or LASSO. In addition, the procedure is even more compelling as the predictor on which it is based showed significant improvements in cross-validated fit, for instance area under the curve (AUC for a receiver-operator curve (ROC. Thus, given that 1 our VIM

On the importance of paleoclimate modelling for improving predictions of future climate change

Directory of Open Access Journals (Sweden)

J. C. Hargreaves

2009-12-01

Full Text Available We use an ensemble of runs from the MIROC3.2 AGCM with slab-ocean to explore the extent to which mid-Holocene simulations are relevant to predictions of future climate change. The results are compared with similar analyses for the Last Glacial Maximum (LGM and pre-industrial control climate. We suggest that the paleoclimate epochs can provide some independent validation of the models that is also relevant for future predictions. Considering the paleoclimate epochs, we find that the stronger global forcing and hence larger climate change at the LGM makes this likely to be the more powerful one for estimating the large-scale changes that are anticipated due to anthropogenic forcing. The phenomena in the mid-Holocene simulations which are most strongly correlated with future changes (i.e., the mid to high northern latitude land temperature and monsoon precipitation do, however, coincide with areas where the LGM results are not correlated with future changes, and these are also areas where the paleodata indicate significant climate changes have occurred. Thus, these regions and phenomena for the mid-Holocene may be useful for model improvement and validation.

Quantifying and Predicting Three-Dimensional Heterogeneity in Transient Storage Using Roving Profiling

Science.gov (United States)

Kaplan, D. A.; Reaver, N.; Hensley, R. T.; Cohen, M. J.

2017-12-01

Hydraulic transport is an important component of nutrient spiraling in streams. Quantifying conservative solute transport is a prerequisite for understanding the cycling and fate of reactive solutes, such as nutrients. Numerous studies have modeled solute transport within streams using the one-dimensional advection, dispersion and storage (ADS) equation calibrated to experimental data from tracer experiments. However, there are limitations to the information about in-stream transient storage that can be derived from calibrated ADS model parameters. Transient storage (TS) in the ADS model is most often modeled as a single process, and calibrated model parameters are "lumped" values that are the best-fit representation of multiple real-world TS processes. In this study, we developed a roving profiling method to assess and predict spatial heterogeneity of in-stream TS. We performed five tracer experiments on three spring-fed rivers in Florida (USA) using Rhodamine WT. During each tracer release, stationary fluorometers were deployed to measure breakthrough curves for multiple reaches within the river. Teams of roving samplers moved along the rivers measuring tracer concentrations at various locations and depths within the reaches. A Bayesian statistical method was used to calibrate the ADS model to the stationary breakthrough curves, resulting in probability distributions for both the advective and TS zone as a function of river distance and time. Rover samples were then assigned a probability of being from either the advective or TS zone by comparing measured concentrations to the probability distributions of concentrations in the ADS advective and TS zones. A regression model was used to predict the probability of any in-stream position being located within the advective versus TS zone based on spatiotemporal predictors (time, river position, depth, and distance from bank) and eco-geomorphological feature (eddies, woody debris, benthic depressions, and aquatic

Chaos and the (un)predictability of evolution in a changing environment.

Science.gov (United States)

Rego-Costa, Artur; Débarre, Florence; Chevin, Luis-Miguel

2018-02-01

Among the factors that may reduce the predictability of evolution, chaos, characterized by a strong dependence on initial conditions, has received much less attention than randomness due to genetic drift or environmental stochasticity. It was recently shown that chaos in phenotypic evolution arises commonly under frequency-dependent selection caused by competitive interactions mediated by many traits. This result has been used to argue that chaos should often make evolutionary dynamics unpredictable. However, populations also evolve largely in response to external changing environments, and such environmental forcing is likely to influence the outcome of evolution in systems prone to chaos. We investigate how a changing environment causing oscillations of an optimal phenotype interacts with the internal dynamics of an eco-evolutionary system that would be chaotic in a constant environment. We show that strong environmental forcing can improve the predictability of evolution by reducing the probability of chaos arising, and by dampening the magnitude of chaotic oscillations. In contrast, weak forcing can increase the probability of chaos, but it also causes evolutionary trajectories to track the environment more closely. Overall, our results indicate that, although chaos may occur in evolution, it does not necessarily undermine its predictability. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Osteotomy simulation and soft tissue prediction using computer tomography scans

International Nuclear Information System (INIS)

Teschner, M.; Girod, S.; Girod, B.

1999-01-01

In this paper, a system is presented that can be used to simulate osteotomies of the skull and to estimate the resulting of tissue changes. Thus, the three-dimensional, photorealistic, postoperative appearance of a patient can be assessed. The system is based on a computer tomography scan and a photorealistic laser scan of the patient's face. In order to predict the postoperative appearance of a patient the soft tissue must follow the movement of the underlying bone. In this paper, a multi-layer soft tissue model is proposed that is based on springs. It incorporates features like skin turgor, gravity and sliding bone contact. The prediction of soft tissue changes due to bone realignments is computed using a very efficient and robust optimization method. The system can handle individual patient data sets and has been tested with several clinical cases. (author)

Short-term changes in arterial inflammation predict long-term changes in atherosclerosis progression

Energy Technology Data Exchange (ETDEWEB)

Joseph, Philip [Massachusetts General Hospital and Harvard Medical School, Cardiology Division and Cardiac MR PET CT Program, Boston, MA (United States); McMaster University, Population Health Research Institute, Department of Medicine, and Department of Radiology, Hamilton, ON (Canada); Ishai, Amorina; Tawakol, Ahmed [Massachusetts General Hospital and Harvard Medical School, Cardiology Division and Cardiac MR PET CT Program, Boston, MA (United States); Mani, Venkatesh [Icahn School of Medicine at Mount Sinai School of Medicine, Translational and Molecular Imaging Institute and Department of Radiology, New York, NY (United States); Kallend, David [The Medicines Company, Parsippany, NJ (United States); Rudd, James H.F. [University of Cambridge, Division of Cardiovascular Medicine, Cambridge (United Kingdom); Fayad, Zahi A. [Icahn School of Medicine at Mount Sinai School of Medicine, Translational and Molecular Imaging Institute and Department of Radiology, New York, NY (United States); Icahn School of Medicine at Mount Sinai School of Medicine, Hess CSM Building Floor TMII, Rm S1-104, Translational and Molecular Imaging Institute and Department of Radiology, New York, NY (United States)

2017-01-15

It remains unclear whether changes in arterial wall inflammation are associated with subsequent changes in the rate of structural progression of atherosclerosis. In this sub-study of the dal-PLAQUE clinical trial, multi-modal imaging was performed using 18-fludeoxyglucose (FDG) positron emission tomography (PET, at 0 and 6 months) and magnetic resonance imaging (MRI, at 0 and 24 months). The primary objective was to determine whether increasing FDG uptake at 6 months predicted atherosclerosis progression on MRI at 2 years. Arterial inflammation was measured by the carotid FDG target-to-background ratio (TBR), and atherosclerotic plaque progression was defined as the percentage change in carotid mean wall area (MWA) and mean wall thickness (MWT) on MRI between baseline and 24 months. A total of 42 participants were included in this sub-study. The mean age of the population was 62.5 years, and 12 (28.6 %) were women. In participants with (vs. without) any increase in arterial inflammation over 6 months, the long-term changes in both MWT (% change MWT: 17.49 % vs. 1.74 %, p = 0.038) and MWA (% change MWA: 25.50 % vs. 3.59 %, p = 0.027) were significantly greater. Results remained significant after adjusting for clinical and biochemical covariates. Individuals with no increase in arterial inflammation over 6 months had no significant structural progression of atherosclerosis over 24 months as measured by MWT (p = 0.616) or MWA (p = 0.373). Short-term changes in arterial inflammation are associated with long-term structural atherosclerosis progression. These data support the concept that therapies that reduce arterial inflammation may attenuate or halt progression of atherosclerosis. (orig.)

Short-term changes in arterial inflammation predict long-term changes in atherosclerosis progression

International Nuclear Information System (INIS)

Joseph, Philip; Ishai, Amorina; Tawakol, Ahmed; Mani, Venkatesh; Kallend, David; Rudd, James H.F.; Fayad, Zahi A.

2017-01-01

It remains unclear whether changes in arterial wall inflammation are associated with subsequent changes in the rate of structural progression of atherosclerosis. In this sub-study of the dal-PLAQUE clinical trial, multi-modal imaging was performed using 18-fludeoxyglucose (FDG) positron emission tomography (PET, at 0 and 6 months) and magnetic resonance imaging (MRI, at 0 and 24 months). The primary objective was to determine whether increasing FDG uptake at 6 months predicted atherosclerosis progression on MRI at 2 years. Arterial inflammation was measured by the carotid FDG target-to-background ratio (TBR), and atherosclerotic plaque progression was defined as the percentage change in carotid mean wall area (MWA) and mean wall thickness (MWT) on MRI between baseline and 24 months. A total of 42 participants were included in this sub-study. The mean age of the population was 62.5 years, and 12 (28.6 %) were women. In participants with (vs. without) any increase in arterial inflammation over 6 months, the long-term changes in both MWT (% change MWT: 17.49 % vs. 1.74 %, p = 0.038) and MWA (% change MWA: 25.50 % vs. 3.59 %, p = 0.027) were significantly greater. Results remained significant after adjusting for clinical and biochemical covariates. Individuals with no increase in arterial inflammation over 6 months had no significant structural progression of atherosclerosis over 24 months as measured by MWT (p = 0.616) or MWA (p = 0.373). Short-term changes in arterial inflammation are associated with long-term structural atherosclerosis progression. These data support the concept that therapies that reduce arterial inflammation may attenuate or halt progression of atherosclerosis. (orig.)

Automatic measurement for dimensional changes of woven fabrics based on texture

Science.gov (United States)

Liu, Jihong; Jiang, Hongxia; Liu, X.; Chai, Zhilei

2014-01-01

Dimensional change or shrinkage is an important functional attribute of woven fabrics that affects their basic function and price in the market. This paper presents a machine vision system that evaluates the shrinkage of woven fabrics by analyzing the change of fabric construction. The proposed measurement method has three features. (i) There will be no stain of shrinkage markers on the fabric specimen compared to the existing measurement method. (ii) The system can be used on fabric with reduced area. (iii) The system can be installed and used as a laboratory or industrial application system. The method processed can process the image of the fabric and is divided into four steps: acquiring a relative image from the sample of the woven fabric, obtaining a gray image and then the segmentation of the warp and weft from the fabric based on fast Fourier transform and inverse fast Fourier transform, calculation of the distance of the warp or weft sets by gray projection method and character shrinkage of the woven fabric by the average distance, coefficient of variation of distance and so on. Experimental results on virtual and physical woven fabrics indicated that the method provided could obtain the shrinkage information of woven fabric in detail. The method was programmed by Matlab software, and a graphical user interface was built by Delphi. The program has potential for practical use in the textile industry.

Methodology for dimensional variation analysis of ITER integrated systems

International Nuclear Information System (INIS)

Fuentes, F. Javier; Trouvé, Vincent; Cordier, Jean-Jacques; Reich, Jens

2016-01-01

Highlights: • Tokamak dimensional management methodology, based on 3D variation analysis, is presented. • Dimensional Variation Model implementation workflow is described. • Methodology phases are described in detail. The application of this methodology to the tolerance analysis of ITER Vacuum Vessel is presented. • Dimensional studies are a valuable tool for the assessment of Tokamak PCR (Project Change Requests), DR (Deviation Requests) and NCR (Non-Conformance Reports). - Abstract: The ITER machine consists of a large number of complex systems highly integrated, with critical functional requirements and reduced design clearances to minimize the impact in cost and performances. Tolerances and assembly accuracies in critical areas could have a serious impact in the final performances, compromising the machine assembly and plasma operation. The management of tolerances allocated to part manufacture and assembly processes, as well as the control of potential deviations and early mitigation of non-compliances with the technical requirements, is a critical activity on the project life cycle. A 3D tolerance simulation analysis of ITER Tokamak machine has been developed based on 3DCS dedicated software. This integrated dimensional variation model is representative of Tokamak manufacturing functional tolerances and assembly processes, predicting accurate values for the amount of variation on critical areas. This paper describes the detailed methodology to implement and update the Tokamak Dimensional Variation Model. The model is managed at system level. The methodology phases are illustrated by its application to the Vacuum Vessel (VV), considering the status of maturity of VV dimensional variation model. The following topics are described in this paper: • Model description and constraints. • Model implementation workflow. • Management of input and output data. • Statistical analysis and risk assessment. The management of the integration studies based on

Methodology for dimensional variation analysis of ITER integrated systems

Energy Technology Data Exchange (ETDEWEB)

Fuentes, F. Javier, E-mail: FranciscoJavier.Fuentes@iter.org [ITER Organization, Route de Vinon-sur-Verdon—CS 90046, 13067 St Paul-lez-Durance (France); Trouvé, Vincent [Assystem Engineering & Operation Services, rue J-M Jacquard CS 60117, 84120 Pertuis (France); Cordier, Jean-Jacques; Reich, Jens [ITER Organization, Route de Vinon-sur-Verdon—CS 90046, 13067 St Paul-lez-Durance (France)

2016-11-01

Highlights: • Tokamak dimensional management methodology, based on 3D variation analysis, is presented. • Dimensional Variation Model implementation workflow is described. • Methodology phases are described in detail. The application of this methodology to the tolerance analysis of ITER Vacuum Vessel is presented. • Dimensional studies are a valuable tool for the assessment of Tokamak PCR (Project Change Requests), DR (Deviation Requests) and NCR (Non-Conformance Reports). - Abstract: The ITER machine consists of a large number of complex systems highly integrated, with critical functional requirements and reduced design clearances to minimize the impact in cost and performances. Tolerances and assembly accuracies in critical areas could have a serious impact in the final performances, compromising the machine assembly and plasma operation. The management of tolerances allocated to part manufacture and assembly processes, as well as the control of potential deviations and early mitigation of non-compliances with the technical requirements, is a critical activity on the project life cycle. A 3D tolerance simulation analysis of ITER Tokamak machine has been developed based on 3DCS dedicated software. This integrated dimensional variation model is representative of Tokamak manufacturing functional tolerances and assembly processes, predicting accurate values for the amount of variation on critical areas. This paper describes the detailed methodology to implement and update the Tokamak Dimensional Variation Model. The model is managed at system level. The methodology phases are illustrated by its application to the Vacuum Vessel (VV), considering the status of maturity of VV dimensional variation model. The following topics are described in this paper: • Model description and constraints. • Model implementation workflow. • Management of input and output data. • Statistical analysis and risk assessment. The management of the integration studies based on

Predicting the effects of climate change on marine communities and the consequences for fisheries

DEFF Research Database (Denmark)

Jennings, Simon; Brander, Keith

2010-01-01

for the community under the same climate scenario. The main weakness of the community approach is that the methods predict abundance and production by size-class rather than taxonomic group, and society would be particularly concerned if climate driven changes had a strong effect on the relative production...... of fishable and non-fishable species in the community. The main strength of the community approach is that it provides widely applicable ‘null’ models for assessing the biological effects of climate change and a baseline for model comparisons.......Climate effects on the structure and function of marine communities have received scant attention. The few existing approaches for predicting climate effects suggest that community responses might be predicted from the responses of component populations. These approaches require a very complex...

Landscape genomic prediction for restoration of a Eucalyptus foundation species under climate change.

Science.gov (United States)

Supple, Megan Ann; Bragg, Jason G; Broadhurst, Linda M; Nicotra, Adrienne B; Byrne, Margaret; Andrew, Rose L; Widdup, Abigail; Aitken, Nicola C; Borevitz, Justin O

2018-04-24

As species face rapid environmental change, we can build resilient populations through restoration projects that incorporate predicted future climates into seed sourcing decisions. Eucalyptus melliodora is a foundation species of a critically endangered community in Australia that is a target for restoration. We examined genomic and phenotypic variation to make empirical based recommendations for seed sourcing. We examined isolation by distance and isolation by environment, determining high levels of gene flow extending for 500 km and correlations with climate and soil variables. Growth experiments revealed extensive phenotypic variation both within and among sampling sites, but no site-specific differentiation in phenotypic plasticity. Model predictions suggest that seed can be sourced broadly across the landscape, providing ample diversity for adaptation to environmental change. Application of our landscape genomic model to E. melliodora restoration projects can identify genomic variation suitable for predicted future climates, thereby increasing the long term probability of successful restoration. © 2018, Supple et al.

Predicting CD4 count changes among patients on antiretroviral treatment: Application of data mining techniques.

Science.gov (United States)

Kebede, Mihiretu; Zegeye, Desalegn Tigabu; Zeleke, Berihun Megabiaw

2017-12-01

To monitor the progress of therapy and disease progression, periodic CD4 counts are required throughout the course of HIV/AIDS care and support. The demand for CD4 count measurement is increasing as ART programs expand over the last decade. This study aimed to predict CD4 count changes and to identify the predictors of CD4 count changes among patients on ART. A cross-sectional study was conducted at the University of Gondar Hospital from 3,104 adult patients on ART with CD4 counts measured at least twice (baseline and most recent). Data were retrieved from the HIV care clinic electronic database and patients` charts. Descriptive data were analyzed by SPSS version 20. Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology was followed to undertake the study. WEKA version 3.8 was used to conduct a predictive data mining. Before building the predictive data mining models, information gain values and correlation-based Feature Selection methods were used for attribute selection. Variables were ranked according to their relevance based on their information gain values. J48, Neural Network, and Random Forest algorithms were experimented to assess model accuracies. The median duration of ART was 191.5 weeks. The mean CD4 count change was 243 (SD 191.14) cells per microliter. Overall, 2427 (78.2%) patients had their CD4 counts increased by at least 100 cells per microliter, while 4% had a decline from the baseline CD4 value. Baseline variables including age, educational status, CD8 count, ART regimen, and hemoglobin levels predicted CD4 count changes with predictive accuracies of J48, Neural Network, and Random Forest being 87.1%, 83.5%, and 99.8%, respectively. Random Forest algorithm had a superior performance accuracy level than both J48 and Artificial Neural Network. The precision, sensitivity and recall values of Random Forest were also more than 99%. Nearly accurate prediction results were obtained using Random Forest algorithm. This algorithm could be

Two-dimensional electron flow in pulsed power transmission lines and plasma opening switches

International Nuclear Information System (INIS)

Church, B.W.; Longcope, D.W.; Ng, C.K.; Sudan, R.N.

1991-01-01

The operation of magnetically insulated transmission lines (MITL) and the interruption of current in a plasma opening switch (POS) are determined by the physics of the electrons emitted by the cathode surface. A mathematical model describes the self-consistent two-dimensional flow of an electron fluid. A finite element code, FERUS, has been developed to solve the two equations which describe Poisson's and Ampere's law in two dimensions. The solutions from this code are obtained for parameters where the electron orbits are considerably modified by the self-magnetic field of the current. Next, the self-insulated electron flow in a MITL with a step change in cross-section is studied using a conventional two-dimensional fully electromagnetic particle-in-cell code, MASK. The equations governing two-dimensional quasi-static electron flow are solved numerically by a third technique which is suitable for predicting current interruption in a POS. The object of the study is to determine the critical load impedance, Z CL , required for current interruption for a given applied voltage, cathode voltage and plasma length. (author). 9 refs, 5 figs

Change in the Pathologic Supraspinatus: A Three-Dimensional Model of Fiber Bundle Architecture within Anterior and Posterior Regions

Directory of Open Access Journals (Sweden)

Soo Y. Kim

2015-01-01

Full Text Available Supraspinatus tendon tears are common and lead to changes in the muscle architecture. To date, these changes have not been investigated for the distinct regions and parts of the pathologic supraspinatus. The purpose of this study was to create a novel three-dimensional (3D model of the muscle architecture throughout the supraspinatus and to compare the architecture between muscle regions and parts in relation to tear severity. Twelve cadaveric specimens with varying degrees of tendon tears were used. Three-dimensional coordinates of fiber bundles were collected in situ using serial dissection and digitization. Data were reconstructed and modeled in 3D using Maya. Fiber bundle length (FBL and pennation angle (PA were computed and analyzed. FBL was significantly shorter in specimens with large retracted tears compared to smaller tears, with the deeper fibers being significantly shorter than other parts in the anterior region. PA was significantly greater in specimens with large retracted tears, with the superficial fibers often demonstrating the largest PA. The posterior region was absent in two specimens with extensive tears. Architectural changes associated with tendon tears affect the regions and varying depths of supraspinatus differently. The results provide important insights on residual function of the pathologic muscle, and the 3D model includes detailed data that can be used in future modeling studies.

Quasi-integrability and two-dimensional QCD

International Nuclear Information System (INIS)

Abdalla, E.; Mohayaee, R.

1996-10-01

The notion of integrability in two-dimensional QCD is discussed. We show that in spite of an infinite number of conserved charges, particle production is not entirely suppressed. This phenomenon, which we call quasi-integrability, is explained in terms of quantum corrections to the combined algebra of higher-conserved and spectrum-generating currents. We predict the qualitative form of particle production probabilities and verify that they are in agreement with numerical data. We also discuss four-dimensional self-dual Yang-Mills theory in the light of our results. (author). 25 refs, 4 figs, 1 tab

Perceived stress and anhedonia predict short-and long-term weight change, respectively, in healthy adults.

Science.gov (United States)

Ibrahim, Mostafa; Thearle, Marie S; Krakoff, Jonathan; Gluck, Marci E

2016-04-01

Perceived stress; emotional eating; anhedonia; depression and dietary restraint, hunger, and disinhibition have been studied as risk factors for obesity. However, the majority of studies have been cross-sectional and the directionality of these relationships remains unclear. In this longitudinal study, we assess their impact on future weight change. Psychological predictors of weight change in short- (6month) and long-term (>1year) periods were studied in 65 lean and obese individuals in two cohorts. Subjects participated in studies of food intake and metabolism that did not include any type of medication or weight loss interventions. They completed psychological questionnaires at baseline and weight change was monitored at follow-up visits. At six months, perceived stress predicted weight gain (r(2)=0.23, P=0.02). There was a significant interaction (r(2)=.38, P=0.009) between perceived stress and positive emotional eating, such that higher scores in both predicted greater weight gain, while those with low stress but high emotional eating scores lost weight. For long-term, higher anhedonia scores predicted weight gain (r(2)=0.24, P=0.04). Depression moderated these effects such that higher scores in both predicted weight gain but higher depression and lower anhedonia scores predicted weight loss. There are different behavioral determinants for short- and long-term weight change. Targeting perceived stress may help with short-term weight loss while depression and anhedonia may be better targets for long-term weight regulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow.

Science.gov (United States)

van Strien, Maarten J; Keller, Daniela; Holderegger, Rolf; Ghazoul, Jaboury; Kienast, Felix; Bolliger, Janine

2014-03-01

For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape-genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper (Stethophyma grossum), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable (F(ST) and mean pairwise assignment probability). With a modified leave-one-out cross-validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape-change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape-change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape-genetic models in conservation and landscape planning.

Quantitative prediction of respiratory tidal volume based on the external torso volume change: a potential volumetric surrogate

Energy Technology Data Exchange (ETDEWEB)

Li Guang; Arora, Naveen C; Xie Huchen; Ning, Holly; Citrin, Deborah; Kaushal, Aradhana; Zach, Leor; Camphausen, Kevin; Miller, Robert W [Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892 (United States); Lu Wei; Low, Daniel [Department of Radiation Oncology, Washington University School of Medicine, St Louis, MO 63110 (United States)], E-mail: ligeorge@mail.nih.gov

2009-04-07

An external respiratory surrogate that not only highly correlates with but also quantitatively predicts internal tidal volume should be useful in guiding four-dimensional computed tomography (4DCT), as well as 4D radiation therapy (4DRT). A volumetric surrogate should have advantages over external fiducial point(s) for monitoring respiration-induced motion of the torso, which deforms in synchronization with a patient-specific breathing pattern. This study establishes a linear relationship between the external torso volume change (TVC) and lung air volume change (AVC) by validating a proposed volume conservation hypothesis (TVC = AVC) throughout the respiratory cycle using 4DCT and spirometry. Fourteen patients' torso 4DCT images and corresponding spirometric tidal volumes were acquired to examine this hypothesis. The 4DCT images were acquired using dual surrogates in cine mode and amplitude-based binning in 12 respiratory stages, minimizing residual motion artifacts. Torso and lung volumes were calculated using threshold-based segmentation algorithms and volume changes were calculated relative to the full-exhalation stage. The TVC and AVC, as functions of respiratory stages, were compared, showing a high correlation (r = 0.992 {+-} 0.005, p < 0.0001) as well as a linear relationship (slope = 1.027 {+-} 0.061, R{sup 2} = 0.980) without phase shift. The AVC was also compared to the spirometric tidal volumes, showing a similar linearity (slope = 1.030 {+-} 0.092, R{sup 2} = 0.947). In contrast, the thoracic and abdominal heights measured from 4DCT showed relatively low correlation (0.28 {+-} 0.44 and 0.82 {+-} 0.30, respectively) and location-dependent phase shifts. This novel approach establishes the foundation for developing an external volumetric respiratory surrogate.

Computational modeling for prediction of the shear stress of three-dimensional isotropic and aligned fiber networks.

Science.gov (United States)

Park, Seungman

2017-09-01

Interstitial flow (IF) is a creeping flow through the interstitial space of the extracellular matrix (ECM). IF plays a key role in diverse biological functions, such as tissue homeostasis, cell function and behavior. Currently, most studies that have characterized IF have focused on the permeability of ECM or shear stress distribution on the cells, but less is known about the prediction of shear stress on the individual fibers or fiber networks despite its significance in the alignment of matrix fibers and cells observed in fibrotic or wound tissues. In this study, I developed a computational model to predict shear stress for different structured fibrous networks. To generate isotropic models, a random growth algorithm and a second-order orientation tensor were employed. Then, a three-dimensional (3D) solid model was created using computer-aided design (CAD) software for the aligned models (i.e., parallel, perpendicular and cubic models). Subsequently, a tetrahedral unstructured mesh was generated and flow solutions were calculated by solving equations for mass and momentum conservation for all models. Through the flow solutions, I estimated permeability using Darcy's law. Average shear stress (ASS) on the fibers was calculated by averaging the wall shear stress of the fibers. By using nonlinear surface fitting of permeability, viscosity, velocity, porosity and ASS, I devised new computational models. Overall, the developed models showed that higher porosity induced higher permeability, as previous empirical and theoretical models have shown. For comparison of the permeability, the present computational models were matched well with previous models, which justify our computational approach. ASS tended to increase linearly with respect to inlet velocity and dynamic viscosity, whereas permeability was almost the same. Finally, the developed model nicely predicted the ASS values that had been directly estimated from computational fluid dynamics (CFD). The present

Three-dimensional space changes after premature loss of a maxillary primary first molar.

Science.gov (United States)

Park, Kitae; Jung, Da-Woon; Kim, Ji-Yeon

2009-11-01

A space maintainer is generally preferred when a primary first molar is lost before or during active eruption of the first permanent molars in order to prevent space loss. However, controversy prevails regarding the space loss after eruption of the permanent first molars. The purpose of this study was to examine spatial changes subsequent to premature loss of a maxillary primary first molar after the eruption of the permanent first molars. Thirteen children, five girls and eight boys, expecting premature extraction of a maxillary primary first molar because of caries and/or failed pulp therapy, were selected. Spatial changes were investigated using a three-dimensional laser scanner by comparing the primary molar space, arch width, arch length, and arch perimeter before and after the extraction of a maxillary primary first molar. Also, the inclination and angulation changes in the maxillary primary canines, primary second molars, and permanent first molars adjacent to the extraction site were investigated before and after the extraction of the maxillary primary first molar in order to examine the source of space loss. There was no statistically significant space loss on the extraction side compared to the control side (P = 0.33). No consistent findings were seen on the inclination and angulation changes on the extraction side. The premature loss of a maxillary primary first molar, in cases with class I molar relationship, has limited influence on the space in permanent dentition.

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

DEFF Research Database (Denmark)

Hudson, Lawrence N; Newbold, Tim; Contu, Sara

2017-01-01

The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity ...

An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer

Directory of Open Access Journals (Sweden)

Lockwood William W

2010-05-01

Full Text Available Abstract Background Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer. Results Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations. Conclusions Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.

Three-dimensional wedge filling in ordered and disordered systems

International Nuclear Information System (INIS)

Greenall, M J; Parry, A O; Romero-Enrique, J M

2004-01-01

We investigate interfacial structural and fluctuation effects occurring at continuous filling transitions in 3D wedge geometries. We show that fluctuation-induced wedge covariance relations that have been reported recently for 2D filling and wetting have mean-field or classical analogues that apply to higher-dimensional systems. Classical wedge covariance emerges from analysis of filling in shallow wedges based on a simple interfacial Hamiltonian model and is supported by detailed numerical investigations of filling within a more microscopic Landau-like density functional theory. Evidence is presented that classical wedge covariance is also obeyed for filling in more acute wedges in the asymptotic critical regime. For sufficiently short-ranged forces mean-field predictions for the filling critical exponents and covariance are destroyed by pseudo-one-dimensional interfacial fluctuations. We argue that in this filling fluctuation regime the critical exponents describing the divergence of length scales are related to values of the interfacial wandering exponent ζ(d) defined for planar interfaces in (bulk) two-dimensional (d = 2) and three-dimensional (d = 3) systems. For the interfacial height l w ∼ θ-α) -β w , with θ the contact angle and α the wedge tilt angle, we find β w = ζ(2)/2(1-ζ(3)). For pure systems (thermal disorder) we recover the known result β w = 1/4 predicted by interfacial Hamiltonian studies whilst for random-bond disorder we predict the universal critical exponent β ∼ even in the presence of dispersion forces. We revisit the transfer matrix theory of three-dimensional filling based on an effective interfacial Hamiltonian model and discuss the interplay between breather, tilt and torsional interfacial fluctuations. We show that the coupling of the modes allows the problem to be mapped onto a quantum mechanical problem as conjectured by previous authors. The form of the interfacial height probability distribution function predicted by

Changes in event-related potential functional networks predict traumatic brain injury in piglets.

Science.gov (United States)

Atlan, Lorre S; Lan, Ingrid S; Smith, Colin; Margulies, Susan S

2018-06-01

Traumatic brain injury is a leading cause of cognitive and behavioral deficits in children in the US each year. None of the current diagnostic tools, such as quantitative cognitive and balance tests, have been validated to identify mild traumatic brain injury in infants, adults and animals. In this preliminary study, we report a novel, quantitative tool that has the potential to quickly and reliably diagnose traumatic brain injury and which can track the state of the brain during recovery across multiple ages and species. Using 32 scalp electrodes, we recorded involuntary auditory event-related potentials from 22 awake four-week-old piglets one day before and one, four, and seven days after two different injury types (diffuse and focal) or sham. From these recordings, we generated event-related potential functional networks and assessed whether the patterns of the observed changes in these networks could distinguish brain-injured piglets from non-injured. Piglet brains exhibited significant changes after injury, as evaluated by five network metrics. The injury prediction algorithm developed from our analysis of the changes in the event-related potentials functional networks ultimately produced a tool with 82% predictive accuracy. This novel approach is the first application of auditory event-related potential functional networks to the prediction of traumatic brain injury. The resulting tool is a robust, objective and predictive method that offers promise for detecting mild traumatic brain injury, in particular because collecting event-related potentials data is noninvasive and inexpensive. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Simulation on three dimensional bubble formation using MARS

International Nuclear Information System (INIS)

Kunugi, Tomoaki

1997-01-01

This paper describes a numerical simulation on three-dimensional bubble formation by means of the MARS (Multi-interfaces Advection and Reconstruction Solver) developed by the author. The comparison between two-dimensional and three-dimensional simulation on an agglomeration of two bubbles is discussed. Moreover, some simulation results regarding a phase change phenomena such as a boiling and condensation in a two dimensional enclosure with heated and cooled walls are presented. (author)

Correlation between hindfoot joint three-dimensional kinematics and the changes of the medial arch angle in stage II posterior tibial tendon dysfunction flatfoot.

Science.gov (United States)

Zhang, Yi-Jun; Xu, Jian; Wang, Yue; Lin, Xiang-Jin; Ma, Xin

2015-02-01

The aim of this study was to explore the correlation between the kinematics of the hindfoot joint and the medial arch angle change in stage II posterior tibial tendon dysfunction flatfoot three-dimensionally under loading. Computed tomography (CT) scans of 12 healthy feet and 12 feet with stage II posterior tibial tendon dysfunction flatfoot were taken both in non- and full-body-weight-bearing condition. The CT images of the hindfoot bones were reconstructed into three-dimensional models with Mimics and Geomagic reverse engineering software. The three-dimensional changes of the hindfoot joint were calculated to determine their correlation to the medial longitudinal arch angle. The medial arch angle change was larger in stage II posterior tibial tendon dysfunction flatfoot compared to that in healthy foot under loading. The rotation and translation of the talocalcaneal joint, the talonavicular joint and the calcanocuboid joint had little influence on the change of the medial arch angle in healthy foot. However, the eversion of the talocalcaneal joint, the proximal translation of the calcaneus relative to the talus and the dorsiflexion of talonavicular joint could increase the medial arch angle in stage II posterior tibial tendon dysfunction flatfoot under loading. Joint instability occurred in patients with stage II posterior tibial tendon dysfunction flatfoot under loading. Limitation of over movement of the talocalcaneal joint and the talonavicular joint may help correct the medial longitudinal arch in stage II posterior tibial tendon dysfunction flatfoot. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting impacts of climate change on Fasciola hepatica risk.

Science.gov (United States)

Fox, Naomi J; White, Piran C L; McClean, Colin J; Marion, Glenn; Evans, Andy; Hutchings, Michael R

2011-01-10

Fasciola hepatica (liver fluke) is a physically and economically devastating parasitic trematode whose rise in recent years has been attributed to climate change. Climate has an impact on the free-living stages of the parasite and its intermediate host Lymnaea truncatula, with the interactions between rainfall and temperature having the greatest influence on transmission efficacy. There have been a number of short term climate driven forecasts developed to predict the following season's infection risk, with the Ollerenshaw index being the most widely used. Through the synthesis of a modified Ollerenshaw index with the UKCP09 fine scale climate projection data we have developed long term seasonal risk forecasts up to 2070 at a 25 km square resolution. Additionally UKCIP gridded datasets at 5 km square resolution from 1970-2006 were used to highlight the climate-driven increase to date. The maps show unprecedented levels of future fasciolosis risk in parts of the UK, with risk of serious epidemics in Wales by 2050. The seasonal risk maps demonstrate the possible change in the timing of disease outbreaks due to increased risk from overwintering larvae. Despite an overall long term increase in all regions of the UK, spatio-temporal variation in risk levels is expected. Infection risk will reduce in some areas and fluctuate greatly in others with a predicted decrease in summer infection for parts of the UK due to restricted water availability. This forecast is the first approximation of the potential impacts of climate change on fasciolosis risk in the UK. It can be used as a basis for indicating where active disease surveillance should be targeted and where the development of improved mitigation or adaptation measures is likely to bring the greatest benefits.

Predicting impacts of climate change on Fasciola hepatica risk.

Directory of Open Access Journals (Sweden)

Naomi J Fox

2011-01-01

Full Text Available Fasciola hepatica (liver fluke is a physically and economically devastating parasitic trematode whose rise in recent years has been attributed to climate change. Climate has an impact on the free-living stages of the parasite and its intermediate host Lymnaea truncatula, with the interactions between rainfall and temperature having the greatest influence on transmission efficacy. There have been a number of short term climate driven forecasts developed to predict the following season's infection risk, with the Ollerenshaw index being the most widely used. Through the synthesis of a modified Ollerenshaw index with the UKCP09 fine scale climate projection data we have developed long term seasonal risk forecasts up to 2070 at a 25 km square resolution. Additionally UKCIP gridded datasets at 5 km square resolution from 1970-2006 were used to highlight the climate-driven increase to date. The maps show unprecedented levels of future fasciolosis risk in parts of the UK, with risk of serious epidemics in Wales by 2050. The seasonal risk maps demonstrate the possible change in the timing of disease outbreaks due to increased risk from overwintering larvae. Despite an overall long term increase in all regions of the UK, spatio-temporal variation in risk levels is expected. Infection risk will reduce in some areas and fluctuate greatly in others with a predicted decrease in summer infection for parts of the UK due to restricted water availability. This forecast is the first approximation of the potential impacts of climate change on fasciolosis risk in the UK. It can be used as a basis for indicating where active disease surveillance should be targeted and where the development of improved mitigation or adaptation measures is likely to bring the greatest benefits.

Predicting the Responses of Soil Nitrite-Oxidizers to Multi-Factorial Global Change: A Trait-Based Approach

DEFF Research Database (Denmark)

Le Roux, Xavier; Bouskill, Nicholas J.; Niboyet, Audrey

2016-01-01

Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil...... functions to global change. Here, using a long-term field experiment in a California grassland, we studied the main and interactive effects of three global change factors (increased atmospheric CO2 concentration, precipitation and nitrogen addition, and all their factorial combinations, based on global...

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

NARCIS (Netherlands)

Hudson, Lawrence N; Newbold, Tim; Contu, Sara; Hill, Samantha L L; Lysenko, Igor; De Palma, Adriana; Phillips, Helen R P; Alhusseini, Tamera I; Bedford, Felicity E; Bennett, Dominic J; Booth, Hollie; Burton, Victoria J; Chng, Charlotte W T; Choimes, Argyrios; Correia, David L P; Day, Julie; Echeverría-Londoño, Susy; Emerson, Susan R; Gao, Di; Garon, Morgan; Harrison, Michelle L K; Ingram, Daniel J; Jung, Martin; Kemp, Victoria; Kirkpatrick, Lucinda; Martin, Callum D; Pan, Yuan; Pask-Hale, Gwilym D; Pynegar, Edwin L; Robinson, Alexandra N; Sanchez-Ortiz, Katia; Senior, Rebecca A; Simmons, Benno I; White, Hannah J; Zhang, Hanbin; Aben, Job; Abrahamczyk, Stefan; Adum, Gilbert B; Aguilar-Barquero, Virginia; Aizen, Marcelo A; Albertos, Belén; Alcala, E L; Del Mar Alguacil, Maria; Alignier, Audrey; Ancrenaz, Marc; Andersen, Alan N; Arbeláez-Cortés, Enrique; Armbrecht, Inge; Arroyo-Rodríguez, Víctor; Aumann, Tom; Axmacher, Jan C; Azhar, Badrul; Azpiroz, Adrián B; Baeten, Lander; Bakayoko, Adama; Báldi, András; Banks, John E; Baral, Sharad K; Barlow, Jos; Barratt, Barbara I P; Barrico, Lurdes; Bartolommei, Paola; Barton, Diane M; Basset, Yves; Batáry, Péter; Bates, Adam J; Baur, Bruno; Bayne, Erin M; Beja, Pedro; Benedick, Suzan; Berg, Åke; Bernard, Henry; Berry, Nicholas J; Bhatt, Dinesh; Bicknell, Jake E; Bihn, Jochen H; Blake, Robin J; Bobo, Kadiri S; Bóçon, Roberto; Boekhout, Teun; Böhning-Gaese, Katrin; Bonham, Kevin J; Borges, Paulo A V; Borges, Sérgio H; Boutin, Céline; Bouyer, Jérémy; Bragagnolo, Cibele; Brandt, Jodi S; Brearley, Francis Q; Brito, Isabel; Bros, Vicenç; Brunet, Jörg; Buczkowski, Grzegorz; Buddle, Christopher M; Bugter, Rob; Buscardo, Erika; Buse, Jörn; Cabra-García, Jimmy; Cáceres, Nilton C; Cagle, Nicolette L; Calviño-Cancela, María; Cameron, Sydney A; Cancello, Eliana M; Caparrós, Rut; Cardoso, Pedro; Carpenter, Dan; Carrijo, Tiago F; Carvalho, Anelena L; Cassano, Camila R; Castro, Helena; Castro-Luna, Alejandro A; Rolando, Cerda B; Cerezo, Alexis; Chapman, Kim Alan; Chauvat, Matthieu; Christensen, Morten; Clarke, Francis M; Cleary, Daniel F R; Colombo, Giorgio; Connop, Stuart P; Craig, Michael D; Cruz-López, Leopoldo; Cunningham, Saul A; D'Aniello, Biagio; D'Cruze, Neil; da Silva, Pedro Giovâni; Dallimer, Martin; Danquah, Emmanuel; Darvill, Ben; Dauber, Jens; Davis, Adrian L V; Dawson, Jeff; de Sassi, Claudio; de Thoisy, Benoit; Deheuvels, Olivier; Dejean, Alain; Devineau, Jean-Louis; Diekötter, Tim; Dolia, Jignasu V; Domínguez, Erwin; Dominguez-Haydar, Yamileth; Dorn, Silvia; Draper, Isabel; Dreber, Niels; Dumont, Bertrand; Dures, Simon G; Dynesius, Mats; Edenius, Lars; Eggleton, Paul; Eigenbrod, Felix; Elek, Zoltán; Entling, Martin H; Esler, Karen J; de Lima, Ricardo F; Faruk, Aisyah; Farwig, Nina; Fayle, Tom M; Felicioli, Antonio; Felton, Annika M; Fensham, Roderick J; Fernandez, Ignacio C; Ferreira, Catarina C; Ficetola, Gentile F; Fiera, Cristina; Filgueiras, Bruno K C; Fırıncıoğlu, Hüseyin K; Flaspohler, David; Floren, Andreas; Fonte, Steven J; Fournier, Anne; Fowler, Robert E; Franzén, Markus; Fraser, Lauchlan H; Fredriksson, Gabriella M; Freire, Geraldo B; Frizzo, Tiago L M; Fukuda, Daisuke; Furlani, Dario; Gaigher, René; Ganzhorn, Jörg U; García, Karla P; Garcia-R, Juan C; Garden, Jenni G; Garilleti, Ricardo; Ge, Bao-Ming; Gendreau-Berthiaume, Benoit; Gerard, Philippa J; Gheler-Costa, Carla; Gilbert, Benjamin; Giordani, Paolo; Giordano, Simonetta; Golodets, Carly; Gomes, Laurens G L; Gould, Rachelle K; Goulson, Dave; Gove, Aaron D; Granjon, Laurent; Grass, Ingo; Gray, Claudia L; Grogan, James; Gu, Weibin; Guardiola, Moisès; Gunawardene, Nihara R; Gutierrez, Alvaro G; Gutiérrez-Lamus, Doris L; Haarmeyer, Daniela H; Hanley, Mick E; Hanson, Thor; Hashim, Nor R; Hassan, Shombe N; Hatfield, Richard G; Hawes, Joseph E; Hayward, Matt W; Hébert, Christian; Helden, Alvin J; Henden, John-André; Henschel, Philipp; Hernández, Lionel; Herrera, James P; Herrmann, Farina; Herzog, Felix; Higuera-Diaz, Diego; Hilje, Branko; Höfer, Hubert; Hoffmann, Anke; Horgan, Finbarr G; Hornung, Elisabeth; Horváth, Roland; Hylander, Kristoffer; Isaacs-Cubides, Paola; Ishida, Hiroaki; Ishitani, Masahiro; Jacobs, Carmen T; Jaramillo, Víctor J; Jauker, Birgit; Hernández, F Jiménez; Johnson, McKenzie F; Jolli, Virat; Jonsell, Mats; Juliani, S Nur; Jung, Thomas S; Kapoor, Vena; Kappes, Heike; Kati, Vassiliki; Katovai, Eric; Kellner, Klaus; Kessler, Michael; Kirby, Kathryn R; Kittle, Andrew M; Knight, Mairi E; Knop, Eva; Kohler, Florian; Koivula, Matti; Kolb, Annette; Kone, Mouhamadou; Kőrösi, Ádám; Krauss, Jochen; Kumar, Ajith; Kumar, Raman; Kurz, David J; Kutt, Alex S; Lachat, Thibault; Lantschner, Victoria; Lara, Francisco; Lasky, Jesse R; Latta, Steven C; Laurance, William F; Lavelle, Patrick; Le Féon, Violette; LeBuhn, Gretchen; Légaré, Jean-Philippe; Lehouck, Valérie; Lencinas, María V; Lentini, Pia E; Letcher, Susan G; Li, Qi; Litchwark, Simon A; Littlewood, Nick A; Liu, Yunhui; Lo-Man-Hung, Nancy; López-Quintero, Carlos A; Louhaichi, Mounir; Lövei, Gabor L; Lucas-Borja, Manuel Esteban; Luja, Victor H; Luskin, Matthew S; MacSwiney G, M Cristina; Maeto, Kaoru; Magura, Tibor; Mallari, Neil Aldrin; Malone, Louise A; Malonza, Patrick K; Malumbres-Olarte, Jagoba; Mandujano, Salvador; Måren, Inger E; Marin-Spiotta, Erika; Marsh, Charles J; Marshall, E J P; Martínez, Eliana; Martínez Pastur, Guillermo; Moreno Mateos, David; Mayfield, Margaret M; Mazimpaka, Vicente; McCarthy, Jennifer L; McCarthy, Kyle P; McFrederick, Quinn S; McNamara, Sean; Medina, Nagore G; Medina, Rafael; Mena, Jose L; Mico, Estefania; Mikusinski, Grzegorz; Milder, Jeffrey C; Miller, James R; Miranda-Esquivel, Daniel R; Moir, Melinda L; Morales, Carolina L; Muchane, Mary N; Muchane, Muchai; Mudri-Stojnic, Sonja; Munira, A Nur; Muoñz-Alonso, Antonio; Munyekenye, B F; Naidoo, Robin; Naithani, A; Nakagawa, Michiko; Nakamura, Akihiro; Nakashima, Yoshihiro; Naoe, Shoji; Nates-Parra, Guiomar; Navarrete Gutierrez, Dario A; Navarro-Iriarte, Luis; Ndang'ang'a, Paul K; Neuschulz, Eike L; Ngai, Jacqueline T; Nicolas, Violaine; Nilsson, Sven G; Noreika, Norbertas; Norfolk, Olivia; Noriega, Jorge Ari; Norton, David A; Nöske, Nicole M; Nowakowski, A Justin; Numa, Catherine; O'Dea, Niall; O'Farrell, Patrick J; Oduro, William; Oertli, Sabine; Ofori-Boateng, Caleb; Oke, Christopher Omamoke; Oostra, Vicencio; Osgathorpe, Lynne M; Otavo, Samuel Eduardo; Page, Navendu V; Paritsis, Juan; Parra-H, Alejandro; Parry, Luke; Pe'er, Guy; Pearman, Peter B; Pelegrin, Nicolás; Pélissier, Raphaël; Peres, Carlos A; Peri, Pablo L; Persson, Anna S; Petanidou, Theodora; Peters, Marcell K; Pethiyagoda, Rohan S; Phalan, Ben; Philips, T Keith; Pillsbury, Finn C; Pincheira-Ulbrich, Jimmy; Pineda, Eduardo; Pino, Joan; Pizarro-Araya, Jaime; Plumptre, A J; Poggio, Santiago L; Politi, Natalia; Pons, Pere; Poveda, Katja; Power, Eileen F; Presley, Steven J; Proença, Vânia; Quaranta, Marino; Quintero, Carolina; Rader, Romina; Ramesh, B R; Ramirez-Pinilla, Martha P; Ranganathan, Jai; Rasmussen, Claus; Redpath-Downing, Nicola A; Reid, J Leighton; Reis, Yana T; Rey Benayas, José M; Rey-Velasco, Juan Carlos; Reynolds, Chevonne; Ribeiro, Danilo Bandini; Richards, Miriam H; Richardson, Barbara A; Richardson, Michael J; Ríos, Rodrigo Macip; Robinson, Richard; Robles, Carolina A; Römbke, Jörg; Romero-Duque, Luz Piedad; Rös, Matthias; Rosselli, Loreta; Rossiter, Stephen J; Roth, Dana S; Roulston, T'ai H; Rousseau, Laurent; Rubio, André V; Ruel, Jean-Claude; Sadler, Jonathan P; Sáfián, Szabolcs; Saldaña-Vázquez, Romeo A; Sam, Katerina; Samnegård, Ulrika; Santana, Joana; Santos, Xavier; Savage, Jade; Schellhorn, Nancy A; Schilthuizen, Menno; Schmiedel, Ute; Schmitt, Christine B; Schon, Nicole L; Schüepp, Christof; Schumann, Katharina; Schweiger, Oliver; Scott, Dawn M; Scott, Kenneth A; Sedlock, Jodi L; Seefeldt, Steven S; Shahabuddin, Ghazala; Shannon, Graeme; Sheil, Douglas; Sheldon, Frederick H; Shochat, Eyal; Siebert, Stefan J; Silva, Fernando A B; Simonetti, Javier A; Slade, Eleanor M; Smith, Jo; Smith-Pardo, Allan H; Sodhi, Navjot S; Somarriba, Eduardo J; Sosa, Ramón A; Soto Quiroga, Grimaldo; St-Laurent, Martin-Hugues; Starzomski, Brian M; Stefanescu, Constanti; Steffan-Dewenter, Ingolf; Stouffer, Philip C; Stout, Jane C; Strauch, Ayron M; Struebig, Matthew J; Su, Zhimin; Suarez-Rubio, Marcela; Sugiura, Shinji; Summerville, Keith S; Sung, Yik-Hei; Sutrisno, Hari; Svenning, Jens-Christian; Teder, Tiit; Threlfall, Caragh G; Tiitsaar, Anu; Todd, Jacqui H; Tonietto, Rebecca K; Torre, Ignasi; Tóthmérész, Béla; Tscharntke, Teja; Turner, Edgar C; Tylianakis, Jason M; Uehara-Prado, Marcio; Urbina-Cardona, Nicolas; Vallan, Denis; Vanbergen, Adam J; Vasconcelos, Heraldo L; Vassilev, Kiril; Verboven, Hans A F; Verdasca, Maria João; Verdú, José R; Vergara, Carlos H; Vergara, Pablo M; Verhulst, Jort; Virgilio, Massimiliano; Vu, Lien Van; Waite, Edward M; Walker, Tony R; Wang, Hua-Feng; Wang, Yanping; Watling, James I; Weller, Britta; Wells, Konstans; Westphal, Catrin; Wiafe, Edward D; Williams, Christopher D; Willig, Michael R; Woinarski, John C Z; Wolf, Jan H D; Wolters, Volkmar; Woodcock, Ben A; Wu, Jihua; Wunderle, Joseph M; Yamaura, Yuichi; Yoshikura, Satoko; Yu, Douglas W; Zaitsev, Andrey S; Zeidler, Juliane; Zou, Fasheng; Collen, Ben; Ewers, Rob M; Mace, Georgina M; Purves, Drew W; Scharlemann, Jörn P W; Purvis, Andy

The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of

Six-month changes in spirituality and religiousness in alcoholics predict drinking outcomes at nine months.

Science.gov (United States)

Robinson, Elizabeth A R; Krentzman, Amy R; Webb, Jon R; Brower, Kirk J

2011-07-01

Although spiritual change is hypothesized to contribute to recovery from alcohol dependence, few studies have used prospective data to investigate this hypothesis. Prior studies have also been limited to treatment-seeking and Alcoholics Anonymous (AA) samples. This study included alcohol-dependent individuals, both in treatment and not, to investigate the effect of spiritual and religious (SR) change on subsequent drinking outcomes, independent of AA involvement. Alcoholics (N = 364) were recruited for a panel study from two abstinence-based treatment centers, a moderation drinking program, and untreated individuals from the local community. Quantitative measures of SR change between baseline and 6 months were used to predict 9-month drinking outcomes, controlling for baseline drinking and AA involvement. Significant 6-month changes in 8 of 12 SR measures were found, which included private SR practices, beliefs, daily spiritual experiences, three measures of forgiveness, negative religious coping, and purpose in life. Increases in private SR practices and forgiveness of self were the strongest predictors of improvements in drinking outcomes. Changes in daily spiritual experiences, purpose in life, a general measure of forgiveness, and negative religious coping also predicted favorable drinking outcomes. SR change predicted good drinking outcomes in alcoholics, even when controlling for AA involvement. SR variables, broadly defined, deserve attention in fostering change even among those who do not affiliate with AA or religious institutions. Last, future research should include SR variables, particularly various types of forgiveness, given the strong effects found for forgiveness of self.

Low-dimensionality and predictability of solar wind and global magnetosphere during magnetic storms

OpenAIRE

Zivkovic, Tatjana; Rypdal, Kristoffer

2011-01-01

This article is part of Tatjana Živkovics' doctoral thesis. Available in Munin at http://hdl.handle.net/10037/3231 The storm index SYM-H, the solar wind velocity v, and interplanetary magnetic field Bz show no signatures of low-dimensional dynamics in quiet periods, but tests for determinism in the time series indicate that SYM-H exhibits a significant low-dimensional component during storm time, suggesting that self-organization takes place during magnetic storms. Even though our analysis...

Three dimensional changes in maxillary complete dentures immersed in water for seven days after polymerization

Directory of Open Access Journals (Sweden)

Shinsuke Sadamori

2008-03-01

Full Text Available The purpose of this study was to investigate the three dimensional changes in the fitting surface and artificial teeth of maxillary complete dentures which were fabricated using two different polymerizing processes: heat polymerization (HP and microwave polymerization (MP, after immersion in water for seven days. The amount of distortion in the molar region of the alveolar ridge was significantly different between HP and MP. However, the overall distortion of the dentures polymerized using both methods was similar. The distortion due to immersion in water for seven days compensated for the polymerization distortion, but the amount of distortion was very slight.

Wave climate change, coastline response and hazard prediction in New South Wales, Australia

International Nuclear Information System (INIS)

Goodwin, Ian D.; Verdon, Danielle; Cowell, Peter

2007-01-01

Full text: Full text: Considerable research effort has been directed towards understanding and the gross prediction of shoreline response to sea level rise (eg. Cowell ef a/. 2003a, b). In contrast, synoptic prediction of changes in the planform configuration of shorelines in response to changes in wind and wave climates over many decades has been limited by the lack of geohistorical data on shoreline alignment evolution and long time series of wave climate. This paper presents new data sets on monthly mean wave direction variability based on: a. Waverider buoy data; b. a reconstruction of monthly mid-shelf wave direction, 1877 to 2002 AD from historical MSLP data (Goodwin 2005); and c. a multi-decadal reconstruction of wave direction, in association with the Interdecadal Pacific Oscillation and the Southern Annular Mode of climate variability, covering the past millennium. A model of coastline response to the wave climate variability is presented for northern and central New South Wales (NSW) for decadal to multi-decadal time scales, and is based on instrumental and geohistorical data. The sensitivity of the coastline position and alignment, and beach state to mean and extreme wave climate changes is demonstrated (e.g. Goodwin et al. 2006). State changes in geometric shoreline alignment rotation, sand volume (progradation/recession) for NSW and mean wave direction, are shown to be in agreement with the low-frequency change in Pacific-wide climate. Synoptic typing of climate patterns using Self Organised Mapping methods is used to downscale CSIRO GCM output for this century. The synoptic types are correlated to instrumental wave climate data and coastal behaviour. The shifts in downscaled synoptic types for 2030 and 2070 AD are then used as the basis for predicting mean wave climate changes, coastal behaviour and hazards along the NSW coastline. The associated coastal hazards relate to the definition of coastal land loss through rising sea levels and shoreline

Changes in psychiatric symptoms among persons with methamphetamine dependence predicts changes in severity of drug problems but not frequency of use.

Science.gov (United States)

Polcin, Douglas L; Korcha, Rachael; Bond, Jason; Galloway, Gantt; Nayak, Madhabika

2016-01-01

Few studies have examined how changes in psychiatric symptoms over time are associated with changes in drug use and severity of drug problems. No studies have examined these relationships among methamphetamine (MA)-dependent persons receiving motivational interviewing within the context of standard outpatient treatment. Two hundred seventeen individuals with MA dependence were randomly assigned to a standard single session of motivational interviewing (MI) or an intensive 9-session model of MI. Both groups received standard outpatient group treatment. The Addiction Severity Index (ASI) and timeline follow-back (TLFB) for MA use were administered at treatment entry and 2-, 4-, and 6-month follow-ups. Changes in ASI psychiatric severity between baseline and 2 months predicted changes in ASI drug severity during the same time period, but not changes on measures of MA use. Item analysis of the ASI drug scale showed that psychiatric severity predicted how troubled or bothered participants were by their drug us, how important they felt it was for them to get treatment, and the number of days they experienced drug problems. However, it did not predict the number days they used drugs in the past 30 days. These associations did not differ between study conditions, and they persisted when psychiatric severity and outcomes were compared across 4- and 6-month time periods. Results are among the first to track how changes in psychiatric severity over time are associated with changes in MA use and severity of drug problems. Treatment efforts targeting reduction of psychiatric symptoms among MA-dependent persons might be helpful in reducing the level of distress and problems associated with MA use but not how often it is used. There is a need for additional research describing the circumstances under which the experiences and perceptions of drug-related problems diverge from frequency of consumption.

Anomalous dimensionality dependence of diffusion in a rugged energy landscape: How pathological is one dimension?

Science.gov (United States)

Seki, Kazuhiko; Bagchi, Kaushik; Bagchi, Biman

2016-05-01

Diffusion in one dimensional rugged energy landscape (REL) is predicted to be pathologically different (from any higher dimension) with a much larger chance of encountering broken ergodicity [D. L. Stein and C. M. Newman, AIP Conf. Proc. 1479, 620 (2012)]. However, no quantitative study of this difference has been reported, despite the prevalence of multidimensional physical models in the literature (like a high dimensional funnel guiding protein folding/unfolding). Paradoxically, some theoretical studies of these phenomena still employ a one dimensional diffusion description for analytical tractability. We explore the dimensionality dependent diffusion on REL by carrying out an effective medium approximation based analytical calculations and compare them with the available computer simulation results. We find that at an intermediate level of ruggedness (assumed to have a Gaussian distribution), where diffusion is well-defined, the value of the effective diffusion coefficient depends on dimensionality and changes (increases) by several factors (˜5-10) in going from 1d to 2d. In contrast, the changes in subsequent transitions (like 2d to 3d and 3d to 4d and so on) are far more modest, of the order of 10-20% only. When ruggedness is given by random traps with an exponential distribution of barrier heights, the mean square displacement (MSD) is sub-diffusive (a well-known result), but the growth of MSD is described by different exponents in one and higher dimensions. The reason for such strong ruggedness induced retardation in the case of one dimensional REL is discussed. We also discuss the special limiting case of infinite dimension (d = ∞) where the effective medium approximation becomes exact and where theoretical results become simple. We discuss, for the first time, the role of spatial correlation in the landscape on diffusion of a random walker.

The Predictive Utility of Hypnotizability: The Change in Suggestibility Produced by Hypnosis

Science.gov (United States)

Milling, Leonard S.; Coursen, Elizabeth L.; Shores, Jessica S.; Waszkiewicz, Jolanta A.

2010-01-01

Objective: The predictive utility of hypnotizability, conceptualized as the change in suggestibility produced by a hypnotic induction, was investigated in the suggested reduction of experimental pain. Method: One hundred and seventy-three participants were assessed for nonhypnotic imaginative suggestibility. Thereafter, participants experienced…

Changing relationships between land use and environmental characteristics and their consequences for spatially explicit land-use change prediction

NARCIS (Netherlands)

Bakker, M.; Veldkamp, A.

2012-01-01

Spatially explicit land-use change prediction is often based on environmental characteristics of land-use types, such as soil type and slope, as observed at one time instant. This approach presumes that relationships between land use and environment are constant over time. We argue that such

The predictive skill of species distribution models for plankton in a changing climate

DEFF Research Database (Denmark)

Brun, Philipp Georg; Kiørboe, Thomas; Licandro, Priscilla

2016-01-01

Statistical species distribution models (SDMs) are increasingly used to project spatial relocations of marine taxa under future climate change scenarios. However, tests of their predictive skill in the real-world are rare. Here, we use data from the Continuous Plankton Recorder program, one...... null models, is essential to assess the robustness of projections of marine planktonic species under climate change...

Three-dimensional simulation of flow, salinity, sediment, and radionuclide movements in the Hudson River estuary

International Nuclear Information System (INIS)

Onishi, Y.; Trent, D.S.

1985-04-01

The three-dimensional, finite difference model, FLESCOT simulates time-varying movements of flow, turbulent kinetic energy, salinity, water temperature, sediment, and contaminants in estuarine, coastal, and ocean waters. The model was applied to a 106-km (66-mi) reach of the Hudson River estuary in New York between Chelsea and the mouth of the river. It predicted the time-varying, three-dimensional distributions of tidal flow, salinity, three separate groups of sediments (i.e., sand, silt, and clay), and a radionuclide ( 137 Cs) in both dissolved and particulate (those sorbed by sediments) forms for over 40 days. The model also calculated riverbed elevation changes caused by sediment deposition and bed erosion, bed sediment size distribution and armoring, and distributions of the particulate 137 Cs sorbed by sand, silt, and clay in the bed

Solving one-dimensional phase change problems with moving grid method and mesh free radial basis functions

International Nuclear Information System (INIS)

Vrankar, L.; Turk, G.; Runovc, F.; Kansa, E.J.

2006-01-01

Many heat-transfer problems involve a change of phase of material due to solidification or melting. Applications include: the safety studies of nuclear reactors (molten core concrete interaction), the drilling of high ice-content soil, the storage of thermal energy, etc. These problems are often called Stefan's or moving boundary value problems. Mathematically, the interface motion is expressed implicitly in an equation for the conservation of thermal energy at the interface (Stefan's conditions). This introduces a non-linear character to the system which treats each problem somewhat uniquely. The exact solution of phase change problems is limited exclusively to the cases in which e.g. the heat transfer regions are infinite or semi-infinite one dimensional-space. Therefore, solution is obtained either by approximate analytical solution or by numerical methods. Finite-difference methods and finite-element techniques have been used extensively for numerical solution of moving boundary problems. Recently, the numerical methods have focused on the idea of using a mesh-free methodology for the numerical solution of partial differential equations based on radial basis functions. In our case we will study solid-solid transformation. The numerical solutions will be compared with analytical solutions. Actually, in our work we will examine usefulness of radial basis functions (especially multiquadric-MQ) for one-dimensional Stefan's problems. The position of the moving boundary will be simulated by moving grid method. The resultant system of RBF-PDE will be solved by affine space decomposition. (author)

Effects of the addition of nanoparticulate calcium carbonate on setting time, dimensional change, compressive strength, solubility and pH of MTA.

Science.gov (United States)

Bernardi, A; Bortoluzzi, E A; Felippe, W T; Felippe, M C S; Wan, W S; Teixeira, C S

2017-01-01

To evaluate nanoparticulate calcium carbonate (NPCC) using transmission electron microscopy and the effects of NPCC addition to MTA in regard to the setting time, dimensional change, compressive strength, solubility and pH. The experimental groups were G1 (MTA), G2 (MTA with 5% NPCC) and G3 (MTA with 10% NPCC). The tests followed ISO and ADA standards. The specimens in the dimensional change and compressive strength tests were measured immediately after setting, after 24 h and after 30 days. In the solubility test, rings filled with cement were weighed after setting and after 30 days. The pH was measured after 24 h and 30 days. The data were analysed with the ANOVA, Tukey's and Kruskal-Wallis tests (α = 5%). The setting time was reduced (P  G2 > G3). The solubility test revealed a difference amongst the groups when the specimens were hydrated: G2 > G1 > G3 and dehydrated: G3 > G2 > G1. The pH of the groups was similar at 24 h with higher values in each group after 30 days (P calcium carbonate had a cubic morphology with few impurities. The addition of nanoparticulate calcium carbonate to MTA accelerated the setting time, decreased compressive strength and, after 30 days, resulted in lower dimensional change (G2), higher solubility and a higher pH. © 2015 International Endodontic Journal. Published by John Wiley & Sons Ltd.

Predicting implementation from organizational readiness for change: a study protocol

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Kelly P Adam

2011-07-01

Full Text Available Abstract Background There is widespread interest in measuring organizational readiness to implement evidence-based practices in clinical care. However, there are a number of challenges to validating organizational measures, including inferential bias arising from the halo effect and method bias - two threats to validity that, while well-documented by organizational scholars, are often ignored in health services research. We describe a protocol to comprehensively assess the psychometric properties of a previously developed survey, the Organizational Readiness to Change Assessment. Objectives Our objective is to conduct a comprehensive assessment of the psychometric properties of the Organizational Readiness to Change Assessment incorporating methods specifically to address threats from halo effect and method bias. Methods and Design We will conduct three sets of analyses using longitudinal, secondary data from four partner projects, each testing interventions to improve the implementation of an evidence-based clinical practice. Partner projects field the Organizational Readiness to Change Assessment at baseline (n = 208 respondents; 53 facilities, and prospectively assesses the degree to which the evidence-based practice is implemented. We will conduct predictive and concurrent validities using hierarchical linear modeling and multivariate regression, respectively. For predictive validity, the outcome is the change from baseline to follow-up in the use of the evidence-based practice. We will use intra-class correlations derived from hierarchical linear models to assess inter-rater reliability. Two partner projects will also field measures of job satisfaction for convergent and discriminant validity analyses, and will field Organizational Readiness to Change Assessment measures at follow-up for concurrent validity (n = 158 respondents; 33 facilities. Convergent and discriminant validities will test associations between organizational readiness and

Ab initio and template-based prediction of multi-class distance maps by two-dimensional recursive neural networks

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Martin Alberto JM

2009-01-01

Full Text Available Abstract Background Prediction of protein structures from their sequences is still one of the open grand challenges of computational biology. Some approaches to protein structure prediction, especially ab initio ones, rely to some extent on the prediction of residue contact maps. Residue contact map predictions have been assessed at the CASP competition for several years now. Although it has been shown that exact contact maps generally yield correct three-dimensional structures, this is true only at a relatively low resolution (3–4 Å from the native structure. Another known weakness of contact maps is that they are generally predicted ab initio, that is not exploiting information about potential homologues of known structure. Results We introduce a new class of distance restraints for protein structures: multi-class distance maps. We show that Cα trace reconstructions based on 4-class native maps are significantly better than those from residue contact maps. We then build two predictors of 4-class maps based on recursive neural networks: one ab initio, or relying on the sequence and on evolutionary information; one template-based, or in which homology information to known structures is provided as a further input. We show that virtually any level of sequence similarity to structural templates (down to less than 10% yields more accurate 4-class maps than the ab initio predictor. We show that template-based predictions by recursive neural networks are consistently better than the best template and than a number of combinations of the best available templates. We also extract binary residue contact maps at an 8 Å threshold (as per CASP assessment from the 4-class predictors and show that the template-based version is also more accurate than the best template and consistently better than the ab initio one, down to very low levels of sequence identity to structural templates. Furthermore, we test both ab-initio and template-based 8 �

Revisiting concepts of thermal physiology: Predicting responses of mammals to climate change.

Science.gov (United States)

Mitchell, Duncan; Snelling, Edward P; Hetem, Robyn S; Maloney, Shane K; Strauss, Willem Maartin; Fuller, Andrea

2018-02-26

The accuracy of predictive models (also known as mechanistic or causal models) of animal responses to climate change depends on properly incorporating the principles of heat transfer and thermoregulation into those models. Regrettably, proper incorporation of these principles is not always evident. We have revisited the relevant principles of thermal physiology and analysed how they have been applied in predictive models of large mammals, which are particularly vulnerable, to climate change. We considered dry heat exchange, evaporative heat transfer, the thermoneutral zone and homeothermy, and we examined the roles of size and shape in the thermal physiology of large mammals. We report on the following misconceptions in influential predictive models: underestimation of the role of radiant heat transfer, misassignment of the role and misunderstanding of the sustainability of evaporative cooling, misinterpretation of the thermoneutral zone as a zone of thermal tolerance or as a zone of sustainable energetics, confusion of upper critical temperature and critical thermal maximum, overestimation of the metabolic energy cost of evaporative cooling, failure to appreciate that the current advantages of size and shape will become disadvantageous as climate change advances, misassumptions about skin temperature and, lastly, misconceptions about the relationship between body core temperature and its variability with body mass in large mammals. Not all misconceptions invalidate the models, but we believe that preventing inappropriate assumptions from propagating will improve model accuracy, especially as models progress beyond their current typically static format to include genetic and epigenetic adaptation that can result in phenotypic plasticity. © 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society.

Long Range Aircraft Trajectory Prediction

OpenAIRE

Magister, Tone

2009-01-01

The subject of the paper is the improvement of the aircraft future trajectory prediction accuracy for long-range airborne separation assurance. The strategic planning of safe aircraft flights and effective conflict avoidance tactics demand timely and accurate conflict detection based upon future four–dimensional airborne traffic situation prediction which is as accurate as each aircraft flight trajectory prediction. The improved kinematics model of aircraft relative flight considering flight ...

Electron crystallography of three dimensional protein crystals

NARCIS (Netherlands)

Georgieva, Dilyana

2008-01-01

This thesis describes an investigation of the potential of electron diffraction for studying three dimensional sub-micro-crystals of proteins and pharmaceuticals. A prerequisite for using electron diffraction for structural studies is the predictable availability of tiny crystals. A method for

Personality traits and individual differences predict threat-induced changes in postural control.

Science.gov (United States)

Zaback, Martin; Cleworth, Taylor W; Carpenter, Mark G; Adkin, Allan L

2015-04-01

This study explored whether specific personality traits and individual differences could predict changes in postural control when presented with a height-induced postural threat. Eighty-two healthy young adults completed questionnaires to assess trait anxiety, trait movement reinvestment (conscious motor processing, movement self-consciousness), physical risk-taking, and previous experience with height-related activities. Tests of static (quiet standing) and anticipatory (rise to toes) postural control were completed under low and high postural threat conditions. Personality traits and individual differences significantly predicted height-induced changes in static, but not anticipatory postural control. Individuals less prone to taking physical risks were more likely to lean further away from the platform edge and sway at higher frequencies and smaller amplitudes. Individuals more prone to conscious motor processing were more likely to lean further away from the platform edge and sway at larger amplitudes. Individuals more self-conscious about their movement appearance were more likely to sway at smaller amplitudes. Evidence is also provided that relationships between physical risk-taking and changes in static postural control are mediated through changes in fear of falling and physiological arousal. Results from this study may have indirect implications for balance assessment and treatment; however, further work exploring these factors in patient populations is necessary. Copyright © 2015 Elsevier B.V. All rights reserved.

Predictive modelling of the spatial pattern of past and future forest cover changes in India

Science.gov (United States)

Reddy, C. Sudhakar; Singh, Sonali; Dadhwal, V. K.; Jha, C. S.; Rao, N. Rama; Diwakar, P. G.

2017-02-01

This study was carried out to simulate the forest cover changes in India using Land Change Modeler. Classified multi-temporal long-term forest cover data was used to generate the forest covers of 1880 and 2025. The spatial data were overlaid with variables such as the proximity to roads, settlements, water bodies, elevation and slope to determine the relationship between forest cover change and explanatory variables. The predicted forest cover in 1880 indicates an area of 10,42,008 km2, which represents 31.7% of the geographical area of India. About 40% of the forest cover in India was lost during the time interval of 1880-2013. Ownership of majority of forest lands by non-governmental agencies and large scale shifting cultivation are responsible for higher deforestation rates in the Northeastern states. The six states of the Northeast (Assam, Manipur, Meghalaya, Mizoram, Nagaland, Tripura) and one union territory (Andaman & Nicobar Islands) had shown an annual gross rate of deforestation of >0.3 from 2005 to 2013 and has been considered in the present study for the prediction of future forest cover in 2025. The modelling results predicted widespread deforestation in Northeast India and in Andaman & Nicobar Islands and hence is likely to affect the remaining forests significantly before 2025. The multi-layer perceptron neural network has predicted the forest cover for the period of 1880 and 2025 with a Kappa statistic of >0.70. The model predicted a further decrease of 2305 km2 of forest area in the Northeast and Andaman & Nicobar Islands by 2025. The majority of the protected areas are successful in the protection of the forest cover in the Northeast due to management practices, with the exception of Manas, Sonai-Rupai, Nameri and Marat Longri. The predicted forest cover scenario for the year 2025 would provide useful inputs for effective resource management and help in biodiversity conservation and for mitigating climate change.

Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO.

Directory of Open Access Journals (Sweden)

Mingzheng Peng

Full Text Available The aim of this study was to predict Ki-67 labeling index (LI preoperatively by three-dimensional (3D CT image parameters for pathologic assessment of GGO nodules. Diameter, total volume (TV, the maximum CT number (MAX, average CT number (AVG and standard deviation of CT number within the whole GGO nodule (STD were measured by 3D CT workstation. By detection of immunohistochemistry and Image Software Pro Plus 6.0, different Ki-67 LI were measured and statistically analyzed among preinvasive adenocarcinoma (PIA, minimally invasive adenocarcinoma (MIA and invasive adenocarcinoma (IAC. Receiver operating characteristic (ROC curve, Spearman correlation analysis and multiple linear regression analysis with cross-validation were performed to further research a quantitative correlation between Ki-67 labeling index and radiological parameters. Diameter, TV, MAX, AVG and STD increased along with PIA, MIA and IAC significantly and consecutively. In the multiple linear regression model by a stepwise way, we obtained an equation: prediction of Ki-67 LI=0.022*STD+0.001* TV+2.137 (R=0.595, R's square=0.354, p<0.001, which can predict Ki-67 LI as a proliferative marker preoperatively. Diameter, TV, MAX, AVG and STD could discriminate pathologic categories of GGO nodules significantly. Ki-67 LI of early lung adenocarcinoma presenting GGO can be predicted by radiologic parameters based on 3D CT for differential diagnosis.

A new series of two-dimensional silicon crystals with versatile electronic properties

Science.gov (United States)

Chae, Kisung; Kim, Duck Young; Son, Young-Woo

2018-04-01

Silicon (Si) is one of the most extensively studied materials owing to its significance to semiconductor science and technology. While efforts to find a new three-dimensional (3D) Si crystal with unusual properties have made some progress, its two-dimensional (2D) phases have not yet been explored as much. Here, based on a newly developed systematic ab initio materials searching strategy, we report a series of novel 2D Si crystals with unprecedented structural and electronic properties. The new structures exhibit perfectly planar outermost surface layers of a distorted hexagonal network with their thicknesses varying with the atomic arrangement inside. Dramatic changes in electronic properties ranging from semimetal to semiconducting with indirect energy gaps and even to one with direct energy gaps are realized by varying thickness as well as by surface oxidation. Our predicted 2D Si crystals with flat surfaces and tunable electronic properties will shed light on the development of silicon-based 2D electronics technology.

Towards realistic flow modelling. Creation and evaluation of two-dimensional simulated porous media: An image analysis approach

Science.gov (United States)

Anguy, Yannick; Bernard, Dominique; Ehrlich, Robert

1996-05-01

This work is part of an attempt to quantify the relationship between the permeability tensor ( K) and the micro-structure of natural porous media. A brief account is first provided of popular theories used to relate the micro-structure to K. Reasons for the lack of predictive power and restricted generality of current models are discussed. An alternative is an empirically based implicit model wherein K is expressed as a consequence of a few “pore-types” arising from the dynamics of depositional processes. The analytical form of that implicit model arises from evidence of universal association between pore-type and throat size in sandstones and carbonates. An explicit model, relying on the local change of scale technique is then addressed. That explicit model allows, from knowledge of the three-dimensional micro-geometry to calculate K explicitly without having recourse to any constitutive assumptions. The predictive and general character of the explicit model is underlined. The relevance of the change of scale technique is recalled to be contingent on the availability of rock-like three-dimensional synthetic media. A random stationary ergodic process is developed, that allows us to generate three-dimensional synthetic media from a two-dimensional autocorrelation function r(λ x ,λ y ) and associated probability density function ∈ β measured on a single binary image. The focus of this work is to ensure the rock-like character of those synthetic media. This is done first through a direct approach: n two-dimensional synthetic media, derived from single set ( ∈ β , r(λ x ,λ y )) yield n permeability tensors K {/i-1,n i} (calculated by the local change of scale) of the same order. This is a necessary condition to ensure that r(λ x ,λ y ) and ∈ β carry all structural information relevant to K. The limits of this direct approach, in terms of required Central Process Unit time and Memory is underlined, raising the need for an alternative. This is done by

Design principle for improved three-dimensional ac electro-osmotic pumps

Science.gov (United States)

Burch, Damian; Bazant, Martin Z.

2008-05-01

Three-dimensional (3D) ac electro-osmotic (ACEO) pumps have recently been developed that are much faster and more robust than previous planar designs. The basic idea is to create a “fluid conveyor belt” by placing opposing ACEO slip velocities at different heights. Current designs involve electrodes with electroplated steps, whose heights have been optimized in simulations and experiments. Here, we consider changing the boundary conditions—rather than the geometry—and predict that flow rates can be further doubled by fabricating 3D features with nonpolarizable materials. This amplifies the fluid conveyor belt by removing opposing flows on the vertical surfaces, and it increases the slip velocities that drive the flow.

Predicting Seagrass Occurrence in a Changing Climate Using Random Forests

Science.gov (United States)

Aydin, O.; Butler, K. A.

2017-12-01

Seagrasses are marine plants that can quickly sequester vast amounts of carbon (up to 100 times more and 12 times faster than tropical forests). In this work, we present an integrated GIS and machine learning approach to build a data-driven model of seagrass presence-absence. We outline a random forest approach that avoids the prevalence bias in many ecological presence-absence models. One of our goals is to predict global seagrass occurrence from a spatially limited training sample. In addition, we conduct a sensitivity study which investigates the vulnerability of seagrass to changing climate conditions. We integrate multiple data sources including fine-scale seagrass data from MarineCadastre.gov and the recently available globally extensive publicly available Ecological Marine Units (EMU) dataset. These data are used to train a model for seagrass occurrence along the U.S. coast. In situ oceans data are interpolated using Empirical Bayesian Kriging (EBK) to produce globally extensive prediction variables. A neural network is used to estimate probable future values of prediction variables such as ocean temperature to assess the impact of a warming climate on seagrass occurrence. The proposed workflow can be generalized to many presence-absence models.

Space can substitute for time in predicting climate-change effects on biodiversity

Science.gov (United States)

Blois, Jessica L.; Williams, John W.; Fitzpatrick, Matthew C.; Jackson, Stephen T.; Ferrier, Simon

2013-01-01

“Space-for-time” substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption—that drivers of spatial gradients of species composition also drive temporal changes in diversity—rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as “time-for-time” predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

Space can substitute for time in predicting climate-change effects on biodiversity.

Science.gov (United States)

Blois, Jessica L; Williams, John W; Fitzpatrick, Matthew C; Jackson, Stephen T; Ferrier, Simon

2013-06-04

"Space-for-time" substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption--that drivers of spatial gradients of species composition also drive temporal changes in diversity--rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as "time-for-time" predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

The predictive value of three-dimensional Doppler ultrasonography in determining implantation in patients underwent in vitro fertilization

Directory of Open Access Journals (Sweden)

Yusuf Çakmak

2015-12-01

Full Text Available Objective: The aim of this study is to evaluate the relationship between endometrial and sub-endometrial blood flow and implantation rate in patients whose undergone in vitro fertilization. Methods: A prospective study was conducted. Long protocol and antagonist regimens were administered to the patients. Endometrial and sub-endometrial blood flow was evaluated by using 3 dimensional Doppler ultrasonography on the day of oocyt retrieval measurement. For comparison pregnant and non-pregnant women in terms of endometrial and sub-endometrial blood flow, t test was used. The p value was considered statistically meaningful as 0.05. In long protocol group, the number of embryo was greater in pregnant women than non-pregnant women (p=0.012. The number of transferred embryo increased pregnancy rate almost 3.5 fold (p=0.002. Conclusion: The endometrial and subendometrial blood flow is not reliable factor in prediction pregnancy or implantation.

Three-dimensional evaluation of soft tissue changes in the orofacial region after tooth-borne and bone-borne surgically assisted rapid maxillary expansion

NARCIS (Netherlands)

Nada, R.M.; Loon, B. van; Maal, T.J.J.; Berge, S.J.; Mostafa, Y.A.; Kuijpers-Jagtman, A.M.; Schols, J.G.J.H.

2013-01-01

OBJECTIVES: This study seeks to three-dimensionally assess soft tissue changes in the orofacial region following tooth-borne and bone-borne surgically assisted rapid maxillary expansion (SARME). MATERIALS AND METHODS: This prospective cohort study included 40 skeletally mature patients with

A two-parameter model to predict fracture in the transition

International Nuclear Information System (INIS)

DeAquino, C.T.; Landes, J.D.; McCabe, D.E.

1995-01-01

A model is proposed that uses a numerical characterization of the crack tip stress field modified by the J - Q constraint theory and a weak link assumption to predict fracture behavior in the transition for reactor vessel steels. This model predicts the toughness scatter band for a component model from a toughness scatter band measured on a test specimen geometry. The model has been applied previously to two-dimensional through cracks. Many applications to actual components structures involve three-dimensional surface flaws. These cases require a more difficult level of analysis and need additional information. In this paper, both the current model for two-dimensional cracks and an approach needed to extend the model for the prediction of transition fracture behavior in three-dimensional surface flaws are discussed. Examples are presented to show how the model can be applied and in some cases to compare with other test results. (author). 13 refs., 7 figs

Asymptotically Honest Confidence Regions for High Dimensional

DEFF Research Database (Denmark)

Caner, Mehmet; Kock, Anders Bredahl

While variable selection and oracle inequalities for the estimation and prediction error have received considerable attention in the literature on high-dimensional models, very little work has been done in the area of testing and construction of confidence bands in high-dimensional models. However...... develop an oracle inequality for the conservative Lasso only assuming the existence of a certain number of moments. This is done by means of the Marcinkiewicz-Zygmund inequality which in our context provides sharper bounds than Nemirovski's inequality. As opposed to van de Geer et al. (2014) we allow...

Improvement of a three-dimensional atmospheric dynamic model and examination of its performance over complex terrain

International Nuclear Information System (INIS)

Nagai, Haruyasu; Yamazawa, Hiromi

1994-11-01

A three-dimensional atmospheric dynamic model (PHYSIC) was improved and its performance was examined using the meteorological data observed at a coastal area with a complex terrain. To introduce synoptic meteorological conditions into the model, the initial and boundary conditions were improved. By this improvement, the model can predict the temporal change of wind field for more than 24 hours. Moreover, the model successfully simulates the land and sea breeze observed at Shimokita area in the summer of 1992. (author)

Predicting adult weight change in the real world: a systematic review and meta-analysis accounting for compensatory changes in energy intake or expenditure.

Science.gov (United States)

Dhurandhar, E J; Kaiser, K A; Dawson, J A; Alcorn, A S; Keating, K D; Allison, D B

2015-08-01

Public health and clinical interventions for obesity in free-living adults may be diminished by individual compensation for the intervention. Approaches to predict weight outcomes do not account for all mechanisms of compensation, so they are not well suited to predict outcomes in free-living adults. Our objective was to quantify the range of compensation in energy intake or expenditure observed in human randomized controlled trials (RCTs). We searched multiple databases (PubMed, CINAHL, SCOPUS, Cochrane, ProQuest, PsycInfo) up to 1 August 2012 for RCTs evaluating the effect of dietary and/or physical activity interventions on body weight/composition. subjects per treatment arm ≥5; ≥1 week intervention; a reported outcome of body weight/body composition; the intervention was either a prescribed amount of over- or underfeeding and/or supervised or monitored physical activity was prescribed; ≥80% compliance; and an objective method was used to verify compliance with the intervention (for example, observation and electronic monitoring). Data were independently extracted and analyzed by multiple reviewers with consensus reached by discussion. We compared observed weight change with predicted weight change using two models that predict weight change accounting only for metabolic compensation. Twenty-eight studies met inclusion criteria. Overfeeding studies indicate 96% less weight gain than expected if no compensation occurred. Dietary restriction and exercise studies may result in up to 12-44% and 55-64% less weight loss than expected, respectively, under an assumption of no behavioral compensation. Compensation is substantial even in high-compliance conditions, resulting in far less weight change than would be expected. The simple algorithm we report allows for more realistic predictions of intervention effects in free-living populations by accounting for the significant compensation that occurs.

Predicted thermal and stress environments in the vicinity of repository openings

International Nuclear Information System (INIS)

Bauer, S.J.; Hardy, M.P.; Lin, M.

1991-01-01

An understanding of the thermal and stress environment in the vicinity of repository openings is important for preclosure performance considerations and worker health and safety considerations for the proposed high-level radioactive waste repository at Yucca Mountain. This paper presents the results of two and three dimensional numerical analyses which have determined the thermal and stress environments for typical repository openings. In general, it is predicted that openings close to heat sources attain high temperatures and experience a significant stress increase. Openings away from heat sources experience more uniform temperature changes and experience a stress change which results in part from a far-field thermal loading

CNNcon: improved protein contact maps prediction using cascaded neural networks.

Directory of Open Access Journals (Sweden)

Wang Ding

Full Text Available BACKGROUNDS: Despite continuing progress in X-ray crystallography and high-field NMR spectroscopy for determination of three-dimensional protein structures, the number of unsolved and newly discovered sequences grows much faster than that of determined structures. Protein modeling methods can possibly bridge this huge sequence-structure gap with the development of computational science. A grand challenging problem is to predict three-dimensional protein structure from its primary structure (residues sequence alone. However, predicting residue contact maps is a crucial and promising intermediate step towards final three-dimensional structure prediction. Better predictions of local and non-local contacts between residues can transform protein sequence alignment to structure alignment, which can finally improve template based three-dimensional protein structure predictors greatly. METHODS: CNNcon, an improved multiple neural networks based contact map predictor using six sub-networks and one final cascade-network, was developed in this paper. Both the sub-networks and the final cascade-network were trained and tested with their corresponding data sets. While for testing, the target protein was first coded and then input to its corresponding sub-networks for prediction. After that, the intermediate results were input to the cascade-network to finish the final prediction. RESULTS: The CNNcon can accurately predict 58.86% in average of contacts at a distance cutoff of 8 Å for proteins with lengths ranging from 51 to 450. The comparison results show that the present method performs better than the compared state-of-the-art predictors. Particularly, the prediction accuracy keeps steady with the increase of protein sequence length. It indicates that the CNNcon overcomes the thin density problem, with which other current predictors have trouble. This advantage makes the method valuable to the prediction of long length proteins. As a result, the effective

Prediction of the impacts of climate changes on the stream flow of ...

African Journals Online (AJOL)

Abstract. Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on Ajali River watershed, Aguobu-Umumba, Ezeagu, Enugu State, Nigeria. The model was first used to simulate stream flow using observed data. After model run, parameterization, sensitivity analysis, the monthly ...

Longitudinal and concurrent dimensional changes of cellulose aggregate fibrils during sorption stages

International Nuclear Information System (INIS)

Lee, Jung Myoung; Pawlak, Joel J.; Heitmann, John A.

2010-01-01

Atomic force microscopy (AFM) studies of the dimensional changes of cellulose microfibril materials, called cellulose aggregate fibrils (approx. 100 μm x 3 μm x 300 nm), exposed to two distinct relative humidities of 80% and 23% for 24 h and then suddenly subjected to 50% RH and 23 deg. C show that the fibrils are responsive to the surrounding environments in a nonspecific fashion. AFM images (10 μm x 10 μm) of the individual straight cellulose aggregate fibrils were taken as a function of elapsed time during both desorption and adsorption of moisture. The longitudinal distance between discrete natural defects observed on the cellulose aggregate fibrils as well as the width, cross-sectional area, and height of the cellulose aggregate fibril were measured from the AFM images. The length of the cellulose aggregate fibrils was found to have reduced after exposure to either high or low relative humidity, and then placement in ambient conditions. Over time in ambient conditions, the cellulose aggregate fibrils progressively relaxed to their original length during both desorption and adsorption of moisture. However, the relaxation rate during adsorption was faster than that during desorption. The possible explanations for this phenomenon are discussed including the sample preparation method, volume conservation, entropy elasticity, and free volume theory. The changes in the width, height, and cross-sectional area are also discussed.

Lack of evidence for low-dimensional chaos in heart rate variability

DEFF Research Database (Denmark)

Kanters, J K; Holstein-Rathlou, N H; Agner, E

1994-01-01

INTRODUCTION: The term chaos is used to describe erratic or apparently random time-dependent behavior in deterministic systems. It has been suggested that the variability observed in the normal heart rate may be due to chaos, but this question has not been settled. METHODS AND RESULTS: Heart rate...... in the experimental data, but the prediction error as a function of the prediction length increased at a slower rate than characteristic of a low-dimensional chaotic system. CONCLUSION: There is no evidence for low-dimensional chaos in the time series of RR intervals from healthy human subjects. However, nonlinear...

Dimensional Changes of Alginate Dental Impression Materials-An Invitro Study.

Science.gov (United States)

Kulkarni, Manisha M; Thombare, Ram U

2015-08-01

Dentists are always looking ahead for more dimensionally stable material for accurate and successful fabrication of prosthesis in this competitive world. Arrival of newer materials and increased material market puts dentists in dilemma for selection of material. The study evaluated the effect of variations in time of pour and temperature on dimensional stability of three brands of commercially available alginates. Velplast, Marieflex & Zelgan alginate impression materials were evaluated by measuring dimensional accuracy of the master cast. A die was prepared and mounted on the apparatus for the ease of impression making. The prepared casts were categorized into five groups and made up of three brands of alginate impression material with variation in time of pour viz: immediate, 20&40 minutes interval and with varying temperature of 25(0)C, 30(0)C & 40(0)C. Impressions showed least distortion at varying degrees of temperature for 20 minutes, but the values obtained by storing of alginate impressions for 20 minutes at 30(0)C were found to be nearly accurate than the values obtained by storing of impression at 40(0)C. However, storing showed shrinkage of impressions. Marieflex showed better accuracy in comparison with other two materials. Maintenance of temperature and humidity play key role during storage & transport to prevent distortion. But the study suggests immediate pouring which will minimize the distortion. The manipulation instructions, temperature of mixing water, environment & water powder ratio also plays key role in minimizing the distortion.

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

Science.gov (United States)

Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha C.; Thompson, Jill; Zimmerman, Jess K.; Murphy, Lora

2018-01-01

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured inter-annual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including above-ground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.

Comparison between two-dimensional and three-dimensional quantitative coronary angiography for the prediction of functional severity in true bifurcation lesions: Insights from the randomized DK-CRUSH II, III, and IV trials.

Science.gov (United States)

Zhang, Yao-Jun; Zhu, Hao; Shi, Shun-Yi; Muramatsu, Takashi; Pan, Dao-Rong; Ye, Fei; Zhang, Jun-Jie; Tian, Nai-Liang; Bourantas, Christos V; Chen, Shao-Liang

2016-03-01

This study investigated the diagnostic accuracy of three-dimensional quantitative coronary angiography (3D-QCA) compared with conventional 2D-QCA for predicting functional severity assessed by fractional flow reserve (FFR) for true bifurcation lesions. Based on pooled data from the randomized DK-CRUSH II, III, and IV trials, we evaluated the patients with true bifurcation lesions who underwent coronary angiography together with functional evaluations using FFR in both the main vessel and the side branch. Off-line 2D- and 3D-QCA analyses were conducted using dedicated bifurcation QCA analysis software. Measurements of minimum lumen diameter (MLD), percentage diameter stenosis (% DS), and minimum lumen area (MLA) were compared between 2D- and 3D-QCA, and we evaluated their predictive values of functionally significant FFR. Ninety patients were eligible for enrollment in the present study. In the main vessel, MLA measured by 3D-QCA was the most accurate predictor of FFR <0.75 (C statistic 0.85, P < 0.001), while MLD measured by 2D-QCA was a similarly accurate predictor (C statistic 0.85, P < 0.001). In the side branch, the best metrics for predicting FFR <0.75 were % DS measured by 2D-QCA with a C statistic value of 0.91 (P < 0.001) and MLA measured by 3D-QCA with a C statistic value of 0.81 (P < 0.001). However, both 2D- and 3D-QCA metrics exhibited low accuracies for predicting FFR <0.75 in intermediate bifurcation lesions. 3D-QCA analysis for true bifurcation lesions did not improve the predictive accuracy of functionally significant FFR compared with 2D-QCA analysis. In lesions with intermediate stenosis, the diagnostic performance of both 2D- and 3D-QCA-derived measurements in differentiating functional severity is limited. © 2016 Wiley Periodicals, Inc.

A GIS-model for predicting the impact of climate change on shore erosion in hydroelectric reservoirs

International Nuclear Information System (INIS)

Penner, L.A.; Zimmer, T.A.M.; St Laurent, M.

2008-01-01

Shoreline erosion affects inland lakes and hydroelectric reservoirs in several ways. This poster described a vector-based geographic information system (GIS) model designed to predict changes in shore zone geometry, top-of-bluff recession, and eroded sediment volumes. The model was designed for use in Manitoba Hydro's reservoirs in northern Manitoba, and simulated near-shore downcutting and bank recession caused by wind-generated waves. Parameters for the model included deep water wave energy, and water level fluctuations. Effective wave energy was seen as a function of the water level fluctuation range, wave conditions, and near-shore slope. The model was validated by field monitoring studies that included repeated shore zone transect surveys and sediment coring studies. Results of the study showed that the model provides a systematic method of predicting potential changes in erosion associated with climatic change. The volume and mass of eroded sediment predicted for the different modelling scenarios will be used as input data for future sedimentation models. tabs., figs

On-line analysis of algae in water by discrete three-dimensional fluorescence spectroscopy.

Science.gov (United States)

Zhao, Nanjing; Zhang, Xiaoling; Yin, Gaofang; Yang, Ruifang; Hu, Li; Chen, Shuang; Liu, Jianguo; Liu, Wenqing

2018-03-19

In view of the problem of the on-line measurement of algae classification, a method of algae classification and concentration determination based on the discrete three-dimensional fluorescence spectra was studied in this work. The discrete three-dimensional fluorescence spectra of twelve common species of algae belonging to five categories were analyzed, the discrete three-dimensional standard spectra of five categories were built, and the recognition, classification and concentration prediction of algae categories were realized by the discrete three-dimensional fluorescence spectra coupled with non-negative weighted least squares linear regression analysis. The results show that similarities between discrete three-dimensional standard spectra of different categories were reduced and the accuracies of recognition, classification and concentration prediction of the algae categories were significantly improved. By comparing with that of the chlorophyll a fluorescence excitation spectra method, the recognition accuracy rate in pure samples by discrete three-dimensional fluorescence spectra is improved 1.38%, and the recovery rate and classification accuracy in pure diatom samples 34.1% and 46.8%, respectively; the recognition accuracy rate of mixed samples by discrete-three dimensional fluorescence spectra is enhanced by 26.1%, the recovery rate of mixed samples with Chlorophyta 37.8%, and the classification accuracy of mixed samples with diatoms 54.6%.

Technique for the measurement of dimensional changes of natural microfibril materials under variable humidity environments

International Nuclear Information System (INIS)

Lee, Jung Myoung; Heitmann, John A.; Pawlak, Joel J.

2007-01-01

An algorithm was developed to analyze the dimensions of line scan data of step-shaped disconitunities acquired with an atomic force microscope. The effect of a number of AFM parameters on the quantitative imaging of step features was discussed. Quantitiative imaging using AFM was shown to be very reproducible as five successive scans of a standard step height grating produced less than 3% variation in measured parameters. A cellulose microfibril, called cellulose aggregate fibril (CAF), with dimensions of ∼50,000 nm x 2000 nm x 300 nm derived from papermaking fibers was scanned under cyclic relative humdity conditions with the relative humidity starting at 50% then raising to 80% followed by a decrease in the relative humidity to 28%. Changes in the width of the CAF were weakly correlated with changes in the relative humdity, while changes in the height and area of the CAF were positively correlated with the relative humdity. The length of the CAF was negatively correlated with the given relative humdity cycle. These findings have significant implications in paper dimensional stability and the engineering of cellulose micro and nano-fiber composites

Can tail damage outbreaks in the pig be predicted by behavioural change?

Science.gov (United States)

Larsen, Mona Lilian Vestbjerg; Andersen, Heidi Mai-Lis; Pedersen, Lene Juul

2016-03-01

Tail biting, resulting in outbreaks of tail damage in pigs, is a multifactorial welfare and economic problem which is usually partly prevented through tail docking. According to European Union legislation, tail docking is not allowed on a routine basis; thus there is a need for alternative preventive methods. One strategy is the surveillance of the pigs' behaviour for known preceding indicators of tail damage, which makes it possible to predict a tail damage outbreak and prevent it in proper time. This review discusses the existing literature on behavioural changes observed prior to a tail damage outbreak. Behaviours found to change prior to an outbreak include increased activity level, increased performance of enrichment object manipulation, and a changed proportion of tail posture with more tails between the legs. Monitoring these types of behaviours is also discussed for the purpose of developing an automatic warning system for tail damage outbreaks, with activity level showing promising results for being monitored automatically. Encouraging results have been found so far for the development of an automatic warning system; however, there is a need for further investigation and development, starting with the description of the temporal development of the predictive behaviour in relation to tail damage outbreaks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Extinction maps toward the Milky Way bulge: Two-dimensional and three-dimensional tests with apogee

Energy Technology Data Exchange (ETDEWEB)

Schultheis, M. [Université de Nice Sophia-Antipolis, CNRS, Observatoire de Côte d' Azur, Laboratoire Lagrange, 06304 Nice Cedex 4 (France); Zasowski, G. [Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218 (United States); Allende Prieto, C. [Instituto de Astrofísica de Canarias, Calle Vía Láctea s/n, E-38205 La Laguna, Tenerife (Spain); Anders, F.; Chiappini, C. [Leibniz-Institut für Astrophysik Potsdam (AIP), D-14482 Potsdam (Germany); Beaton, R. L.; García Pérez, A. E.; Majewski, S. R. [Department of Astronomy, University of Virginia, Charlottesville, VA 22904 (United States); Beers, T. C. [National Optical Astronomy Observatory, Tucson, AZ 85719 (United States); Bizyaev, D. [Apache Point Observatory, Sunspot, NM 88349 (United States); Frinchaboy, P. M. [Department of Physics and Astronomy, Texas Christian University, TCU Box 298840, Fort Worth, TX 76129 (United States); Ge, J. [Astronomy Department, University of Florida, Gainesville, FL 32611 (United States); Hearty, F.; Schneider, D. P. [Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802 (United States); Holtzman, J. [New Mexico State University, Las Cruces, NM 88003 (United States); Muna, D. [Department of Astronomy, The Ohio State University, Columbus, OH 43210 (United States); Nidever, D. [Department of Astronomy, University of Michigan, Ann Arbor, MI 48109 (United States); Shetrone, M., E-mail: mathias.schultheis@oca.eu, E-mail: gail.zasowski@gmail.com [McDonald Observatory, The University of Texas at Austin, Austin, TX 78712 (United States)

2014-07-01

Galactic interstellar extinction maps are powerful and necessary tools for Milky Way structure and stellar population analyses, particularly toward the heavily reddened bulge and in the midplane. However, due to the difficulty of obtaining reliable extinction measures and distances for a large number of stars that are independent of these maps, tests of their accuracy and systematics have been limited. Our goal is to assess a variety of photometric stellar extinction estimates, including both two-dimensional and three-dimensional extinction maps, using independent extinction measures based on a large spectroscopic sample of stars toward the Milky Way bulge. We employ stellar atmospheric parameters derived from high-resolution H-band Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectra, combined with theoretical stellar isochrones, to calculate line-of-sight extinction and distances for a sample of more than 2400 giants toward the Milky Way bulge. We compare these extinction values to those predicted by individual near-IR and near+mid-IR stellar colors, two-dimensional bulge extinction maps, and three-dimensional extinction maps. The long baseline, near+mid-IR stellar colors are, on average, the most accurate predictors of the APOGEE extinction estimates, and the two-dimensional and three-dimensional extinction maps derived from different stellar populations along different sightlines show varying degrees of reliability. We present the results of all of the comparisons and discuss reasons for the observed discrepancies. We also demonstrate how the particular stellar atmospheric models adopted can have a strong impact on this type of analysis, and discuss related caveats.

Extinction maps toward the Milky Way bulge: Two-dimensional and three-dimensional tests with apogee

International Nuclear Information System (INIS)

Schultheis, M.; Zasowski, G.; Allende Prieto, C.; Anders, F.; Chiappini, C.; Beaton, R. L.; García Pérez, A. E.; Majewski, S. R.; Beers, T. C.; Bizyaev, D.; Frinchaboy, P. M.; Ge, J.; Hearty, F.; Schneider, D. P.; Holtzman, J.; Muna, D.; Nidever, D.; Shetrone, M.

2014-01-01

Galactic interstellar extinction maps are powerful and necessary tools for Milky Way structure and stellar population analyses, particularly toward the heavily reddened bulge and in the midplane. However, due to the difficulty of obtaining reliable extinction measures and distances for a large number of stars that are independent of these maps, tests of their accuracy and systematics have been limited. Our goal is to assess a variety of photometric stellar extinction estimates, including both two-dimensional and three-dimensional extinction maps, using independent extinction measures based on a large spectroscopic sample of stars toward the Milky Way bulge. We employ stellar atmospheric parameters derived from high-resolution H-band Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectra, combined with theoretical stellar isochrones, to calculate line-of-sight extinction and distances for a sample of more than 2400 giants toward the Milky Way bulge. We compare these extinction values to those predicted by individual near-IR and near+mid-IR stellar colors, two-dimensional bulge extinction maps, and three-dimensional extinction maps. The long baseline, near+mid-IR stellar colors are, on average, the most accurate predictors of the APOGEE extinction estimates, and the two-dimensional and three-dimensional extinction maps derived from different stellar populations along different sightlines show varying degrees of reliability. We present the results of all of the comparisons and discuss reasons for the observed discrepancies. We also demonstrate how the particular stellar atmospheric models adopted can have a strong impact on this type of analysis, and discuss related caveats.

Three-dimensional particle image velocimetry measurement technique

International Nuclear Information System (INIS)

Hassan, Y.A.; Seeley, C.H.; Henderson, J.A.; Schmidl, W.D.

2004-01-01

The experimental flow visualization tool, Particle Image Velocimetry (PIV), is being used to determine the velocity field in two-dimensional fluid flows. In the past few years, the technique has been improved to allow the capture of flow fields in three dimensions. This paper describes changes which were made to two existing two-dimensional tracking algorithms to enable them to track three-dimensional PIV data. Results of the tests performed on these three-dimensional routines with synthetic data are presented. Experimental data was also used to test the tracking algorithms. The test setup which was used to acquire the three-dimensional experimental data is described, along with the results from both of the tracking routines which were used to analyze the experimental data. (author)

Influence of the medium's dimensionality on defect-mediated turbulence.

Science.gov (United States)

St-Yves, Ghislain; Davidsen, Jörn

2015-03-01

Spatiotemporal chaos in oscillatory and excitable media is often characterized by the presence of phase singularities called defects. Understanding such defect-mediated turbulence and its dependence on the dimensionality of a given system is an important challenge in nonlinear dynamics. This is especially true in the context of ventricular fibrillation in the heart, where the importance of the thickness of the ventricular wall is contentious. Here, we study defect-mediated turbulence arising in two different regimes in a conceptual model of excitable media and investigate how the statistical character of the turbulence changes if the thickness of the medium is changed from (quasi-) two- dimensional to three dimensional. We find that the thickness of the medium does not have a significant influence in, far from onset, fully developed turbulence while there is a clear transition if the system is close to a spiral instability. We provide clear evidence that the observed transition and change in the mechanism that drives the turbulent behavior is purely a consequence of the dimensionality of the medium. Using filament tracking, we further show that the statistical properties in the three-dimensional medium are different from those in turbulent regimes arising from filament instabilities like the negative line tension instability. Simulations also show that the presence of this unique three-dimensional turbulent dynamics is not model specific.

Prediction of crack density and electrical resistance changes in indium tin oxide/polymer thin films under tensile loading

KAUST Repository

Mora Cordova, Angel

2014-06-11

We present unified predictions for the crack onset strain, evolution of crack density, and changes in electrical resistance in indium tin oxide/polymer thin films under tensile loading. We propose a damage mechanics model to quantify and predict such changes as an alternative to fracture mechanics formulations. Our predictions are obtained by assuming that there are no flaws at the onset of loading as opposed to the assumptions of fracture mechanics approaches. We calibrate the crack onset strain and the damage model based on experimental data reported in the literature. We predict crack density and changes in electrical resistance as a function of the damage induced in the films. We implement our model in the commercial finite element software ABAQUS using a user subroutine UMAT. We obtain fair to good agreement with experiments. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Predicted macroinvertebrate response to water diversion from a montane stream using two-dimensional hydrodynamic models and zero flow approximation

Science.gov (United States)

Holmquist, Jeffrey G.; Waddle, Terry J.

2013-01-01

We used two-dimensional hydrodynamic models for the assessment of water diversion effects on benthic macroinvertebrates and associated habitat in a montane stream in Yosemite National Park, Sierra Nevada Mountains, CA, USA. We sampled the macroinvertebrate assemblage via Surber sampling, recorded detailed measurements of bed topography and flow, and coupled a two-dimensional hydrodynamic model with macroinvertebrate indicators to assess habitat across a range of low flows in 2010 and representative past years. We also made zero flow approximations to assess response of fauna to extreme conditions. The fauna of this montane reach had a higher percentage of Ephemeroptera, Plecoptera, and Trichoptera (%EPT) than might be expected given the relatively low faunal diversity of the study reach. The modeled responses of wetted area and area-weighted macroinvertebrate metrics to decreasing discharge indicated precipitous declines in metrics as flows approached zero. Changes in area-weighted metrics closely approximated patterns observed for wetted area, i.e., area-weighted invertebrate metrics contributed relatively little additional information above that yielded by wetted area alone. Loss of habitat area in this montane stream appears to be a greater threat than reductions in velocity and depth or changes in substrate, and the modeled patterns observed across years support this conclusion. Our models suggest that step function losses of wetted area may begin when discharge in the Merced falls to 0.02 m3/s; proportionally reducing diversions when this threshold is reached will likely reduce impacts in low flow years.

Two-dimensional multiferroics in monolayer group IV monochalcogenides

Science.gov (United States)

Wang, Hua; Qian, Xiaofeng

2017-03-01

Low-dimensional multiferroic materials hold great promises in miniaturized device applications such as nanoscale transducers, actuators, sensors, photovoltaics, and nonvolatile memories. Here, using first-principles theory we predict that two-dimensional (2D) monolayer group IV monochalcogenides including GeS, GeSe, SnS, and SnSe are a class of 2D semiconducting multiferroics with giant strongly-coupled in-plane spontaneous ferroelectric polarization and spontaneous ferroelastic lattice strain that are thermodynamically stable at room temperature and beyond, and can be effectively modulated by elastic strain engineering. Their optical absorption spectra exhibit strong in-plane anisotropy with visible-spectrum excitonic gaps and sizable exciton binding energies, rendering the unique characteristics of low-dimensional semiconductors. More importantly, the predicted low domain wall energy and small migration barrier together with the coupled multiferroic order and anisotropic electronic structures suggest their great potentials for tunable multiferroic functional devices by manipulating external electrical, mechanical, and optical field to control the internal responses, and enable the development of four device concepts including 2D ferroelectric memory, 2D ferroelastic memory, and 2D ferroelastoelectric nonvolatile photonic memory as well as 2D ferroelectric excitonic photovoltaics.

Nonlinear model predictive control of a passenger vehicle for automated lane changes

NARCIS (Netherlands)

Acosta, A.F.; Marquez-Ruiz, A.; Espinosa, J.J.

2017-01-01

This article presents a nonlinear Model Predictive Control (MPC) for lane changes, based on a simplified Single Track Model (STM) of the vehicle. The STM includes the position of the vehicle in global coordinates as a state so that the position of the target lane can be specified to the MPC for

Prediction of hospital mortality by changes in the estimated glomerular filtration rate (eGFR).

LENUS (Irish Health Repository)

Berzan, E

2015-03-01

Deterioration of physiological or laboratory variables may provide important prognostic information. We have studied whether a change in estimated glomerular filtration rate (eGFR) value calculated using the (Modification of Diet in Renal Disease (MDRD) formula) over the hospital admission, would have predictive value. An analysis was performed on all emergency medical hospital episodes (N = 61964) admitted between 1 January 2002 and 31 December 2011. A stepwise logistic regression model examined the relationship between mortality and change in renal function from admission to discharge. The fully adjusted Odds Ratios (OR) for 5 classes of GFR deterioration showed a stepwise increased risk of 30-day death with OR\\'s of 1.42 (95% CI: 1.20, 1.68), 1.59 (1.27, 1.99), 2.71 (2.24, 3.27), 5.56 (4.54, 6.81) and 11.9 (9.0, 15.6) respectively. The change in eGFR during a clinical episode, following an emergency medical admission, powerfully predicts the outcome.

Tire Changes, Fresh Air, and Yellow Flags: Challenges in Predictive Analytics for Professional Racing.

Science.gov (United States)

Tulabandhula, Theja; Rudin, Cynthia

2014-06-01

Our goal is to design a prediction and decision system for real-time use during a professional car race. In designing a knowledge discovery process for racing, we faced several challenges that were overcome only when domain knowledge of racing was carefully infused within statistical modeling techniques. In this article, we describe how we leveraged expert knowledge of the domain to produce a real-time decision system for tire changes within a race. Our forecasts have the potential to impact how racing teams can optimize strategy by making tire-change decisions to benefit their rank position. Our work significantly expands previous research on sports analytics, as it is the only work on analytical methods for within-race prediction and decision making for professional car racing.

THE DEVELOPMENT AND USE OF A MODEL TO PREDICT SUSTAINABILITY OF CHANGE IN HEALTH CARE SETTINGS.

Science.gov (United States)

Molfenter, Todd; Ford, James H; Bhattacharya, Abhik

2011-01-01

Innovations adopted through organizational change initiatives are often not sustained leading to diminished quality, productivity, and consumer satisfaction. Research explaining variance in the use of adopted innovations in health care settings is sparse, suggesting the need for a theoretical model to guide research and practice. In this article, we describe the development of a hybrid conjoint decision theoretic model designed to predict the sustainability of organizational change in health care settings. An initial test of the model's predictive validity using expert scored hypothetic profiles resulted in an r-squared value of .77. The test of this model offers a theoretical base for future research on the sustainability of change in health care settings.

Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method.

Directory of Open Access Journals (Sweden)

Marharyta Petukh

2015-07-01

Full Text Available A new methodology termed Single Amino Acid Mutation based change in Binding free Energy (SAAMBE was developed to predict the changes of the binding free energy caused by mutations. The method utilizes 3D structures of the corresponding protein-protein complexes and takes advantage of both approaches: sequence- and structure-based methods. The method has two components: a MM/PBSA-based component, and an additional set of statistical terms delivered from statistical investigation of physico-chemical properties of protein complexes. While the approach is rigid body approach and does not explicitly consider plausible conformational changes caused by the binding, the effect of conformational changes, including changes away from binding interface, on electrostatics are mimicked with amino acid specific dielectric constants. This provides significant improvement of SAAMBE predictions as indicated by better match against experimentally determined binding free energy changes over 1300 mutations in 43 proteins. The final benchmarking resulted in a very good agreement with experimental data (correlation coefficient 0.624 while the algorithm being fast enough to allow for large-scale calculations (the average time is less than a minute per mutation.

Dimensional ranges and rolling efficiency in a tandem cold rolling mill

Energy Technology Data Exchange (ETDEWEB)

Larkiola, J.

1997-12-31

In this work, physical models and a neural network theory have been combined in order to predict the properties of a steel strip and to optimise the process parameters in cold rolling. The prediction of the deformation resistance of the material and the friction parameter is based on the physical model presented by Bland, Ford and Ellis and artificial neural network computing (ANN). The accuracy of these models has been tested and proved by using a large amount of the measured data. With the aid of these models it has been shown that (a) the small change to the relative reduction distribution can have a clear effect upon the rolling efficiency, (b) the dimensional ranges of the tandem cold roll mill can be determined and optimised and (c) the possibility to cold roll a new product of new width, strength or thickness can be determined and the parameters of the tandem cold rolling process can be optimised. (orig.) 43 refs.

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

International Nuclear Information System (INIS)

Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.; Chen, Xiao

2017-01-01

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. It relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.

Ensembles-based predictions of climate change impacts on bioclimatic zones in Northeast Asia

Science.gov (United States)

Choi, Y.; Jeon, S. W.; Lim, C. H.; Ryu, J.

2017-12-01

Biodiversity is rapidly declining globally and efforts are needed to mitigate this continually increasing loss of species. Clustering of areas with similar habitats can be used to prioritize protected areas and distribute resources for the conservation of species, selection of representative sample areas for research, and evaluation of impacts due to environmental changes. In this study, Northeast Asia (NEA) was classified into 14 bioclimatic zones using statistical techniques, which are correlation analysis and principal component analysis (PCA), and the iterative self-organizing data analysis technique algorithm (ISODATA). Based on these bioclimatic classification, we predicted shift of bioclimatic zones due to climate change. The input variables include the current climatic data (1960-1990) and the future climatic data of the HadGEM2-AO model (RCP 4.5(2050, 2070) and 8.5(2050, 2070)) provided by WorldClim. Using these data, multi-modeling methods including maximum likelihood classification, random forest, and species distribution modelling have been used to project the impact of climate change on the spatial distribution of bioclimatic zones within NEA. The results of various models were compared and analyzed by overlapping each result. As the result, significant changes in bioclimatic conditions can be expected throughout the NEA by 2050s and 2070s. The overall zones moved upward and some zones were predicted to disappear. This analysis provides the basis for understanding potential impacts of climate change on biodiversity and ecosystem. Also, this could be used more effectively to support decision making on climate change adaptation.

Forest processes and global environmental change: predicting the effects of individual and multiple stressors

Science.gov (United States)

John Aber; Ronald P. Neilson; Steve McNulty; James M. Lenihan; Dominque Bachelet; Raymond J. Drapek

2001-01-01

The purpose of this article is to review the state of prediction of forest ecosystem response to envisioned changes in the physical and chemical climate. These results are offered as one part of the forest sector analysis of the National Assessment of the Potential Consequences of Climate Variability and Change. This article has three sections. The first offers a very...

Prediction of Android and Gynoid Body Adiposity via a Three-dimensional Stereovision Body Imaging System and Dual-Energy X-ray Absorptiometry.

Science.gov (United States)

Lee, Jane J; Freeland-Graves, Jeanne H; Pepper, M Reese; Stanforth, Philip R; Xu, Bugao

2015-01-01

Current methods for measuring regional body fat are expensive and inconvenient compared to the relative cost-effectiveness and ease of use of a stereovision body imaging (SBI) system. The primary goal of this research is to develop prediction models for android and gynoid fat by body measurements assessed via SBI and dual-energy x-ray absorptiometry (DXA). Subsequently, mathematical equations for prediction of total and regional (trunk, leg) body adiposity were established via parameters measured by SBI and DXA. A total of 121 participants were randomly assigned into primary and cross-validation groups. Body measurements were obtained via traditional anthropometrics, SBI, and DXA. Multiple regression analysis was conducted to develop mathematical equations by demographics and SBI assessed body measurements as independent variables and body adiposity (fat mass and percentage fat) as dependent variables. The validity of the prediction models was evaluated by a split sample method and Bland-Altman analysis. The R(2) of the prediction equations for fat mass and percentage body fat were 93.2% and 76.4% for android and 91.4% and 66.5% for gynoid, respectively. The limits of agreement for the fat mass and percentage fat were -0.06 ± 0.87 kg and -0.11% ± 1.97% for android and -0.04 ± 1.58 kg and -0.19% ± 4.27% for gynoid. Prediction values for fat mass and percentage fat were 94.6% and 88.9% for total body, 93.9% and 71.0% for trunk, and 92.4% and 64.1% for leg, respectively. The three-dimensional (3D) SBI produces reliable parameters that can predict android and gynoid as well as total and regional (trunk, leg) fat mass.

Dimensional Stability of Two Polyvinyl Siloxane Impression Materials in Different Time Intervals

Directory of Open Access Journals (Sweden)

Aalaei Sh

2015-12-01

Full Text Available Statement of the Problem: Dental prosthesis is usually made indirectly; there- fore dimensional stability of the impression material is very important. Every few years, new impression materials with different manufacturers’ claims regarding their better properties are introduced to the dental markets which require more research to evaluate their true dimensional changes. Objectives: The aim of this study was to evaluate dimensional stability of additional silicone impression material (Panasil® and Affinis® in different time intervals. Materials and Methods: In this experimental study, using two additional silicones (Panasil® and Affinis®, we made sixty impressions of standard die in similar conditions of 23 °C and 59% relative humidity by a special tray. The die included three horizontal and two vertical lines that were parallel. The vertical line crossed the horizontal ones at a point that served as reference for measurement. All impressions were poured with high strength dental stone. The dimensions were measured by stereo-microscope by two examiners in three interval storage times (1, 24 and 168 hours.The data were statistically analyzed using t-test and ANOVA. Results: All of the stone casts were larger than the standard die. Dimensional changes of Panasil and Affinis were 0.07%, 0.24%, 0.27% and 0.02%, 0.07%, 0.16% after 1, 24 and 168 hours, respectively. Dimensional change for two impression materials wasn’t significant in the interval time, expect for Panasil after one week (p = 0.004. Conclusions: According to the limitations of this study, Affinis impressions were dimensionally more stable than Panasil ones, but it was not significant. Dimensional change of Panasil impression showed a statistically significant difference after one week. Dimensional changes of both impression materials were based on ADA standard limitation in all time intervals (< 0.5%; therefore, dimensional stability of this impression was accepted at least

Three-dimensional versus two-dimensional sonography of the temporomandibular joint in comparison to MRI

Energy Technology Data Exchange (ETDEWEB)

Landes, Constantin A. [Oral, Maxillofacial and Plastic Facial Surgery, Frankfurt University Medical Centre, Theodor-Stern-Kai 7, 60596 Frankfurt (Germany)]. E-mail: c.landes@lycos.com; Goral, Wojciech A. [Oral, Maxillofacial and Plastic Facial Surgery, Frankfurt University Medical Centre, Theodor-Stern-Kai 7, 60596 Frankfurt (Germany)]. E-mail: w.goral@gmx.de; Sader, Robert [Oral, Maxillofacial and Plastic Facial Surgery, Frankfurt University Medical Centre, Theodor-Stern-Kai 7, 60596 Frankfurt (Germany)]. E-mail: r.sader@em.uni-frankfurt.de; Mack, Martin G. [Department of Diagnostic and Interventional Radiology, Frankfurt University Medical Centre, Theodor-Stern-Kai 7, 60596 Frankfurt (Germany)]. E-mail: martinmack@arcor.de

2007-02-15

Aim: To compare clinical feasibility of static two-dimensional (2D) to three-dimensional (3D) sonography of the temporomandibular joint (TMJ) in assessment of disk dislocation and joint degeneration compared to magnetic resonance imaging (MRI). Method: Thirty-three patients, 66 TMJ were prospectively sonographed 2D and 3D (8-12.5 MHz step motor scan), in occlusion and maximum opening with a probe position parallel inferior to the zygomatic arch. Axial 2D images were judged independent from the 3D scans; 3D volumes were cut axial, sagittal, frontal and rotated in real-time. Disk position and joint degeneration were assessed and compared to a subsequent MRI examination. Results: The specific appearance of the disk was hypoechogenic overlying a hyperechogenic condyle in axial (2D) or sagittal and frontal (3D) viewing. Specificity of 2D sonography for disk dislocation was 63%, sensitivity 58%, accuracy 64%, positive predictive value 46%, negative predictive value 73%; for joint degeneration synonymously 59/68/61/38/83%. 3D sonography for disk displacement reached synonymously 68/60/69/51/76%, for joint degeneration 75/65/73/48/86%. 2D sonographic diagnoses of disk dislocation in the closed mouth position and of joint degeneration showed significantly different results from the expected values (MRI) in {chi} {sup 2} testing; 3D diagnoses of disk dislocation in closed mouth position, of joint degeneration, 2D and 3D diagnoses in open mouth position were nonsignificant. Conclusions: Acceptable was the overall negative predictive value, as specificity and accuracy for joint degeneration in 3D. 3D appears superior diagnosing disk dislocation in closed mouth position as for overall joint degeneration. Sensitivity, accuracy and positive predictive value will have to ameliorate with future equipment of higher resolution in real-time 2D and 3D, if sonographic screening shall be clinically applied prior to MRI.

An Overview of Multi-Dimensional Models of the Sacramento–San Joaquin Delta

Directory of Open Access Journals (Sweden)

Michael L. MacWilliams

2016-12-01

Full Text Available doi: https://doi.org/10.15447/sfews.2016v14iss4art2Over the past 15 years, the development and application of multi-dimensional hydrodynamic models in San Francisco Bay and the Sacramento–San Joaquin Delta has transformed our ability to analyze and understand the underlying physics of the system. Initial applications of three-dimensional models focused primarily on salt intrusion, and provided a valuable resource for investigating how sea level rise and levee failures in the Delta could influence water quality in the Delta under future conditions. However, multi-dimensional models have also provided significant insights into some of the fundamental biological relationships that have shaped our thinking about the system by exploring the relationship among X2, flow, fish abundance, and the low salinity zone. Through the coupling of multi-dimensional models with wind wave and sediment transport models, it has been possible to move beyond salinity to understand how large-scale changes to the system are likely to affect sediment dynamics, and to assess the potential effects on species that rely on turbidity for habitat. Lastly, the coupling of multi-dimensional hydrodynamic models with particle tracking models has led to advances in our thinking about residence time, the retention of food organisms in the estuary, the effect of south Delta exports on larval entrainment, and the pathways and behaviors of salmonids that travel through the Delta. This paper provides an overview of these recent advances and how they have increased our understanding of the distribution and movement of fish and food organisms. The applications presented serve as a guide to the current state of the science of Delta modeling and provide examples of how we can use multi-dimensional models to predict how future Delta conditions will affect both fish and water supply.

Three-dimensional quantitative structure-property relationship (3D-QSPR) models for prediction of thermodynamic properties of polychlorinated biphenyls (PCBs): enthalpy of vaporization.

Science.gov (United States)

Puri, Swati; Chickos, James S; Welsh, William J

2002-01-01

Three-dimensional Quantitative Structure-Property Relationship (QSPR) models have been derived using Comparative Molecular Field Analysis (CoMFA) to correlate the vaporization enthalpies of a representative set of polychlorinated biphenyls (PCBs) at 298.15 K with their CoMFA-calculated physicochemical properties. Various alignment schemes, such as inertial, as is, and atom fit, were employed in this study. The CoMFA models were also developed using different partial charge formalisms, namely, electrostatic potential (ESP) charges and Gasteiger-Marsili (GM) charges. The most predictive model for vaporization enthalpy (Delta(vap)H(m)(298.15 K)), with atom fit alignment and Gasteiger-Marsili charges, yielded r2 values 0.852 (cross-validated) and 0.996 (conventional). The vaporization enthalpies of PCBs increased with the number of chlorine atoms and were found to be larger for the meta- and para-substituted isomers. This model was used to predict Delta(vap)H(m)(298.15 K) of the entire set of 209 PCB congeners.

Climate change and predicting soil loss from rainfall

Science.gov (United States)

Kinnell, Peter

2017-04-01

Conceptually, rainfall has a certain capacity to cause soil loss from an eroding area while soil surfaces have a certain resistance to being eroded by rainfall. The terms "rainfall erosivity' and "soil erodibility" are frequently used to encapsulate the concept and in the Revised Universal Soil Loss Equation (RUSLE), the most widely used soil loss prediction equation in the world, average annual values of the R "erosivity" factor and the K "erodibility" factor provide a basis for accounting for variation in rainfall erosion associated with geographic variations of climate and soils. In many applications of RUSLE, R and K are considered to be independent but in reality they are not. In RUSLE2, provision has been made to take account of the fact that K values determined using soil physical factors have to be adjusted for variations in climate because runoff is not directly included as a factor in determining R. Also, the USLE event erosivity index EI30 is better related to accounting for event sediment concentration than event soil loss. While the USLE-M, a modification of the USLE which includes runoff as a factor in determining the event erosivity index provides better estimates of event soil loss when event runoff is known, runoff prediction provides a challenge to modelling event soil loss as climate changes

An experimental study: quantitatively evaluating the change of the content of collagen fibres in penis with two-dimensional ShearWave™ Elastography.

Science.gov (United States)

Qiao, X-H; Zhang, J-J; Gao, F; Li, F; Bai, M; Du, L-F; Xing, J-F

2017-06-01

The purpose of this study was to explore the value of two-dimensional ShearWave ™ Elastography (2D-SWE) on quantitatively evaluating the change of the content of collagen fibres in penis. Twenty male Sprague Dawley rats were divided into the pre-sexual maturity group (Group 1) and the sexual decline group (Group 2) according to age. The ultrafast ultrasound device Aixplorer ® (SuperSonic Imagine, Aix-en-Provence, France) was used for 2D-SWE imaging of penis, and the measurement index was shear wave stiffness (SWS). The immunohistochemistry was used to analyse the content of collagen fibres in penis, and the measurement index was positive area percentage (PAP). The differences of SWS between the two groups and PAP between the two groups were analysed. SWS of Group 1 and Group 2 was 10.18 ± 1.09 and 8.02 ± 1.34 kPa, and SWS of Group 2 was significantly lower than Group 1 (p penis measured with 2D-SWE would change significantly as well. Two-dimensional SWE can be used to quantitatively evaluate the change of the content of collagen fibres in penis. © 2016 Blackwell Verlag GmbH.

Change in attachment predicts change in emotion regulation particularly among 5-HTTLPR short-allele homozygotes.

Science.gov (United States)

Viddal, Kristine Rensvik; Berg-Nielsen, Turid Suzanne; Belsky, Jay; Wichstrøm, Lars

2017-07-01

In view of the theory that the attachment relationship provides a foundation for the development of emotion regulation, here, we evaluated (a) whether change in attachment security from 4 to 6 years predicts change in emotion regulation from 6 to 8 years and (b) whether 5-HTTLPR moderates this relation in a Norwegian community sample (n = 678, 99.7% Caucasian). Attachment was measured with the Manchester Child Attachment Story Task, and teachers completed the Emotion Regulation Checklist. Attachment security was modestly stable, with children becoming more secure over time. Regression analyses revealed that increased attachment security from 4 to 6 forecasted increases in emotion regulation from 6 to 8 and decreased attachment security forecasted decreases in emotion regulation. This effect was strongest among the 5-HTTLPR short-allele homozygotes and, according to competitive model fitting, in a differential-susceptibility manner. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

Science.gov (United States)

Lawrence N. Hudson; Joseph Wunderle M.; And Others

2016-01-01

The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to...

Has growth mixture modeling improved our understanding of how early change predicts psychotherapy outcome?

Science.gov (United States)

Koffmann, Andrew

2017-03-02

Early change in psychotherapy predicts outcome. Seven studies have used growth mixture modeling [GMM; Muthén, B. (2001). Second-generation structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class-latent growth modeling. In L. M. Collins & A. G. Sawyers (Eds.), New methods for the analysis of change (pp. 291-322). Washington, DC: American Psychological Association] to identify patient classes based on early change but have yielded conflicting results. Here, we review the earlier studies and apply GMM to a new data set. In a university-based training clinic, 251 patients were administered the Outcome Questionnaire-45 [Lambert, M. J., Hansen, N. B., Umphress, V., Lunnen, K., Okiishi, J., Burlingame, G., … Reisinger, C. W. (1996). Administration and scoring manual for the Outcome Questionnaire (OQ 45.2). Wilmington, DE: American Professional Credentialing Services] at each psychotherapy session. We used GMM to identify class structure based on change in the first six sessions and examined trajectories as predictors of outcome. The sample was best described as a single class. There was no evidence of autoregressive trends in the data. We achieved better fit to the data by permitting latent variables some degree of kurtosis, rather than to assume multivariate normality. Treatment outcome was predicted by the amount of early improvement, regardless of initial level of distress. The presence of sudden early gains or losses did not further improve outcome prediction. Early improvement is an easily computed, powerful predictor of psychotherapy outcome. The use of GMM to investigate the relationship between change and outcome is technically complex and computationally intensive. To date, it has not been particularly informative.

Withdrawal-Related Changes in Delay Discounting Predict Short-Term Smoking Abstinence.

Science.gov (United States)

Miglin, Rickie; Kable, Joseph W; Bowers, Maureen E; Ashare, Rebecca L

2017-06-01

Impulsive decision making is associated with smoking behavior and reflects preferences for smaller, immediate rewards and intolerance of temporal delays. Nicotine withdrawal may alter impulsive decision making and time perception. However, little is known about whether withdrawal-related changes in decision making and time perception predict smoking relapse. Forty-five smokers (14 female) completed two laboratory sessions, one following 24-hour abstinence and one smoking-as-usual (order counterbalanced; biochemically verified abstinence). During each visit, participants completed measures of time perception, decision making (ie, discount rates), craving, and withdrawal. Following the second laboratory session, subjects underwent a well-validated model of short-term abstinence (quit week) with small monetary incentives for each day of biochemically confirmed abstinence. Smokers significantly overestimated time during abstinence, compared to smoking-as-usual (p = .021), but there were no abstinence effects on discount rates (p = .6). During the quit week, subjects were abstinent for 3.5 days (SD = 2.15) and smoked a total of 12.9 cigarettes (SD = 15.8). Importantly, higher discount rates (ie, preferences for immediate rewards) during abstinence (abstinence minus smoking difference score) predicted greater number of days abstinent (p = .01) and fewer cigarettes smoked during the quit week (p = .02). Withdrawal-related change in time reproduction did not predict relapse (p = .2). These data suggest that individuals who have a greater preference for immediate rewards during abstinence (vs. smoking-as-usual) may be more successful at maintaining short-term abstinence when provided with frequent (eg, daily) versus less frequent incentive schedules (eg, 1 month). Abstinence-induced changes in decision making may be important for identifying smokers who may benefit from interventions that incentivize abstinence such as contingency management (CM). The present results

A Two Dimensional Prediction of Solar Cycle 25

Science.gov (United States)

Munoz-Jaramillo, A.; Martens, P. C.

2017-12-01

To this date solar cycle most cycle predictions have focused on the forecast of solar cycle amplitude and cycle bell-curve shape. However, recent intriguing observational results suggest that all solar cycles follow the same longitudinal path regardless of their amplitude, and have a very similar decay once they reach a sufficient level of maturity. Cast in the light of our current understanding, these results suggest that the toroidal fields inside the Sun are subject to a very high turbulent diffusivity (of the order of magnitude of mixing-length estimates), and their equatorward propagation is driven by a steady meridional flow. Assuming this is the case, we will revisit the relationship between the polar fields at minimum and the amplitude of the next cycle and deliver a new generation of polar-field based predictions that include the depth of the minimum, as well as the latitude and time of the first active regions of solar cycle 25.

The literary uses of high-dimensional space

Directory of Open Access Journals (Sweden)

Ted Underwood

2015-12-01

Full Text Available Debates over “Big Data” shed more heat than light in the humanities, because the term ascribes new importance to statistical methods without explaining how those methods have changed. What we badly need instead is a conversation about the substantive innovations that have made statistical modeling useful for disciplines where, in the past, it truly wasn’t. These innovations are partly technical, but more fundamentally expressed in what Leo Breiman calls a new “culture” of statistical modeling. Where 20th-century methods often required humanists to squeeze our unstructured texts, sounds, or images into some special-purpose data model, new methods can handle unstructured evidence more directly by modeling it in a high-dimensional space. This opens a range of research opportunities that humanists have barely begun to discuss. To date, topic modeling has received most attention, but in the long run, supervised predictive models may be even more important. I sketch their potential by describing how Jordan Sellers and I have begun to model poetic distinction in the long 19th century—revealing an arc of gradual change much longer than received literary histories would lead us to expect.

Predicting effects of environmental change on river inflows to ...

Science.gov (United States)

Estuarine river watersheds provide valued ecosystem services to their surrounding communities including drinking water, fish habitat, and regulation of estuarine water quality. However, the provisioning of these services can be affected by changes in the quantity and quality of river water, such as those caused by altered landscapes or shifting temperatures or precipitation. We used the ecohydrology model, VELMA, in the Trask River watershed to simulate the effects of environmental change scenarios on estuarine river inputs to Tillamook Bay (OR) estuary. The Trask River watershed is 453 km2 and contains extensive agriculture, silviculture, urban, and wetland areas. VELMA was parameterized using existing spatial datasets of elevation, soil type, land use, air temperature, precipitation, river flow, and water quality. Simulated land use change scenarios included alterations in the distribution of the nitrogen-fixing tree species Alnus rubra, and comparisons of varying timber harvest plans. Scenarios involving spatial and temporal shifts in air temperature and precipitation trends were also simulated. Our research demonstrates the utility of ecohydrology models such as VELMA to aid in watershed management decision-making. Model outputs of river water flow, temperature, and nutrient concentrations can be used to predict effects on drinking water quality, salmonid populations, and estuarine water quality. This modeling effort is part of a larger framework of

Three-dimensional echocardiographic assessment of the repaired mitral valve.

Science.gov (United States)

Maslow, Andrew; Mahmood, Feroze; Poppas, Athena; Singh, Arun

2014-02-01

This study examined the geometric changes of the mitral valve (MV) after repair using conventional and three-dimensional echocardiography. Prospective evaluation of consecutive patients undergoing mitral valve repair. Tertiary care university hospital. Fifty consecutive patients scheduled for elective repair of the mitral valve for regurgitant disease. Intraoperative transesophageal echocardiography. Assessments of valve area (MVA) were performed using two-dimensional planimetry (2D-Plan), pressure half-time (PHT), and three-dimensional planimetry (3D-Plan). In addition, the direction of ventricular inflow was assessed from the three-dimensional imaging. Good correlations (r = 0.83) and agreement (-0.08 +/- 0.43 cm(2)) were seen between the MVA measured with 3D-Plan and PHT, and were better than either compared to 2D-Plan. MVAs were smaller after repair of functional disease repaired with an annuloplasty ring. After repair, ventricular inflow was directed toward the lateral ventricular wall. Subgroup analysis showed that the change in inflow angle was not different after repair of functional disease (168 to 171 degrees) as compared to those presenting with degenerative disease (168 to 148 degrees; p<0.0001). Three-dimensional imaging provides caregivers with a unique ability to assess changes in valve function after mitral valve repair. Copyright © 2014 Elsevier Inc. All rights reserved.

A dimensional approach to assessing personality functioning: examining personality trait domains utilizing DSM-IV personality disorder criteria.

Science.gov (United States)

Christopher Fowler, J; Sharp, Carla; Kalpakci, Allison; Madan, Alok; Clapp, Joshua; Allen, Jon G; Christopher Frueh, B; Oldham, John M

2015-01-01

This study compared a dimensional, trait domain approach to characterizing personality pathology with the traditional polythetic approach with respect to their associations with interpersonal functioning and personality traits from the five factor model. Psychiatric inpatients (N=1476) were administered the Structured Clinical Interview for DSM-IV Axis II personality disorders. Dimensional representations of trait domains were derived from reorganizing DSM-IV criteria into personality trait domains from DSM-5 Alternative Model. Dimensional scores and personality disorder (PD) total criterion scores served as independent variables in predicting interpersonal profile clusters, as well as extraversion, agreeableness conscientiousness, neuroticism and openness from the five factor model traits. Trait domain scores and PD criteria totals were significantly correlated with submissive interpersonal style yet none proved significant in regression analyses. Avoidant and borderline PD total criteria were negatively associated with a normative interpersonal style. Combined trait domain of detachment and avoidant PD total criteria predicted a hostile/withdrawn interpersonal style. The trait domain of detachment was negatively associated with five factor traits of extroversion, whereas borderline PD total criteria were negatively associated with conscientiousness. Avoidant and borderline PD total criteria were positively associated with neuroticism. The cross-cutting dimensional approach provided useful information in predicting a hostile/withdrawn interpersonal style as well as extroversion. Importantly, PD criterion scores and dimensional trait scores combined to predict this interpersonal style providing support to the alternative model of personality diagnosis in DSM-5. Clinicians are encouraged to assess dimensions of personality traits as these are related to interpersonal problems frequently encountered in psychiatric settings. While potentially useful, the dimensional

Making predictions in a changing world-inference, uncertainty, and learning.

Science.gov (United States)

O'Reilly, Jill X

2013-01-01

To function effectively, brains need to make predictions about their environment based on past experience, i.e., they need to learn about their environment. The algorithms by which learning occurs are of interest to neuroscientists, both in their own right (because they exist in the brain) and as a tool to model participants' incomplete knowledge of task parameters and hence, to better understand their behavior. This review focusses on a particular challenge for learning algorithms-how to match the rate at which they learn to the rate of change in the environment, so that they use as much observed data as possible whilst disregarding irrelevant, old observations. To do this algorithms must evaluate whether the environment is changing. We discuss the concepts of likelihood, priors and transition functions, and how these relate to change detection. We review expected and estimation uncertainty, and how these relate to change detection and learning rate. Finally, we consider the neural correlates of uncertainty and learning. We argue that the neural correlates of uncertainty bear a resemblance to neural systems that are active when agents actively explore their environments, suggesting that the mechanisms by which the rate of learning is set may be subject to top down control (in circumstances when agents actively seek new information) as well as bottom up control (by observations that imply change in the environment).

Spin dynamics in a two-dimensional quantum gas

DEFF Research Database (Denmark)

Pedersen, Poul Lindholm; Gajdacz, Miroslav; Deuretzbacher, Frank

2014-01-01

We have investigated spin dynamics in a two-dimensional quantum gas. Through spin-changing collisions, two clouds with opposite spin orientations are spontaneously created in a Bose-Einstein condensate. After ballistic expansion, both clouds acquire ring-shaped density distributions with superimp......We have investigated spin dynamics in a two-dimensional quantum gas. Through spin-changing collisions, two clouds with opposite spin orientations are spontaneously created in a Bose-Einstein condensate. After ballistic expansion, both clouds acquire ring-shaped density distributions...

Cod Gadus morhua and climate change: processes, productivity and prediction

DEFF Research Database (Denmark)

Brander, Keith

2010-01-01

the causes. Investigation of cod Gadus morhua populations across the whole North Atlantic Ocean has shown large-scale patterns of change in productivity due to lower individual growth and condition, caused by large-scale climate forcing. If a population is being heavily exploited then a drop in productivity......Environmental factors act on individual fishes directly and indirectly. The direct effects on rates and behaviour can be studied experimentally and in the field, particularly with the advent of ever smarter tags for tracking fishes and their environment. Indirect effects due to changes in food......, predators, parasites and diseases are much more difficult to estimate and predict. Climate can affect all life-history stages through direct and indirect processes and although the consequences in terms of growth, survival and reproductive output can be monitored, it is often difficult to determine...

Radiation Dosimetry Using Three-Dimensional Optical Random Access Memories

International Nuclear Information System (INIS)

Moscovitch, M.

2001-01-01

The ability to determine particle type and energy plays an important role in the dosimetry of heavy charged particles (HCP) and neutrons. A new approach to radiation dosimetry is presented, which is shown to be capable of particle type and energy discrimination. This method is based on utilizing radiation induced changes in the digital information stored on three-dimensional optical random access memories (3D ORAM). 3D ORAM is a small cube (a few mm 3 ) composed of poly(methyl methacrylate) doped with a photochromic dye, and it was originally proposed as a memory device in high speed parallel computers. A Nd:YAG laser system is used to write and read binary information (bits) on the ORAM, which functions as a charged particle detector. Both the read and the write processes use two laser beams that simultaneously strike the material to cause a color change at their intersection (similar to the darkening of light-sensitive sunglasses when exposed to sunlight.) The laser produces color changes in the ORAM, which then reverts to the original color (''bit-flips'') at sites where energy is deposited from interaction with incident HCP or neutron-recoil protons. The feasibility of this approach was demonstrated both theoretically and experimentally. Calculations based on track structure theory (TST) predict that when HCP interact with the ORAM material, the local energy deposition is capable of inducing measurable ''bit-flips''. These predictions were recently confirmed experimentally using two types of ORAM systems, one based on spirobenzopyran and the other on anthracene, as the photochromic dyes

Radiation dosimetry using three-dimensional optical random access memories

International Nuclear Information System (INIS)

Moscovitch, M.; Phillips, G.W.; Cullum, B.M.; Mobley, J.; Bogard, J.S.; Emfietzoglou, D.; Vo-Dinh, T.

2002-01-01

The ability to determine particle type and energy plays an important role in the dosimetry of heavy charged particles (HCP) and neutrons. A new approach to radiation dosimetry is presented, which is shown to be capable of particle type and energy discrimination. This method is based on utilising radiation induced changes in the digital information stored on three-dimensional optical random access memories (3D ORAM). 3D ORAM is a small cube (a few mm 3 ) composed of poly(methyl methacrylate) doped with a photochromic dye, and it was originally proposed as a memory device in high speed parallel computers. A Nd:YAG laser system is used to write and read binary information (bits) on the ORAM, which functions as a charged particle detector. Both the read and the write processes use two laser beams that simultaneously strike the material to cause a colour change at their intersection (similar to the darkening of light-sensitive sunglasses when exposed to sunlight). The laser produces colour changes in the ORAM, which then reverts to the original colour ('bit-flips') at sites where energy is deposited from interaction with incident HCP or neutron-recoil protons. The feasibility of this approach was demonstrated both theoretically and experimentally. Calculations based on track structure theory predict that when HCP interact with the ORAM material, the local energy deposition is capable of inducing measurable 'bit-flips'. These predictions were recently confirmed experimentally using two types of ORAM systems, one based on spirobenzopyran and the other on anthracene, as the photochromic dyes. (author)

Predicting space climate change

Science.gov (United States)

Balcerak, Ernie

2011-10-01

Galactic cosmic rays and solar energetic particles can be hazardous to humans in space, damage spacecraft and satellites, pose threats to aircraft electronics, and expose aircrew and passengers to radiation. A new study shows that these threats are likely to increase in coming years as the Sun approaches the end of the period of high solar activity known as “grand solar maximum,” which has persisted through the past several decades. High solar activity can help protect the Earth by repelling incoming galactic cosmic rays. Understanding the past record can help scientists predict future conditions. Barnard et al. analyzed a 9300-year record of galactic cosmic ray and solar activity based on cosmogenic isotopes in ice cores as well as on neutron monitor data. They used this to predict future variations in galactic cosmic ray flux, near-Earth interplanetary magnetic field, sunspot number, and probability of large solar energetic particle events. The researchers found that the risk of space weather radiation events will likely increase noticeably over the next century compared with recent decades and that lower solar activity will lead to increased galactic cosmic ray levels. (Geophysical Research Letters, doi:10.1029/2011GL048489, 2011)

Can positional MRI predict dynamic changes in the medial plantar arch?

DEFF Research Database (Denmark)

Johannsen, Finn E; Hansen, Philip; Stallknecht, Sandra

2016-01-01

BACKGROUND: Positional MRI (pMRI) allows for three-dimensional visual assessment of navicular position. In this exploratory pilot study pMRI was validated against a stretch sensor device, which measures movement of the medial plantar arch. We hypothesized that a combined pMRI measure incorporating...... and c) standing position with addition of 10 % body weight during static loading of the foot. Stretch sensor measurements were also performed during barefoot walking. RESULTS: The total change in navicular position measured by pMRI was 10.3 mm (CI: 7.0 to 13.5 mm). No further displacement occurred when.......08). CONCLUSIONS: Total navicular bone displacements determined by pMRI showed concurrent validity with stretch sensor measurements but only so under static loading conditions. Although assessment of total navicular displacement by combining concomitant vertical and medial navicular bone movements would appear...

Predictive accuracy of changes in transvaginal sonographic cervical length over time for preterm birth: a systematic review and metaanalysis.

Science.gov (United States)

Conde-Agudelo, Agustin; Romero, Roberto

2015-12-01

To determine the accuracy of changes in transvaginal sonographic cervical length over time in predicting preterm birth in women with singleton and twin gestations. PubMed, Embase, Cinahl, Lilacs, and Medion (all from inception to June 30, 2015), bibliographies, Google scholar, and conference proceedings. Cohort or cross-sectional studies reporting on the predictive accuracy for preterm birth of changes in cervical length over time. Two reviewers independently selected studies, assessed the risk of bias, and extracted the data. Summary receiver-operating characteristic curves, pooled sensitivities and specificities, and summary likelihood ratios were generated. Fourteen studies met the inclusion criteria, of which 7 provided data on singleton gestations (3374 women) and 8 on twin gestations (1024 women). Among women with singleton gestations, the shortening of cervical length over time had a low predictive accuracy for preterm birth at predictive accuracy for preterm birth at predictive accuracies for preterm birth of cervical length shortening over time and the single initial and/or final cervical length measurement in 8 of 11 studies that provided data for making these comparisons. In the largest and highest-quality study, a single measurement of cervical length obtained at 24 or 28 weeks of gestation was significantly more predictive of preterm birth than any decrease in cervical length between these gestational ages. Change in transvaginal sonographic cervical length over time is not a clinically useful test to predict preterm birth in women with singleton or twin gestations. A single cervical length measurement obtained between 18 and 24 weeks of gestation appears to be a better test to predict preterm birth than changes in cervical length over time. Published by Elsevier Inc.

Caregiver Responsiveness to the Family Bereavement Program: What predicts responsiveness? What does responsiveness predict?

OpenAIRE

Schoenfelder, Erin N.; Sandler, Irwin N.; Millsap, Roger E.; Wolchik, Sharlene A.; Berkel, Cady; Ayers, Timothy S.

2013-01-01

The study developed a multi-dimensional measure to assess participant responsiveness to a preventive intervention, and applied this measure to study how participant baseline characteristics predict responsiveness and how responsiveness predicts program outcomes. The study was conducted with caregivers who participated in the parenting-focused component of the Family Bereavement Program (FBP), a prevention program for families that have experienced parental death. The sample consisted of 89 ca...

Is Personality Fixed? Personality Changes as Much as "Variable" Economic Factors and More Strongly Predicts Changes to Life Satisfaction

Science.gov (United States)

Boyce, Christopher J.; Wood, Alex M.; Powdthavee, Nattavudh

2013-01-01

Personality is the strongest and most consistent cross-sectional predictor of high subjective well-being. Less predictive economic factors, such as higher income or improved job status, are often the focus of applied subjective well-being research due to a perception that they can change whereas personality cannot. As such there has been limited…

Approaches to predicting potential impacts of climate change on forest disease: An example with Armillaria root disease

Science.gov (United States)

Ned B. Klopfenstein; Mee-Sook Kim; John W. Hanna; Bryce A. Richardson; John E. Lundquist

2011-01-01

Climate change will likely have dramatic impacts on forest health because many forest trees could become maladapted to climate. Furthermore, climate change will have additional impacts on forest health through changes in the distribution and severity of forest disease. Methods are needed to predict the influence of climate change on forest disease so that appropriate...

Relativity and the dimensionality of the world

CERN Document Server

2007-01-01

All physicists would agree that one of the most fundamental problems of the 21st century physics is the dimensionality of the world. In the four-dimensional world of Minkowski (or Minkowski spacetime) the most challenging problem is the nature of the temporal dimension. In Minkowski spacetime it is merely one of the four dimensions, which means that it is entirely given like the other three spacial dimensions. If the temporal dimension were not given in its entirety and only one constantly changing moment of it existed, Minkowski spacetime would be reduced to the ordinary three-dimensional space. But if the physical world, represented by Minkowski spacetime, is indeed four-dimensional with time being the fourth dimension, then such a world is drastically different from its image based on our perceptions. Minkowski four-dimensional world is a block Universe, a frozen world in which nothing happens since all moments of time are given ‘at once', which means that physical bodies are four-dimensional worldtubes ...

Knowledge-based prediction of three-dimensional dose distributions for external beam radiotherapy

International Nuclear Information System (INIS)

Shiraishi, Satomi; Moore, Kevin L.

2016-01-01

Purpose: To demonstrate knowledge-based 3D dose prediction for external beam radiotherapy. Methods: Using previously treated plans as training data, an artificial neural network (ANN) was trained to predict a dose matrix based on patient-specific geometric and planning parameters, such as the closest distance (r) to planning target volume (PTV) and organ-at-risks (OARs). Twenty-three prostate and 43 stereotactic radiosurgery/radiotherapy (SRS/SRT) cases with at least one nearby OAR were studied. All were planned with volumetric-modulated arc therapy to prescription doses of 81 Gy for prostate and 12–30 Gy for SRS. Using these clinically approved plans, ANNs were trained to predict dose matrix and the predictive accuracy was evaluated using the dose difference between the clinical plan and prediction, δD = D clin − D pred . The mean (〈δD r 〉), standard deviation (σ δD r ), and their interquartile range (IQR) for the training plans were evaluated at a 2–3 mm interval from the PTV boundary (r PTV ) to assess prediction bias and precision. Initially, unfiltered models which were trained using all plans in the cohorts were created for each treatment site. The models predict approximately the average quality of OAR sparing. Emphasizing a subset of plans that exhibited superior to the average OAR sparing during training, refined models were created to predict high-quality rectum sparing for prostate and brainstem sparing for SRS. Using the refined model, potentially suboptimal plans were identified where the model predicted further sparing of the OARs was achievable. Replans were performed to test if the OAR sparing could be improved as predicted by the model. Results: The refined models demonstrated highly accurate dose distribution prediction. For prostate cases, the average prediction bias for all voxels irrespective of organ delineation ranged from −1% to 0% with maximum IQR of 3% over r PTV ∈ [ − 6, 30] mm. The average prediction error was less

Predicting changes in cardiac myocyte contractility during early drug discovery with in vitro assays

International Nuclear Information System (INIS)

Morton, M.J.; Armstrong, D.; Abi Gerges, N.; Bridgland-Taylor, M.; Pollard, C.E.; Bowes, J.; Valentin, J.-P.

2014-01-01

Cardiovascular-related adverse drug effects are a major concern for the pharmaceutical industry. Activity of an investigational drug at the L-type calcium channel could manifest in a number of ways, including changes in cardiac contractility. The aim of this study was to define which of the two assay technologies – radioligand-binding or automated electrophysiology – was most predictive of contractility effects in an in vitro myocyte contractility assay. The activity of reference and proprietary compounds at the L-type calcium channel was measured by radioligand-binding assays, conventional patch-clamp, automated electrophysiology, and by measurement of contractility in canine isolated cardiac myocytes. Activity in the radioligand-binding assay at the L-type Ca channel phenylalkylamine binding site was most predictive of an inotropic effect in the canine cardiac myocyte assay. The sensitivity was 73%, specificity 83% and predictivity 78%. The radioligand-binding assay may be run at a single test concentration and potency estimated. The least predictive assay was automated electrophysiology which showed a significant bias when compared with other assay formats. Given the importance of the L-type calcium channel, not just in cardiac function, but also in other organ systems, a screening strategy emerges whereby single concentration ligand-binding can be performed early in the discovery process with sufficient predictivity, throughput and turnaround time to influence chemical design and address a significant safety-related liability, at relatively low cost. - Highlights: • The L-type calcium channel is a significant safety liability during drug discovery. • Radioligand-binding to the L-type calcium channel can be measured in vitro. • The assay can be run at a single test concentration as part of a screening cascade. • This measurement is highly predictive of changes in cardiac myocyte contractility

Predicting changes in cardiac myocyte contractility during early drug discovery with in vitro assays

Energy Technology Data Exchange (ETDEWEB)

Morton, M.J., E-mail: michael.morton@astrazeneca.com [Discovery Sciences, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom); Armstrong, D.; Abi Gerges, N. [Drug Safety and Metabolism, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom); Bridgland-Taylor, M. [Discovery Sciences, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom); Pollard, C.E.; Bowes, J.; Valentin, J.-P. [Drug Safety and Metabolism, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom)

2014-09-01

Cardiovascular-related adverse drug effects are a major concern for the pharmaceutical industry. Activity of an investigational drug at the L-type calcium channel could manifest in a number of ways, including changes in cardiac contractility. The aim of this study was to define which of the two assay technologies – radioligand-binding or automated electrophysiology – was most predictive of contractility effects in an in vitro myocyte contractility assay. The activity of reference and proprietary compounds at the L-type calcium channel was measured by radioligand-binding assays, conventional patch-clamp, automated electrophysiology, and by measurement of contractility in canine isolated cardiac myocytes. Activity in the radioligand-binding assay at the L-type Ca channel phenylalkylamine binding site was most predictive of an inotropic effect in the canine cardiac myocyte assay. The sensitivity was 73%, specificity 83% and predictivity 78%. The radioligand-binding assay may be run at a single test concentration and potency estimated. The least predictive assay was automated electrophysiology which showed a significant bias when compared with other assay formats. Given the importance of the L-type calcium channel, not just in cardiac function, but also in other organ systems, a screening strategy emerges whereby single concentration ligand-binding can be performed early in the discovery process with sufficient predictivity, throughput and turnaround time to influence chemical design and address a significant safety-related liability, at relatively low cost. - Highlights: • The L-type calcium channel is a significant safety liability during drug discovery. • Radioligand-binding to the L-type calcium channel can be measured in vitro. • The assay can be run at a single test concentration as part of a screening cascade. • This measurement is highly predictive of changes in cardiac myocyte contractility.

Progress of radiotherapy by three-dimensional treatment planning

International Nuclear Information System (INIS)

Imada, Hajime; Nomoto, Satoshi; Takahashi, Hiroyuki; Nakata, Hajime

1998-01-01

The recent progress of three-dimensional radiation treatment planning was reviewed. And clinical cases such as lung cancer and breast cancer are introduced. In the University of Occupational and Development Health, the treatment system FOCUS which is made up of CT simulator and linac was used mainly. Three-dimensional treatment planning was carried for about 90% of 330 patients who underwent radiotherapy for one year. The target becomes to be accurate and dose distribution with all CT slices in radiation field can be confirmed by using three-dimensional radiation treatment planning apparatus. High dose irradiation localized to tumor part is possible. Relations between total dose and volume of normal tissue and/or tumor can be estimated numerically and easily by DVH. A prediction of indication and affection became possible by this procedure. In conclusion, generalization of three-dimensional radiation treatment planning will bring progress of more effective radiotherapy with less adverse reaction. (K.H.). 21 refs

Predictive zero-dimensional combustion model for DI diesel engine feed-forward control

International Nuclear Information System (INIS)

Catania, Andrea Emilio; Finesso, Roberto; Spessa, Ezio

2011-01-01

Highlights: → Zero-dimensional low-throughput combustion model for real-time control in diesel engine applications. → Feed-forward control of MFB50, p max and IMEP in both conventional and PCCI combustion modes. → Capability of resolving the contribution to HRR of each injection pulse in multiple injection schedule. → Ignition delay and model parameters estimated through physically consistent and easy-to-tune correlations. - Abstract: An innovative zero-dimensional predictive combustion model has been developed for the estimation of HRR (heat release rate) and in-cylinder pressure traces. This model has been assessed and applied to conventional and PCCI (premixed charge compression ignition) DI diesel engines for model-based feed-forward control purposes. The injection rate profile is calculated on the basis of the injected fuel quantities and on the injection parameters, such as SOI (start of injection), ET (energizing time), and DT (dwell time), taking the injector NOD (nozzle opening delay) and NCD (nozzle closure delay) into account. The injection rate profile in turn allows the released chemical energy Q ch to be estimated. The approach starts from the assumption that, at each time instant, the HRR is proportional to the energy associated with the accumulated fuel mass in the combustion chamber. The main novelties of the proposed approach consist of the method that is adopted to estimate the fuel ignition delay and of injection rate splitting for HRR estimation. The procedure allows an accurate calculation to be made of the different combustion parameters that are important for engine calibration, such as SOC (start of combustion) and MFB50 (50% of fuel mass fraction burned angle). On the basis of an estimation of the fuel released chemical energy, of the heat globally exchanged from the charge with the walls and of the energy associated with the fuel evaporation, the charge net energy is calculated, for a subsequent evaluation of the in

Changes in Mitral Annular Geometry after Aortic Valve Replacement: A Three-Dimensional Transesophageal Echocardiographic Study

Science.gov (United States)

Mahmood, Feroze; Warraich, Haider J.; Gorman, Joseph H.; Gorman, Robert C.; Chen, Tzong-Huei; Panzica, Peter; Maslow, Andrew; Khabbaz, Kamal

2014-01-01

Background and aim of the study Intraoperative real-time three-dimensional transesophageal echocardiography (RT-3D TEE) was used to examine the geometric changes that occur in the mitral annulus immediately after aortic valve replacement (AVR). Methods A total of 35 patients undergoing elective surgical AVR under cardiopulmonary bypass was enrolled in the study. Intraoperative RT-3D TEE was used prospectively to acquire volumetric echocardiographic datasets immediately before and after AVR. The 3D echocardiographic data were analyzed offline using TomTec® Mitral Valve Assessment software to assess changes in specific mitral annular geometric parameters. Results Datasets were successfully acquired and analyzed for all patients. A significant reduction was noted in the mitral annular area (-16.3%, p <0.001), circumference (-8.9% p <0.001) and the anteroposterior (-6.3%, p = 0.019) and anterolateral-posteromedial (-10.5%, p <0.001) diameters. A greater reduction was noted in the anterior annulus length compared to the posterior annulus length (10.5% versus 62%, p <0.05) after AVR. No significant change was seen in the non-planarity angle, coaptation depth, and closure line length. During the period of data acquisition before and after AVR, no significant change was noted in the central venous pressure or left ventricular end-diastolic diameter. Conclusion The mitral annulus undergoes significant geometric changes immediately after AVR Notably, a 16.3% reduction was observed in the mitral annular area. The anterior annulus underwent a greater reduction in length compared to the posterior annulus, which suggested the existence of a mechanical compression by the prosthetic valve. PMID:23409347

Rapid prediction of multi-dimensional NMR data sets

International Nuclear Information System (INIS)

Gradmann, Sabine; Ader, Christian; Heinrich, Ines; Nand, Deepak; Dittmann, Marc; Cukkemane, Abhishek; Dijk, Marc van; Bonvin, Alexandre M. J. J.; Engelhard, Martin; Baldus, Marc

2012-01-01

We present a computational environment for Fast Analysis of multidimensional NMR DAta Sets (FANDAS) that allows assembling multidimensional data sets from a variety of input parameters and facilitates comparing and modifying such “in silico” data sets during the various stages of the NMR data analysis. The input parameters can vary from (partial) NMR assignments directly obtained from experiments to values retrieved from in silico prediction programs. The resulting predicted data sets enable a rapid evaluation of sample labeling in light of spectral resolution and structural content, using standard NMR software such as Sparky. In addition, direct comparison to experimental data sets can be used to validate NMR assignments, distinguish different molecular components, refine structural models or other parameters derived from NMR data. The method is demonstrated in the context of solid-state NMR data obtained for the cyclic nucleotide binding domain of a bacterial cyclic nucleotide-gated channel and on membrane-embedded sensory rhodopsin II. FANDAS is freely available as web portal under WeNMR (http://www.wenmr.eu/services/FANDAShttp://www.wenmr.eu/services/FANDAS).

Rapid prediction of multi-dimensional NMR data sets

Energy Technology Data Exchange (ETDEWEB)

Gradmann, Sabine; Ader, Christian [Utrecht University, Faculty of Science, Bijvoet Center for Biomolecular Research (Netherlands); Heinrich, Ines [Max Planck Institute for Molecular Physiology, Department of Physical Biochemistry (Germany); Nand, Deepak [Utrecht University, Faculty of Science, Bijvoet Center for Biomolecular Research (Netherlands); Dittmann, Marc [Max Planck Institute for Molecular Physiology, Department of Physical Biochemistry (Germany); Cukkemane, Abhishek; Dijk, Marc van; Bonvin, Alexandre M. J. J. [Utrecht University, Faculty of Science, Bijvoet Center for Biomolecular Research (Netherlands); Engelhard, Martin [Max Planck Institute for Molecular Physiology, Department of Physical Biochemistry (Germany); Baldus, Marc, E-mail: m.baldus@uu.nl [Utrecht University, Faculty of Science, Bijvoet Center for Biomolecular Research (Netherlands)

2012-12-15

We present a computational environment for Fast Analysis of multidimensional NMR DAta Sets (FANDAS) that allows assembling multidimensional data sets from a variety of input parameters and facilitates comparing and modifying such 'in silico' data sets during the various stages of the NMR data analysis. The input parameters can vary from (partial) NMR assignments directly obtained from experiments to values retrieved from in silico prediction programs. The resulting predicted data sets enable a rapid evaluation of sample labeling in light of spectral resolution and structural content, using standard NMR software such as Sparky. In addition, direct comparison to experimental data sets can be used to validate NMR assignments, distinguish different molecular components, refine structural models or other parameters derived from NMR data. The method is demonstrated in the context of solid-state NMR data obtained for the cyclic nucleotide binding domain of a bacterial cyclic nucleotide-gated channel and on membrane-embedded sensory rhodopsin II. FANDAS is freely available as web portal under WeNMR (http://www.wenmr.eu/services/FANDAShttp://www.wenmr.eu/services/FANDAS).

Two-Dimensional SiO2/VO2 Photonic Crystals with Statically Visible and Dynamically Infrared Modulated for Smart Window Deployment.

Science.gov (United States)

Ke, Yujie; Balin, Igal; Wang, Ning; Lu, Qi; Tok, Alfred Iing Yoong; White, Timothy J; Magdassi, Shlomo; Abdulhalim, Ibrahim; Long, Yi

2016-12-07

Two-dimensional (2D) photonic structures, widely used for generating photonic band gaps (PBG) in a variety of materials, are for the first time integrated with the temperature-dependent phase change of vanadium dioxide (VO 2 ). VO 2 possesses thermochromic properties, whose potential remains unrealized due to an undesirable yellow-brown color. Here, a SiO 2 /VO 2 core/shell 2D photonic crystal is demonstrated to exhibit static visible light tunability and dynamic near-infrared (NIR) modulation. Three-dimensional (3D) finite difference time domain (FDTD) simulations predict that the transmittance can be tuned across the visible spectrum, while maintaining good solar regulation efficiency (ΔT sol = 11.0%) and high solar transmittance (T lum = 49.6%). Experiments show that the color changes of VO 2 films are accompanied by NIR modulation. This work presents a novel way to manipulate VO 2 photonic structures to modulate light transmission as a function of wavelength at different temperatures.

Three-dimensional anatomy of equine incisors: tooth length, enamel cover and age related changes

Science.gov (United States)

2013-01-01

Background Equine incisors are subjected to continuous occlusal wear causing multiple, age related changes of the extragingival crown. It is assumed that the occlusal wear is compensated by continued tooth elongation at the apical ends of the teeth. In this study, μCT-datasets offered the opportunity to analyze the three-dimensional appearance of the extra- and intraalveolar parts of the enamel containing dental crown as well as of the enamel-free dental root. Multiple morphometric measurements elucidated age related, morphological changes within the intraalveolar part of the incisors. Results Equine incisors possess a unique enamel cover displaying large indentations on the mesial and distal sides. After eruption tooth elongation at the apical end outbalances occlusal wear for two to four years resulting in increasing incisor length in this period of time. Remarkably, this maximum length is maintained for about ten years, up to a tooth age of 13 to 15 years post eruption. Variances in the total length of individual teeth are related to different Triadan positions (central-, middle- and corner incisors) as well as to the upper and lower arcades. Conclusion Equine incisors are able to fully compensate occlusal wear for a limited period of time. However, after this ability ceases, it is expected that a diminished intraalveolar tooth length will cause massive changes in periodontal biomechanics. The time point of these morphodynamic and biomechanical changes (13 to 15 years post eruption) occurs in coincidence with the onset of a recently described destructive disease of equine incisor (equine odontoclastic tooth resorption and hypercementosis) in aged horses. However, further biomechanical, cell biological and microbiological investigations are needed to elucidate a correlation between age related changes of incisor morphology and this disease. PMID:24321365

Mathematical modeling of left ventricular dimensional changes in mice during aging

Directory of Open Access Journals (Sweden)

Yang Tianyi

2012-12-01

Full Text Available Abstract Cardiac aging is characterized by diastolic dysfunction of the left ventricle (LV, which is due in part to increased LV wall stiffness. In the diastolic phase, myocytes are relaxed and extracellular matrix (ECM is a critical determinant to the changes of LV wall stiffness. To evaluate the effects of ECM composition on cardiac aging, we developed a mathematical model to predict LV dimension and wall stiffness changes in aging mice by integrating mechanical laws and our experimental results. We measured LV dimension, wall thickness, LV mass, and collagen content for wild type (WT C57/BL6J mice of ages ranging from 7.3 months to those of 34.0 months. The model was established using the thick wall theory and stretch-induced tissue growth to an isotropic and homogeneous elastic composite with mixed constituents. The initial conditions of the simulation were set based on the data from the young mice. Matlab simulations of this mathematical model demonstrated that the model captured the major features of LV remodeling with age and closely approximated experimental results. Specifically, the temporal progression of the LV interior and exterior dimensions demonstrated the same trend and order-of-magnitude change as our experimental results. In conclusion, we present here a validated mathematical model of cardiac aging that applies the thick-wall theory and stretch-induced tissue growth to LV remodeling with age.

Fast core prediction simulator for load follow control

International Nuclear Information System (INIS)

Yim, Man Sung; Lee, Sang Hoon; Lee, Un Chul

1990-01-01

An operator-assisting system for the reactor core control under power changing operating condition was developed. The system is consisted of core simulator routine and Xenon and Iodine initial condition generation routine. The initial condition generation routine, without exactly knowing the core status, is capable of providing accurate number densities and axial offset conditions of Xenon and Iodine after several hours of predictor- corrector calculations using the plant instrumentation signals of power level and power axial offset. The core simulator routine, even with the two node core model, gives equivalently accurate results as the one-dimensional model for the core behaviour simulation under power changing condition and can provide proper control strategies for load follow operation. The core simulator can also be used by the operator to develop remedial actions to restore the distorted power distribution by using its prediction capability

Proarrhythmia risk prediction using human induced pluripotent stem cell-derived cardiomyocytes.

Science.gov (United States)

Yamazaki, Daiju; Kitaguchi, Takashi; Ishimura, Masakazu; Taniguchi, Tomohiko; Yamanishi, Atsuhiro; Saji, Daisuke; Takahashi, Etsushi; Oguchi, Masao; Moriyama, Yuta; Maeda, Sanae; Miyamoto, Kaori; Morimura, Kaoru; Ohnaka, Hiroki; Tashibu, Hiroyuki; Sekino, Yuko; Miyamoto, Norimasa; Kanda, Yasunari

2018-04-01

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are expected to become a useful tool for proarrhythmia risk prediction in the non-clinical drug development phase. Several features including electrophysiological properties, ion channel expression profile and drug responses were investigated using commercially available hiPSC-CMs, such as iCell-CMs and Cor.4U-CMs. Although drug-induced arrhythmia has been extensively examined by microelectrode array (MEA) assays in iCell-CMs, it has not been fully understood an availability of Cor.4U-CMs for proarrhythmia risk. Here, we evaluated the predictivity of proarrhythmia risk using Cor.4U-CMs. MEA assay revealed linear regression between inter-spike interval and field potential duration (FPD). The hERG inhibitor E-4031 induced reverse-use dependent FPD prolongation. We next evaluated the proarrhythmia risk prediction by a two-dimensional map, which we have previously proposed. We determined the relative torsade de pointes risk score, based on the extent of FPD with Fridericia's correction (FPDcF) change and early afterdepolarization occurrence, and calculated the margins normalized to free effective therapeutic plasma concentrations. The drugs were classified into three risk groups using the two-dimensional map. This risk-categorization system showed high concordance with the torsadogenic information obtained by a public database CredibleMeds. Taken together, these results indicate that Cor.4U-CMs can be used for drug-induced proarrhythmia risk prediction. Copyright © 2018 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Prediction of two-dimensional diluted magnetic semiconductors: Doped monolayer MoS2 systems

KAUST Repository

Cheng, Yingchun

2013-03-05

Using first-principles calculations, we propose a two-dimensional diluted magnetic semiconductor: monolayer MoS2 doped by transition metals. Doping of transition metal atoms from the IIIB to VIB groups results in nonmagnetic states, since the number of valence electrons is smaller or equal to that of Mo. Doping of atoms from the VIIB to IIB groups becomes energetically less and less favorable. Magnetism is observed for Mn, Fe, Co, Zn, Cd, and Hg doping, while for the other dopants from these groups it is suppressed by Jahn-Teller distortions. Analysis of the binding energies and magnetic properties indicates that (Mo,X)S2 (X=Mn, Fe, Co, and Zn) are promising systems to explore two-dimensional diluted magnetic semiconductors.

Categorical and dimensional study of the predictive factors of the development of a psychotrauma in victims of car accidents.

Science.gov (United States)

Berna, G; Vaiva, G; Ducrocq, F; Duhem, S; Nandrino, J L

2012-01-01

This study aimed to evaluate the predictive factors of the emergence of complete PTSD and subsyndromal PTSD (defined as individuals exposed to a traumatic event with at least one psychopathological impact, such as hyperarousal, avoidance or persistent re-experiencing) following a motor vehicle accident (MVA). We recruited 155 adult MVA patients, physically injured and admitted to trauma service, over two years. In the week following the accident, patients were asked to complete questionnaires assessing their social situation (sex, age, marital and employment status, prior MVA or trauma), comorbidity (MINI), distress (PDI) and dissociation (PDEQ) experienced during and immediately after the trauma. An evaluation using the CAPS was conducted six months after the trauma to assess a possible PTSD. At six months, 25.8% of the participants developed subsyndromal symptoms and 7.74% developed complete PTSD. The three symptoms that best discriminated the groups were dysphoric emotion, perceived life threat and dissociation. Logistic regression results showed that the strongest predictor of PTSD was the perceived life threat. In addition, a dimensional approach to the results revealed significant correlations between (1) peritraumatic distress and persistent re-experiencing or hyperarousal and (2) dissociation score and avoidance strategy. The presence of a prior traumatic event reinforces avoidance strategies. Our results stress that peritraumatic factors (especially the perception of a life threat) are good predictors of PTSD development. A dimensional perspective allows better identification of psychological complications following an MVA. Copyright © 2011 Elsevier Ltd. All rights reserved.

Predicting protein folding rate change upon point mutation using residue-level coevolutionary information.

Science.gov (United States)

Mallik, Saurav; Das, Smita; Kundu, Sudip

2016-01-01

Change in folding kinetics of globular proteins upon point mutation is crucial to a wide spectrum of biological research, such as protein misfolding, toxicity, and aggregations. Here we seek to address whether residue-level coevolutionary information of globular proteins can be informative to folding rate changes upon point mutations. Generating residue-level coevolutionary networks of globular proteins, we analyze three parameters: relative coevolution order (rCEO), network density (ND), and characteristic path length (CPL). A point mutation is considered to be equivalent to a node deletion of this network and respective percentage changes in rCEO, ND, CPL are found linearly correlated (0.84, 0.73, and -0.61, respectively) with experimental folding rate changes. The three parameters predict the folding rate change upon a point mutation with 0.031, 0.045, and 0.059 standard errors, respectively. © 2015 Wiley Periodicals, Inc.

Knowledge-based prediction of three-dimensional dose distributions for external beam radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Shiraishi, Satomi; Moore, Kevin L., E-mail: kevinmoore@ucsd.edu [Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California 92093 (United States)

2016-01-15

Purpose: To demonstrate knowledge-based 3D dose prediction for external beam radiotherapy. Methods: Using previously treated plans as training data, an artificial neural network (ANN) was trained to predict a dose matrix based on patient-specific geometric and planning parameters, such as the closest distance (r) to planning target volume (PTV) and organ-at-risks (OARs). Twenty-three prostate and 43 stereotactic radiosurgery/radiotherapy (SRS/SRT) cases with at least one nearby OAR were studied. All were planned with volumetric-modulated arc therapy to prescription doses of 81 Gy for prostate and 12–30 Gy for SRS. Using these clinically approved plans, ANNs were trained to predict dose matrix and the predictive accuracy was evaluated using the dose difference between the clinical plan and prediction, δD = D{sub clin} − D{sub pred}. The mean (〈δD{sub r}〉), standard deviation (σ{sub δD{sub r}}), and their interquartile range (IQR) for the training plans were evaluated at a 2–3 mm interval from the PTV boundary (r{sub PTV}) to assess prediction bias and precision. Initially, unfiltered models which were trained using all plans in the cohorts were created for each treatment site. The models predict approximately the average quality of OAR sparing. Emphasizing a subset of plans that exhibited superior to the average OAR sparing during training, refined models were created to predict high-quality rectum sparing for prostate and brainstem sparing for SRS. Using the refined model, potentially suboptimal plans were identified where the model predicted further sparing of the OARs was achievable. Replans were performed to test if the OAR sparing could be improved as predicted by the model. Results: The refined models demonstrated highly accurate dose distribution prediction. For prostate cases, the average prediction bias for all voxels irrespective of organ delineation ranged from −1% to 0% with maximum IQR of 3% over r{sub PTV} ∈ [ − 6, 30] mm. The