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Sample records for accurately predict ice

  1. Arctic Sea Ice Predictability and the Sea Ice Prediction Network

    NASA Astrophysics Data System (ADS)

    Wiggins, H. V.; Stroeve, J. C.

    2014-12-01

    Drastic reductions in Arctic sea ice cover have increased the demand for Arctic sea ice predictions by a range of stakeholders, including local communities, resource managers, industry and the public. The science of sea-ice prediction has been challenged to keep up with these developments. Efforts such as the SEARCH Sea Ice Outlook (SIO; http://www.arcus.org/sipn/sea-ice-outlook) and the Sea Ice for Walrus Outlook have provided a forum for the international sea-ice prediction and observing community to explore and compare different approaches. The SIO, originally organized by the Study of Environmental Change (SEARCH), is now managed by the new Sea Ice Prediction Network (SIPN), which is building a collaborative network of scientists and stakeholders to improve arctic sea ice prediction. The SIO synthesizes predictions from a variety of methods, including heuristic and from a statistical and/or dynamical model. In a recent study, SIO data from 2008 to 2013 were analyzed. The analysis revealed that in some years the predictions were very successful, in other years they were not. Years that were anomalous compared to the long-term trend have proven more difficult to predict, regardless of which method was employed. This year, in response to feedback from users and contributors to the SIO, several enhancements have been made to the SIO reports. One is to encourage contributors to provide spatial probability maps of sea ice cover in September and the first day each location becomes ice-free; these are an example of subseasonal to seasonal, local-scale predictions. Another enhancement is a separate analysis of the modeling contributions. In the June 2014 SIO report, 10 of 28 outlooks were produced from models that explicitly simulate sea ice from dynamic-thermodynamic sea ice models. Half of the models included fully-coupled (atmosphere, ice, and ocean) models that additionally employ data assimilation. Both of these subsets (models and coupled models with data

  2. DRA/NASA/ONERA Collaboration on Icing Research. Part 2; Prediction of Airfoil Ice Accretion

    NASA Technical Reports Server (NTRS)

    Wright, William B.; Gent, R. W.; Guffond, Didier

    1997-01-01

    This report presents results from a joint study by DRA, NASA, and ONERA for the purpose of comparing, improving, and validating the aircraft icing computer codes developed by each agency. These codes are of three kinds: (1) water droplet trajectory prediction, (2) ice accretion modeling, and (3) transient electrothermal deicer analysis. In this joint study, the agencies compared their code predictions with each other and with experimental results. These comparison exercises were published in three technical reports, each with joint authorship. DRA published and had first authorship of Part 1 - Droplet Trajectory Calculations, NASA of Part 2 - Ice Accretion Prediction, and ONERA of Part 3 - Electrothermal Deicer Analysis. The results cover work done during the period from August 1986 to late 1991. As a result, all of the information in this report is dated. Where necessary, current information is provided to show the direction of current research. In this present report on ice accretion, each agency predicted ice shapes on two dimensional airfoils under icing conditions for which experimental ice shapes were available. In general, all three codes did a reasonable job of predicting the measured ice shapes. For any given experimental condition, one of the three codes predicted the general ice features (i.e., shape, impingement limits, mass of ice) somewhat better than did the other two. However, no single code consistently did better than the other two over the full range of conditions examined, which included rime, mixed, and glaze ice conditions. In several of the cases, DRA showed that the user's knowledge of icing can significantly improve the accuracy of the code prediction. Rime ice predictions were reasonably accurate and consistent among the codes, because droplets freeze on impact and the freezing model is simple. Glaze ice predictions were less accurate and less consistent among the codes, because the freezing model is more complex and is critically

  3. Analytical ice shape predictions for flight in natural icing conditions

    NASA Technical Reports Server (NTRS)

    Berkowitz, Brian M.; Riley, James T.

    1988-01-01

    LEWICE is an analytical ice prediction code that has been evaluated against icing tunnel data, but on a more limited basis against flight data. Ice shapes predicted by LEWICE is compared with experimental ice shapes accreted on the NASA Lewis Icing Research Aircraft. The flight data selected for comparison includes liquid water content recorded using a hot wire device and droplet distribution data from a laser spectrometer; the ice shape is recorded using stereo photography. The main findings are as follows: (1) An equivalent sand grain roughness correlation different from that used for LEWICE tunnel comparisons must be employed to obtain satisfactory results for flight; (2) Using this correlation and making no other changes in the code, the comparisons to ice shapes accreted in flight are in general as good as the comparisons to ice shapes accreted in the tunnel (as in the case of tunnel ice shapes, agreement is least reliable for large glaze ice shapes at high angles of attack); (3) In some cases comparisons can be somewhat improved by utilizing the code so as to take account of the variation of parameters such as liquid water content, which may vary significantly in flight.

  4. Predicting ice accretion and alleviating galloping on overhead power lines

    NASA Astrophysics Data System (ADS)

    Lu, Mingliang

    2002-04-01

    Both the static and dynamic effects of an ice storm on an overhead power line are investigated fairly comprehensively in this thesis. To determine the static, extreme ice load as well as the combined ice and wind load, a systematic procedure is established based on extensive freezing rain experiments and a Monte Carlo simulation. On the other hand, a dynamic effect---galloping---is examined quite extensively with the objective of better understanding its behavior. A novel add-on device---the hybrid nutation damper (HND)---is proposed to control galloping. Its effectiveness is assessed numerically by using a modified, 3DOF based, galloping software. The present investigations lead to the following findings. (i) Goodwin's simple theoretical model surprisingly predicts, quite accurately, the temporally changing weight of not only a dry ice growth but also a wet ice growth for a fixed, unheated conductor sample. (ii) The maximum ice loading may vary significantly over a power line's planned lifetime because of the randomness of an ice storm and its characteristics as well as the uncertainty involved in identifying the extreme probability distribution of the ice loading. Consequently, backup protection is presently essential for a power line in an ice prone area. (iii) A conductor's torsional flexibility does not appear to affect the growth of the accreted ice weight but it modifies the ice shape significantly. (iv) Three representative ice shapes (a crescent, D-like and icicle pendant) can initiate galloping so that galloping may occur in any icing condition. (v) A noticeable swingback or twist appears to develop only when their respective natural frequencies coincide with the plunge's natural frequency. (vi) A hydraulic jump is the major source of energy dissipation in a nutation damper. A properly induced rotation can significantly enhance a nutation damper's performance. (vii) A hybrid nutation damper has been demonstrated to be a promising means of alleviating

  5. Sea Ice Prediction Has Easy and Difficult Years

    NASA Technical Reports Server (NTRS)

    Hamilton, Lawrence C.; Bitz, Cecilia M.; Blanchard-Wrigglesworth, Edward; Cutler, Matthew; Kay, Jennifer; Meier, Walter N.; Stroeve, Julienne; Wiggins, Helen

    2014-01-01

    Arctic sea ice follows an annual cycle, reaching its low point in September each year. The extent of sea ice remaining at this low point has been trending downwards for decades as the Arctic warms. Around the long-term downward trend, however, there is significant variation in the minimum extent from one year to the next. Accurate forecasts of yearly conditions would have great value to Arctic residents, shipping companies, and other stakeholders and are the subject of much current research. Since 2008 the Sea Ice Outlook (SIO) (http://www.arcus.org/search-program/seaiceoutlook) organized by the Study of Environmental Arctic Change (SEARCH) (http://www.arcus.org/search-program) has invited predictions of the September Arctic sea ice minimum extent, which are contributed from the Arctic research community. Individual predictions, based on a variety of approaches, are solicited in three cycles each year in early June, July, and August. (SEARCH 2013).

  6. Predicting Accumulations of Ice on Aerodynamic Surfaces

    NASA Technical Reports Server (NTRS)

    Bidwell, Colin; Potapczuk, Mark; Addy, Gene; Wright, William

    2003-01-01

    LEWICE is a computer program that predicts the accumulation of ice on two-dimensional aerodynamic surfaces under conditions representative of the flight of an aircraft through an icing cloud. The software first calculates the airflow surrounding the body of interest, then uses the airflow to compute the trajectories of water droplets that impinge on the surface of the body. The droplet trajectories are also used to compute impingement limits and local collection efficiencies, which are used in subsequent ice-growth calculations and are also useful for designing systems to protect against icing. Next, the software predicts the shape of accumulating ice by modeling transfers of mass and energy in small control volumes. The foregoing computations are repeated over several computational time steps until the total icing exposure time is reached. Results of computations by LEWICE have been compared with an extensive database of measured ice shapes obtained from experiments, and have been shown to closely approximate those shapes under most conditions of interest to the aviation community.

  7. Gravel transport by ice in a subarctic river from accurate laser scanning

    NASA Astrophysics Data System (ADS)

    Lotsari, Eliisa; Wang, Yunsheng; Kaartinen, Harri; Jaakkola, Anttoni; Kukko, Antero; Vaaja, Matti; Hyyppä, Hannu; Hyyppä, Juha; Alho, Petteri

    2015-10-01

    For decades the importance of ice and the effects of cold-region processes on river channel morphology have been discussed, with a general consensus as to their importance emerging only recently. River ice cover, anchor ice, frazil ice, and ice jams may not only scour the channel bed and banks but also pick up, transport, and deposit fine sediments and gravels during winter, especially during the spring ice breakup period. However, knowledge of the interactions between coarse sediment transport and ice processes remains insufficient, particularly in rockier river reaches, with a lack of accurate and sufficiently extensive data hindering their quantification. The aim of this study was to quantify and analyse the impact of river ice on gravel transport in a subarctic river during one winter via the acquisition of laser scanning data for the river channel and ice surface. Terrestrial and mobile laser scanning were performed in 2012-2013 on the Tana River in northern Finland. Both of these techniques are considered accurate and applicable for detecting elevation and volumetric changes in river bed, defining gravel clast sizes, and detecting the movement of individual clasts. More importantly, ice surface, thickness, and decay during spring were also captured via laser scanning. In the winter of 2012-2013, a period characterised by an absence of ice jams and mid-winter ice-decay periods, with spring ice breakup discharges close to average yearly conditions, ice had the most significant role, greater than that of flowing water, in erosion and transport of coarse sediment from the channel bed and gently sloping banks. Changes in river bed elevation and volume were recorded throughout the study site, and erosion predominated. In addition to broader scale erosion, the movement of single clasts up to 2 m in size occurred. However, the observed overall channel change patterns did not coincide with the areas of fastest ice decay. The obtained results could also be applied to

  8. Hounsfield unit density accurately predicts ESWL success.

    PubMed

    Magnuson, William J; Tomera, Kevin M; Lance, Raymond S

    2005-01-01

    Extracorporeal shockwave lithotripsy (ESWL) is a commonly used non-invasive treatment for urolithiasis. Helical CT scans provide much better and detailed imaging of the patient with urolithiasis including the ability to measure density of urinary stones. In this study we tested the hypothesis that density of urinary calculi as measured by CT can predict successful ESWL treatment. 198 patients were treated at Alaska Urological Associates with ESWL between January 2002 and April 2004. Of these 101 met study inclusion with accessible CT scans and stones ranging from 5-15 mm. Follow-up imaging demonstrated stone freedom in 74.2%. The overall mean Houndsfield density value for stone-free compared to residual stone groups were significantly different ( 93.61 vs 122.80 p < 0.0001). We determined by receiver operator curve (ROC) that HDV of 93 or less carries a 90% or better chance of stone freedom following ESWL for upper tract calculi between 5-15mm.

  9. A parallel high-order accurate finite element nonlinear Stokes ice sheet model and benchmark experiments

    SciTech Connect

    Leng, Wei; Ju, Lili; Gunzburger, Max; Price, Stephen; Ringler, Todd

    2012-01-01

    The numerical modeling of glacier and ice sheet evolution is a subject of growing interest, in part because of the potential for models to inform estimates of global sea level change. This paper focuses on the development of a numerical model that determines the velocity and pressure fields within an ice sheet. Our numerical model features a high-fidelity mathematical model involving the nonlinear Stokes system and combinations of no-sliding and sliding basal boundary conditions, high-order accurate finite element discretizations based on variable resolution grids, and highly scalable parallel solution strategies, all of which contribute to a numerical model that can achieve accurate velocity and pressure approximations in a highly efficient manner. We demonstrate the accuracy and efficiency of our model by analytical solution tests, established ice sheet benchmark experiments, and comparisons with other well-established ice sheet models.

  10. Impact of sea ice initialisation on sea ice and atmosphere prediction skill on seasonal timescales

    NASA Astrophysics Data System (ADS)

    Guemas, Virginie; Chevallier, Matthieu; Deque, Michel; Bellprat, Omar; Doblas-Reyes, Francisco; Fuckar, Neven-Stjepan

    2016-04-01

    We present a robust assessment of the impact of sea ice initialisation from observations on the sea ice and atmosphere prediction skill. We ran two ensemble seasonal prediction experiments from 1979 to 2012: one using the highest possible quality for sea ice initial conditions and another where sea ice is initialized from a climatology, with two forecast systems. During the freezing season in the Arctic Ocean, sea ice forecasts become skilful with sea ice initialization until three to five months ahead, thanks to the memory held by sea ice thickness. During the melting season in both the Arctic and Antarctic Oceans, sea ice forecasts are skilful for seven and two months respectively with negligible differences between the two experiments, the memory being held by the ocean heat content. A weak impact on the atmosphere prediction skill is obtained.

  11. Impact of sea ice initialization on sea ice and atmosphere prediction skill on seasonal timescales

    NASA Astrophysics Data System (ADS)

    Guemas, V.; Chevallier, M.; Déqué, M.; Bellprat, O.; Doblas-Reyes, F.

    2016-04-01

    We present a robust assessment of the impact of sea ice initialization from reconstructions of the real state on the sea ice and atmosphere prediction skill. We ran two ensemble seasonal prediction experiments from 1979 to 2012 : one using realistic sea ice initial conditions and another where sea ice is initialized from a climatology, with two forecast systems. During the melting season in the Arctic Ocean, sea ice forecasts become skilful with sea ice initialization until 3-5 months ahead, thanks to the memory held by sea ice thickness. During the freezing season in both the Arctic and Antarctic Oceans, sea ice forecasts are skilful for 7 and 2 months, respectively, with negligible differences between the two experiments, the memory being held by the ocean heat content. A weak impact on the atmosphere prediction skill is obtained.

  12. Off-Ice Anaerobic Power Does Not Predict On-Ice Repeated Shift Performance in Hockey.

    PubMed

    Peterson, Ben J; Fitzgerald, John S; Dietz, Calvin C; Ziegler, Kevin S; Baker, Sarah E; Snyder, Eric M

    2016-09-01

    Peterson, BJ, Fitzgerald, JS, Dietz, CC, Ziegler, KS, Baker, SE, and Snyder, EM. Off-ice anaerobic power does not predict on-ice repeated shift performance in hockey. J Strength Cond Res 30(9): 2375-2381, 2016-Anaerobic power is a significant predictor of acceleration and top speed in team sport athletes. Historically, these findings have been applied to ice hockey although recent research has brought their validity for this sport into question. As ice hockey emphasizes the ability to repeatedly produce power, single bout anaerobic power tests should be examined to determine their ability to predict on-ice performance. We tested whether conventional off-ice anaerobic power tests could predict on-ice acceleration, top speed, and repeated shift performance. Forty-five hockey players, aged 18-24 years, completed anthropometric, off-ice, and on-ice tests. Anthropometric and off-ice testing included height, weight, body composition, vertical jump, and Wingate tests. On-ice testing consisted of acceleration, top speed, and repeated shift fatigue tests. Vertical jump (VJ) (r = -0.42; r = -0.58), Wingate relative peak power (WRPP) (r = -0.32; r = -0.43), and relative mean power (WRMP) (r = -0.34; r = -0.48) were significantly correlated (p ≤ 0.05) to on-ice acceleration and top speed, respectively. Conversely, none of the off-ice tests correlated with on-ice repeated shift performance, as measured by first gate, second gate, or total course fatigue; VJ (r = 0.06; r = 0.13; r = 0.09), WRPP (r = 0.06; r = 0.14; r = 0.10), or WRMP (r = -0.10; r = -0.01; r = -0.01). Although conventional off-ice anaerobic power tests predict single bout on-ice acceleration and top speed, they neither predict the repeated shift ability of the player, nor are good markers for performance in ice hockey.

  13. The Effect of Excess Snow on Sea Ice in a Global Ice-Ocean Prediction System

    NASA Astrophysics Data System (ADS)

    Winter, B.; Bélair, S.; Lemieux, J. F.

    2014-12-01

    Snow cover on sea ice acts as a thermal insulator, greatly reducing the upward heat flux from the ocean through the ice, specifically through thin ice. The treatment of snow in the CICE sea ice model does not include the effects of blowing snow, thereby leading to an unrealistically thick snow layer on the ice. We investigate the consequences of this excess snow for the upward heat fluxes throughout the year, and how this impacts forecast accuracy in a global ice-ocean prediction model (GIOPS). First results will be presented, and computationally efficient solutions will be discussed.

  14. Transmission line icing prediction based on DWT feature extraction

    NASA Astrophysics Data System (ADS)

    Ma, T. N.; Niu, D. X.; Huang, Y. L.

    2016-08-01

    Transmission line icing prediction is the premise of ensuring the safe operation of the network as well as the very important basis for the prevention of freezing disasters. In order to improve the prediction accuracy of icing, a transmission line icing prediction model based on discrete wavelet transform (DWT) feature extraction was built. In this method, a group of high and low frequency signals were obtained by DWT decomposition, and were fitted and predicted by using partial least squares regression model (PLS) and wavelet least square support vector model (w-LSSVM). Finally, the final result of the icing prediction was obtained by adding the predicted values of the high and low frequency signals. The results showed that the method is effective and feasible in the prediction of transmission line icing.

  15. On the Accurate Prediction of CME Arrival At the Earth

    NASA Astrophysics Data System (ADS)

    Zhang, Jie; Hess, Phillip

    2016-07-01

    We will discuss relevant issues regarding the accurate prediction of CME arrival at the Earth, from both observational and theoretical points of view. In particular, we clarify the importance of separating the study of CME ejecta from the ejecta-driven shock in interplanetary CMEs (ICMEs). For a number of CME-ICME events well observed by SOHO/LASCO, STEREO-A and STEREO-B, we carry out the 3-D measurements by superimposing geometries onto both the ejecta and sheath separately. These measurements are then used to constrain a Drag-Based Model, which is improved through a modification of including height dependence of the drag coefficient into the model. Combining all these factors allows us to create predictions for both fronts at 1 AU and compare with actual in-situ observations. We show an ability to predict the sheath arrival with an average error of under 4 hours, with an RMS error of about 1.5 hours. For the CME ejecta, the error is less than two hours with an RMS error within an hour. Through using the best observations of CMEs, we show the power of our method in accurately predicting CME arrival times. The limitation and implications of our accurate prediction method will be discussed.

  16. Predicting uncertainty in future marine ice sheet volume using Bayesian statistical methods

    NASA Astrophysics Data System (ADS)

    Davis, A. D.

    2015-12-01

    The marine ice instability can trigger rapid retreat of marine ice streams. Recent observations suggest that marine ice systems in West Antarctica have begun retreating. However, unknown ice dynamics, computationally intensive mathematical models, and uncertain parameters in these models make predicting retreat rate and ice volume difficult. In this work, we fuse current observational data with ice stream/shelf models to develop probabilistic predictions of future grounded ice sheet volume. Given observational data (e.g., thickness, surface elevation, and velocity) and a forward model that relates uncertain parameters (e.g., basal friction and basal topography) to these observations, we use a Bayesian framework to define a posterior distribution over the parameters. A stochastic predictive model then propagates uncertainties in these parameters to uncertainty in a particular quantity of interest (QoI)---here, the volume of grounded ice at a specified future time. While the Bayesian approach can in principle characterize the posterior predictive distribution of the QoI, the computational cost of both the forward and predictive models makes this effort prohibitively expensive. To tackle this challenge, we introduce a new Markov chain Monte Carlo method that constructs convergent approximations of the QoI target density in an online fashion, yielding accurate characterizations of future ice sheet volume at significantly reduced computational cost.Our second goal is to attribute uncertainty in these Bayesian predictions to uncertainties in particular parameters. Doing so can help target data collection, for the purpose of constraining the parameters that contribute most strongly to uncertainty in the future volume of grounded ice. For instance, smaller uncertainties in parameters to which the QoI is highly sensitive may account for more variability in the prediction than larger uncertainties in parameters to which the QoI is less sensitive. We use global sensitivity

  17. Factors affecting dynamical seasonal prediction of the Arctic sea ice

    NASA Astrophysics Data System (ADS)

    Wang, W.; Chen, M.; Kumar, A.; Hung, M.

    2013-12-01

    Arctic sea ice variability has received increasing attention during the last decade. Seasonal prediction of the Arctic sea ice has been primarily produced with statistical methods during the past years. A few operational centers have recently implemented dynamical sea ice component in the coupled atmosphere-ocean forecast systems for seasonal climate prediction. Yet various issues remain to be resolved for an improved prediction of seasonal sea ice variations. In this study, we analyze the forecast of sea ice extent in the NCEP Climate Forecast System version 2 (CFSv2) and address factors that affect the representation of the observed sea ice variability in the forecast model. The analysis will be based on retrospective and real-time 9-month forecasts from the CFSv2 for 1982-2012. We will first assess the overall performance of the CFSv2 in capturing the observed sea ice extent climatology, long-term trend, and interannual anomalies. We will then discuss factors that affect the sea ice prediction, including: (1) consistency of the initialization of the observed sea ice concentration, (2) impacts of surface heat fluxes related to atmospheric model physics, (3) bias in sea surface temperatures, and (4) impacts of initial sea ice thickness.

  18. Ice Accretion Prediction on Wind Turbines and Consequent Power Losses

    NASA Astrophysics Data System (ADS)

    Yirtici, Ozcan; Tuncer, Ismail H.; Ozgen, Serkan

    2016-09-01

    Ice accretion on wind turbine blades modifies the sectional profiles and causes alteration in the aerodynamic characteristic of the blades. The objective of this study is to determine performance losses on wind turbines due to the formation of ice in cold climate regions and mountainous areas where wind energy resources are found. In this study, the Blade Element Momentum method is employed together with an ice accretion prediction tool in order to estimate the ice build-up on wind turbine blades and the energy production for iced and clean blades. The predicted ice shapes of the various airfoil profiles are validated with the experimental data and it is shown that the tool developed is promising to be used in the prediction of power production losses of wind turbines.

  19. How predictable is a summer-ice free Arctic?

    NASA Astrophysics Data System (ADS)

    Jahn, Alexandra

    2016-04-01

    There is large interest from different stakeholders in when we will first see a summer ice-free Arctic Ocean. However, while the CMIP5 models agree that we will see a further decline of the Arctic sea ice cover over the 21st century, their projections of when an ice-free Arctic will occur has a range of over 100 years for even the strongest forcing scenario, the RCP8.5. A large part of this uncertainty stems from model biases in the simulation of Arctic sea ice in some models. But apart from this bias, how predictable is the Arctic sea ice extent and the timing of the first ice-free Arctic summer in general? Using the Community Earth System Model (CESM) large ensemble with 40+ members for RCP8.5 and the CESM medium ensemble with 15 members for RCP4.5, we will show that internal variability leads to a range of ~20 years for predictions of threshold crossing of Arctic sea ice, limiting the long-term predictability of when an ice-free Arctic Ocean can first be expected. A detailed analysis of the trajectories of the individual ensemble members will reveal whether there are features of the climate system that allow an improvement of this predictability as we get closer to a summer ice-free Arctic.

  20. A statistical analysis of icing prediction in complex terrains

    NASA Astrophysics Data System (ADS)

    Terborg, Amanda M.

    The issue of icing has been around for decades in aviation industry, and while notable improvements have been made in the study of the formation and process of icing, the prediction of icing events is a challenge that has yet to be completely overcome. Low level icing prediction, particularly in complex terrain, has been bumped to the back burner in an attempt to perfect the models created for in-flight icing. However, over the years there have been a number of different, non-model methods used to better refine the variable involved in low-level icing prediction. One of those methods comes through statistical analysis and modeling, particularly through the use of the Classification and Regression Tree (CART) techniques. These techniques examine the statistical significance of each predictor within a data set to determine various decision rules. Those rules in which the overall misclassification error is the smallest are then used to construct a decision tree and can be used to create a forecast for icing events. Using adiabatically adjusted Rapid Update Cycle (RUC) interpolated sounding data these CART techniques are used in this study to examine icing events in the White Mountains of New Hampshire, specifically on the summit of Mount Washington. The Mount Washington Observatory (MWO), which sits on the summit and is manned year around by weather observers, is no stranger to icing occurrences. In fact, the summit sees icing events from October all the way until April, and occasionally even into May. In this study, these events are examined in detail for the October 2010 to April 2011 season, and five CART models generated for icing in general, rime icing, and glaze icing in attempt to create a decision tree or trees with a high predictive accuracy. Also examined in this study for the October 2010 to April 2011 icing season is the Air Weather Service Pamphlet (AWSP) algorithm, a decision tree model currently in use by the Air Force to predict icing events. Producing

  1. Passive samplers accurately predict PAH levels in resident crayfish.

    PubMed

    Paulik, L Blair; Smith, Brian W; Bergmann, Alan J; Sower, Greg J; Forsberg, Norman D; Teeguarden, Justin G; Anderson, Kim A

    2016-02-15

    Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict polycyclic aromatic hydrocarbon (PAH) levels in signal crayfish, Pacifastacus leniusculus. Resident crayfish were collected at 5 sites within and outside of the Portland Harbor Superfund Megasite (PHSM) in the Willamette River in Portland, Oregon. LDPE deployment was spatially and temporally paired with crayfish collection. Crayfish visceral and tail tissue, as well as water-deployed LDPE, were extracted and analyzed for 62 PAHs using GC-MS/MS. Freely-dissolved concentrations (Cfree) of PAHs in water were calculated from concentrations in LDPE. Carcinogenic risks were estimated for all crayfish tissues, using benzo[a]pyrene equivalent concentrations (BaPeq). ∑PAH were 5-20 times higher in viscera than in tails, and ∑BaPeq were 6-70 times higher in viscera than in tails. Eating only tail tissue of crayfish would therefore significantly reduce carcinogenic risk compared to also eating viscera. Additionally, PAH levels in crayfish were compared to levels in crayfish collected 10 years earlier. PAH levels in crayfish were higher upriver of the PHSM and unchanged within the PHSM after the 10-year period. Finally, a linear regression model predicted levels of 34 PAHs in crayfish viscera with an associated R-squared value of 0.52 (and a correlation coefficient of 0.72), using only the Cfree PAHs in water. On average, the model predicted PAH concentrations in crayfish tissue within a factor of 2.4 ± 1.8 of measured concentrations. This affirms that passive water sampling accurately estimates PAH contamination in crayfish. Furthermore, the strong predictive ability of this simple model suggests

  2. Plant diversity accurately predicts insect diversity in two tropical landscapes.

    PubMed

    Zhang, Kai; Lin, Siliang; Ji, Yinqiu; Yang, Chenxue; Wang, Xiaoyang; Yang, Chunyan; Wang, Hesheng; Jiang, Haisheng; Harrison, Rhett D; Yu, Douglas W

    2016-09-01

    Plant diversity surely determines arthropod diversity, but only moderate correlations between arthropod and plant species richness had been observed until Basset et al. (Science, 338, 2012 and 1481) finally undertook an unprecedentedly comprehensive sampling of a tropical forest and demonstrated that plant species richness could indeed accurately predict arthropod species richness. We now require a high-throughput pipeline to operationalize this result so that we can (i) test competing explanations for tropical arthropod megadiversity, (ii) improve estimates of global eukaryotic species diversity, and (iii) use plant and arthropod communities as efficient proxies for each other, thus improving the efficiency of conservation planning and of detecting forest degradation and recovery. We therefore applied metabarcoding to Malaise-trap samples across two tropical landscapes in China. We demonstrate that plant species richness can accurately predict arthropod (mostly insect) species richness and that plant and insect community compositions are highly correlated, even in landscapes that are large, heterogeneous and anthropogenically modified. Finally, we review how metabarcoding makes feasible highly replicated tests of the major competing explanations for tropical megadiversity. PMID:27474399

  3. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    DOE PAGES

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; et al

    2013-03-07

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of chargedmore » peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.« less

  4. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    SciTech Connect

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; Rose, Kristie L.; Tabb, David L.

    2013-03-07

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of charged peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.

  5. Using reanalysis data for the prediction of seasonal wind turbine power losses due to icing

    NASA Astrophysics Data System (ADS)

    Burtch, Daniel G.

    The Northern Plains region of the United States is home to a significant amount of potential wind energy. However, in winter months capturing this potential power is severely impacted by the meteorological conditions, in the form of icing. Predicting the expected loss in power production due to icing is a valuable parameter that can be used in wind turbine operations, determination of wind turbine site locations and long-term energy estimates which are used for financing purposes. Currently, losses due to icing must be estimated when developing predictions for turbine feasibility and financing studies, while icing maps, a tool commonly used in Europe, are lacking in the United States. This study uses the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset in conjunction with turbine production data and in-situ wind measurements to investigate six methods of predicting seasonal losses (October-March) due to icing at two sites located in Petersburg, ND and Valley City, ND. The prediction of icing losses is based on temperature and relative humidity thresholds and is accomplished using six methods. Three methods use a Measure-Correlate-Predict (MCP) and flow model (WAsP) analysis for the determination of wind speeds and MERRA for temperature and relative humidity, while three methods use MERRA for all three variables. For each season from 2002 to 2010, the predicted losses due to icing are determined for a range of relative humidity thresholds and compared with observed icing losses. An optimal relative humidity is then determined and tested on all seasons from 2002 to 2013. The prediction methods are then compared to a common practice used in the wind energy industry of assuming a constant percentage loss for icing over the same time period. The three methods using MERRA data alone show severe deficiencies in the accurate determination of wind speeds which leads to a large underprediction in accurate power output. Of the three MCP

  6. Passive samplers accurately predict PAH levels in resident crayfish.

    PubMed

    Paulik, L Blair; Smith, Brian W; Bergmann, Alan J; Sower, Greg J; Forsberg, Norman D; Teeguarden, Justin G; Anderson, Kim A

    2016-02-15

    Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict polycyclic aromatic hydrocarbon (PAH) levels in signal crayfish, Pacifastacus leniusculus. Resident crayfish were collected at 5 sites within and outside of the Portland Harbor Superfund Megasite (PHSM) in the Willamette River in Portland, Oregon. LDPE deployment was spatially and temporally paired with crayfish collection. Crayfish visceral and tail tissue, as well as water-deployed LDPE, were extracted and analyzed for 62 PAHs using GC-MS/MS. Freely-dissolved concentrations (Cfree) of PAHs in water were calculated from concentrations in LDPE. Carcinogenic risks were estimated for all crayfish tissues, using benzo[a]pyrene equivalent concentrations (BaPeq). ∑PAH were 5-20 times higher in viscera than in tails, and ∑BaPeq were 6-70 times higher in viscera than in tails. Eating only tail tissue of crayfish would therefore significantly reduce carcinogenic risk compared to also eating viscera. Additionally, PAH levels in crayfish were compared to levels in crayfish collected 10 years earlier. PAH levels in crayfish were higher upriver of the PHSM and unchanged within the PHSM after the 10-year period. Finally, a linear regression model predicted levels of 34 PAHs in crayfish viscera with an associated R-squared value of 0.52 (and a correlation coefficient of 0.72), using only the Cfree PAHs in water. On average, the model predicted PAH concentrations in crayfish tissue within a factor of 2.4 ± 1.8 of measured concentrations. This affirms that passive water sampling accurately estimates PAH contamination in crayfish. Furthermore, the strong predictive ability of this simple model suggests

  7. Mouse models of human AML accurately predict chemotherapy response

    PubMed Central

    Zuber, Johannes; Radtke, Ina; Pardee, Timothy S.; Zhao, Zhen; Rappaport, Amy R.; Luo, Weijun; McCurrach, Mila E.; Yang, Miao-Miao; Dolan, M. Eileen; Kogan, Scott C.; Downing, James R.; Lowe, Scott W.

    2009-01-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients. PMID:19339691

  8. A Community Ice Sheet Model for Sea Level Prediction

    NASA Astrophysics Data System (ADS)

    Lipscomb, William; Bindschadler, Robert; Bueler, Ed; Holland, David; Johnson, Jesse; Price, Stephen

    2009-01-01

    Building a Next-Generation Community Ice Sheet Model; Los Alamos, New Mexico, 18-20 August 2008; Recent observations show that ice sheets can respond to climate change on annual to decadal timescales and that the Greenland and West Antarctic ice sheets are losing mass at an increasing rate. The current generation of ice sheet models cannot provide credible predictions of ice sheet retreat, as underscored by the Intergovernmental Panel on Climate Change (IPCC) in its Fourth Assessment Report (2007). The IPCC provided neither a best estimate nor an upper bound for 21st-century sea level rise because of uncertainties in the dynamic response of ice sheets. In response to this need, a workshop was held at Los Alamos National Laboratory (LANL). The workshop was sponsored by the LANL Institute for Geophysics and Planetary Physics, with additional support from the U.S. Department of Energy and National Science Foundation. The workshop's goal was to create a detailed plan (including commitments from individual researchers) for developing, testing, and implementing a Community Ice Sheet Model (CISM) to aid in predicting sea level rise. This model will be freely available to the glaciology and climate modeling communities and will be the ice sheet component of the Community Climate System Model (CCSM), a major contributor to IPCC assessments.

  9. Predictive model for ice formation on superhydrophobic surfaces.

    PubMed

    Bahadur, Vaibhav; Mishchenko, Lidiya; Hatton, Benjamin; Taylor, J Ashley; Aizenberg, Joanna; Krupenkin, Tom

    2011-12-01

    The prevention and control of ice accumulation has important applications in aviation, building construction, and energy conversion devices. One area of active research concerns the use of superhydrophobic surfaces for preventing ice formation. The present work develops a physics-based modeling framework to predict ice formation on cooled superhydrophobic surfaces resulting from the impact of supercooled water droplets. This modeling approach analyzes the multiple phenomena influencing ice formation on superhydrophobic surfaces through the development of submodels describing droplet impact dynamics, heat transfer, and heterogeneous ice nucleation. These models are then integrated together to achieve a comprehensive understanding of ice formation upon impact of liquid droplets at freezing conditions. The accuracy of this model is validated by its successful prediction of the experimental findings that demonstrate that superhydrophobic surfaces can fully prevent the freezing of impacting water droplets down to surface temperatures of as low as -20 to -25 °C. The model can be used to study the influence of surface morphology, surface chemistry, and fluid and thermal properties on dynamic ice formation and identify parameters critical to achieving icephobic surfaces. The framework of the present work is the first detailed modeling tool developed for the design and analysis of surfaces for various ice prevention/reduction strategies. PMID:21899285

  10. Predictions of airfoil aerodynamic performance degradation due to icing

    NASA Technical Reports Server (NTRS)

    Shaw, Robert J.; Potapezuk, Mark G.; Bidwell, Colin S.

    1988-01-01

    An overview of NASA's ongoing efforts to develop an airfoil icing analysis capability is developed. An indication is given to the approaches being followed to calculate the water droplet trajectories past the airfoil, the buildup of ice on the airfoil, and the resultant changes in aerodynamic performance due to the leading edge ice accretion. Examples are given of current code capabilities/limitations through comparisons of predictions with experimental data gathered in various calibration/validation experiments. A brief discussion of future efforts to extend the analysis to handle three dimensional components is included.

  11. Computational Fluid Dynamics-Icing: a Predictive Tool for In-Flight Icing Risk Management

    NASA Astrophysics Data System (ADS)

    Zeppetelli, Danial

    In-flight icing is a hazard that continues to afflict the aviation industry, despite all the research and efforts to mitigate the risks. The recurrence of these types of accidents has given renewed impetus to the development of advanced analytical predictive tools to study both the accretion of ice on aircraft components in flight, and the aerodynamic consequences of such ice accumulations. In this work, an in-depth analysis of the occurrence of in-flight icing accidents and incidents was conducted to identify high-risk flight conditions. To investigate these conditions more thoroughly, a computational fluid dynamics model of a representative airfoil was developed to recreate experiments from the icing wind tunnel that occurred in controlled flight conditions. The ice accumulations and resulting aerodynamic performance degradations of the airfoil were computed for a range or pitch angles and flight speeds. These simulations revealed substantial performance losses such as reduced maximum lift, and decreased stall angle. From these results, an icing hazard analysis tool was developed, using risk management principles, to evaluate the dangers of in-flight icing for a specific aircraft based on the atmospheric conditions it is expected to encounter, as well as the effectiveness of aircraft certification procedures. This method is then demonstrated through the simulation of in-flight icing scenarios based on real flight data from accidents and incidents. The risk management methodology is applied to the results of the simulations and the predicted performance degradation is compared to recorded aircraft performance characteristics at the time of the occurrence. The aircraft performance predictions and resulting risk assessment are found to correspond strongly to the pilot's comments as well as to the severity of the incident.

  12. Fast and accurate predictions of covalent bonds in chemical space.

    PubMed

    Chang, K Y Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O Anatole

    2016-05-01

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (∼1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H2 (+). Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  13. Fast and accurate predictions of covalent bonds in chemical space

    NASA Astrophysics Data System (ADS)

    Chang, K. Y. Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O. Anatole

    2016-05-01

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (˜1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H 2+ . Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  14. Fast and accurate predictions of covalent bonds in chemical space.

    PubMed

    Chang, K Y Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O Anatole

    2016-05-01

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (∼1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H2 (+). Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  15. Predicted slowdown in the rate of Atlantic sea ice loss

    NASA Astrophysics Data System (ADS)

    Yeager, Stephen G.; Karspeck, Alicia R.; Danabasoglu, Gokhan

    2015-12-01

    Coupled climate models initialized from historical climate states and subject to anthropogenic forcings can produce skillful decadal predictions of sea surface temperature change in the subpolar North Atlantic. The skill derives largely from initialization, which improves the representation of slow changes in ocean circulation and associated poleward heat transport. We show that skillful predictions of decadal trends in Arctic winter sea ice extent are also possible, particularly in the Atlantic sector. External radiative forcing contributes to the skill of retrospective decadal sea ice predictions, but the spatial and temporal accuracy is greatly enhanced by the more realistic representation of ocean heat transport anomalies afforded by initialization. Recent forecasts indicate that a spin-down of the thermohaline circulation that began near the turn of the century will continue, and this will result in near-neutral decadal trends in Atlantic winter sea ice extent in the coming years, with decadal growth in select regions.

  16. The Influence of Viscous Effects on Ice Accretion Prediction and Airfoil Performance Predictions

    NASA Technical Reports Server (NTRS)

    Kreeger, Richard E.; Wright, William B.

    2005-01-01

    A computational study was conducted to evaluate the effectiveness of using a viscous flow solution in an ice accretion code and the resulting accuracy of aerodynamic performance prediction. Ice shapes were obtained for one single-element and one multi-element airfoil using both potential flow and Navier-Stokes flowfields in the LEWICE ice accretion code. Aerodynamics were then calculated using a Navier-Stokes flow solver.

  17. An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions

    PubMed Central

    Deng, Xin; Gumm, Jordan; Karki, Suman; Eickholt, Jesse; Cheng, Jianlin

    2015-01-01

    Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale. PMID:26198229

  18. PredictSNP: robust and accurate consensus classifier for prediction of disease-related mutations.

    PubMed

    Bendl, Jaroslav; Stourac, Jan; Salanda, Ondrej; Pavelka, Antonin; Wieben, Eric D; Zendulka, Jaroslav; Brezovsky, Jan; Damborsky, Jiri

    2014-01-01

    Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp.

  19. Accurately Predicting Complex Reaction Kinetics from First Principles

    NASA Astrophysics Data System (ADS)

    Green, William

    Many important systems contain a multitude of reactive chemical species, some of which react on a timescale faster than collisional thermalization, i.e. they never achieve a Boltzmann energy distribution. Usually it is impossible to fully elucidate the processes by experiments alone. Here we report recent progress toward predicting the time-evolving composition of these systems a priori: how unexpected reactions can be discovered on the computer, how reaction rates are computed from first principles, and how the many individual reactions are efficiently combined into a predictive simulation for the whole system. Some experimental tests of the a priori predictions are also presented.

  20. Does more accurate exposure prediction necessarily improve health effect estimates?

    PubMed

    Szpiro, Adam A; Paciorek, Christopher J; Sheppard, Lianne

    2011-09-01

    A unique challenge in air pollution cohort studies and similar applications in environmental epidemiology is that exposure is not measured directly at subjects' locations. Instead, pollution data from monitoring stations at some distance from the study subjects are used to predict exposures, and these predicted exposures are used to estimate the health effect parameter of interest. It is usually assumed that minimizing the error in predicting the true exposure will improve health effect estimation. We show in a simulation study that this is not always the case. We interpret our results in light of recently developed statistical theory for measurement error, and we discuss implications for the design and analysis of epidemiologic research.

  1. Data-driven Analysis and Prediction of Arctic Sea Ice

    NASA Astrophysics Data System (ADS)

    Kondrashov, D. A.; Chekroun, M.; Ghil, M.; Yuan, X.; Ting, M.

    2015-12-01

    We present results of data-driven predictive analyses of sea ice over the main Arctic regions. Our approach relies on the Multilayer Stochastic Modeling (MSM) framework of Kondrashov, Chekroun and Ghil [Physica D, 2015] and it leads to prognostic models of sea ice concentration (SIC) anomalies on seasonal time scales.This approach is applied to monthly time series of leading principal components from the multivariate Empirical Orthogonal Function decomposition of SIC and selected climate variables over the Arctic. We evaluate the predictive skill of MSM models by performing retrospective forecasts with "no-look ahead" forup to 6-months ahead. It will be shown in particular that the memory effects included in our non-Markovian linear MSM models improve predictions of large-amplitude SIC anomalies in certain Arctic regions. Furtherimprovements allowed by the MSM framework will adopt a nonlinear formulation, as well as alternative data-adaptive decompositions.

  2. Direct Pressure Monitoring Accurately Predicts Pulmonary Vein Occlusion During Cryoballoon Ablation

    PubMed Central

    Kosmidou, Ioanna; Wooden, Shannnon; Jones, Brian; Deering, Thomas; Wickliffe, Andrew; Dan, Dan

    2013-01-01

    Cryoballoon ablation (CBA) is an established therapy for atrial fibrillation (AF). Pulmonary vein (PV) occlusion is essential for achieving antral contact and PV isolation and is typically assessed by contrast injection. We present a novel method of direct pressure monitoring for assessment of PV occlusion. Transcatheter pressure is monitored during balloon advancement to the PV antrum. Pressure is recorded via a single pressure transducer connected to the inner lumen of the cryoballoon. Pressure curve characteristics are used to assess occlusion in conjunction with fluoroscopic or intracardiac echocardiography (ICE) guidance. PV occlusion is confirmed when loss of typical left atrial (LA) pressure waveform is observed with recordings of PA pressure characteristics (no A wave and rapid V wave upstroke). Complete pulmonary vein occlusion as assessed with this technique has been confirmed with concurrent contrast utilization during the initial testing of the technique and has been shown to be highly accurate and readily reproducible. We evaluated the efficacy of this novel technique in 35 patients. A total of 128 veins were assessed for occlusion with the cryoballoon utilizing the pressure monitoring technique; occlusive pressure was demonstrated in 113 veins with resultant successful pulmonary vein isolation in 111 veins (98.2%). Occlusion was confirmed with subsequent contrast injection during the initial ten procedures, after which contrast utilization was rapidly reduced or eliminated given the highly accurate identification of occlusive pressure waveform with limited initial training. Verification of PV occlusive pressure during CBA is a novel approach to assessing effective PV occlusion and it accurately predicts electrical isolation. Utilization of this method results in significant decrease in fluoroscopy time and volume of contrast. PMID:23485956

  3. Is Three-Dimensional Soft Tissue Prediction by Software Accurate?

    PubMed

    Nam, Ki-Uk; Hong, Jongrak

    2015-11-01

    The authors assessed whether virtual surgery, performed with a soft tissue prediction program, could correctly simulate the actual surgical outcome, focusing on soft tissue movement. Preoperative and postoperative computed tomography (CT) data for 29 patients, who had undergone orthognathic surgery, were obtained and analyzed using the Simplant Pro software. The program made a predicted soft tissue image (A) based on presurgical CT data. After the operation, we obtained actual postoperative CT data and an actual soft tissue image (B) was generated. Finally, the 2 images (A and B) were superimposed and analyzed differences between the A and B. Results were grouped in 2 classes: absolute values and vector values. In the absolute values, the left mouth corner was the most significant error point (2.36 mm). The right mouth corner (2.28 mm), labrale inferius (2.08 mm), and the pogonion (2.03 mm) also had significant errors. In vector values, prediction of the right-left side had a left-sided tendency, the superior-inferior had a superior tendency, and the anterior-posterior showed an anterior tendency. As a result, with this program, the position of points tended to be located more left, anterior, and superior than the "real" situation. There is a need to improve the prediction accuracy for soft tissue images. Such software is particularly valuable in predicting craniofacial soft tissues landmarks, such as the pronasale. With this software, landmark positions were most inaccurate in terms of anterior-posterior predictions.

  4. Prediction of ice accretion on a swept NACA 0012 airfoil and comparisons to flight test results

    NASA Technical Reports Server (NTRS)

    Reehorst, Andrew L.

    1992-01-01

    In the winter of 1989-90, an icing research flight project was conducted to obtain swept wing ice accretion data. Utilizing the NASA Lewis Research Center's DHC-6 DeHavilland Twin Otter aircraft, research flights were made into known icing conditions in Northeastern Ohio. The icing cloud environment and aircraft flight data were measured and recorded by an onboard data acquisition system. Upon entry into the icing environment, a 24 inch span, 15 inch chord NACA 0012 airfoil was extended from the aircraft and set to the desired sweep angle. After the growth of a well defined ice shape, the airfoil was retracted into the aircraft cabin for ice shape documentation. The ice accretions were recorded by ice tracings and photographs. Ice accretions were mostly of the glaze type and exhibited scalloping. The ice was accreted at sweep angles of 0, 30, and 45 degrees. A 3-D ice accretion prediction code was used to predict ice profiles for five selected flight test runs, which include sweep angle of zero, 30, and 45 degrees. The code's roughness input parameter was adjusted for best agreement. A simple procedure was added to the code to account for 3-D ice scalloping effects. The predicted ice profiles are compared to their respective flight test counterparts. This is the first attempt to predict ice profiles on swept wings with significant scalloped ice formations.

  5. Towards Accurate Ab Initio Predictions of the Spectrum of Methane

    NASA Technical Reports Server (NTRS)

    Schwenke, David W.; Kwak, Dochan (Technical Monitor)

    2001-01-01

    We have carried out extensive ab initio calculations of the electronic structure of methane, and these results are used to compute vibrational energy levels. We include basis set extrapolations, core-valence correlation, relativistic effects, and Born- Oppenheimer breakdown terms in our calculations. Our ab initio predictions of the lowest lying levels are superb.

  6. Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

    PubMed Central

    Rossetti, Andrea O.; van Rootselaar, Anne-Fleur; Wesenberg Kjaer, Troels; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Rosén, Ingmar; Åneman, Anders; Erlinge, David; Gasche, Yvan; Hassager, Christian; Hovdenes, Jan; Kjaergaard, Jesper; Kuiper, Michael; Pellis, Tommaso; Stammet, Pascal; Wanscher, Michael; Wetterslev, Jørn; Wise, Matt P.; Cronberg, Tobias

    2016-01-01

    Objective: To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. Methods: In this cohort study, 4 EEG specialists, blinded to outcome, evaluated prospectively recorded EEGs in the Target Temperature Management trial (TTM trial) that randomized patients to 33°C vs 36°C. Routine EEG was performed in patients still comatose after rewarming. EEGs were classified into highly malignant (suppression, suppression with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3–5 until 180 days. Results: Eight TTM sites randomized 202 patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present specificity increased to 96% (p < 0.001). Specificity and sensitivity were not significantly affected by targeted temperature or sedation. A benign EEG was found in 1% of the patients with a poor outcome. Conclusions: Highly malignant EEG after rewarming reliably predicted poor outcome in half of patients without false predictions. An isolated finding of a single malignant feature did not predict poor outcome whereas a benign EEG was highly predictive of a good outcome. PMID:26865516

  7. PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations

    PubMed Central

    Bendl, Jaroslav; Stourac, Jan; Salanda, Ondrej; Pavelka, Antonin; Wieben, Eric D.; Zendulka, Jaroslav; Brezovsky, Jan; Damborsky, Jiri

    2014-01-01

    Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp. PMID:24453961

  8. Accurate contact predictions using covariation techniques and machine learning

    PubMed Central

    Kosciolek, Tomasz

    2015-01-01

    ABSTRACT Here we present the results of residue–residue contact predictions achieved in CASP11 by the CONSIP2 server, which is based around our MetaPSICOV contact prediction method. On a set of 40 target domains with a median family size of around 40 effective sequences, our server achieved an average top‐L/5 long‐range contact precision of 27%. MetaPSICOV method bases on a combination of classical contact prediction features, enhanced with three distinct covariation methods embedded in a two‐stage neural network predictor. Some unique features of our approach are (1) the tuning between the classical and covariation features depending on the depth of the input alignment and (2) a hybrid approach to generate deepest possible multiple‐sequence alignments by combining jackHMMer and HHblits. We discuss the CONSIP2 pipeline, our results and show that where the method underperformed, the major factor was relying on a fixed set of parameters for the initial sequence alignments and not attempting to perform domain splitting as a preprocessing step. Proteins 2016; 84(Suppl 1):145–151. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:26205532

  9. How Accurately Can We Predict Eclipses for Algol? (Poster abstract)

    NASA Astrophysics Data System (ADS)

    Turner, D.

    2016-06-01

    (Abstract only) beta Persei, or Algol, is a very well known eclipsing binary system consisting of a late B-type dwarf that is regularly eclipsed by a GK subgiant every 2.867 days. Eclipses, which last about 8 hours, are regular enough that predictions for times of minima are published in various places, Sky & Telescope magazine and The Observer's Handbook, for example. But eclipse minimum lasts for less than a half hour, whereas subtle mistakes in the current ephemeris for the star can result in predictions that are off by a few hours or more. The Algol system is fairly complex, with the Algol A and Algol B eclipsing system also orbited by Algol C with an orbital period of nearly 2 years. Added to that are complex long-term O-C variations with a periodicity of almost two centuries that, although suggested by Hoffmeister to be spurious, fit the type of light travel time variations expected for a fourth star also belonging to the system. The AB sub-system also undergoes mass transfer events that add complexities to its O-C behavior. Is it actually possible to predict precise times of eclipse minima for Algol months in advance given such complications, or is it better to encourage ongoing observations of the star so that O-C variations can be tracked in real time?

  10. Prediction of sea ice thickness cluster in the Northern Hemisphere

    NASA Astrophysics Data System (ADS)

    Fuckar, Neven-Stjepan; Guemas, Virginie; Johnson, Nathaniel; Doblas-Reyes, Francisco

    2016-04-01

    Sea ice thickness (SIT) has a potential to contain substantial climate memory and predictability in the northern hemisphere (NH) sea ice system. We use 5-member NH SIT, reconstructed with an ocean-sea-ice general circulation model (NEMOv3.3 with LIM2) with a simple data assimilation routine, to determine NH SIT modes of variability disentangled from the long-term climate change. Specifically, we apply the K-means cluster analysis - one of nonhierarchical clustering methods that partition data into modes or clusters based on their distances in the physical - to determine optimal number of NH SIT clusters (K=3) and their historical variability. To examine prediction skill of NH SIT clusters in EC-Earth2.3, a state-of-the-art coupled climate forecast system, we use 5-member ocean and sea ice initial conditions (IC) from the same ocean-sea-ice historical reconstruction and atmospheric IC from ERA-Interim reanalysis. We focus on May 1st and Nov 1st start dates from 1979 to 2010. Common skill metrics of probability forecast, such as rank probability skill core and ROC (relative operating characteristics - hit rate versus false alarm rate) and reliability diagrams show that our dynamical model predominately perform better than the 1st order Marko chain forecast (that beats climatological forecast) over the first forecast year. On average May 1st start dates initially have lower skill than Nov 1st start dates, but their skill is degraded at slower rate than skill of forecast started on Nov 1st.

  11. Data-Driven Modeling and Prediction of Arctic Sea Ice

    NASA Astrophysics Data System (ADS)

    Kondrashov, Dmitri; Chekroun, Mickael; Ghil, Michael

    2016-04-01

    We present results of data-driven predictive analyses of sea ice over the main Arctic regions. Our approach relies on the Multilayer Stochastic Modeling (MSM) framework of Kondrashov, Chekroun and Ghil [Physica D, 2015] and it leads to probabilistic prognostic models of sea ice concentration (SIC) anomalies on seasonal time scales. This approach is applied to monthly time series of state-of-the-art data-adaptive decompositions of SIC and selected climate variables over the Arctic. We evaluate the predictive skill of MSM models by performing retrospective forecasts with "no-look ahead" for up to 6-months ahead. It will be shown in particular that the memory effects included intrinsically in the formulation of our non-Markovian MSM models allow for improvements of the prediction skill of large-amplitude SIC anomalies in certain Arctic regions on the one hand, and of September Sea Ice Extent, on the other. Further improvements allowed by the MSM framework will adopt a nonlinear formulation and explore next-generation data-adaptive decompositions, namely modification of Principal Oscillation Patterns (POPs) and rotated Multichannel Singular Spectrum Analysis (M-SSA).

  12. Accurate and predictive antibody repertoire profiling by molecular amplification fingerprinting

    PubMed Central

    Khan, Tarik A.; Friedensohn, Simon; de Vries, Arthur R. Gorter; Straszewski, Jakub; Ruscheweyh, Hans-Joachim; Reddy, Sai T.

    2016-01-01

    High-throughput antibody repertoire sequencing (Ig-seq) provides quantitative molecular information on humoral immunity. However, Ig-seq is compromised by biases and errors introduced during library preparation and sequencing. By using synthetic antibody spike-in genes, we determined that primer bias from multiplex polymerase chain reaction (PCR) library preparation resulted in antibody frequencies with only 42 to 62% accuracy. Additionally, Ig-seq errors resulted in antibody diversity measurements being overestimated by up to 5000-fold. To rectify this, we developed molecular amplification fingerprinting (MAF), which uses unique molecular identifier (UID) tagging before and during multiplex PCR amplification, which enabled tagging of transcripts while accounting for PCR efficiency. Combined with a bioinformatic pipeline, MAF bias correction led to measurements of antibody frequencies with up to 99% accuracy. We also used MAF to correct PCR and sequencing errors, resulting in enhanced accuracy of full-length antibody diversity measurements, achieving 98 to 100% error correction. Using murine MAF-corrected data, we established a quantitative metric of recent clonal expansion—the intraclonal diversity index—which measures the number of unique transcripts associated with an antibody clone. We used this intraclonal diversity index along with antibody frequencies and somatic hypermutation to build a logistic regression model for prediction of the immunological status of clones. The model was able to predict clonal status with high confidence but only when using MAF error and bias corrected Ig-seq data. Improved accuracy by MAF provides the potential to greatly advance Ig-seq and its utility in immunology and biotechnology. PMID:26998518

  13. Accurate predictions for the production of vaporized water

    SciTech Connect

    Morin, E.; Montel, F.

    1995-12-31

    The production of water vaporized in the gas phase is controlled by the local conditions around the wellbore. The pressure gradient applied to the formation creates a sharp increase of the molar water content in the hydrocarbon phase approaching the well; this leads to a drop in the pore water saturation around the wellbore. The extent of the dehydrated zone which is formed is the key controlling the bottom-hole content of vaporized water. The maximum water content in the hydrocarbon phase at a given pressure, temperature and salinity is corrected by capillarity or adsorption phenomena depending on the actual water saturation. Describing the mass transfer of the water between the hydrocarbon phases and the aqueous phase into the tubing gives a clear idea of vaporization effects on the formation of scales. Field example are presented for gas fields with temperatures ranging between 140{degrees}C and 180{degrees}C, where water vaporization effects are significant. Conditions for salt plugging in the tubing are predicted.

  14. Change in BMI accurately predicted by social exposure to acquaintances.

    PubMed

    Oloritun, Rahman O; Ouarda, Taha B M J; Moturu, Sai; Madan, Anmol; Pentland, Alex Sandy; Khayal, Inas

    2013-01-01

    Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R(2). This study found a model that explains 68% (p<0.0001) of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends.

  15. Three dimensional numerical prediction of icing related power and energy losses on a wind turbine

    NASA Astrophysics Data System (ADS)

    Sagol, Ece

    , while the latter performs all the steps in the 3D domain. The Fully-3D method yields more accurate predictions for a clean blade. For icing conditions, a validation is not possible, owing to the lack of experimental data. However, the two methods produce quite different results for the performance of the ice shape and the iced blade. A critical analysis of the results shows that, although the computational cost of the Fully-3D method is much higher, icing analyses in 2D may lack accuracy, because the ice shape and the related power loss are compromised by not considering the 3D features of rotational flow. While performing the CFD computations on the iced blade, the rough surface of the ice is smoothed to a degree, in order to prevent numerical instability and to keep the mesh size within a reasonable limit. However, roughness effects cannot be excluded altogether, as they contribute significantly to performance reduction. We consider roughness through a modification in the CFD code, and assess its effect on performance for the clean blade.

  16. A constitutive framework for predicting weakening and reduced buttressing of ice shelves based on observations of the progressive deterioration of the remnant Larsen B Ice Shelf

    NASA Astrophysics Data System (ADS)

    Borstad, Chris; Khazendar, Ala; Scheuchl, Bernd; Morlighem, Mathieu; Larour, Eric; Rignot, Eric

    2016-03-01

    The increasing contribution of the Antarctic Ice Sheet to sea level rise is linked to reductions in ice shelf buttressing, driven in large part by basal melting of ice shelves. These ocean-driven buttressing losses are being compounded as ice shelves weaken and fracture. To date, model projections of ice sheet evolution have not accounted for weakening ice shelves. Here we present the first constitutive framework for ice deformation that explicitly includes mechanical weakening, based on observations of the progressive degradation of the remnant Larsen B Ice Shelf from 2000 to 2015. We implement this framework in an ice sheet model and are able to reproduce most of the observed weakening of the ice shelf. In addition to predicting ice shelf weakening and reduced buttressing, this new framework opens the door for improved understanding and predictions of iceberg calving, meltwater routing and hydrofracture, and ice shelf collapse.

  17. Prospects for improved seasonal Arctic sea ice predictions from multivariate data assimilation

    NASA Astrophysics Data System (ADS)

    Massonnet, François; Fichefet, Thierry; Goosse, Hugues

    2015-04-01

    Predicting the summer Arctic sea ice conditions a few months in advance has become a challenging priority. Seasonal prediction is partly an initial condition problem; therefore, a good knowledge of the initial sea ice state is necessary to hopefully produce reliable forecasts. Most of the intrinsic memory of sea ice lies in its thickness, but consistent and homogeneous observational networks of sea ice thickness are still limited in space and time. To overcome this problem, we constrain the ocean-sea ice model NEMO-LIM3 with gridded sea ice concentration retrievals from satellite observations using the ensemble Kalman filter. No sea ice thickness products are assimilated. However, thanks to the multivariate formalism of the data assimilation method used, sea ice thickness is globally updated in a consistent way whenever observations of concentration are available. We compare in this paper the skill of 27 pairs of initialized and uninitialized seasonal Arctic sea ice hindcasts spanning 1983-2009, driven by the same atmospheric forcing as to isolate the pure role of initial conditions on the prediction skill. The results exhibit the interest of multivariate sea ice initialization for the seasonal predictions of the September ice concentration and are particularly encouraging for hindcasts in the 2000s. In line with previous studies showing the interest of data assimilation for sea ice thickness reconstruction, our results thus show that sea ice data assimilation is also a promising tool for short-term prediction, and that current seasonal sea ice forecast systems could gain predictive skill from a more realistic sea ice initialization.

  18. The CONCEPTS Global Ice-Ocean Prediction System: Establishing an Environmental Prediction Capability in Canada

    NASA Astrophysics Data System (ADS)

    Pellerin, Pierre; Smith, Gregory; Testut, Charles-Emmanuel; Surcel Colan, Dorina; Roy, Francois; Reszka, Mateusz; Dupont, Frederic; Lemieux, Jean-Francois; Beaudoin, Christiane; He, Zhongjie; Belanger, Jean-Marc; Deacu, Daniel; Lu, Yimin; Buehner, Mark; Davidson, Fraser; Ritchie, Harold; Lu, Youyu; Drevillon, Marie; Tranchant, Benoit; Garric, Gilles

    2015-04-01

    Here we describe a new system implemented recently at the Canadian Meteorological Centre (CMC) entitled the Global Ice Ocean Prediction System (GIOPS). GIOPS provides ice and ocean analyses and 10 day forecasts daily at 00GMT on a global 1/4° resolution grid. GIOPS includes a full multivariate ocean data assimilation system that combines satellite observations of sea level anomaly and sea surface temperature (SST) together with in situ observations of temperature and salinity. In situ observations are obtained from a variety of sources including: the Argo network of autonomous profiling floats, moorings, ships of opportunity, marine mammals and research cruises. Ocean analyses are blended with sea ice analyses produced by the Global Ice Analysis System.. GIOPS has been developed as part of the Canadian Operational Network of Coupled Environmental PredicTion Systems (CONCEPTS) tri-departmental initiative between Environment Canada, Fisheries and Oceans Canada and National Defense. The development of GIOPS was made through a partnership with Mercator-Océan, a French operational oceanography group. Mercator-Océan provided the ocean data assimilation code and assistance with the system implementation. GIOPS has undergone a rigorous evaluation of the analysis, trial and forecast fields demonstrating its capacity to provide high-quality products in a robust and reliable framework. In particular, SST and ice concentration forecasts demonstrate a clear benefit with respect to persistence. These results support the use of GIOPS products within other CMC operational systems, and more generally, as part of a Government of Canada marine core service. Impact of a two-way coupling between the GEM atmospheric model and NEMO-CICE ocean-ice model will also be presented.

  19. Properties prediction of non-toxic ice inhibitors

    SciTech Connect

    Pachter, R.; Trohalaki, S.

    1996-10-01

    Toxic de-icing compounds currently employed in jet fuels (ethylene glycol monomethyl ether and diethylene glycol monomethyl ether) dissolve in the water {open_quote}bottoms{close_quote} present in storage tanks, thus producing hazardous waste which requires expensive disposal. The fastest and most cost effective way to develop alternative compounds is to design desirable features theoretically and thus direct the synthesis of those candidates having sought after properties. Empirical and quantum mechanical approaches for partition coefficients calculations, as well as Quantitative Structure Property Relationship (QSAR) evaluations, were investigated. We demonstrate that molecular orbital calculations have to be used for a reliable prediction of partition coefficients, and moreover that the conformational response to solvent is significant. Although the values of the calculated partition coefficients are not in full agreement with experimental results, the trends are well reproduced. QSAR estimations to elucidate the toxicity of the proposed alternative compounds are reported and assessed. An approach for deriving phase diagrams of a binary mixture is outlined, where molecular dynamics (MD) simulations are performed on bulk systems consisting of pure water, pure de-icer, and binary mixtures of de-icer and water. Analysis of the NO trajectories yield insights into the de-icing mechanism and form a basis for comparison of different de-icers.

  20. Predictions of depth-to-ice on asteroids based on an asynchronous model of temperature, impact stirring, and ice loss

    NASA Astrophysics Data System (ADS)

    Schorghofer, Norbert

    2016-09-01

    Water ice near the surface of main belt asteroids is gradually lost to space. A mantle of low thermal conductivity causes large surface temperature amplitudes, and thus increased cooling by thermal re-radiation, lowering temperatures well below the fast-rotator limit. A computational barrier for modeling this ice loss is the multi-scale character of the problem: accurate temperatures require many time steps within a solar day, but ice retreats slowly over billions of years. This barrier is overcome with asynchronous coupling: Models of temperature, ice loss, and impact stirring each use their own time steps and are coupled with one another. The model is applied to 1 Ceres and 7968 Elst-Pizarro. On Ceres, ice can be expected in the top half meter poleward of 60° latitude on both hemispheres, even if excursions of the axis tilt took place, and even in the presence of impact gardening. At the poles, ice can be expected within a centimeter of the surface. The retreating ice crust leads to emission of water from the surface, mainly at the equator; the gradually retreating ice supplies a water exosphere less dense than has been observed by the Herschel telescope. For Main Belt Comet Elst-Pizarro, depths to ice depend on the properties of the surface mantle. For a dust mantle estimated depths are on the order of a decimeter; for a rocky surface the depth at the pole is on the order of one meter. Hence, it could have been activated by a small impact that exposed buried ice.

  1. Internal Variability Limits the Predictability of a Summer Ice-Free Arctic

    NASA Astrophysics Data System (ADS)

    Jahn, A.; Holland, M. M.; Kay, J. E.

    2014-12-01

    The transition to a summer ice-free Arctic Ocean has attracted much attention, but climate model simulations in CMIP5 vary widely in their prediction of when we will reach a summer ice-free state. To quantify the contribution of internal variability to the spread of projections and to assess the limit of predictability of the year we will reach a summer ice-free Arctic we will present results from the new Large Ensemble with the Community Earth System Model (CESM). The CESM is a state of the art climate system model that has shown skill in capturing the observed decline of Arctic sea ice. The CESM Large Ensemble has 30 members for 1920-2100 that only differ through round-of level perturbations in the initial state. It is an unprecedented opportunity to analyze the contribution of natural variability to the simulated climate evolution within one model, as it provides enough ensemble members to characterize the probability distribution of many climate phenomena. Focusing on Arctic sea ice predictability, we find that the individual ensemble members first reach an ice-free Arctic in September (defined as a sea ice extent of 1 million km2) over a period of 21 years (2032-2053), with the majority of the ensemble members first reaching September ice-free conditions in the 5-year period from 2040-2044. This large spread shows the large impact of internal variability on the timing of reaching an ice-free Arctic, which severely limits the predictability of a summer ice-free Arctic we can expect from CMIP-type climate models. In addition to results on the predictability of an ice-free Arctic, we will also present results on the probability of hiatus periods in sea ice loss and of rapid ice loss events (RILEs), based on the CESM large ensemble.

  2. A hydrologically inspired approach to predicting fjord bedrock elevation at the ice-ocean interface of the Greenland Ice Sheet

    NASA Astrophysics Data System (ADS)

    Williams, Chris; Bamber, Jonathan; Cochran, James; Cornford, Stephen; Dowdeswell, Julian; Jordan, Tom; Morlighem, Mathieu; Palmer, Steven; Siegert, Martin; Tinto, Kirsty; Paden, John

    2016-04-01

    Measurements of ice sheet basal topography provide vital boundary conditions for numerical modelling of ice sheet evolution and are key to understanding observations of ice sheet dynamics. A consistent issue with existing bed topography products for the Greenland Ice Sheet - developed using ice thickness observations from ice penetrating radar, interpolation, and mass conservation (Bamber et al., 2013, Morlighem et al., 2014) - is the poor quantification of near coastal bathymetry. Accurate mapping of bedrock elevation in these areas is important as glaciers local to these regions have been observed to have the largest velocities, greatest associated mass changes, and are therefore most sensitive to uncertainties in basal boundary conditions when modelling ice motion (e.g. Nick et al., 2013). Sparse data availability and resultant coarse rendering of digital elevation products at the edges of existing ice sheet bed elevation products poses issues, particularly when integrating models over longer periods of time (e.g. Vieli and Nick, 2011). Improving data coverage in these regions is a further priority as fjord bathymetry is known to provide a strong control on ocean circulation and ice-ocean forcing (e.g. Straneo et al., 2011) which have been related to changes observed in tidewater glacier systems (e.g. Murray et al., 2010). We have developed a method that improves existing products of the Greenland Ice Sheet bed rock and surrounding bathymetry through [1] the addition of new bathymetric and ice thickness data where available and [2] the integration of generalised fjord structures in data sparse regions to better inform interpolation routines. Following the release of the last Greenland bed topography-bathymetry product (Bamber et al., 2013), new data acquired through gravity inversion as well as single and multi-beam echo sounding are included, improving bed elevation data density and coverage. In fjords which remain data sparse, idealised fjord geometry is

  3. Broad-scale predictability of carbohydrates and exopolymers in Antarctic and Arctic sea ice.

    PubMed

    Underwood, Graham J C; Aslam, Shazia N; Michel, Christine; Niemi, Andrea; Norman, Louiza; Meiners, Klaus M; Laybourn-Parry, Johanna; Paterson, Harriet; Thomas, David N

    2013-09-24

    Sea ice can contain high concentrations of dissolved organic carbon (DOC), much of which is carbohydrate-rich extracellular polymeric substances (EPS) produced by microalgae and bacteria inhabiting the ice. Here we report the concentrations of dissolved carbohydrates (dCHO) and dissolved EPS (dEPS) in relation to algal standing stock [estimated by chlorophyll (Chl) a concentrations] in sea ice from six locations in the Southern and Arctic Oceans. Concentrations varied substantially within and between sampling sites, reflecting local ice conditions and biological content. However, combining all data revealed robust statistical relationships between dCHO concentrations and the concentrations of different dEPS fractions, Chl a, and DOC. These relationships were true for whole ice cores, bottom ice (biomass rich) sections, and colder surface ice. The distribution of dEPS was strongly correlated to algal biomass, with the highest concentrations of both dEPS and non-EPS carbohydrates in the bottom horizons of the ice. Complex EPS was more prevalent in colder surface sea ice horizons. Predictive models (validated against independent data) were derived to enable the estimation of dCHO concentrations from data on ice thickness, salinity, and vertical position in core. When Chl a data were included a higher level of prediction was obtained. The consistent patterns reflected in these relationships provide a strong basis for including estimates of regional and seasonal carbohydrate and dEPS carbon budgets in coupled physical-biogeochemical models, across different types of sea ice from both polar regions.

  4. Multivariable time series prediction for the icing process on overhead power transmission line.

    PubMed

    Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

    2014-01-01

    The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters. PMID:25136653

  5. Multivariable Time Series Prediction for the Icing Process on Overhead Power Transmission Line

    PubMed Central

    Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

    2014-01-01

    The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters. PMID:25136653

  6. Improving Sea Ice Prediction in the NCEP Climate Forecast System Model

    NASA Astrophysics Data System (ADS)

    Collow, T. W.; Wang, W.; Kumar, A.

    2015-12-01

    Skillful prediction of Arctic sea ice is important for the wide variety of interests focused in that region. However, the current operational system used by the NOAA Climate Prediction Center does not adequately predict the seasonal climatology of sea ice extent and maintains too high sea ice coverage across the Arctic. It is thought that the primary reasoning for this lies in the initialization of sea ice thickness. Experiments are carried out using the Climate Forecast System (CFSv2) model with an improved sea ice thickness initialization from the Pan-Arctic Ice Ocean Analysis and Assimilation System (PIOMAS) rather than the default Climate Forecast System Reanalysis (CFSR) sea ice thickness data. All other variables are initialized from CFSR. In addition, physics parameterizations are adjusted to better simulate real world conditions. Here we focus on hindcasts initialized from 2005-2014. Although the seasonal cycle of sea ice is generally better captured in runs that use PIOMAS sea ice thickness initialization, local sea ice freeze in early winter in the Bering Strait and Chukchi Sea is delayed when both sea ice thickness configurations are used. In addition ice freeze in the North Atlantic is more pronounced than in the observations. This shows that simply changing initial sea ice thickness is not enough to improve forecasts for all locations. Modeled atmospheric and oceanic parameters are investigated including the radiation budget, land surface temperature advection, and sub-surface oceanic heat flow to diagnose possible reasons for the modeling deficiencies, and further modifications to the model will be discussed.

  7. Mind-set and close relationships: when bias leads to (In)accurate predictions.

    PubMed

    Gagné, F M; Lydon, J E

    2001-07-01

    The authors investigated whether mind-set influences the accuracy of relationship predictions. Because people are more biased in their information processing when thinking about implementing an important goal, relationship predictions made in an implemental mind-set were expected to be less accurate than those made in a more impartial deliberative mind-set. In Study 1, open-ended thoughts of students about to leave for university were coded for mind-set. In Study 2, mind-set about a major life goal was assessed using a self-report measure. In Study 3, mind-set was experimentally manipulated. Overall, mind-set interacted with forecasts to predict relationship survival. Forecasts were more accurate in a deliberative mind-set than in an implemental mind-set. This effect was more pronounced for long-term than for short-term relationship survival. Finally, deliberatives were not pessimistic; implementals were unduly optimistic.

  8. Multiple Off-Ice Performance Variables Predict On-Ice Skating Performance in Male and Female Division III Ice Hockey Players.

    PubMed

    Janot, Jeffrey M; Beltz, Nicholas M; Dalleck, Lance D

    2015-09-01

    The purpose of this study was to determine if off-ice performance variables could predict on-ice skating performance in Division III collegiate hockey players. Both men (n = 15) and women (n = 11) hockey players (age = 20.5 ± 1.4 years) participated in the study. The skating tests were agility cornering S-turn, 6.10 m acceleration, 44.80 m speed, modified repeat skate, and 15.20 m full speed. Off-ice variables assessed were years of playing experience, height, weight and percent body fat and off-ice performance variables included vertical jump (VJ), 40-yd dash (36.58m), 1-RM squat, pro-agility, Wingate peak power and peak power percentage drop (% drop), and 1.5 mile (2.4km) run. Results indicated that 40-yd dash (36.58m), VJ, 1.5 mile (2.4km) run, and % drop were significant predictors of skating performance for repeat skate (slowest, fastest, and average time) and 44.80 m speed time, respectively. Four predictive equations were derived from multiple regression analyses: 1) slowest repeat skate time = 2.362 + (1.68 x 40-yd dash time) + (0.005 x 1.5 mile run), 2) fastest repeat skate time = 9.762 - (0.089 x VJ) - (0.998 x 40-yd dash time), 3) average repeat skate time = 7.770 + (1.041 x 40-yd dash time) - (0.63 x VJ) + (0.003 x 1.5 mile time), and 4) 47.85 m speed test = 7.707 - (0.050 x VJ) - (0.01 x % drop). It was concluded that selected off-ice tests could be used to predict on-ice performance regarding speed and recovery ability in Division III male and female hockey players. Key pointsThe 40-yd dash (36.58m) and vertical jump tests are significant predictors of on-ice skating performance specific to speed.In addition to 40-yd dash and vertical jump, the 1.5 mile (2.4km) run for time and percent power drop from the Wingate anaerobic power test were also significant predictors of skating performance that incorporates the aspect of recovery from skating activity.Due to the specificity of selected off-ice variables as predictors of on-ice performance, coaches can

  9. Multiple Off-Ice Performance Variables Predict On-Ice Skating Performance in Male and Female Division III Ice Hockey Players

    PubMed Central

    Janot, Jeffrey M.; Beltz, Nicholas M.; Dalleck, Lance D.

    2015-01-01

    The purpose of this study was to determine if off-ice performance variables could predict on-ice skating performance in Division III collegiate hockey players. Both men (n = 15) and women (n = 11) hockey players (age = 20.5 ± 1.4 years) participated in the study. The skating tests were agility cornering S-turn, 6.10 m acceleration, 44.80 m speed, modified repeat skate, and 15.20 m full speed. Off-ice variables assessed were years of playing experience, height, weight and percent body fat and off-ice performance variables included vertical jump (VJ), 40-yd dash (36.58m), 1-RM squat, pro-agility, Wingate peak power and peak power percentage drop (% drop), and 1.5 mile (2.4km) run. Results indicated that 40-yd dash (36.58m), VJ, 1.5 mile (2.4km) run, and % drop were significant predictors of skating performance for repeat skate (slowest, fastest, and average time) and 44.80 m speed time, respectively. Four predictive equations were derived from multiple regression analyses: 1) slowest repeat skate time = 2.362 + (1.68 x 40-yd dash time) + (0.005 x 1.5 mile run), 2) fastest repeat skate time = 9.762 - (0.089 x VJ) - (0.998 x 40-yd dash time), 3) average repeat skate time = 7.770 + (1.041 x 40-yd dash time) - (0.63 x VJ) + (0.003 x 1.5 mile time), and 4) 47.85 m speed test = 7.707 - (0.050 x VJ) - (0.01 x % drop). It was concluded that selected off-ice tests could be used to predict on-ice performance regarding speed and recovery ability in Division III male and female hockey players. Key points The 40-yd dash (36.58m) and vertical jump tests are significant predictors of on-ice skating performance specific to speed. In addition to 40-yd dash and vertical jump, the 1.5 mile (2.4km) run for time and percent power drop from the Wingate anaerobic power test were also significant predictors of skating performance that incorporates the aspect of recovery from skating activity. Due to the specificity of selected off-ice variables as predictors of on-ice performance, coaches

  10. Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases.

    PubMed

    Pagán, Josué; Risco-Martín, José L; Moya, José M; Ayala, José L

    2016-08-01

    Prediction of symptomatic crises in chronic diseases allows to take decisions before the symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of medical alarms. The prediction horizon is in this case an important parameter in order to fulfill the pharmacokinetics of medications, or the time response of medical services. This paper presents a study about the prediction limits of a chronic disease with symptomatic crises: the migraine. For that purpose, this work develops a methodology to build predictive migraine models and to improve these predictions beyond the limits of the initial models. The maximum prediction horizon is analyzed, and its dependency on the selected features is studied. A strategy for model selection is proposed to tackle the trade off between conservative but robust predictive models, with respect to less accurate predictions with higher horizons. The obtained results show a prediction horizon close to 40min, which is in the time range of the drug pharmacokinetics. Experiments have been performed in a realistic scenario where input data have been acquired in an ambulatory clinical study by the deployment of a non-intrusive Wireless Body Sensor Network. Our results provide an effective methodology for the selection of the future horizon in the development of prediction algorithms for diseases experiencing symptomatic crises. PMID:27260782

  11. SIFTER search: a web server for accurate phylogeny-based protein function prediction.

    PubMed

    Sahraeian, Sayed M; Luo, Kevin R; Brenner, Steven E

    2015-07-01

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. The SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.

  12. A method of predicting flow rates required to achieve anti-icing performance with a porous leading edge ice protection system

    NASA Technical Reports Server (NTRS)

    Kohlman, D. L.

    1983-01-01

    A proposed method of analytically predicting the minimum fluid flow rate required to provide anti-ice protection with a porous leading edge system on a wing under a given set of flight conditions is presented. Results of the proposed method are compared with the actual results of an icing test of a real wing section in the NASA Lewis Icing Research Tunnel.

  13. On the possibility and predictability of rapid Arctic winter sea-ice loss

    NASA Astrophysics Data System (ADS)

    Bathiany, Sebastian; Notz, Dirk; Mauritsen, Thorsten; Raedel, Gaby; Brovkin, Victor; van der Bolt, Bregje; Scheffer, Marten; van Nes, Egbert; Williamson, Mark; Lenton, Tim

    2016-04-01

    We examine the transition from a seasonally ice-covered Arctic to an Arctic Ocean that is sea-ice free all year round under increasing atmospheric CO2 levels. Using two column models and nine Earth System Models, we investigate how rapid such Arctic winter sea-ice loss can be, and whether an abrupt ice loss can be predicted from observed trends in variance or autocorrelation. Such statistical indicators have been proposed as early warning signals of abrupt shifts that are caused by positive feedbacks. We show that in comprehensive climate models, the loss of winter sea-ice area is faster than the preceding loss of summer sea-ice area for the same rate of warming. In two of the models, several million km2 of winter sea ice are lost within only one decade. Their behaviour resembles the catastrophic winter ice loss in a column model where the stable ice-covered state suddenly disappears at a bifurcation point, implying an irreversible and abrupt shift to the ice-free solution. However, we argue that winter sea-ice loss in comprehensive models is reversible and not associated with the existence of multiple steady states. The large sensitivity of winter sea-ice area in complex models is caused by the asymmetry between melting and freezing: An ice-free summer requires the complete melt of even the thickest sea ice, which is why the perennial ice coverage decreases only gradually as more and more of the thinner ice melts away. In winter, however, sea-ice areal coverage remains high as long as sea ice still forms, and then drops to zero wherever the ocean warms sufficiently to no longer form ice during winter. As this mechanism occurs in every model we analyse and is independent of any specific parameterisation, it is likely to be relevant in the real world. We also find that expected trends in variance and autocorrelation of sea-ice area and thickness are not specific to the existence or the mechanism of abrupt ice loss. For example, natural fluctuations of ice volume

  14. A Single Linear Prediction Filter that Accurately Predicts the AL Index

    NASA Astrophysics Data System (ADS)

    McPherron, R. L.; Chu, X.

    2015-12-01

    The AL index is a measure of the strength of the westward electrojet flowing along the auroral oval. It has two components: one from the global DP-2 current system and a second from the DP-1 current that is more localized near midnight. It is generally believed that the index a very poor measure of these currents because of its dependence on the distance of stations from the source of the two currents. In fact over season and solar cycle the coupling strength defined as the steady state ratio of the output AL to the input coupling function varies by a factor of four. There are four factors that lead to this variation. First is the equinoctial effect that modulates coupling strength with peaks (strongest coupling) at the equinoxes. Second is the saturation of the polar cap potential which decreases coupling strength as the strength of the driver increases. Since saturation occurs more frequently at solar maximum we obtain the result that maximum coupling strength occurs at equinox at solar minimum. A third factor is ionospheric conductivity with stronger coupling at summer solstice as compared to winter. The fourth factor is the definition of a solar wind coupling function appropriate to a given index. We have developed an optimum coupling function depending on solar wind speed, density, transverse magnetic field, and IMF clock angle which is better than previous functions. Using this we have determined the seasonal variation of coupling strength and developed an inverse function that modulates the optimum coupling function so that all seasonal variation is removed. In a similar manner we have determined the dependence of coupling strength on solar wind driver strength. The inverse of this function is used to scale a linear prediction filter thus eliminating the dependence on driver strength. Our result is a single linear filter that is adjusted in a nonlinear manner by driver strength and an optimum coupling function that is seasonal modulated. Together this

  15. A review of the kinetic detail required for accurate predictions of normal shock waves

    NASA Technical Reports Server (NTRS)

    Muntz, E. P.; Erwin, Daniel A.; Pham-Van-diep, Gerald C.

    1991-01-01

    Several aspects of the kinetic models used in the collision phase of Monte Carlo direct simulations have been studied. Accurate molecular velocity distribution function predictions require a significantly increased number of computational cells in one maximum slope shock thickness, compared to predictions of macroscopic properties. The shape of the highly repulsive portion of the interatomic potential for argon is not well modeled by conventional interatomic potentials; this portion of the potential controls high Mach number shock thickness predictions, indicating that the specification of the energetic repulsive portion of interatomic or intermolecular potentials must be chosen with care for correct modeling of nonequilibrium flows at high temperatures. It has been shown for inverse power potentials that the assumption of variable hard sphere scattering provides accurate predictions of the macroscopic properties in shock waves, by comparison with simulations in which differential scattering is employed in the collision phase. On the other hand, velocity distribution functions are not well predicted by the variable hard sphere scattering model for softer potentials at higher Mach numbers.

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

    NASA Astrophysics Data System (ADS)

    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

  17. How predictable is the timing of a summer ice-free Arctic?

    NASA Astrophysics Data System (ADS)

    Jahn, Alexandra; Kay, Jennifer E.; Holland, Marika M.; Hall, David M.

    2016-09-01

    Climate model simulations give a large range of over 100 years for predictions of when the Arctic could first become ice free in the summer, and many studies have attempted to narrow this uncertainty range. However, given the chaotic nature of the climate system, what amount of spread in the prediction of an ice-free summer Arctic is inevitable? Based on results from large ensemble simulations with the Community Earth System Model, we show that internal variability alone leads to a prediction uncertainty of about two decades, while scenario uncertainty between the strong (Representative Concentration Pathway (RCP) 8.5) and medium (RCP4.5) forcing scenarios adds at least another 5 years. Common metrics of the past and present mean sea ice state (such as ice extent, volume, and thickness) as well as global mean temperatures do not allow a reduction of the prediction uncertainty from internal variability.

  18. Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break.

    PubMed

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

    2016-10-01

    The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. 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 endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future. PMID:27272707

  19. Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break.

    PubMed

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

    2016-10-01

    The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. 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 endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future.

  20. Arctic Sea ice model sensitivities.

    SciTech Connect

    Peterson, Kara J.; Bochev, Pavel Blagoveston; Paskaleva, Biliana Stefanova

    2010-12-01

    Arctic sea ice is an important component of the global climate system and, due to feedback effects, the Arctic ice cover is changing rapidly. Predictive mathematical models are of paramount importance for accurate estimates of the future ice trajectory. However, the sea ice components of Global Climate Models (GCMs) vary significantly in their prediction of the future state of Arctic sea ice and have generally underestimated the rate of decline in minimum sea ice extent seen over the past thirty years. One of the contributing factors to this variability is the sensitivity of the sea ice state to internal model parameters. A new sea ice model that holds some promise for improving sea ice predictions incorporates an anisotropic elastic-decohesive rheology and dynamics solved using the material-point method (MPM), which combines Lagrangian particles for advection with a background grid for gradient computations. We evaluate the variability of this MPM sea ice code and compare it with the Los Alamos National Laboratory CICE code for a single year simulation of the Arctic basin using consistent ocean and atmospheric forcing. Sensitivities of ice volume, ice area, ice extent, root mean square (RMS) ice speed, central Arctic ice thickness,and central Arctic ice speed with respect to ten different dynamic and thermodynamic parameters are evaluated both individually and in combination using the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA). We find similar responses for the two codes and some interesting seasonal variability in the strength of the parameters on the solution.

  1. Accurate similarity index based on activity and connectivity of node for link prediction

    NASA Astrophysics Data System (ADS)

    Li, Longjie; Qian, Lvjian; Wang, Xiaoping; Luo, Shishun; Chen, Xiaoyun

    2015-05-01

    Recent years have witnessed the increasing of available network data; however, much of those data is incomplete. Link prediction, which can find the missing links of a network, plays an important role in the research and analysis of complex networks. Based on the assumption that two unconnected nodes which are highly similar are very likely to have an interaction, most of the existing algorithms solve the link prediction problem by computing nodes' similarities. The fundamental requirement of those algorithms is accurate and effective similarity indices. In this paper, we propose a new similarity index, namely similarity based on activity and connectivity (SAC), which performs link prediction more accurately. To compute the similarity between two nodes, this index employs the average activity of these two nodes in their common neighborhood and the connectivities between them and their common neighbors. The higher the average activity is and the stronger the connectivities are, the more similar the two nodes are. The proposed index not only commendably distinguishes the contributions of paths but also incorporates the influence of endpoints. Therefore, it can achieve a better predicting result. To verify the performance of SAC, we conduct experiments on 10 real-world networks. Experimental results demonstrate that SAC outperforms the compared baselines.

  2. Predicting Clear-Sky Reflectance Over Snow/Ice in Polar Regions

    NASA Technical Reports Server (NTRS)

    Chen, Yan; Sun-Mack, Sunny; Arduini, Robert F.; Hong, Gang; Minnis, Patrick

    2015-01-01

    Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the nearinfrared (NIR; 1.24, 1.6 or 2.13 micrometers), visible (VIS; 0.63 micrometers) and vegetation (VEG; 0.86 micrometers) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to help identify clouds and retrieve their properties in both snow-free and snow-covered conditions. Thus, it is critical to have reliable distributions of clear-sky albedo for all of these channels. In CERES Edition 4 (Ed4), the 1.24-micrometer channel is used to retrieve cloud optical depth over snow/ice-covered surfaces. Thus, it is especially critical to accurately predict the 1.24-micrometer clear-sky albedo alpha and reflectance rho for a given location and time. Snow albedo and reflectance patterns are very complex due to surface texture, particle shapes and sizes, melt water, and vegetation protrusions from the snow surface. To minimize those effects, this study focuses on the permanent snow cover of Antarctica where vegetation is absent and melt water is minimal. Clear-sky albedos are determined as a function of solar zenith angle (SZA) from observations over all scenes determined to be cloud-free to produce a normalized directional albedo model (DRM). The DRM is used to develop alpha(SZA=0 degrees) on 10 foot grid for each season. These values provide the basis for predicting r at any location and set of viewing & illumination conditions. This paper examines the accuracy of this approach for two theoretical snow surface reflectance models.

  3. Sea ice occurrence predicts genetic isolation in the Arctic fox.

    PubMed

    Geffen, Eli; Waidyaratne, Sitara; Dalén, Love; Angerbjörn, Anders; Vila, Carles; Hersteinsson, Pall; Fuglei, Eva; White, Paula A; Goltsman, Michael; Kapel, Christian M O; Wayne, Robert K

    2007-10-01

    Unlike Oceanic islands, the islands of the Arctic Sea are not completely isolated from migration by terrestrial vertebrates. The pack ice connects many Arctic Sea islands to the mainland during winter months. The Arctic fox (Alopex lagopus), which has a circumpolar distribution, populates numerous islands in the Arctic Sea. In this study, we used genetic data from 20 different populations, spanning the entire distribution of the Arctic fox, to identify barriers to dispersal. Specifically, we considered geographical distance, occurrence of sea ice, winter temperature, ecotype, and the presence of red fox and polar bear as nonexclusive factors that influence the dispersal behaviour of individuals. Using distance-based redundancy analysis and the BIOENV procedure, we showed that occurrence of sea ice is the key predictor and explained 40-60% of the genetic distance among populations. In addition, our analysis identified the Commander and Pribilof Islands Arctic populations as genetically unique suggesting they deserve special attention from a conservation perspective.

  4. Sea ice occurrence predicts genetic isolation in the Arctic fox.

    PubMed

    Geffen, Eli; Waidyaratne, Sitara; Dalén, Love; Angerbjörn, Anders; Vila, Carles; Hersteinsson, Pall; Fuglei, Eva; White, Paula A; Goltsman, Michael; Kapel, Christian M O; Wayne, Robert K

    2007-10-01

    Unlike Oceanic islands, the islands of the Arctic Sea are not completely isolated from migration by terrestrial vertebrates. The pack ice connects many Arctic Sea islands to the mainland during winter months. The Arctic fox (Alopex lagopus), which has a circumpolar distribution, populates numerous islands in the Arctic Sea. In this study, we used genetic data from 20 different populations, spanning the entire distribution of the Arctic fox, to identify barriers to dispersal. Specifically, we considered geographical distance, occurrence of sea ice, winter temperature, ecotype, and the presence of red fox and polar bear as nonexclusive factors that influence the dispersal behaviour of individuals. Using distance-based redundancy analysis and the BIOENV procedure, we showed that occurrence of sea ice is the key predictor and explained 40-60% of the genetic distance among populations. In addition, our analysis identified the Commander and Pribilof Islands Arctic populations as genetically unique suggesting they deserve special attention from a conservation perspective. PMID:17868292

  5. Accurate prediction of the linear viscoelastic properties of highly entangled mono and bidisperse polymer melts.

    PubMed

    Stephanou, Pavlos S; Mavrantzas, Vlasis G

    2014-06-01

    We present a hierarchical computational methodology which permits the accurate prediction of the linear viscoelastic properties of entangled polymer melts directly from the chemical structure, chemical composition, and molecular architecture of the constituent chains. The method entails three steps: execution of long molecular dynamics simulations with moderately entangled polymer melts, self-consistent mapping of the accumulated trajectories onto a tube model and parameterization or fine-tuning of the model on the basis of detailed simulation data, and use of the modified tube model to predict the linear viscoelastic properties of significantly higher molecular weight (MW) melts of the same polymer. Predictions are reported for the zero-shear-rate viscosity η0 and the spectra of storage G'(ω) and loss G″(ω) moduli for several mono and bidisperse cis- and trans-1,4 polybutadiene melts as well as for their MW dependence, and are found to be in remarkable agreement with experimentally measured rheological data. PMID:24908037

  6. Accurate prediction of the linear viscoelastic properties of highly entangled mono and bidisperse polymer melts

    NASA Astrophysics Data System (ADS)

    Stephanou, Pavlos S.; Mavrantzas, Vlasis G.

    2014-06-01

    We present a hierarchical computational methodology which permits the accurate prediction of the linear viscoelastic properties of entangled polymer melts directly from the chemical structure, chemical composition, and molecular architecture of the constituent chains. The method entails three steps: execution of long molecular dynamics simulations with moderately entangled polymer melts, self-consistent mapping of the accumulated trajectories onto a tube model and parameterization or fine-tuning of the model on the basis of detailed simulation data, and use of the modified tube model to predict the linear viscoelastic properties of significantly higher molecular weight (MW) melts of the same polymer. Predictions are reported for the zero-shear-rate viscosity η0 and the spectra of storage G'(ω) and loss G″(ω) moduli for several mono and bidisperse cis- and trans-1,4 polybutadiene melts as well as for their MW dependence, and are found to be in remarkable agreement with experimentally measured rheological data.

  7. Prediction of ice shapes and their effect on airfoil performance

    NASA Technical Reports Server (NTRS)

    Shin, Jaiwon; Berkowitz, Brian; Chen, Hsun H.; Cebeci, Tuncer

    1991-01-01

    Calculations of ice shapes and the resulting drag increases are presented for experimental data on an NACA 0012 airfoil. They were made with a combination of LEWICE and interactive boundary-layer codes for a wide range of conditions which include airspeed and temperature, the droplet size and liquid water content of the cloud, and the angle of attack of the airfoil. In all cases the calculated results account for the drag increase due to ice accretion and, in general, show good agreement with data.

  8. Prediction of ice shapes and their effect on airfoil performance

    NASA Technical Reports Server (NTRS)

    Shin, Jaiwon; Berkowitz, Brian; Chen, Hsun; Cebeci, Tuncer

    1991-01-01

    Calculations of ice shapes and the resulting drag increases are presented for experimental data on a NACA 0012 airfoil. They were made with a combination of LEWICE and interactive boundary-layer codes for a wide range of conditions which include air speed and temperature, the droplet size and liquid water content of the cloud, and the angle of attack of the airfoil. In all cases, the calculated results account for the drag increase due to ice accretion and, in general, show good agreement.

  9. Seasonal sea ice predictions for the Arctic based on assimilation of remotely sensed observations

    NASA Astrophysics Data System (ADS)

    Kauker, F.; Kaminski, T.; Ricker, R.; Toudal-Pedersen, L.; Dybkjaer, G.; Melsheimer, C.; Eastwood, S.; Sumata, H.; Karcher, M.; Gerdes, R.

    2015-10-01

    The recent thinning and shrinking of the Arctic sea ice cover has increased the interest in seasonal sea ice forecasts. Typical tools for such forecasts are numerical models of the coupled ocean sea ice system such as the North Atlantic/Arctic Ocean Sea Ice Model (NAOSIM). The model uses as input the initial state of the system and the atmospheric boundary condition over the forecasting period. This study investigates the potential of remotely sensed ice thickness observations in constraining the initial model state. For this purpose it employs a variational assimilation system around NAOSIM and the Alfred Wegener Institute's CryoSat-2 ice thickness product in conjunction with the University of Bremen's snow depth product and the OSI SAF ice concentration and sea surface temperature products. We investigate the skill of predictions of the summer ice conditions starting in March for three different years. Straightforward assimilation of the above combination of data streams results in slight improvements over some regions (especially in the Beaufort Sea) but degrades the over-all fit to independent observations. A considerable enhancement of forecast skill is demonstrated for a bias correction scheme for the CryoSat-2 ice thickness product that uses a spatially varying scaling factor.

  10. Prediction of Accurate Thermochemistry of Medium and Large Sized Radicals Using Connectivity-Based Hierarchy (CBH).

    PubMed

    Sengupta, Arkajyoti; Raghavachari, Krishnan

    2014-10-14

    Accurate modeling of the chemical reactions in many diverse areas such as combustion, photochemistry, or atmospheric chemistry strongly depends on the availability of thermochemical information of the radicals involved. However, accurate thermochemical investigations of radical systems using state of the art composite methods have mostly been restricted to the study of hydrocarbon radicals of modest size. In an alternative approach, systematic error-canceling thermochemical hierarchy of reaction schemes can be applied to yield accurate results for such systems. In this work, we have extended our connectivity-based hierarchy (CBH) method to the investigation of radical systems. We have calibrated our method using a test set of 30 medium sized radicals to evaluate their heats of formation. The CBH-rad30 test set contains radicals containing diverse functional groups as well as cyclic systems. We demonstrate that the sophisticated error-canceling isoatomic scheme (CBH-2) with modest levels of theory is adequate to provide heats of formation accurate to ∼1.5 kcal/mol. Finally, we predict heats of formation of 19 other large and medium sized radicals for which the accuracy of available heats of formation are less well-known. PMID:26588131

  11. Users manual for the NASA Lewis Ice Accretion Prediction Code (LEWICE)

    NASA Technical Reports Server (NTRS)

    Ruff, Gary A.; Berkowitz, Brian M.

    1990-01-01

    LEWICE is an ice accretion prediction code that applies a time-stepping procedure to calculate the shape of an ice accretion. The potential flow field is calculated in LEWICE using the Douglas Hess-Smith 2-D panel code (S24Y). This potential flow field is then used to calculate the trajectories of particles and the impingement points on the body. These calculations are performed to determine the distribution of liquid water impinging on the body, which then serves as input to the icing thermodynamic code. The icing thermodynamic model is based on the work of Messinger, but contains several major modifications and improvements. This model is used to calculate the ice growth rate at each point on the surface of the geometry. By specifying an icing time increment, the ice growth rate can be interpreted as an ice thickness which is added to the body, resulting in the generation of new coordinates. This procedure is repeated, beginning with the potential flow calculations, until the desired icing time is reached. The operation of LEWICE is illustrated through the use of five examples. These examples are representative of the types of applications expected for LEWICE. All input and output is discussed, along with many of the diagnostic messages contained in the code. Several error conditions that may occur in the code for certain icing conditions are identified, and a course of action is recommended. LEWICE has been used to calculate a variety of ice shapes, but should still be considered a research code. The code should be exercised further to identify any shortcomings and inadequacies. Any modifications identified as a result of these cases, or of additional experimental results, should be incorporated into the model. Using it as a test bed for improvements to the ice accretion model is one important application of LEWICE.

  12. The importance of spring atmospheric conditions for predictions of the Arctic summer sea ice extent

    NASA Astrophysics Data System (ADS)

    Kapsch, Marie-Luise; Graversen, Rune G.; Economou, Theodoros; Tjernström, Michael

    2014-07-01

    Recent studies have shown that atmospheric processes in spring play an important role for the initiation of the summer ice melt and therefore may strongly influence the September sea ice concentration (SSIC). Here a simple statistical regression model based on only atmospheric spring parameters is applied in order to predict the SSIC over the major part of the Arctic Ocean. By using spring anomalies of downwelling longwave radiation or atmospheric water vapor as predictor variables, correlation coefficients between observed and predicted SSIC of up to 0.5 are found. These skills of seasonal SSIC predictions are similar to those obtained using more complex dynamical forecast systems, despite the fact that the simple model applied here takes neither information of the sea ice state, oceanic conditions nor feedback mechanisms during summer into account. The results indicate that a realistic representation of spring atmospheric conditions in the prediction system plays an important role for the predictive skills of a model system.

  13. A Novel Method for Accurate Operon Predictions in All SequencedProkaryotes

    SciTech Connect

    Price, Morgan N.; Huang, Katherine H.; Alm, Eric J.; Arkin, Adam P.

    2004-12-01

    We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83% accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacterpylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, and its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from sixphylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC6803 has many operons even though it has unusually wide spacings between conserved adjacent genes.

  14. Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space.

    PubMed

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; von Lilienfeld, O Anatole; Müller, Klaus-Robert; Tkatchenko, Alexandre

    2015-06-18

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. In addition, the same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.

  15. Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

    SciTech Connect

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; von Lilienfeld, O. Anatole; Müller, Klaus -Robert; Tkatchenko, Alexandre

    2015-06-04

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.

  16. Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

    DOE PAGES

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; von Lilienfeld, O. Anatole; Müller, Klaus -Robert; Tkatchenko, Alexandre

    2015-06-04

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstratemore » prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.« less

  17. Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

    PubMed Central

    2015-01-01

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. In addition, the same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies. PMID:26113956

  18. Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

    NASA Technical Reports Server (NTRS)

    Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

    2011-01-01

    A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

  19. A seamless approach to understanding and predicting Arctic sea ice in Met Office modelling systems.

    PubMed

    Hewitt, Helene T; Ridley, Jeff K; Keen, Ann B; West, Alex E; Peterson, K Andrew; Rae, Jamie G L; Milton, Sean F; Bacon, Sheldon

    2015-07-13

    Recent CMIP5 models predict large losses of summer Arctic sea ice, with only mitigation scenarios showing sustainable summer ice. Sea ice is inherently part of the climate system, and heat fluxes affecting sea ice can be small residuals of much larger air-sea fluxes. We discuss analysis of energy budgets in the Met Office climate models which point to the importance of early summer processes (such as clouds and meltponds) in determining both the seasonal cycle and the trend in ice decline. We give examples from Met Office modelling systems to illustrate how the seamless use of models for forecasting on time scales from short range to decadal might help to unlock the drivers of high latitude biases in climate models.

  20. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    DOE PAGES

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-05-15

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less

  1. Accurate Prediction of Severe Allergic Reactions by a Small Set of Environmental Parameters (NDVI, Temperature)

    PubMed Central

    Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

    2015-01-01

    Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions. PMID:25794106

  2. SIFTER search: a web server for accurate phylogeny-based protein function prediction.

    PubMed

    Sahraeian, Sayed M; Luo, Kevin R; Brenner, Steven E

    2015-07-01

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. The SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded. PMID:25979264

  3. Microstructure-Dependent Gas Adsorption: Accurate Predictions of Methane Uptake in Nanoporous Carbons

    SciTech Connect

    Ihm, Yungok; Cooper, Valentino R; Gallego, Nidia C; Contescu, Cristian I; Morris, James R

    2014-01-01

    We demonstrate a successful, efficient framework for predicting gas adsorption properties in real materials based on first-principles calculations, with a specific comparison of experiment and theory for methane adsorption in activated carbons. These carbon materials have different pore size distributions, leading to a variety of uptake characteristics. Utilizing these distributions, we accurately predict experimental uptakes and heats of adsorption without empirical potentials or lengthy simulations. We demonstrate that materials with smaller pores have higher heats of adsorption, leading to a higher gas density in these pores. This pore-size dependence must be accounted for, in order to predict and understand the adsorption behavior. The theoretical approach combines: (1) ab initio calculations with a van der Waals density functional to determine adsorbent-adsorbate interactions, and (2) a thermodynamic method that predicts equilibrium adsorption densities by directly incorporating the calculated potential energy surface in a slit pore model. The predicted uptake at P=20 bar and T=298 K is in excellent agreement for all five activated carbon materials used. This approach uses only the pore-size distribution as an input, with no fitting parameters or empirical adsorbent-adsorbate interactions, and thus can be easily applied to other adsorbent-adsorbate combinations.

  4. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    SciTech Connect

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-05-15

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.

  5. Change in heat capacity accurately predicts vibrational coupling in enzyme catalyzed reactions.

    PubMed

    Arcus, Vickery L; Pudney, Christopher R

    2015-08-01

    The temperature dependence of kinetic isotope effects (KIEs) have been used to infer the vibrational coupling of the protein and or substrate to the reaction coordinate, particularly in enzyme-catalyzed hydrogen transfer reactions. We find that a new model for the temperature dependence of experimentally determined observed rate constants (macromolecular rate theory, MMRT) is able to accurately predict the occurrence of vibrational coupling, even where the temperature dependence of the KIE fails. This model, that incorporates the change in heat capacity for enzyme catalysis, demonstrates remarkable consistency with both experiment and theory and in many respects is more robust than models used at present.

  6. Accurate verification of the conserved-vector-current and standard-model predictions

    SciTech Connect

    Sirlin, A.; Zucchini, R.

    1986-10-20

    An approximate analytic calculation of O(Z..cap alpha../sup 2/) corrections to Fermi decays is presented. When the analysis of Koslowsky et al. is modified to take into account the new results, it is found that each of the eight accurately studied scrFt values differs from the average by approx. <1sigma, thus significantly improving the comparison of experiments with conserved-vector-current predictions. The new scrFt values are lower than before, which also brings experiments into very good agreement with the three-generation standard model, at the level of its quantum corrections.

  7. Implementation of a one-dimensional enthalpy sea-ice model in a simple pycnocline prediction model for sea-ice data assimilation studies

    NASA Astrophysics Data System (ADS)

    Wu, Xinrong; Zhang, Shaoqing; Liu, Zhengyu

    2016-02-01

    To further explore enthalpy-based sea-ice assimilation, a one-dimensional (1D) enthalpy sea-ice model is implemented into a simple pycnocline prediction model. The 1D enthalpy sea-ice model includes the physical processes such as brine expulsion, flushing, and salt diffusion. After being coupled with the atmosphere and ocean components, the enthalpy sea-ice model can be integrated stably and serves as an important modulator of model variability. Results from a twin experiment show that the sea-ice data assimilation in the enthalpy space can produce smaller root-mean-square errors of model variables than the traditional scheme that assimilates the observations of ice concentration, especially for slow-varying states. This study provides some insights into the improvement of sea-ice data assimilation in a coupled general circulation model.

  8. Importance of initial conditions in seasonal predictions of Arctic sea ice extent

    NASA Astrophysics Data System (ADS)

    Msadek, R.; Vecchi, G. A.; Winton, M.; Gudgel, R. G.

    2014-07-01

    We present seasonal predictions of Arctic sea ice extent (SIE) over the 1982-2013 period using two suites of retrospective forecasts initialized from a fully coupled ocean-atmosphere-sea ice assimilation system. High skill scores are found in predicting year-to-year fluctuations of Arctic SIE, with significant correlations up to 7 month ahead for September detrended anomalies. Predictions over the recent era, which coincides with an improved observational coverage, outperform the earlier period for most target months. We find, however, a degradation of skill in September during the last decade, a period of sea ice thinning in observations. The two prediction models, Climate Model version 2.1 (CM2.1) and Forecast-oriented Low Ocean Resolution (FLOR), share very similar ocean and ice component and initialization but differ by their atmospheric component. FLOR has improved climatological atmospheric circulation and sea ice mean state, but its skill is overall similar to CM2.1 for most seasons, which suggests a key role for initial conditions in predicting seasonal SIE fluctuations.

  9. ILT based defect simulation of inspection images accurately predicts mask defect printability on wafer

    NASA Astrophysics Data System (ADS)

    Deep, Prakash; Paninjath, Sankaranarayanan; Pereira, Mark; Buck, Peter

    2016-05-01

    At advanced technology nodes mask complexity has been increased because of large-scale use of resolution enhancement technologies (RET) which includes Optical Proximity Correction (OPC), Inverse Lithography Technology (ILT) and Source Mask Optimization (SMO). The number of defects detected during inspection of such mask increased drastically and differentiation of critical and non-critical defects are more challenging, complex and time consuming. Because of significant defectivity of EUVL masks and non-availability of actinic inspection, it is important and also challenging to predict the criticality of defects for printability on wafer. This is one of the significant barriers for the adoption of EUVL for semiconductor manufacturing. Techniques to decide criticality of defects from images captured using non actinic inspection images is desired till actinic inspection is not available. High resolution inspection of photomask images detects many defects which are used for process and mask qualification. Repairing all defects is not practical and probably not required, however it's imperative to know which defects are severe enough to impact wafer before repair. Additionally, wafer printability check is always desired after repairing a defect. AIMSTM review is the industry standard for this, however doing AIMSTM review for all defects is expensive and very time consuming. Fast, accurate and an economical mechanism is desired which can predict defect printability on wafer accurately and quickly from images captured using high resolution inspection machine. Predicting defect printability from such images is challenging due to the fact that the high resolution images do not correlate with actual mask contours. The challenge is increased due to use of different optical condition during inspection other than actual scanner condition, and defects found in such images do not have correlation with actual impact on wafer. Our automated defect simulation tool predicts

  10. Toward an Accurate Prediction of the Arrival Time of Geomagnetic-Effective Coronal Mass Ejections

    NASA Astrophysics Data System (ADS)

    Shi, T.; Wang, Y.; Wan, L.; Cheng, X.; Ding, M.; Zhang, J.

    2015-12-01

    Accurately predicting the arrival of coronal mass ejections (CMEs) to the Earth based on remote images is of critical significance for the study of space weather. Here we make a statistical study of 21 Earth-directed CMEs, specifically exploring the relationship between CME initial speeds and transit times. The initial speed of a CME is obtained by fitting the CME with the Graduated Cylindrical Shell model and is thus free of projection effects. We then use the drag force model to fit results of the transit time versus the initial speed. By adopting different drag regimes, i.e., the viscous, aerodynamics, and hybrid regimes, we get similar results, with a least mean estimation error of the hybrid model of 12.9 hr. CMEs with a propagation angle (the angle between the propagation direction and the Sun-Earth line) larger than their half-angular widths arrive at the Earth with an angular deviation caused by factors other than the radial solar wind drag. The drag force model cannot be reliably applied to such events. If we exclude these events in the sample, the prediction accuracy can be improved, i.e., the estimation error reduces to 6.8 hr. This work suggests that it is viable to predict the arrival time of CMEs to the Earth based on the initial parameters with fairly good accuracy. Thus, it provides a method of forecasting space weather 1-5 days following the occurrence of CMEs.

  11. Intermolecular potentials and the accurate prediction of the thermodynamic properties of water

    SciTech Connect

    Shvab, I.; Sadus, Richard J.

    2013-11-21

    The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g/cm{sup 3} for a wide range of temperatures (298–650 K) and pressures (0.1–700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC/E and TIP4P/2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys. 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC/E and TIP4P/2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.

  12. Predictability of winter temperature in China from previous autumn Arctic sea ice

    NASA Astrophysics Data System (ADS)

    Zuo, Jinqing; Ren, Hong-Li; Wu, Bingyi; Li, Weijing

    2016-10-01

    The potential predictability of winter temperature in China from autumn Arctic sea ice anomalies is studied by examining and statistically modeling the large-scale interannual covariability between them on the basis of singular value decomposition analysis. It is demonstrated that an intimate relationship exists between September and October sea ice anomalies in the Eurasian Arctic and following winter temperature anomalies in China, except in the Tibetan Plateau. When the autumn sea ice anomalies decline in the Eurasian Arctic, above-normal pressure anomalies appear to prevail over the region from the Eurasian Arctic to Eastern Europe and Mongolia, and below-normal anomalies prevail over the mid-latitudes of Asia and Northwestern Pacific in the following winter. Consequently, the winter Siberian High and East Asian trough are both strengthened, favoring the southward invasion of high-latitude cold air masses and thus cold temperature anomalies in China. It is found that the Siberian High plays a crucial role in delivering effects of the autumn Arctic sea ice anomalies on winter temperature variability in China. Based on this evidence, a statistical model is established to examine the potential predictability of winter temperature anomalies in China by taking the autumn Arctic sea ice signals as a predictor. Validation shows considerable skill in predicting winter temperature anomalies over a large part of China, indicating a significant potential for improving winter climate prediction in China.

  13. Predictions replaced by facts: a keystone species' behavioural responses to declining arctic sea-ice.

    PubMed

    Hamilton, Charmain D; Lydersen, Christian; Ims, Rolf A; Kovacs, Kit M

    2015-11-01

    Since the first documentation of climate-warming induced declines in arctic sea-ice, predictions have been made regarding the expected negative consequences for endemic marine mammals. But, several decades later, little hard evidence exists regarding the responses of these animals to the ongoing environmental changes. Herein, we report the first empirical evidence of a dramatic shift in movement patterns and foraging behaviour of the arctic endemic ringed seal (Pusa hispida), before and after a major collapse in sea-ice in Svalbard, Norway. Among other changes to the ice-regime, this collapse shifted the summer position of the marginal ice zone from over the continental shelf, northward to the deep Arctic Ocean Basin. Following this change, which is thought to be a 'tipping point', subadult ringed seals swam greater distances, showed less area-restricted search behaviour, dived for longer periods, exhibited shorter surface intervals, rested less on sea-ice and did less diving directly beneath the ice during post-moulting foraging excursions. In combination, these behavioural changes suggest increased foraging effort and thus also likely increases in the energetic costs of finding food. Continued declines in sea-ice are likely to result in distributional changes, range reductions and population declines in this keystone arctic species. PMID:26582841

  14. Analysis and Prediction of Ice Shedding for a Full-Scale Heated Tail Rotor

    NASA Technical Reports Server (NTRS)

    Kreeger, Richard E.; Work, Andrew; Douglass, Rebekah; Gazella, Matthew; Koster, Zakery; Turk, Jodi

    2016-01-01

    When helicopters are to fly in icing conditions, it is necessary to consider the possibility of ice shed from the rotor blades. In 2013, a series of tests were conducted on a heated tail rotor at NASA Glenn's Icing Research Tunnel (IRT). The tests produced several shed events that were captured on camera. Three of these shed events were captured at a sufficiently high frame rate to obtain multiple images of the shed ice in flight that had a sufficiently long section of shed ice for analysis. Analysis of these shed events is presented and compared to an analytical Shedding Trajectory Model (STM). The STM is developed and assumes that the ice breaks off instantly as it reaches the end of the blade, while frictional and viscous forces are used as parameters to fit the STM. The trajectory of each shed is compared to that predicted by the STM, where the STM provides information of the shed group of ice as a whole. The limitations of the model's underlying assumptions are discussed in comparison to experimental shed events.

  15. Predictions replaced by facts: a keystone species' behavioural responses to declining arctic sea-ice.

    PubMed

    Hamilton, Charmain D; Lydersen, Christian; Ims, Rolf A; Kovacs, Kit M

    2015-11-01

    Since the first documentation of climate-warming induced declines in arctic sea-ice, predictions have been made regarding the expected negative consequences for endemic marine mammals. But, several decades later, little hard evidence exists regarding the responses of these animals to the ongoing environmental changes. Herein, we report the first empirical evidence of a dramatic shift in movement patterns and foraging behaviour of the arctic endemic ringed seal (Pusa hispida), before and after a major collapse in sea-ice in Svalbard, Norway. Among other changes to the ice-regime, this collapse shifted the summer position of the marginal ice zone from over the continental shelf, northward to the deep Arctic Ocean Basin. Following this change, which is thought to be a 'tipping point', subadult ringed seals swam greater distances, showed less area-restricted search behaviour, dived for longer periods, exhibited shorter surface intervals, rested less on sea-ice and did less diving directly beneath the ice during post-moulting foraging excursions. In combination, these behavioural changes suggest increased foraging effort and thus also likely increases in the energetic costs of finding food. Continued declines in sea-ice are likely to result in distributional changes, range reductions and population declines in this keystone arctic species.

  16. An Evaluation of the Seasonal Arctic Sea Ice Predictions from CFSv2

    NASA Astrophysics Data System (ADS)

    Yang, Q.; Wang, M.; Overland, J. E.

    2015-12-01

    The rapid reductions in Arctic sea ice have been observed in the past several decades, especially at the end of the summer melt season in September. It is necessary to have a reliable seasonal forecast of Arctic sea ice. In this study, we examined the Arctic sea ice predictions produced by NCEP Climate Forecast System version 2 (CFSv2) in the real- time operational mode. Forecasts were initialized monthly for two-year period (March 2014 to September 2015). Forecasts of sea ice extent (SIE) and concentration (SIC) were evaluated against the sea ice analysis (HadISST_ice) from the Hadley Center. We found that the Arctic September SIE forecasts from CFS were overestimated with the biases in SIC mainly originated from the Beaufort Sea, Laptev Sea and Fram Strait. For 2014, we found that the forecast initialized from March with the lead-time of 6 months gave the best September SIE forecast while the forecast initialized from July with the lead-time of 2 months had the worst September SIE forecast. In order to understand the forecast biases in September sea ice, the atmospheric forecasted forcings including incoming solar/Infrared radiation, upward solar/infrared radiation from surface, latent and sensible heat flux, 2-meter air temperature, cloud fraction, sea level pressure and 10-meter wind from CFSv2 were evaluated using the European Center for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) .

  17. Predictions replaced by facts: a keystone species' behavioural responses to declining arctic sea-ice

    PubMed Central

    Hamilton, Charmain D.; Lydersen, Christian; Ims, Rolf A.; Kovacs, Kit M.

    2015-01-01

    Since the first documentation of climate-warming induced declines in arctic sea-ice, predictions have been made regarding the expected negative consequences for endemic marine mammals. But, several decades later, little hard evidence exists regarding the responses of these animals to the ongoing environmental changes. Herein, we report the first empirical evidence of a dramatic shift in movement patterns and foraging behaviour of the arctic endemic ringed seal (Pusa hispida), before and after a major collapse in sea-ice in Svalbard, Norway. Among other changes to the ice-regime, this collapse shifted the summer position of the marginal ice zone from over the continental shelf, northward to the deep Arctic Ocean Basin. Following this change, which is thought to be a ‘tipping point’, subadult ringed seals swam greater distances, showed less area-restricted search behaviour, dived for longer periods, exhibited shorter surface intervals, rested less on sea-ice and did less diving directly beneath the ice during post-moulting foraging excursions. In combination, these behavioural changes suggest increased foraging effort and thus also likely increases in the energetic costs of finding food. Continued declines in sea-ice are likely to result in distributional changes, range reductions and population declines in this keystone arctic species. PMID:26582841

  18. A fast and accurate method to predict 2D and 3D aerodynamic boundary layer flows

    NASA Astrophysics Data System (ADS)

    Bijleveld, H. A.; Veldman, A. E. P.

    2014-12-01

    A quasi-simultaneous interaction method is applied to predict 2D and 3D aerodynamic flows. This method is suitable for offshore wind turbine design software as it is a very accurate and computationally reasonably cheap method. This study shows the results for a NACA 0012 airfoil. The two applied solvers converge to the experimental values when the grid is refined. We also show that in separation the eigenvalues remain positive thus avoiding the Goldstein singularity at separation. In 3D we show a flow over a dent in which separation occurs. A rotating flat plat is used to show the applicability of the method for rotating flows. The shown capabilities of the method indicate that the quasi-simultaneous interaction method is suitable for design methods for offshore wind turbine blades.

  19. Distance scaling method for accurate prediction of slowly varying magnetic fields in satellite missions

    NASA Astrophysics Data System (ADS)

    Zacharias, Panagiotis P.; Chatzineofytou, Elpida G.; Spantideas, Sotirios T.; Capsalis, Christos N.

    2016-07-01

    In the present work, the determination of the magnetic behavior of localized magnetic sources from near-field measurements is examined. The distance power law of the magnetic field fall-off is used in various cases to accurately predict the magnetic signature of an equipment under test (EUT) consisting of multiple alternating current (AC) magnetic sources. Therefore, parameters concerning the location of the observation points (magnetometers) are studied towards this scope. The results clearly show that these parameters are independent of the EUT's size and layout. Additionally, the techniques developed in the present study enable the placing of the magnetometers close to the EUT, thus achieving high signal-to-noise ratio (SNR). Finally, the proposed method is verified by real measurements, using a mobile phone as an EUT.

  20. Differential contribution of visual and auditory information to accurately predict the direction and rotational motion of a visual stimulus.

    PubMed

    Park, Seoung Hoon; Kim, Seonjin; Kwon, MinHyuk; Christou, Evangelos A

    2016-03-01

    Vision and auditory information are critical for perception and to enhance the ability of an individual to respond accurately to a stimulus. However, it is unknown whether visual and auditory information contribute differentially to identify the direction and rotational motion of the stimulus. The purpose of this study was to determine the ability of an individual to accurately predict the direction and rotational motion of the stimulus based on visual and auditory information. In this study, we recruited 9 expert table-tennis players and used table-tennis service as our experimental model. Participants watched recorded services with different levels of visual and auditory information. The goal was to anticipate the direction of the service (left or right) and the rotational motion of service (topspin, sidespin, or cut). We recorded their responses and quantified the following outcomes: (i) directional accuracy and (ii) rotational motion accuracy. The response accuracy was the accurate predictions relative to the total number of trials. The ability of the participants to predict the direction of the service accurately increased with additional visual information but not with auditory information. In contrast, the ability of the participants to predict the rotational motion of the service accurately increased with the addition of auditory information to visual information but not with additional visual information alone. In conclusion, this finding demonstrates that visual information enhances the ability of an individual to accurately predict the direction of the stimulus, whereas additional auditory information enhances the ability of an individual to accurately predict the rotational motion of stimulus.

  1. In vitro transcription accurately predicts lac repressor phenotype in vivo in Escherichia coli

    PubMed Central

    2014-01-01

    A multitude of studies have looked at the in vivo and in vitro behavior of the lac repressor binding to DNA and effector molecules in order to study transcriptional repression, however these studies are not always reconcilable. Here we use in vitro transcription to directly mimic the in vivo system in order to build a self consistent set of experiments to directly compare in vivo and in vitro genetic repression. A thermodynamic model of the lac repressor binding to operator DNA and effector is used to link DNA occupancy to either normalized in vitro mRNA product or normalized in vivo fluorescence of a regulated gene, YFP. An accurate measurement of repressor, DNA and effector concentrations were made both in vivo and in vitro allowing for direct modeling of the entire thermodynamic equilibrium. In vivo repression profiles are accurately predicted from the given in vitro parameters when molecular crowding is considered. Interestingly, our measured repressor–operator DNA affinity differs significantly from previous in vitro measurements. The literature values are unable to replicate in vivo binding data. We therefore conclude that the repressor-DNA affinity is much weaker than previously thought. This finding would suggest that in vitro techniques that are specifically designed to mimic the in vivo process may be necessary to replicate the native system. PMID:25097824

  2. Measuring solar reflectance Part I: Defining a metric that accurately predicts solar heat gain

    SciTech Connect

    Levinson, Ronnen; Akbari, Hashem; Berdahl, Paul

    2010-05-14

    Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, solar position and atmospheric conditions. A widely used solar reflectance metric based on the ASTM Standard E891 beam-normal solar spectral irradiance underestimates the solar heat gain of a spectrally selective 'cool colored' surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland U.S. latitudes, this metric RE891BN can underestimate the annual peak solar heat gain of a typical roof or pavement (slope {le} 5:12 [23{sup o}]) by as much as 89 W m{sup -2}, and underestimate its peak surface temperature by up to 5 K. Using R{sub E891BN} to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool-roof net energy savings by as much as 23%. We define clear-sky air mass one global horizontal ('AM1GH') solar reflectance R{sub g,0}, a simple and easily measured property that more accurately predicts solar heat gain. R{sub g,0} predicts the annual peak solar heat gain of a roof or pavement to within 2 W m{sup -2}, and overestimates N by no more than 3%. R{sub g,0} is well suited to rating the solar reflectances of roofs, pavements and walls. We show in Part II that R{sub g,0} can be easily and accurately measured with a pyranometer, a solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer.

  3. Measuring solar reflectance - Part I: Defining a metric that accurately predicts solar heat gain

    SciTech Connect

    Levinson, Ronnen; Akbari, Hashem; Berdahl, Paul

    2010-09-15

    Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, solar position and atmospheric conditions. A widely used solar reflectance metric based on the ASTM Standard E891 beam-normal solar spectral irradiance underestimates the solar heat gain of a spectrally selective ''cool colored'' surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland US latitudes, this metric R{sub E891BN} can underestimate the annual peak solar heat gain of a typical roof or pavement (slope {<=} 5:12 [23 ]) by as much as 89 W m{sup -2}, and underestimate its peak surface temperature by up to 5 K. Using R{sub E891BN} to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool roof net energy savings by as much as 23%. We define clear sky air mass one global horizontal (''AM1GH'') solar reflectance R{sub g,0}, a simple and easily measured property that more accurately predicts solar heat gain. R{sub g,0} predicts the annual peak solar heat gain of a roof or pavement to within 2 W m{sup -2}, and overestimates N by no more than 3%. R{sub g,0} is well suited to rating the solar reflectances of roofs, pavements and walls. We show in Part II that R{sub g,0} can be easily and accurately measured with a pyranometer, a solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer. (author)

  4. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics

    PubMed Central

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru

    2016-01-01

    Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research. PMID:27571061

  5. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics.

    PubMed

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru

    2016-01-01

    Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research. PMID:27571061

  6. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics.

    PubMed

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru

    2016-01-01

    Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research.

  7. Accurate prediction of solvent accessibility using neural networks-based regression.

    PubMed

    Adamczak, Rafał; Porollo, Aleksey; Meller, Jarosław

    2004-09-01

    Accurate prediction of relative solvent accessibilities (RSAs) of amino acid residues in proteins may be used to facilitate protein structure prediction and functional annotation. Toward that goal we developed a novel method for improved prediction of RSAs. Contrary to other machine learning-based methods from the literature, we do not impose a classification problem with arbitrary boundaries between the classes. Instead, we seek a continuous approximation of the real-value RSA using nonlinear regression, with several feed forward and recurrent neural networks, which are then combined into a consensus predictor. A set of 860 protein structures derived from the PFAM database was used for training, whereas validation of the results was carefully performed on several nonredundant control sets comprising a total of 603 structures derived from new Protein Data Bank structures and had no homology to proteins included in the training. Two classes of alternative predictors were developed for comparison with the regression-based approach: one based on the standard classification approach and the other based on a semicontinuous approximation with the so-called thermometer encoding. Furthermore, a weighted approximation, with errors being scaled by the observed levels of variability in RSA for equivalent residues in families of homologous structures, was applied in order to improve the results. The effects of including evolutionary profiles and the growth of sequence databases were assessed. In accord with the observed levels of variability in RSA for different ranges of RSA values, the regression accuracy is higher for buried than for exposed residues, with overall 15.3-15.8% mean absolute errors and correlation coefficients between the predicted and experimental values of 0.64-0.67 on different control sets. The new method outperforms classification-based algorithms when the real value predictions are projected onto two-class classification problems with several commonly

  8. Measurements and full-field predictions of deformation heterogeneities in ice

    NASA Astrophysics Data System (ADS)

    Montagnat, Maurine; Blackford, Jane R.; Piazolo, Sandra; Arnaud, Laurent; Lebensohn, Ricardo A.

    2011-05-01

    We have made creep experiments on columnar grained ice and characterised the microstructure and intragranular misorientations over a range of length scales. A FFT full-field model was used to predict the deformation behaviour, using the experimentally characterised microstructure as the starting material. This is the first time this combination of techniques has been used to study the deformation of ice. The microstructure was characterised at the cm scale using an optical technique, the automatic ice texture analyser AITA and at the micron scale using electron backscattered diffraction EBSD. The crystallographic texture and intragranular misorientations were fully characterised by EBSD (3 angles). The deformed microstructure frequently showed straight subgrain boundaries often originating at triple points. These were identified as kink bands, and for the first time we have measured the precise misorientation of the kink bands and deduced the nature of the dislocations responsible for them. These dislocations have a basal edge nature and align in contiguous prismatic planes enabling deformation along the c-axis. In addition, non-uniform grain boundaries and regions of recrystallization were seen. We present coupling between fine scale characterization of intragranular misorientations, from experiments, and prediction of internal stresses that cause it. The model predicts the morphology of the observed local misorientations within the grains, however it over predicts the misorientation values. This is because the annealing and recrystallization mechanisms are not taken into account in the model. Ice is excellent as a model material for measuring, predicting and understanding deformation behaviour for polycrystalline materials. Specifically for ice this knowledge is needed to improve models of ice sheet dynamics that are important for climatic signal interpretation.

  9. A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina.

    PubMed

    Maturana, Matias I; Apollo, Nicholas V; Hadjinicolaou, Alex E; Garrett, David J; Cloherty, Shaun L; Kameneva, Tatiana; Grayden, David B; Ibbotson, Michael R; Meffin, Hamish

    2016-04-01

    Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron's electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. PMID:27035143

  10. Accurate load prediction by BEM with airfoil data from 3D RANS simulations

    NASA Astrophysics Data System (ADS)

    Schneider, Marc S.; Nitzsche, Jens; Hennings, Holger

    2016-09-01

    In this paper, two methods for the extraction of airfoil coefficients from 3D CFD simulations of a wind turbine rotor are investigated, and these coefficients are used to improve the load prediction of a BEM code. The coefficients are extracted from a number of steady RANS simulations, using either averaging of velocities in annular sections, or an inverse BEM approach for determination of the induction factors in the rotor plane. It is shown that these 3D rotor polars are able to capture the rotational augmentation at the inner part of the blade as well as the load reduction by 3D effects close to the blade tip. They are used as input to a simple BEM code and the results of this BEM with 3D rotor polars are compared to the predictions of BEM with 2D airfoil coefficients plus common empirical corrections for stall delay and tip loss. While BEM with 2D airfoil coefficients produces a very different radial distribution of loads than the RANS simulation, the BEM with 3D rotor polars manages to reproduce the loads from RANS very accurately for a variety of load cases, as long as the blade pitch angle is not too different from the cases from which the polars were extracted.

  11. A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina

    PubMed Central

    Maturana, Matias I.; Apollo, Nicholas V.; Hadjinicolaou, Alex E.; Garrett, David J.; Cloherty, Shaun L.; Kameneva, Tatiana; Grayden, David B.; Ibbotson, Michael R.; Meffin, Hamish

    2016-01-01

    Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron’s electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. PMID:27035143

  12. ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

    SciTech Connect

    Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.

    2009-02-01

    A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

  13. Accurate First-Principles Spectra Predictions for Planetological and Astrophysical Applications at Various T-Conditions

    NASA Astrophysics Data System (ADS)

    Rey, M.; Nikitin, A. V.; Tyuterev, V.

    2014-06-01

    Knowledge of near infrared intensities of rovibrational transitions of polyatomic molecules is essential for the modeling of various planetary atmospheres, brown dwarfs and for other astrophysical applications 1,2,3. For example, to analyze exoplanets, atmospheric models have been developed, thus making the need to provide accurate spectroscopic data. Consequently, the spectral characterization of such planetary objects relies on the necessity of having adequate and reliable molecular data in extreme conditions (temperature, optical path length, pressure). On the other hand, in the modeling of astrophysical opacities, millions of lines are generally involved and the line-by-line extraction is clearly not feasible in laboratory measurements. It is thus suggested that this large amount of data could be interpreted only by reliable theoretical predictions. There exists essentially two theoretical approaches for the computation and prediction of spectra. The first one is based on empirically-fitted effective spectroscopic models. Another way for computing energies, line positions and intensities is based on global variational calculations using ab initio surfaces. They do not yet reach the spectroscopic accuracy stricto sensu but implicitly account for all intramolecular interactions including resonance couplings in a wide spectral range. The final aim of this work is to provide reliable predictions which could be quantitatively accurate with respect to the precision of available observations and as complete as possible. All this thus requires extensive first-principles quantum mechanical calculations essentially based on three necessary ingredients which are (i) accurate intramolecular potential energy surface and dipole moment surface components well-defined in a large range of vibrational displacements and (ii) efficient computational methods combined with suitable choices of coordinates to account for molecular symmetry properties and to achieve a good numerical

  14. Development of a New Model for Accurate Prediction of Cloud Water Deposition on Vegetation

    NASA Astrophysics Data System (ADS)

    Katata, G.; Nagai, H.; Wrzesinsky, T.; Klemm, O.; Eugster, W.; Burkard, R.

    2006-12-01

    Scarcity of water resources in arid and semi-arid areas is of great concern in the light of population growth and food shortages. Several experiments focusing on cloud (fog) water deposition on the land surface suggest that cloud water plays an important role in water resource in such regions. A one-dimensional vegetation model including the process of cloud water deposition on vegetation has been developed to better predict cloud water deposition on the vegetation. New schemes to calculate capture efficiency of leaf, cloud droplet size distribution, and gravitational flux of cloud water were incorporated in the model. Model calculations were compared with the data acquired at the Norway spruce forest at the Waldstein site, Germany. High performance of the model was confirmed by comparisons of calculated net radiation, sensible and latent heat, and cloud water fluxes over the forest with measurements. The present model provided a better prediction of measured turbulent and gravitational fluxes of cloud water over the canopy than the Lovett model, which is a commonly used cloud water deposition model. Detailed calculations of evapotranspiration and of turbulent exchange of heat and water vapor within the canopy and the modifications are necessary for accurate prediction of cloud water deposition. Numerical experiments to examine the dependence of cloud water deposition on the vegetation species (coniferous and broad-leaved trees, flat and cylindrical grasses) and structures (Leaf Area Index (LAI) and canopy height) are performed using the presented model. The results indicate that the differences of leaf shape and size have a large impact on cloud water deposition. Cloud water deposition also varies with the growth of vegetation and seasonal change of LAI. We found that the coniferous trees whose height and LAI are 24 m and 2.0 m2m-2, respectively, produce the largest amount of cloud water deposition in all combinations of vegetation species and structures in the

  15. Predicting Land-Ice Retreat and Sea-Level Rise with the Community Earth System Model

    SciTech Connect

    Lipscomb, William

    2012-06-19

    Coastal stakeholders need defensible predictions of 21st century sea-level rise (SLR). IPCC assessments suggest 21st century SLR of {approx}0.5 m under aggressive emission scenarios. Semi-empirical models project SLR of {approx}1 m or more by 2100. Although some sea-level contributions are fairly well constrained by models, others are highly uncertain. Recent studies suggest a potential large contribution ({approx}0.5 m/century) from the marine-based West Antarctic Ice Sheet, linked to changes in Southern Ocean wind stress. To assess the likelihood of fast retreat of marine ice sheets, we need coupled ice-sheet/ocean models that do not yet exist (but are well under way). CESM is uniquely positioned to provide integrated, physics based sea-level predictions.

  16. Can radiation therapy treatment planning system accurately predict surface doses in postmastectomy radiation therapy patients?

    SciTech Connect

    Wong, Sharon; Back, Michael; Tan, Poh Wee; Lee, Khai Mun; Baggarley, Shaun; Lu, Jaide Jay

    2012-07-01

    Skin doses have been an important factor in the dose prescription for breast radiotherapy. Recent advances in radiotherapy treatment techniques, such as intensity-modulated radiation therapy (IMRT) and new treatment schemes such as hypofractionated breast therapy have made the precise determination of the surface dose necessary. Detailed information of the dose at various depths of the skin is also critical in designing new treatment strategies. The purpose of this work was to assess the accuracy of surface dose calculation by a clinically used treatment planning system and those measured by thermoluminescence dosimeters (TLDs) in a customized chest wall phantom. This study involved the construction of a chest wall phantom for skin dose assessment. Seven TLDs were distributed throughout each right chest wall phantom to give adequate representation of measured radiation doses. Point doses from the CMS Xio Registered-Sign treatment planning system (TPS) were calculated for each relevant TLD positions and results correlated. There were no significant difference between measured absorbed dose by TLD and calculated doses by the TPS (p > 0.05 (1-tailed). Dose accuracy of up to 2.21% was found. The deviations from the calculated absorbed doses were overall larger (3.4%) when wedges and bolus were used. 3D radiotherapy TPS is a useful and accurate tool to assess the accuracy of surface dose. Our studies have shown that radiation treatment accuracy expressed as a comparison between calculated doses (by TPS) and measured doses (by TLD dosimetry) can be accurately predicted for tangential treatment of the chest wall after mastectomy.

  17. Using timing of ice retreat to predict timing of fall freeze-up in the Arctic

    NASA Astrophysics Data System (ADS)

    Stroeve, Julienne C.; Crawford, Alex D.; Stammerjohn, Sharon

    2016-06-01

    Reliable forecasts of the timing of sea ice advance are needed in order to reduce risks associated with operating in the Arctic as well as planning of human and environmental emergencies. This study investigates the use of a simple statistical model relating the timing of ice retreat to the timing of ice advance, taking advantage of the inherent predictive power supplied by the seasonal ice-albedo feedback and ocean heat uptake. Results show that using the last retreat date to predict the first advance date is applicable in some regions, such as Baffin Bay and the Laptev and East Siberian seas, where a predictive skill is found even after accounting for the long-term trend in both variables. Elsewhere, in the Arctic, there is some predictive skills depending on the year (e.g., Kara and Beaufort seas), but none in regions such as the Barents and Bering seas or the Sea of Okhotsk. While there is some suggestion that the relationship is strengthening over time, this may reflect that higher correlations are expected during periods when the underlying trend is strong.

  18. Full-field predictions of ice dynamic recrystallisation under simple shear conditions

    NASA Astrophysics Data System (ADS)

    Llorens, Maria-Gema; Griera, Albert; Bons, Paul D.; Lebensohn, Ricardo A.; Evans, Lynn A.; Jansen, Daniela; Weikusat, Ilka

    2016-09-01

    Understanding the flow of ice on the microstructural scale is essential for improving our knowledge of large-scale ice dynamics, and thus our ability to predict future changes of ice sheets. Polar ice behaves anisotropically during flow, which can lead to strain localisation. In order to study how dynamic recrystallisation affects to strain localisation in deep levels of polar ice sheets, we present a series of numerical simulations of ice polycrystals deformed under simple-shear conditions. The models explicitly simulate the evolution of microstructures using a full-field approach, based on the coupling of a viscoplastic deformation code (VPFFT) with dynamic recrystallisation codes. The simulations provide new insights into the distribution of stress, strain rate and lattice orientation fields with progressive strain, up to a shear strain of three. Our simulations show how the recrystallisation processes have a strong influence on the resulting microstructure (grain size and shape), while the development of lattice preferred orientations (LPO) appears to be less affected. Activation of non-basal slip systems is enhanced by recrystallisation and induces a strain hardening behaviour up to the onset of strain localisation and strain weakening behaviour. Simulations demonstrate that the strong intrinsic anisotropy of ice crystals is transferred to the polycrystalline scale and results in the development of strain localisation bands than can be masked by grain boundary migration. Therefore, the finite-strain history is non-directly reflected by the final microstructure. Masked strain localisation can be recognised in ice cores, such as the EDML, from the presence of stepped boundaries, microshear and grains with zig-zag geometries.

  19. From the single-scattering properties of ice crystals to climate prediction: A way forward

    NASA Astrophysics Data System (ADS)

    Baran, Anthony J.

    2012-08-01

    Cirrus is composed of non-spherical ice crystals, and against the blue background of the sky, they appear as tenuous wispy clouds, usually located at altitudes greater than about 6 km. Their spatial and temporal distribution about the Earth's atmosphere is significant. With such distributions, their contributions to the Earth's natural greenhouse effect and hydrological cycle are important. Therefore, it is important that climate models are able to predict the radiative effect of cirrus, as well as their contribution to the total amount of ice mass that occurs in the Earth's atmosphere. However, cirrus is composed of ice crystals that can take on a variety of geometrical shapes, from pristine habits such as hexagonal ice columns, hexagonal ice plates and bullet-rosettes, to highly randomized habits, which may have roughened surfaces and/or air cavities. These habits also aggregate together, to form chains of aggregates and compact aggregates. The sizes of these habits may also vary, from about less than 10 μm, to several cm, with the smaller ice crystals usually existing toward cloud-top and the larger ice crystals existing toward the cloud-bottom. Due to this variability of geometrical complexity, size, and ice mass, predicting the magnitude of the cirrus greenhouse effect has proven problematic. To try to constrain these radiative and hydrological uncertainties, since about 2006 there is now available the A-train constellation of satellites, which attempt to quantify the radiative and hydrological contributions of cirrus to the Earth's atmosphere. The A-train obtains nearly simultaneous measurements of cirrus from across the electromagnetic spectrum. Such simultaneous measurements pose challenges for theoretical scattering models of cirrus, as these models must conserve ice mass and be physically consistent across the electromagnetic spectrum. In this review paper, the microphysical properties of cirrus are summarized. The current idealized habit mixture models

  20. Predicting accurate fluorescent spectra for high molecular weight polycyclic aromatic hydrocarbons using density functional theory

    NASA Astrophysics Data System (ADS)

    Powell, Jacob; Heider, Emily C.; Campiglia, Andres; Harper, James K.

    2016-10-01

    The ability of density functional theory (DFT) methods to predict accurate fluorescence spectra for polycyclic aromatic hydrocarbons (PAHs) is explored. Two methods, PBE0 and CAM-B3LYP, are evaluated both in the gas phase and in solution. Spectra for several of the most toxic PAHs are predicted and compared to experiment, including three isomers of C24H14 and a PAH containing heteroatoms. Unusually high-resolution experimental spectra are obtained for comparison by analyzing each PAH at 4.2 K in an n-alkane matrix. All theoretical spectra visually conform to the profiles of the experimental data but are systematically offset by a small amount. Specifically, when solvent is included the PBE0 functional overestimates peaks by 16.1 ± 6.6 nm while CAM-B3LYP underestimates the same transitions by 14.5 ± 7.6 nm. These calculated spectra can be empirically corrected to decrease the uncertainties to 6.5 ± 5.1 and 5.7 ± 5.1 nm for the PBE0 and CAM-B3LYP methods, respectively. A comparison of computed spectra in the gas phase indicates that the inclusion of n-octane shifts peaks by +11 nm on average and this change is roughly equivalent for PBE0 and CAM-B3LYP. An automated approach for comparing spectra is also described that minimizes residuals between a given theoretical spectrum and all available experimental spectra. This approach identifies the correct spectrum in all cases and excludes approximately 80% of the incorrect spectra, demonstrating that an automated search of theoretical libraries of spectra may eventually become feasible.

  1. How accurately can we predict the melting points of drug-like compounds?

    PubMed

    Tetko, Igor V; Sushko, Yurii; Novotarskyi, Sergii; Patiny, Luc; Kondratov, Ivan; Petrenko, Alexander E; Charochkina, Larisa; Asiri, Abdullah M

    2014-12-22

    This article contributes a highly accurate model for predicting the melting points (MPs) of medicinal chemistry compounds. The model was developed using the largest published data set, comprising more than 47k compounds. The distributions of MPs in drug-like and drug lead sets showed that >90% of molecules melt within [50,250]°C. The final model calculated an RMSE of less than 33 °C for molecules from this temperature interval, which is the most important for medicinal chemistry users. This performance was achieved using a consensus model that performed calculations to a significantly higher accuracy than the individual models. We found that compounds with reactive and unstable groups were overrepresented among outlying compounds. These compounds could decompose during storage or measurement, thus introducing experimental errors. While filtering the data by removing outliers generally increased the accuracy of individual models, it did not significantly affect the results of the consensus models. Three analyzed distance to models did not allow us to flag molecules, which had MP values fell outside the applicability domain of the model. We believe that this negative result and the public availability of data from this article will encourage future studies to develop better approaches to define the applicability domain of models. The final model, MP data, and identified reactive groups are available online at http://ochem.eu/article/55638.

  2. Fast and Accurate Prediction of Numerical Relativity Waveforms from Binary Black Hole Coalescences Using Surrogate Models.

    PubMed

    Blackman, Jonathan; Field, Scott E; Galley, Chad R; Szilágyi, Béla; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A

    2015-09-18

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _{-2}Y_{ℓm} waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M_{⊙} to 300M_{⊙} for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).

  3. Fast and Accurate Prediction of Numerical Relativity Waveforms from Binary Black Hole Coalescences Using Surrogate Models.

    PubMed

    Blackman, Jonathan; Field, Scott E; Galley, Chad R; Szilágyi, Béla; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A

    2015-09-18

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _{-2}Y_{ℓm} waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M_{⊙} to 300M_{⊙} for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases). PMID:26430979

  4. How accurately can we predict the melting points of drug-like compounds?

    PubMed

    Tetko, Igor V; Sushko, Yurii; Novotarskyi, Sergii; Patiny, Luc; Kondratov, Ivan; Petrenko, Alexander E; Charochkina, Larisa; Asiri, Abdullah M

    2014-12-22

    This article contributes a highly accurate model for predicting the melting points (MPs) of medicinal chemistry compounds. The model was developed using the largest published data set, comprising more than 47k compounds. The distributions of MPs in drug-like and drug lead sets showed that >90% of molecules melt within [50,250]°C. The final model calculated an RMSE of less than 33 °C for molecules from this temperature interval, which is the most important for medicinal chemistry users. This performance was achieved using a consensus model that performed calculations to a significantly higher accuracy than the individual models. We found that compounds with reactive and unstable groups were overrepresented among outlying compounds. These compounds could decompose during storage or measurement, thus introducing experimental errors. While filtering the data by removing outliers generally increased the accuracy of individual models, it did not significantly affect the results of the consensus models. Three analyzed distance to models did not allow us to flag molecules, which had MP values fell outside the applicability domain of the model. We believe that this negative result and the public availability of data from this article will encourage future studies to develop better approaches to define the applicability domain of models. The final model, MP data, and identified reactive groups are available online at http://ochem.eu/article/55638. PMID:25489863

  5. A survey of factors contributing to accurate theoretical predictions of atomization energies and molecular structures

    NASA Astrophysics Data System (ADS)

    Feller, David; Peterson, Kirk A.; Dixon, David A.

    2008-11-01

    High level electronic structure predictions of thermochemical properties and molecular structure are capable of accuracy rivaling the very best experimental measurements as a result of rapid advances in hardware, software, and methodology. Despite the progress, real world limitations require practical approaches designed for handling general chemical systems that rely on composite strategies in which a single, intractable calculation is replaced by a series of smaller calculations. As typically implemented, these approaches produce a final, or "best," estimate that is constructed from one major component, fine-tuned by multiple corrections that are assumed to be additive. Though individually much smaller than the original, unmanageable computational problem, these corrections are nonetheless extremely costly. This study presents a survey of the widely varying magnitude of the most important components contributing to the atomization energies and structures of 106 small molecules. It combines large Gaussian basis sets and coupled cluster theory up to quadruple excitations for all systems. In selected cases, the effects of quintuple excitations and/or full configuration interaction were also considered. The availability of reliable experimental data for most of the molecules permits an expanded statistical analysis of the accuracy of the approach. In cases where reliable experimental information is currently unavailable, the present results are expected to provide some of the most accurate benchmark values available.

  6. Accurate prediction of band gaps and optical properties of HfO2

    NASA Astrophysics Data System (ADS)

    Ondračka, Pavel; Holec, David; Nečas, David; Zajíčková, Lenka

    2016-10-01

    We report on optical properties of various polymorphs of hafnia predicted within the framework of density functional theory. The full potential linearised augmented plane wave method was employed together with the Tran-Blaha modified Becke-Johnson potential (TB-mBJ) for exchange and local density approximation for correlation. Unit cells of monoclinic, cubic and tetragonal crystalline, and a simulated annealing-based model of amorphous hafnia were fully relaxed with respect to internal positions and lattice parameters. Electronic structures and band gaps for monoclinic, cubic, tetragonal and amorphous hafnia were calculated using three different TB-mBJ parametrisations and the results were critically compared with the available experimental and theoretical reports. Conceptual differences between a straightforward comparison of experimental measurements to a calculated band gap on the one hand and to a whole electronic structure (density of electronic states) on the other hand, were pointed out, suggesting the latter should be used whenever possible. Finally, dielectric functions were calculated at two levels, using the random phase approximation without local field effects and with a more accurate Bethe-Salpether equation (BSE) to account for excitonic effects. We conclude that a satisfactory agreement with experimental data for HfO2 was obtained only in the latter case.

  7. Accurate age scale of the Dome Fuji ice core, Antarctica from O2/N2 ratio of trapped air

    NASA Astrophysics Data System (ADS)

    Kawamura, K.; Aoki, S.; Nakazawa, T.; Suzuki, K.; Parrenin, F.

    2012-04-01

    Chronology of the first Dome Fuji deep ice core (core length: 2,500 m, ice thickness: 3,035 m) for the age range from 80 kyr to 340 kyr ago was established by orbital tuning of measured O2/N2 ratios in trapped air to local summer insolation, with precision better than about 2,000 years (Kawamura et al., 2007). The O2/N2 ratios found in polar ice cores are slightly lower than the atmospheric ratio because of size-dependent molecular fractionation during bubble close-off. The magnitude of this gas fractionation is believed to be governed by the magnitude of snow metamorphism when the layer was originally at the surface, which in turn is controlled by local summer insolation (Fujita et al., 2009). A strong advantage of the O2/N2 chronology is that there is no need to assume a lag between climatic records in the ice core and orbital forcings, becacuse O2/N2 ratios record local insolation through physical processes. Accuracy of the chronology was validated by comparing the O2/N2 chronology with U-Th radiometric chronology of speleothem records (Cheng et al., 2009) for the ends of Terminations II, III and IV, as well as several large climatic events, for which both ice-core CH4 and speleothem δ18O (a proxy for precipitation) show abrupt shifts as seen in the last glacial period. All ages from O2/N2 and U-Th chronology agreed with each other within ~2,000 yr. The O2/N2 chronology permits comparisons between Antarctic climate, greenhouse gases, astronomically calculated orbital parameters, and radiometrically-dated sea level and monsoon records. Here, we completed the measurements of O2/N2 ratios of the second Dome Fuji ice core, which reached bedrock, for the range from 2,400 to 3,028 m (320 - 700 kyr ago) at approximately 2,000-year time resolution. We made significant improvements in ice core storage practices and mass spectrometry. In particular, the ice core samples were stored at about -50 ° C until the air extraction, except during short periods of transportation

  8. Accurate prediction of V1 location from cortical folds in a surface coordinate system

    PubMed Central

    Hinds, Oliver P.; Rajendran, Niranjini; Polimeni, Jonathan R.; Augustinack, Jean C.; Wiggins, Graham; Wald, Lawrence L.; Rosas, H. Diana; Potthast, Andreas; Schwartz, Eric L.; Fischl, Bruce

    2008-01-01

    Previous studies demonstrated substantial variability of the location of primary visual cortex (V1) in stereotaxic coordinates when linear volume-based registration is used to match volumetric image intensities (Amunts et al., 2000). However, other qualitative reports of V1 location (Smith, 1904; Stensaas et al., 1974; Rademacher et al., 1993) suggested a consistent relationship between V1 and the surrounding cortical folds. Here, the relationship between folds and the location of V1 is quantified using surface-based analysis to generate a probabilistic atlas of human V1. High-resolution (about 200 μm) magnetic resonance imaging (MRI) at 7 T of ex vivo human cerebral hemispheres allowed identification of the full area via the stria of Gennari: a myeloarchitectonic feature specific to V1. Separate, whole-brain scans were acquired using MRI at 1.5 T to allow segmentation and mesh reconstruction of the cortical gray matter. For each individual, V1 was manually identified in the high-resolution volume and projected onto the cortical surface. Surface-based intersubject registration (Fischl et al., 1999b) was performed to align the primary cortical folds of individual hemispheres to those of a reference template representing the average folding pattern. An atlas of V1 location was constructed by computing the probability of V1 inclusion for each cortical location in the template space. This probabilistic atlas of V1 exhibits low prediction error compared to previous V1 probabilistic atlases built in volumetric coordinates. The increased predictability observed under surface-based registration suggests that the location of V1 is more accurately predicted by the cortical folds than by the shape of the brain embedded in the volume of the skull. In addition, the high quality of this atlas provides direct evidence that surface-based intersubject registration methods are superior to volume-based methods at superimposing functional areas of cortex, and therefore are better

  9. Effects of solution composition on the theoretical prediction of ice nucleation kinetics and thermodynamics.

    PubMed

    Karlsson, Jens O M

    2010-02-01

    Predictions by various mathematical models of intracellular ice formation (proposed by Mazur, Pitt, Toner, and Karlsson, respectively) were compared to the known thermodynamic and kinetic behavior of ice formation in supercooled aqueous systems. The older models (Mazur, Pitt, and Toner) significantly underestimated the magnitude of colligative nonequilibrium freezing point depression in response to increased concentration of solutes, such as salts or cryoprotectants. Furthermore, kinetics predicted using phenomenological models (by Mazur and Pitt) exhibited implausible temperature-dependence, with the probability of intracellular ice formation being allowed to increase even at temperatures below the glass transition point. The Toner model, on the other hand, produced invalid results at temperatures below -48 degrees C. The Karlsson model was the only model that consistently yielded realistic predictions over a wide range of temperatures and solute concentrations, especially in the presence of cryoprotectant additives. To facilitate adoption of the Karlsson model of intracellular ice nucleation, the complete set of model equations has been collected and described in detail.

  10. Using Reanalysis Data for the Prediction of Seasonal Wind Turbine Power Losses Due to Icing

    NASA Astrophysics Data System (ADS)

    Burtch, D.; Mullendore, G. L.; Delene, D. J.; Storm, B.

    2013-12-01

    The Northern Plains region of the United States is home to a significant amount of potential wind energy. However, in winter months capturing this potential power is severely impacted by the meteorological conditions, in the form of icing. Predicting the expected loss in power production due to icing is a valuable parameter that can be used in wind turbine operations, determination of wind turbine site locations and long-term energy estimates which are used for financing purposes. Currently, losses due to icing must be estimated when developing predictions for turbine feasibility and financing studies, while icing maps, a tool commonly used in Europe, are lacking in the United States. This study uses the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset in conjunction with turbine production data to investigate various methods of predicting seasonal losses (October-March) due to icing at two wind turbine sites located 121 km apart in North Dakota. The prediction of icing losses is based on temperature and relative humidity thresholds and is accomplished using three methods. For each of the three methods, the required atmospheric variables are determined in one of two ways: using industry-specific software to correlate anemometer data in conjunction with the MERRA dataset and using only the MERRA dataset for all variables. For each season, a percentage of the total expected generated power lost due to icing is determined and compared to observed losses from the production data. An optimization is performed in order to determine the relative humidity threshold that minimizes the difference between the predicted and observed values. Eight seasons of data are used to determine an optimal relative humidity threshold, and a further three seasons of data are used to test this threshold. Preliminary results have shown that the optimized relative humidity threshold for the northern turbine is higher than the southern turbine for all methods

  11. Massive Late Noachian South Polar/Southern Upland Ice Deposits: Predictions and Tests of the Late Noachian "Cold and Icy Highlands" Model

    NASA Astrophysics Data System (ADS)

    Head, J. W.

    2016-09-01

    New Noachian climate models predict a "cold and icy highlands": glacial ice dominates the southern highlands around a huge south polar ice deposit. We document the predicted nature of these polar/circumpolar deposits and test it with observations.

  12. Reward sensitivity predicts ice cream-related attentional bias assessed by inattentional blindness.

    PubMed

    Li, Xiaoming; Tao, Qian; Fang, Ya; Cheng, Chen; Hao, Yangyang; Qi, Jianjun; Li, Yu; Zhang, Wei; Wang, Ying; Zhang, Xiaochu

    2015-06-01

    The cognitive mechanism underlying the association between individual differences in reward sensitivity and food craving is unknown. The present study explored the mechanism by examining the role of reward sensitivity in attentional bias toward ice cream cues. Forty-nine college students who displayed high level of ice cream craving (HICs) and 46 who displayed low level of ice cream craving (LICs) performed an inattentional blindness (IB) task which was used to assess attentional bias for ice cream. In addition, reward sensitivity and coping style were assessed by the Behavior Inhibition System/Behavior Activation System Scales and Simplified Coping Style Questionnaire. Results showed significant higher identification rate of the critical stimulus in the HICs than LICs, suggesting greater attentional bias for ice cream in the HICs. It was indicated that attentional bias for food cues persisted even under inattentional condition. Furthermore, a significant correlation was found between the attentional bias and reward sensitivity after controlling for coping style, and reward sensitivity predicted attentional bias for food cues. The mediation analyses showed that attentional bias mediated the relationship between reward sensitivity and food craving. Those findings suggest that the association between individual differences in reward sensitivity and food craving may be attributed to attentional bias for food-related cues.

  13. Unilateral Prostate Cancer Cannot be Accurately Predicted in Low-Risk Patients

    SciTech Connect

    Isbarn, Hendrik; Karakiewicz, Pierre I.; Vogel, Susanne

    2010-07-01

    Purpose: Hemiablative therapy (HAT) is increasing in popularity for treatment of patients with low-risk prostate cancer (PCa). The validity of this therapeutic modality, which exclusively treats PCa within a single prostate lobe, rests on accurate staging. We tested the accuracy of unilaterally unremarkable biopsy findings in cases of low-risk PCa patients who are potential candidates for HAT. Methods and Materials: The study population consisted of 243 men with clinical stage {<=}T2a, a prostate-specific antigen (PSA) concentration of <10 ng/ml, a biopsy-proven Gleason sum of {<=}6, and a maximum of 2 ipsilateral positive biopsy results out of 10 or more cores. All men underwent a radical prostatectomy, and pathology stage was used as the gold standard. Univariable and multivariable logistic regression models were tested for significant predictors of unilateral, organ-confined PCa. These predictors consisted of PSA, %fPSA (defined as the quotient of free [uncomplexed] PSA divided by the total PSA), clinical stage (T2a vs. T1c), gland volume, and number of positive biopsy cores (2 vs. 1). Results: Despite unilateral stage at biopsy, bilateral or even non-organ-confined PCa was reported in 64% of all patients. In multivariable analyses, no variable could clearly and independently predict the presence of unilateral PCa. This was reflected in an overall accuracy of 58% (95% confidence interval, 50.6-65.8%). Conclusions: Two-thirds of patients with unilateral low-risk PCa, confirmed by clinical stage and biopsy findings, have bilateral or non-organ-confined PCa at radical prostatectomy. This alarming finding questions the safety and validity of HAT.

  14. Improving DOE-2's RESYS routine: User defined functions to provide more accurate part load energy use and humidity predictions

    SciTech Connect

    Henderson, Hugh I.; Parker, Danny; Huang, Yu J.

    2000-08-04

    In hourly energy simulations, it is important to properly predict the performance of air conditioning systems over a range of full and part load operating conditions. An important component of these calculations is to properly consider the performance of the cycling air conditioner and how it interacts with the building. This paper presents improved approaches to properly account for the part load performance of residential and light commercial air conditioning systems in DOE-2. First, more accurate correlations are given to predict the degradation of system efficiency at part load conditions. In addition, a user-defined function for RESYS is developed that provides improved predictions of air conditioner sensible and latent capacity at part load conditions. The user function also provides more accurate predictions of space humidity by adding ''lumped'' moisture capacitance into the calculations. The improved cooling coil model and the addition of moisture capacitance predicts humidity swings that are more representative of the performance observed in real buildings.

  15. Arctic Sea Ice Model Sensitivities

    NASA Astrophysics Data System (ADS)

    Peterson, K. J.; Bochev, P.; Paskaleva, B.

    2010-12-01

    Arctic sea ice is an important component of the global climate system and, due to feedback effects, the Arctic ice cover is changing rapidly. Predictive mathematical models are of paramount importance for accurate estimates of the future ice trajectory. However, the sea ice components of Global Climate Models (GCMs) vary significantly in their prediction of the future state of Arctic sea ice and have generally underestimated the rate of decline in minimum sea ice extent seen over the past thirty years. One of the contributing factors to this variability is the sensitivity of the sea ice state to internal model parameters. A new sea ice model that holds some promise for improving sea ice predictions incorporates an anisotropic elastic-decohesive rheology and dynamics solved using the material-point method (MPM), which combines Lagrangian particles for advection with a background grid for gradient computations. We evaluate the variability of this MPM sea ice code and compare it with the Los Alamos National Laboratory CICE code for a single year simulation of the Arctic basin using consistent ocean and atmospheric forcing. Sensitivities of ice volume, ice area, ice extent, root mean square (RMS) ice speed, central Arctic ice thickness,and central Arctic ice speed with respect to ten different dynamic and thermodynamic parameters are evaluated both individually and in combination using the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA). We find similar responses for the two codes and some interesting seasonal variability in the strength of the parameters on the solution. Sandia National Laboratories is a multi-program laboratory operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U. S. Department of Energy’s National Nuclear Security Administration under Contract DE-AC04-94-AL85000.

  16. Accurate prediction model of bead geometry in crimping butt of the laser brazing using generalized regression neural network

    NASA Astrophysics Data System (ADS)

    Rong, Y. M.; Chang, Y.; Huang, Y.; Zhang, G. J.; Shao, X. Y.

    2015-12-01

    There are few researches that concentrate on the prediction of the bead geometry for laser brazing with crimping butt. This paper addressed the accurate prediction of the bead profile by developing a generalized regression neural network (GRNN) algorithm. Firstly GRNN model was developed and trained to decrease the prediction error that may be influenced by the sample size. Then the prediction accuracy was demonstrated by comparing with other articles and back propagation artificial neural network (BPNN) algorithm. Eventually the reliability and stability of GRNN model were discussed from the points of average relative error (ARE), mean square error (MSE) and root mean square error (RMSE), while the maximum ARE and MSE were 6.94% and 0.0303 that were clearly less than those (14.28% and 0.0832) predicted by BPNN. Obviously, it was proved that the prediction accuracy was improved at least 2 times, and the stability was also increased much more.

  17. Predictions of the onset of mini ice age in the 25th solar cycle

    NASA Astrophysics Data System (ADS)

    Kumar, Rajiv

    2016-07-01

    Predictions of the ir-regularty in the 11 year heartbeat of the sun due to asyncronous of the two layered dynamo effect would result in mini ice age as in the Maunder minimum.The onset of this event is expected in the begining of 25th solar cycle and would go to its maximum in the 26th solar cycle.The minimum temperature is expected in 2028 due to the fall of solar activity by 60 % termed as solar hibernation.The predictions are based on the observations obtained by the Royal Greenwich observatory since 1874. Keywords: Dynamo effect,munder minimum,Solar hybernation

  18. Towards more accurate wind and solar power prediction by improving NWP model physics

    NASA Astrophysics Data System (ADS)

    Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo

    2014-05-01

    The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during

  19. Quantum Chemical Study of the Reaction of C+ with Interstellar Ice: Predictions of Vibrational and Electronic Spectra of Reaction Products

    NASA Astrophysics Data System (ADS)

    Woon, David E.

    2015-06-01

    The C+ cation (CII) is the dominant form of carbon in diffuse clouds and an important tracer for star formation in molecular clouds. We studied the low energy deposition of C+ on ice using density functional theory calculations on water clusters as large as 18 H2O. Barrierless reactions occur with water to form two dominant sets of products: HOC + H3O+ and CO- + 2H3O+. In order to provide testable predictions, we have computed both vibrational and electronic spectra for pure ice and processed ice clusters. While vibrational spectroscopy is expected to be able to discern that C+ has reacted with ice by the addition of H3O+ features not present in pure ice, it does not provided characteristic bands that would discern between HOC and CO-. On the other hand, predictions of electronic spectra suggest that low energy absorptions may occur for CO- and not HOC, making it possible to distinguish one product from the other.

  20. A simple accurate method to predict time of ponding under variable intensity rainfall

    NASA Astrophysics Data System (ADS)

    Assouline, S.; Selker, J. S.; Parlange, J.-Y.

    2007-03-01

    The prediction of the time to ponding following commencement of rainfall is fundamental to hydrologic prediction of flood, erosion, and infiltration. Most of the studies to date have focused on prediction of ponding resulting from simple rainfall patterns. This approach was suitable to rainfall reported as average values over intervals of up to a day but does not take advantage of knowledge of the complex patterns of actual rainfall now commonly recorded electronically. A straightforward approach to include the instantaneous rainfall record in the prediction of ponding time and excess rainfall using only the infiltration capacity curve is presented. This method is tested against a numerical solution of the Richards equation on the basis of an actual rainfall record. The predicted time to ponding showed mean error ≤7% for a broad range of soils, with and without surface sealing. In contrast, the standard predictions had average errors of 87%, and worst-case errors exceeding a factor of 10. In addition to errors intrinsic in the modeling framework itself, errors that arise from averaging actual rainfall records over reporting intervals were evaluated. Averaging actual rainfall records observed in Israel over periods of as little as 5 min significantly reduced predicted runoff (75% for the sealed sandy loam and 46% for the silty clay loam), while hourly averaging gave complete lack of prediction of ponding in some of the cases.

  1. Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction.

    PubMed

    Braun, Tatjana; Koehler Leman, Julia; Lange, Oliver F

    2015-12-01

    Recent work has shown that the accuracy of ab initio structure prediction can be significantly improved by integrating evolutionary information in form of intra-protein residue-residue contacts. Following this seminal result, much effort is put into the improvement of contact predictions. However, there is also a substantial need to develop structure prediction protocols tailored to the type of restraints gained by contact predictions. Here, we present a structure prediction protocol that combines evolutionary information with the resolution-adapted structural recombination approach of Rosetta, called RASREC. Compared to the classic Rosetta ab initio protocol, RASREC achieves improved sampling, better convergence and higher robustness against incorrect distance restraints, making it the ideal sampling strategy for the stated problem. To demonstrate the accuracy of our protocol, we tested the approach on a diverse set of 28 globular proteins. Our method is able to converge for 26 out of the 28 targets and improves the average TM-score of the entire benchmark set from 0.55 to 0.72 when compared to the top ranked models obtained by the EVFold web server using identical contact predictions. Using a smaller benchmark, we furthermore show that the prediction accuracy of our method is only slightly reduced when the contact prediction accuracy is comparatively low. This observation is of special interest for protein sequences that only have a limited number of homologs.

  2. A machine learning approach to the accurate prediction of multi-leaf collimator positional errors

    NASA Astrophysics Data System (ADS)

    Carlson, Joel N. K.; Park, Jong Min; Park, So-Yeon; In Park, Jong; Choi, Yunseok; Ye, Sung-Joon

    2016-03-01

    Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these discrepancies, assessed the accuracy of the model predictions, and examined the impact these errors have on quality assurance (QA) procedures and dosimetry. Predictive leaf motion parameters for the models were calculated from the plan files, such as leaf position and velocity, whether the leaf was moving towards or away from the isocenter of the MLC, and many others. Differences in positions between synchronized DICOM-RT planning files and DynaLog files reported during QA delivery were used as a target response for training of the models. The final model is capable of predicting MLC positions during delivery to a high degree of accuracy. For moving MLC leaves, predicted positions were shown to be significantly closer to delivered positions than were planned positions. By incorporating predicted positions into dose calculations in the TPS, increases were shown in gamma passing rates against measured dose distributions recorded during QA delivery. For instance, head and neck plans with 1%/2 mm gamma criteria had an average increase in passing rate of 4.17% (SD  =  1.54%). This indicates that the inclusion of predictions during dose calculation leads to a more realistic representation of plan delivery. To assess impact on the patient, dose volumetric histograms (DVH) using delivered positions were calculated for comparison with planned and predicted DVHs. In all cases, predicted dose volumetric parameters were in closer agreement to the delivered parameters than were the planned parameters, particularly for organs at risk on the periphery of the treatment area. By incorporating the predicted positions into the TPS, the treatment planner is given a more realistic view of the dose distribution as it will truly be

  3. A model predicting the evolution of ice particle size spectra and radiative properties of cirrus clouds. Part 2: Dependence of absorption and extinction on ice crystal morphology

    NASA Technical Reports Server (NTRS)

    Mitchell, David L.; Arnott, W. Patrick

    1994-01-01

    This study builds upon the microphysical modeling described in Part 1 by deriving formulations for the extinction and absorption coefficients in terms of the size distribution parameters predicted from the micro-physical model. The optical depth and single scatter albedo of a cirrus cloud can then be determined, which, along with the asymmetry parameter, are the input parameters needed by cloud radiation models. Through the use of anomalous diffraction theory, analytical expressions were developed describing the absorption and extinction coefficients and the single scatter albedo as functions of size distribution parameters, ice crystal shapes (or habits), wavelength, and refractive index. The extinction coefficient was formulated in terms of the projected area of the size distribution, while the absorption coefficient was formulated in terms of both the projected area and mass of the size distribution. These properties were formulated as explicit functions of ice crystal geometry and were not based on an 'effective radius.' Based on simulations of the second cirrus case study described in Part 1, absorption coefficients predicted in the near infrared for hexagonal columns and rosettes were up to 47% and 71% lower, respectively, than absorption coefficients predicted by using equivalent area spheres. This resulted in single scatter albedos in the near-infrared that were considerably greater than those predicted by the equivalent area sphere method. Reflectances in this region should therefore be underestimated using the equivalent area sphere approach. Cloud optical depth was found to depend on ice crystal habit. When the simulated cirrus cloud contained only bullet rosettes, the optical depth was 142% greater than when the cloud contained only hexagonal columns. This increase produced a doubling in cloud albedo. In the near-infrared (IR), the single scatter albedo also exhibited a significant dependence on ice crystal habit. More research is needed on the

  4. Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli

    PubMed Central

    Kim, Minseung; Rai, Navneet; Zorraquino, Violeta; Tagkopoulos, Ilias

    2016-01-01

    A significant obstacle in training predictive cell models is the lack of integrated data sources. We develop semi-supervised normalization pipelines and perform experimental characterization (growth, transcriptional, proteome) to create Ecomics, a consistent, quality-controlled multi-omics compendium for Escherichia coli with cohesive meta-data information. We then use this resource to train a multi-scale model that integrates four omics layers to predict genome-wide concentrations and growth dynamics. The genetic and environmental ontology reconstructed from the omics data is substantially different and complementary to the genetic and chemical ontologies. The integration of different layers confers an incremental increase in the prediction performance, as does the information about the known gene regulatory and protein-protein interactions. The predictive performance of the model ranges from 0.54 to 0.87 for the various omics layers, which far exceeds various baselines. This work provides an integrative framework of omics-driven predictive modelling that is broadly applicable to guide biological discovery. PMID:27713404

  5. Empirical approaches to more accurately predict benthic-pelagic coupling in biogeochemical ocean models

    NASA Astrophysics Data System (ADS)

    Dale, Andy; Stolpovsky, Konstantin; Wallmann, Klaus

    2016-04-01

    The recycling and burial of biogenic material in the sea floor plays a key role in the regulation of ocean chemistry. Proper consideration of these processes in ocean biogeochemical models is becoming increasingly recognized as an important step in model validation and prediction. However, the rate of organic matter remineralization in sediments and the benthic flux of redox-sensitive elements are difficult to predict a priori. In this communication, examples of empirical benthic flux models that can be coupled to earth system models to predict sediment-water exchange in the open ocean are presented. Large uncertainties hindering further progress in this field include knowledge of the reactivity of organic carbon reaching the sediment, the importance of episodic variability in bottom water chemistry and particle rain rates (for both the deep-sea and margins) and the role of benthic fauna. How do we meet the challenge?

  6. An endometrial gene expression signature accurately predicts recurrent implantation failure after IVF

    PubMed Central

    Koot, Yvonne E. M.; van Hooff, Sander R.; Boomsma, Carolien M.; van Leenen, Dik; Groot Koerkamp, Marian J. A.; Goddijn, Mariëtte; Eijkemans, Marinus J. C.; Fauser, Bart C. J. M.; Holstege, Frank C. P.; Macklon, Nick S.

    2016-01-01

    The primary limiting factor for effective IVF treatment is successful embryo implantation. Recurrent implantation failure (RIF) is a condition whereby couples fail to achieve pregnancy despite consecutive embryo transfers. Here we describe the collection of gene expression profiles from mid-luteal phase endometrial biopsies (n = 115) from women experiencing RIF and healthy controls. Using a signature discovery set (n = 81) we identify a signature containing 303 genes predictive of RIF. Independent validation in 34 samples shows that the gene signature predicts RIF with 100% positive predictive value (PPV). The strength of the RIF associated expression signature also stratifies RIF patients into distinct groups with different subsequent implantation success rates. Exploration of the expression changes suggests that RIF is primarily associated with reduced cellular proliferation. The gene signature will be of value in counselling and guiding further treatment of women who fail to conceive upon IVF and suggests new avenues for developing intervention. PMID:26797113

  7. Accurate ab initio prediction of NMR chemical shifts of nucleic acids and nucleic acids/protein complexes

    PubMed Central

    Victora, Andrea; Möller, Heiko M.; Exner, Thomas E.

    2014-01-01

    NMR chemical shift predictions based on empirical methods are nowadays indispensable tools during resonance assignment and 3D structure calculation of proteins. However, owing to the very limited statistical data basis, such methods are still in their infancy in the field of nucleic acids, especially when non-canonical structures and nucleic acid complexes are considered. Here, we present an ab initio approach for predicting proton chemical shifts of arbitrary nucleic acid structures based on state-of-the-art fragment-based quantum chemical calculations. We tested our prediction method on a diverse set of nucleic acid structures including double-stranded DNA, hairpins, DNA/protein complexes and chemically-modified DNA. Overall, our quantum chemical calculations yield highly/very accurate predictions with mean absolute deviations of 0.3–0.6 ppm and correlation coefficients (r2) usually above 0.9. This will allow for identifying misassignments and validating 3D structures. Furthermore, our calculations reveal that chemical shifts of protons involved in hydrogen bonding are predicted significantly less accurately. This is in part caused by insufficient inclusion of solvation effects. However, it also points toward shortcomings of current force fields used for structure determination of nucleic acids. Our quantum chemical calculations could therefore provide input for force field optimization. PMID:25404135

  8. ICE-COLA: towards fast and accurate synthetic galaxy catalogues optimizing a quasi-N-body method

    NASA Astrophysics Data System (ADS)

    Izard, Albert; Crocce, Martin; Fosalba, Pablo

    2016-07-01

    Next generation galaxy surveys demand the development of massive ensembles of galaxy mocks to model the observables and their covariances, what is computationally prohibitive using N-body simulations. COmoving Lagrangian Acceleration (COLA) is a novel method designed to make this feasible by following an approximate dynamics but with up to three orders of magnitude speed-ups when compared to an exact N-body. In this paper, we investigate the optimization of the code parameters in the compromise between computational cost and recovered accuracy in observables such as two-point clustering and halo abundance. We benchmark those observables with a state-of-the-art N-body run, the MICE Grand Challenge simulation. We find that using 40 time-steps linearly spaced since zi ˜ 20, and a force mesh resolution three times finer than that of the number of particles, yields a matter power spectrum within 1 per cent for k ≲ 1 h Mpc-1 and a halo mass function within 5 per cent of those in the N-body. In turn, the halo bias is accurate within 2 per cent for k ≲ 0.7 h Mpc-1 whereas, in redshift space, the halo monopole and quadrupole are within 4 per cent for k ≲ 0.4 h Mpc-1. These results hold for a broad range in redshift (0 < z < 1) and for all halo mass bins investigated (M > 1012.5 h-1 M⊙). To bring accuracy in clustering to one per cent level we study various methods that re-calibrate halo masses and/or velocities. We thus propose an optimized choice of COLA code parameters as a powerful tool to optimally exploit future galaxy surveys.

  9. Change in body mass accurately and reliably predicts change in body water after endurance exercise.

    PubMed

    Baker, Lindsay B; Lang, James A; Kenney, W Larry

    2009-04-01

    This study tested the hypothesis that the change in body mass (DeltaBM) accurately reflects the change in total body water (DeltaTBW) after prolonged exercise. Subjects (4 men, 4 women; 22-36 year; 66 +/- 10 kg) completed 2 h of interval running (70% VO(2max)) in the heat (30 degrees C), followed by a run to exhaustion (85% VO(2max)), and then sat for a 1 h recovery period. During exercise and recovery, subjects drank fluid or no fluid to maintain their BM, increase BM by 2%, or decrease BM by 2 or 4% in separate trials. Pre- and post-experiment TBW were determined using the deuterium oxide (D(2)O) dilution technique and corrected for D(2)O lost in urine, sweat, breath vapor, and nonaqueous hydrogen exchange. The average difference between DeltaBM and DeltaTBW was 0.07 +/- 1.07 kg (paired t test, P = 0.29). The slope and intercept of the relation between DeltaBM and DeltaTBW were not significantly different from 1 and 0, respectively. The intraclass correlation coefficient between DeltaBM and DeltaTBW was 0.76, which is indicative of excellent reliability between methods. Measuring pre- to post-exercise DeltaBM is an accurate and reliable method to assess the DeltaTBW.

  10. A Regional Model for Seasonal Sea Ice Prediction in the Pacific Sector of the Arctic

    NASA Astrophysics Data System (ADS)

    Yuan, X.; Li, Y.; Chen, D.; Zhang, Q.; Li, C.; Niu, F.; Sun, Y.

    2015-12-01

    The recent results from a linear Markov model for seasonal prediction of pan-Arctic sea ice concentration (SIC) show that sea ice in the Pacific sector has the lowest predictability compared to other regions. One reason could be that the climate variability in the Atlantic sector is so dominant that other signals in the Arctic climate system do not appear in the leading modes used for model construction. This study develops a regional Markov model to improve seasonal forecasting of SIC in the Pacific sector. The model climate system consists of various combinations of the monthly mean series of SIC, sea surface temperature (SST), surface air temperature (SAT), pressure/geopotential height fields and winds at pressure levels. Multivariate empirical orthogonal functions (MEOF) and rotated MEOF are applied to each set of data to reduce the model dimensions. After a series of experiments, the final model configuration selects 23 rotated MEOF modes from a data matrix of three variables (SIC, SST and SAT). This regional model shows considerable improvement in the prediction skill in the Pacific sector in all seasons. The anomaly correlation skill increases by 0.2 at 1- to 4-month leads in the Bering Sea, and by 0.1 at 1- to 10-month leads in the Sea of Okhotsk. In general, the model performs better in summer and fall than in winter and spring. On average, the correlation skill can reach 0.6 at a 2-month (4-month) lead in the Bering Sea (the Sea of Okhotsk).

  11. Towards Accurate Residue-Residue Hydrophobic Contact Prediction for Alpha Helical Proteins Via Integer Linear Optimization

    PubMed Central

    Rajgaria, R.; McAllister, S. R.; Floudas, C. A.

    2008-01-01

    A new optimization-based method is presented to predict the hydrophobic residue contacts in α-helical proteins. The proposed approach uses a high resolution distance dependent force field to calculate the interaction energy between different residues of a protein. The formulation predicts the hydrophobic contacts by minimizing the sum of these contact energies. These residue contacts are highly useful in narrowing down the conformational space searched by protein structure prediction algorithms. The proposed algorithm also offers the algorithmic advantage of producing a rank ordered list of the best contact sets. This model was tested on four independent α-helical protein test sets and was found to perform very well. The average accuracy of the predictions (separated by at least six residues) obtained using the presented method was approximately 66% for single domain proteins. The average true positive and false positive distances were also calculated for each protein test set and they are 8.87 Å and 14.67 Å respectively. PMID:18767158

  12. Accurate prediction of kidney allograft outcome based on creatinine course in the first 6 months posttransplant.

    PubMed

    Fritsche, L; Hoerstrup, J; Budde, K; Reinke, P; Neumayer, H-H; Frei, U; Schlaefer, A

    2005-03-01

    Most attempts to predict early kidney allograft loss are based on the patient and donor characteristics at baseline. We investigated how the early posttransplant creatinine course compares to baseline information in the prediction of kidney graft failure within the first 4 years after transplantation. Two approaches to create a prediction rule for early graft failure were evaluated. First, the whole data set was analysed using a decision-tree building software. The software, rpart, builds classification or regression models; the resulting models can be represented as binary trees. In the second approach, a Hill-Climbing algorithm was applied to define cut-off values for the median creatinine level and creatinine slope in the period between day 60 and 180 after transplantation. Of the 497 patients available for analysis, 52 (10.5%) experienced an early graft loss (graft loss within the first 4 years after transplantation). From the rpart algorithm, a single decision criterion emerged: Median creatinine value on days 60 to 180 higher than 3.1 mg/dL predicts early graft failure (accuracy 95.2% but sensitivity = 42.3%). In contrast, the Hill-Climbing algorithm delivered a cut-off of 1.8 mg/dL for the median creatinine level and a cut-off of 0.3 mg/dL per month for the creatinine slope (sensitivity = 69.5% and specificity 79.0%). Prediction rules based on median and slope of creatinine levels in the first half year after transplantation allow early identification of patients who are at risk of loosing their graft early after transplantation. These patients may benefit from therapeutic measures tailored for this high-risk setting. PMID:15848516

  13. Accurate Prediction of Transposon-Derived piRNAs by Integrating Various Sequential and Physicochemical Features

    PubMed Central

    Luo, Longqiang; Li, Dingfang; Zhang, Wen; Tu, Shikui; Zhu, Xiaopeng; Tian, Gang

    2016-01-01

    Background Piwi-interacting RNA (piRNA) is the largest class of small non-coding RNA molecules. The transposon-derived piRNA prediction can enrich the research contents of small ncRNAs as well as help to further understand generation mechanism of gamete. Methods In this paper, we attempt to differentiate transposon-derived piRNAs from non-piRNAs based on their sequential and physicochemical features by using machine learning methods. We explore six sequence-derived features, i.e. spectrum profile, mismatch profile, subsequence profile, position-specific scoring matrix, pseudo dinucleotide composition and local structure-sequence triplet elements, and systematically evaluate their performances for transposon-derived piRNA prediction. Finally, we consider two approaches: direct combination and ensemble learning to integrate useful features and achieve high-accuracy prediction models. Results We construct three datasets, covering three species: Human, Mouse and Drosophila, and evaluate the performances of prediction models by 10-fold cross validation. In the computational experiments, direct combination models achieve AUC of 0.917, 0.922 and 0.992 on Human, Mouse and Drosophila, respectively; ensemble learning models achieve AUC of 0.922, 0.926 and 0.994 on the three datasets. Conclusions Compared with other state-of-the-art methods, our methods can lead to better performances. In conclusion, the proposed methods are promising for the transposon-derived piRNA prediction. The source codes and datasets are available in S1 File. PMID:27074043

  14. Accurate, conformation-dependent predictions of solvent effects on protein ionization constants

    PubMed Central

    Barth, P.; Alber, T.; Harbury, P. B.

    2007-01-01

    Predicting how aqueous solvent modulates the conformational transitions and influences the pKa values that regulate the biological functions of biomolecules remains an unsolved challenge. To address this problem, we developed FDPB_MF, a rotamer repacking method that exhaustively samples side chain conformational space and rigorously calculates multibody protein–solvent interactions. FDPB_MF predicts the effects on pKa values of various solvent exposures, large ionic strength variations, strong energetic couplings, structural reorganizations and sequence mutations. The method achieves high accuracy, with root mean square deviations within 0.3 pH unit of the experimental values measured for turkey ovomucoid third domain, hen lysozyme, Bacillus circulans xylanase, and human and Escherichia coli thioredoxins. FDPB_MF provides a faithful, quantitative assessment of electrostatic interactions in biological macromolecules. PMID:17360348

  15. FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues

    PubMed Central

    EL-Manzalawy, Yasser; Abbas, Mostafa; Malluhi, Qutaibah; Honavar, Vasant

    2016-01-01

    A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM)-based encoding of the protein sequences. The computational efforts needed for generating PSSMs severely limits the practical utility of protein-RNA interface prediction servers. In this work, we experiment with two approaches, random sampling and sequence similarity reduction, for extracting a representative reference database of protein sequences from more than 50 million protein sequences in UniRef100. Our results suggest that random sampled databases produce better PSSM profiles (in terms of the number of hits used to generate the profile and the distance of the generated profile to the corresponding profile generated using the entire UniRef100 data as well as the accuracy of the machine learning classifier trained using these profiles). Based on our results, we developed FastRNABindR, an improved version of RNABindR for predicting protein-RNA interface residues using PSSM profiles generated using 1% of the UniRef100 sequences sampled uniformly at random. To the best of our knowledge, FastRNABindR is the only protein-RNA interface residue prediction online server that requires generation of PSSM profiles for query sequences and accepts hundreds of protein sequences per submission. Our approach for determining the optimal BLAST database for a protein-RNA interface residue classification task has the potential of substantially speeding up, and hence increasing the practical utility of, other amino acid sequence based predictors of protein-protein and protein

  16. FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues.

    PubMed

    El-Manzalawy, Yasser; Abbas, Mostafa; Malluhi, Qutaibah; Honavar, Vasant

    2016-01-01

    A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM)-based encoding of the protein sequences. The computational efforts needed for generating PSSMs severely limits the practical utility of protein-RNA interface prediction servers. In this work, we experiment with two approaches, random sampling and sequence similarity reduction, for extracting a representative reference database of protein sequences from more than 50 million protein sequences in UniRef100. Our results suggest that random sampled databases produce better PSSM profiles (in terms of the number of hits used to generate the profile and the distance of the generated profile to the corresponding profile generated using the entire UniRef100 data as well as the accuracy of the machine learning classifier trained using these profiles). Based on our results, we developed FastRNABindR, an improved version of RNABindR for predicting protein-RNA interface residues using PSSM profiles generated using 1% of the UniRef100 sequences sampled uniformly at random. To the best of our knowledge, FastRNABindR is the only protein-RNA interface residue prediction online server that requires generation of PSSM profiles for query sequences and accepts hundreds of protein sequences per submission. Our approach for determining the optimal BLAST database for a protein-RNA interface residue classification task has the potential of substantially speeding up, and hence increasing the practical utility of, other amino acid sequence based predictors of protein-protein and protein

  17. Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data

    PubMed Central

    Pagán, Josué; Irene De Orbe, M.; Gago, Ana; Sobrado, Mónica; Risco-Martín, José L.; Vivancos Mora, J.; Moya, José M.; Ayala, José L.

    2015-01-01

    Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives. PMID:26134103

  18. Revisiting the blind tests in crystal structure prediction: accurate energy ranking of molecular crystals.

    PubMed

    Asmadi, Aldi; Neumann, Marcus A; Kendrick, John; Girard, Pascale; Perrin, Marc-Antoine; Leusen, Frank J J

    2009-12-24

    In the 2007 blind test of crystal structure prediction hosted by the Cambridge Crystallographic Data Centre (CCDC), a hybrid DFT/MM method correctly ranked each of the four experimental structures as having the lowest lattice energy of all the crystal structures predicted for each molecule. The work presented here further validates this hybrid method by optimizing the crystal structures (experimental and submitted) of the first three CCDC blind tests held in 1999, 2001, and 2004. Except for the crystal structures of compound IX, all structures were reminimized and ranked according to their lattice energies. The hybrid method computes the lattice energy of a crystal structure as the sum of the DFT total energy and a van der Waals (dispersion) energy correction. Considering all four blind tests, the crystal structure with the lowest lattice energy corresponds to the experimentally observed structure for 12 out of 14 molecules. Moreover, good geometrical agreement is observed between the structures determined by the hybrid method and those measured experimentally. In comparison with the correct submissions made by the blind test participants, all hybrid optimized crystal structures (apart from compound II) have the smallest calculated root mean squared deviations from the experimentally observed structures. It is predicted that a new polymorph of compound V exists under pressure.

  19. Fast and accurate numerical method for predicting gas chromatography retention time.

    PubMed

    Claumann, Carlos Alberto; Wüst Zibetti, André; Bolzan, Ariovaldo; Machado, Ricardo A F; Pinto, Leonel Teixeira

    2015-08-01

    Predictive modeling for gas chromatography compound retention depends on the retention factor (ki) and on the flow of the mobile phase. Thus, different approaches for determining an analyte ki in column chromatography have been developed. The main one is based on the thermodynamic properties of the component and on the characteristics of the stationary phase. These models can be used to estimate the parameters and to optimize the programming of temperatures, in gas chromatography, for the separation of compounds. Different authors have proposed the use of numerical methods for solving these models, but these methods demand greater computational time. Hence, a new method for solving the predictive modeling of analyte retention time is presented. This algorithm is an alternative to traditional methods because it transforms its attainments into root determination problems within defined intervals. The proposed approach allows for tr calculation, with accuracy determined by the user of the methods, and significant reductions in computational time; it can also be used to evaluate the performance of other prediction methods.

  20. Accurate structure prediction of peptide–MHC complexes for identifying highly immunogenic antigens

    SciTech Connect

    Park, Min-Sun; Park, Sung Yong; Miller, Keith R.; Collins, Edward J.; Lee, Ha Youn

    2013-11-01

    Designing an optimal HIV-1 vaccine faces the challenge of identifying antigens that induce a broad immune capacity. One factor to control the breadth of T cell responses is the surface morphology of a peptide–MHC complex. Here, we present an in silico protocol for predicting peptide–MHC structure. A robust signature of a conformational transition was identified during all-atom molecular dynamics, which results in a model with high accuracy. A large test set was used in constructing our protocol and we went another step further using a blind test with a wild-type peptide and two highly immunogenic mutants, which predicted substantial conformational changes in both mutants. The center residues at position five of the analogs were configured to be accessible to solvent, forming a prominent surface, while the residue of the wild-type peptide was to point laterally toward the side of the binding cleft. We then experimentally determined the structures of the blind test set, using high resolution of X-ray crystallography, which verified predicted conformational changes. Our observation strongly supports a positive association of the surface morphology of a peptide–MHC complex to its immunogenicity. Our study offers the prospect of enhancing immunogenicity of vaccines by identifying MHC binding immunogens.

  1. Revisiting the blind tests in crystal structure prediction: accurate energy ranking of molecular crystals.

    PubMed

    Asmadi, Aldi; Neumann, Marcus A; Kendrick, John; Girard, Pascale; Perrin, Marc-Antoine; Leusen, Frank J J

    2009-12-24

    In the 2007 blind test of crystal structure prediction hosted by the Cambridge Crystallographic Data Centre (CCDC), a hybrid DFT/MM method correctly ranked each of the four experimental structures as having the lowest lattice energy of all the crystal structures predicted for each molecule. The work presented here further validates this hybrid method by optimizing the crystal structures (experimental and submitted) of the first three CCDC blind tests held in 1999, 2001, and 2004. Except for the crystal structures of compound IX, all structures were reminimized and ranked according to their lattice energies. The hybrid method computes the lattice energy of a crystal structure as the sum of the DFT total energy and a van der Waals (dispersion) energy correction. Considering all four blind tests, the crystal structure with the lowest lattice energy corresponds to the experimentally observed structure for 12 out of 14 molecules. Moreover, good geometrical agreement is observed between the structures determined by the hybrid method and those measured experimentally. In comparison with the correct submissions made by the blind test participants, all hybrid optimized crystal structures (apart from compound II) have the smallest calculated root mean squared deviations from the experimentally observed structures. It is predicted that a new polymorph of compound V exists under pressure. PMID:19950907

  2. HAAD: A quick algorithm for accurate prediction of hydrogen atoms in protein structures.

    PubMed

    Li, Yunqi; Roy, Ambrish; Zhang, Yang

    2009-08-20

    Hydrogen constitutes nearly half of all atoms in proteins and their positions are essential for analyzing hydrogen-bonding interactions and refining atomic-level structures. However, most protein structures determined by experiments or computer prediction lack hydrogen coordinates. We present a new algorithm, HAAD, to predict the positions of hydrogen atoms based on the positions of heavy atoms. The algorithm is built on the basic rules of orbital hybridization followed by the optimization of steric repulsion and electrostatic interactions. We tested the algorithm using three independent data sets: ultra-high-resolution X-ray structures, structures determined by neutron diffraction, and NOE proton-proton distances. Compared with the widely used programs CHARMM and REDUCE, HAAD has a significantly higher accuracy, with the average RMSD of the predicted hydrogen atoms to the X-ray and neutron diffraction structures decreased by 26% and 11%, respectively. Furthermore, hydrogen atoms placed by HAAD have more matches with the NOE restraints and fewer clashes with heavy atoms. The average CPU cost by HAAD is 18 and 8 times lower than that of CHARMM and REDUCE, respectively. The significant advantage of HAAD in both the accuracy and the speed of the hydrogen additions should make HAAD a useful tool for the detailed study of protein structure and function. Both an executable and the source code of HAAD are freely available at http://zhang.bioinformatics.ku.edu/HAAD.

  3. Accurate single-sequence prediction of solvent accessible surface area using local and global features.

    PubMed

    Faraggi, Eshel; Zhou, Yaoqi; Kloczkowski, Andrzej

    2014-11-01

    We present a new approach for predicting the Accessible Surface Area (ASA) using a General Neural Network (GENN). The novelty of the new approach lies in not using residue mutation profiles generated by multiple sequence alignments as descriptive inputs. Instead we use solely sequential window information and global features such as single-residue and two-residue compositions of the chain. The resulting predictor is both highly more efficient than sequence alignment-based predictors and of comparable accuracy to them. Introduction of the global inputs significantly helps achieve this comparable accuracy. The predictor, termed ASAquick, is tested on predicting the ASA of globular proteins and found to perform similarly well for so-called easy and hard cases indicating generalizability and possible usability for de-novo protein structure prediction. The source code and a Linux executables for GENN and ASAquick are available from Research and Information Systems at http://mamiris.com, from the SPARKS Lab at http://sparks-lab.org, and from the Battelle Center for Mathematical Medicine at http://mathmed.org. PMID:25204636

  4. Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: implications for three-dimensional modeling.

    PubMed

    Bhaskara, Ramachandra M; Padhi, Amrita; Srinivasan, Narayanaswamy

    2014-07-01

    With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions.

  5. Comparative motif discovery combined with comparative transcriptomics yields accurate targetome and enhancer predictions.

    PubMed

    Naval-Sánchez, Marina; Potier, Delphine; Haagen, Lotte; Sánchez, Máximo; Munck, Sebastian; Van de Sande, Bram; Casares, Fernando; Christiaens, Valerie; Aerts, Stein

    2013-01-01

    The identification of transcription factor binding sites, enhancers, and transcriptional target genes often relies on the integration of gene expression profiling and computational cis-regulatory sequence analysis. Methods for the prediction of cis-regulatory elements can take advantage of comparative genomics to increase signal-to-noise levels. However, gene expression data are usually derived from only one species. Here we investigate tissue-specific cross-species gene expression profiling by high-throughput sequencing, combined with cross-species motif discovery. First, we compared different methods for expression level quantification and cross-species integration using Tag-seq data. Using the optimal pipeline, we derived a set of genes with conserved expression during retinal determination across Drosophila melanogaster, Drosophila yakuba, and Drosophila virilis. These genes are enriched for binding sites of eye-related transcription factors including the zinc-finger Glass, a master regulator of photoreceptor differentiation. Validation of predicted Glass targets using RNA-seq in homozygous glass mutants confirms that the majority of our predictions are expressed downstream from Glass. Finally, we tested nine candidate enhancers by in vivo reporter assays and found eight of them to drive GFP in the eye disc, of which seven colocalize with the Glass protein, namely, scrt, chp, dpr10, CG6329, retn, Lim3, and dmrt99B. In conclusion, we show for the first time the combined use of cross-species expression profiling with cross-species motif discovery as a method to define a core developmental program, and we augment the candidate Glass targetome from a single known target gene, lozenge, to at least 62 conserved transcriptional targets. PMID:23070853

  6. Accurate and Rigorous Prediction of the Changes in Protein Free Energies in a Large-Scale Mutation Scan.

    PubMed

    Gapsys, Vytautas; Michielssens, Servaas; Seeliger, Daniel; de Groot, Bert L

    2016-06-20

    The prediction of mutation-induced free-energy changes in protein thermostability or protein-protein binding is of particular interest in the fields of protein design, biotechnology, and bioengineering. Herein, we achieve remarkable accuracy in a scan of 762 mutations estimating changes in protein thermostability based on the first principles of statistical mechanics. The remaining error in the free-energy estimates appears to be due to three sources in approximately equal parts, namely sampling, force-field inaccuracies, and experimental uncertainty. We propose a consensus force-field approach, which, together with an increased sampling time, leads to a free-energy prediction accuracy that matches those reached in experiments. This versatile approach enables accurate free-energy estimates for diverse proteins, including the prediction of changes in the melting temperature of the membrane protein neurotensin receptor 1. PMID:27122231

  7. Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

    NASA Astrophysics Data System (ADS)

    Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.

    2016-02-01

    The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally--a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process.

  8. PSI: A Comprehensive and Integrative Approach for Accurate Plant Subcellular Localization Prediction

    PubMed Central

    Chen, Ming

    2013-01-01

    Predicting the subcellular localization of proteins conquers the major drawbacks of high-throughput localization experiments that are costly and time-consuming. However, current subcellular localization predictors are limited in scope and accuracy. In particular, most predictors perform well on certain locations or with certain data sets while poorly on others. Here, we present PSI, a novel high accuracy web server for plant subcellular localization prediction. PSI derives the wisdom of multiple specialized predictors via a joint-approach of group decision making strategy and machine learning methods to give an integrated best result. The overall accuracy obtained (up to 93.4%) was higher than best individual (CELLO) by ∼10.7%. The precision of each predicable subcellular location (more than 80%) far exceeds that of the individual predictors. It can also deal with multi-localization proteins. PSI is expected to be a powerful tool in protein location engineering as well as in plant sciences, while the strategy employed could be applied to other integrative problems. A user-friendly web server, PSI, has been developed for free access at http://bis.zju.edu.cn/psi/. PMID:24194827

  9. CRYSpred: accurate sequence-based protein crystallization propensity prediction using sequence-derived structural characteristics.

    PubMed

    Mizianty, Marcin J; Kurgan, Lukasz A

    2012-01-01

    Relatively low success rates of X-ray crystallography, which is the most popular method for solving proteins structures, motivate development of novel methods that support selection of tractable protein targets. This aspect is particularly important in the context of the current structural genomics efforts that allow for a certain degree of flexibility in the target selection. We propose CRYSpred, a novel in-silico crystallization propensity predictor that uses a set of 15 novel features which utilize a broad range of inputs including charge, hydrophobicity, and amino acid composition derived from the protein chain, and the solvent accessibility and disorder predicted from the protein sequence. Our method outperforms seven modern crystallization propensity predictors on three, independent from training dataset, benchmark test datasets. The strong predictive performance offered by the CRYSpred is attributed to the careful design of the features, utilization of the comprehensive set of inputs, and the usage of the Support Vector Machine classifier. The inputs utilized by CRYSpred are well-aligned with the existing rules-of-thumb that are used in the structural genomics studies. PMID:21919861

  10. CRYSpred: accurate sequence-based protein crystallization propensity prediction using sequence-derived structural characteristics.

    PubMed

    Mizianty, Marcin J; Kurgan, Lukasz A

    2012-01-01

    Relatively low success rates of X-ray crystallography, which is the most popular method for solving proteins structures, motivate development of novel methods that support selection of tractable protein targets. This aspect is particularly important in the context of the current structural genomics efforts that allow for a certain degree of flexibility in the target selection. We propose CRYSpred, a novel in-silico crystallization propensity predictor that uses a set of 15 novel features which utilize a broad range of inputs including charge, hydrophobicity, and amino acid composition derived from the protein chain, and the solvent accessibility and disorder predicted from the protein sequence. Our method outperforms seven modern crystallization propensity predictors on three, independent from training dataset, benchmark test datasets. The strong predictive performance offered by the CRYSpred is attributed to the careful design of the features, utilization of the comprehensive set of inputs, and the usage of the Support Vector Machine classifier. The inputs utilized by CRYSpred are well-aligned with the existing rules-of-thumb that are used in the structural genomics studies.

  11. Size-extensivity-corrected multireference configuration interaction schemes to accurately predict bond dissociation energies of oxygenated hydrocarbons

    SciTech Connect

    Oyeyemi, Victor B.; Krisiloff, David B.; Keith, John A.; Libisch, Florian; Pavone, Michele; Carter, Emily A.

    2014-01-28

    Oxygenated hydrocarbons play important roles in combustion science as renewable fuels and additives, but many details about their combustion chemistry remain poorly understood. Although many methods exist for computing accurate electronic energies of molecules at equilibrium geometries, a consistent description of entire combustion reaction potential energy surfaces (PESs) requires multireference correlated wavefunction theories. Here we use bond dissociation energies (BDEs) as a foundational metric to benchmark methods based on multireference configuration interaction (MRCI) for several classes of oxygenated compounds (alcohols, aldehydes, carboxylic acids, and methyl esters). We compare results from multireference singles and doubles configuration interaction to those utilizing a posteriori and a priori size-extensivity corrections, benchmarked against experiment and coupled cluster theory. We demonstrate that size-extensivity corrections are necessary for chemically accurate BDE predictions even in relatively small molecules and furnish examples of unphysical BDE predictions resulting from using too-small orbital active spaces. We also outline the specific challenges in using MRCI methods for carbonyl-containing compounds. The resulting complete basis set extrapolated, size-extensivity-corrected MRCI scheme produces BDEs generally accurate to within 1 kcal/mol, laying the foundation for this scheme's use on larger molecules and for more complex regions of combustion PESs.

  12. Accurate predictions of dielectrophoretic force and torque on particles with strong mutual field, particle, and wall interactions

    NASA Astrophysics Data System (ADS)

    Liu, Qianlong; Reifsnider, Kenneth

    2012-11-01

    The basis of dielectrophoresis (DEP) is the prediction of the force and torque on particles. The classical approach to the prediction is based on the effective moment method, which, however, is an approximate approach, assumes infinitesimal particles. Therefore, it is well-known that for finite-sized particles, the DEP approximation is inaccurate as the mutual field, particle, wall interactions become strong, a situation presently attracting extensive research for practical significant applications. In the present talk, we provide accurate calculations of the force and torque on the particles from first principles, by directly resolving the local geometry and properties and accurately accounting for the mutual interactions for finite-sized particles with both dielectric polarization and conduction in a sinusoidally steady-state electric field. Since the approach has a significant advantage, compared to other numerical methods, to efficiently simulate many closely packed particles, it provides an important, unique, and accurate technique to investigate complex DEP phenomena, for example heterogeneous mixtures containing particle chains, nanoparticle assembly, biological cells, non-spherical effects, etc. This study was supported by the Department of Energy under funding for an EFRC (the HeteroFoaM Center), grant no. DE-SC0001061.

  13. Size-extensivity-corrected multireference configuration interaction schemes to accurately predict bond dissociation energies of oxygenated hydrocarbons

    NASA Astrophysics Data System (ADS)

    Oyeyemi, Victor B.; Krisiloff, David B.; Keith, John A.; Libisch, Florian; Pavone, Michele; Carter, Emily A.

    2014-01-01

    Oxygenated hydrocarbons play important roles in combustion science as renewable fuels and additives, but many details about their combustion chemistry remain poorly understood. Although many methods exist for computing accurate electronic energies of molecules at equilibrium geometries, a consistent description of entire combustion reaction potential energy surfaces (PESs) requires multireference correlated wavefunction theories. Here we use bond dissociation energies (BDEs) as a foundational metric to benchmark methods based on multireference configuration interaction (MRCI) for several classes of oxygenated compounds (alcohols, aldehydes, carboxylic acids, and methyl esters). We compare results from multireference singles and doubles configuration interaction to those utilizing a posteriori and a priori size-extensivity corrections, benchmarked against experiment and coupled cluster theory. We demonstrate that size-extensivity corrections are necessary for chemically accurate BDE predictions even in relatively small molecules and furnish examples of unphysical BDE predictions resulting from using too-small orbital active spaces. We also outline the specific challenges in using MRCI methods for carbonyl-containing compounds. The resulting complete basis set extrapolated, size-extensivity-corrected MRCI scheme produces BDEs generally accurate to within 1 kcal/mol, laying the foundation for this scheme's use on larger molecules and for more complex regions of combustion PESs.

  14. The Compensatory Reserve For Early and Accurate Prediction Of Hemodynamic Compromise: A Review of the Underlying Physiology.

    PubMed

    Convertino, Victor A; Wirt, Michael D; Glenn, John F; Lein, Brian C

    2016-06-01

    Shock is deadly and unpredictable if it is not recognized and treated in early stages of hemorrhage. Unfortunately, measurements of standard vital signs that are displayed on current medical monitors fail to provide accurate or early indicators of shock because of physiological mechanisms that effectively compensate for blood loss. As a result of new insights provided by the latest research on the physiology of shock using human experimental models of controlled hemorrhage, it is now recognized that measurement of the body's reserve to compensate for reduced circulating blood volume is the single most important indicator for early and accurate assessment of shock. We have called this function the "compensatory reserve," which can be accurately assessed by real-time measurements of changes in the features of the arterial waveform. In this paper, the physiology underlying the development and evaluation of a new noninvasive technology that allows for real-time measurement of the compensatory reserve will be reviewed, with its clinical implications for earlier and more accurate prediction of shock. PMID:26950588

  15. A novel method to predict visual field progression more accurately, using intraocular pressure measurements in glaucoma patients

    PubMed Central

    Asaoka, Ryo; Fujino, Yuri; Murata, Hiroshi; Miki, Atsuya; Tanito, Masaki; Mizoue, Shiro; Mori, Kazuhiko; Suzuki, Katsuyoshi; Yamashita, Takehiro; Kashiwagi, Kenji; Shoji, Nobuyuki

    2016-01-01

    Visual field (VF) data were retrospectively obtained from 491 eyes in 317 patients with open angle glaucoma who had undergone ten VF tests (Humphrey Field Analyzer, 24-2, SITA standard). First, mean of total deviation values (mTD) in the tenth VF was predicted using standard linear regression of the first five VFs (VF1-5) through to using all nine preceding VFs (VF1-9). Then an ‘intraocular pressure (IOP)-integrated VF trend analysis’ was carried out by simply using time multiplied by IOP as the independent term in the linear regression model. Prediction errors (absolute prediction error or root mean squared error: RMSE) for predicting mTD and also point wise TD values of the tenth VF were obtained from both approaches. The mTD absolute prediction errors associated with the IOP-integrated VF trend analysis were significantly smaller than those from the standard trend analysis when VF1-6 through to VF1-8 were used (p < 0.05). The point wise RMSEs from the IOP-integrated trend analysis were significantly smaller than those from the standard trend analysis when VF1-5 through to VF1-9 were used (p < 0.05). This was especially the case when IOP was measured more frequently. Thus a significantly more accurate prediction of VF progression is possible using a simple trend analysis that incorporates IOP measurements. PMID:27562553

  16. A novel method to predict visual field progression more accurately, using intraocular pressure measurements in glaucoma patients.

    PubMed

    2016-01-01

    Visual field (VF) data were retrospectively obtained from 491 eyes in 317 patients with open angle glaucoma who had undergone ten VF tests (Humphrey Field Analyzer, 24-2, SITA standard). First, mean of total deviation values (mTD) in the tenth VF was predicted using standard linear regression of the first five VFs (VF1-5) through to using all nine preceding VFs (VF1-9). Then an 'intraocular pressure (IOP)-integrated VF trend analysis' was carried out by simply using time multiplied by IOP as the independent term in the linear regression model. Prediction errors (absolute prediction error or root mean squared error: RMSE) for predicting mTD and also point wise TD values of the tenth VF were obtained from both approaches. The mTD absolute prediction errors associated with the IOP-integrated VF trend analysis were significantly smaller than those from the standard trend analysis when VF1-6 through to VF1-8 were used (p < 0.05). The point wise RMSEs from the IOP-integrated trend analysis were significantly smaller than those from the standard trend analysis when VF1-5 through to VF1-9 were used (p < 0.05). This was especially the case when IOP was measured more frequently. Thus a significantly more accurate prediction of VF progression is possible using a simple trend analysis that incorporates IOP measurements. PMID:27562553

  17. Combining multiple regression and principal component analysis for accurate predictions for column ozone in Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Rajab, Jasim M.; MatJafri, M. Z.; Lim, H. S.

    2013-06-01

    This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASA's Atmospheric Infrared Sounder (AIRS), for the entire period (2003-2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameter's variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameter's variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.

  18. Time-dependent neutrino emission from Mrk 421 during flares and predictions for IceCube

    NASA Astrophysics Data System (ADS)

    Petropoulou, Maria; Coenders, Stefan; Dimitrakoudis, Stavros

    2016-07-01

    Blazars, a subclass of active galactic nuclei, are prime candidate sources for the high energy neutrinos recently detected by IceCube. Being one of the brightest sources in the extragalactic X-ray and γ-ray sky as well as one of the nearest blazars to Earth, Mrk 421 is an excellent source for testing the scenario of the blazar-neutrino connection, especially during flares where time-dependent neutrino searches may have a higher detection probability. Here, we model the spectral energy distribution of Mrk 421 during a 13-day flare in 2010 with unprecedented multi-wavelength coverage, and calculate the respective neutrino flux. We find a correlation between the >1 PeV neutrino and photon fluxes, in all energy bands. Using typical IceCube through-going muon event samples with good angular resolution and high statistics, wederive the mean event rate above 100 TeV (˜0.57 evt/yr) and show that it is comparable to that expected from a four-month quiescent period in 2009. Due to the short duration of the flare, an accumulation of similar flares over several years would be necessary to produce a meaningful signal for IceCube. To better assess this, we apply the correlation between the neutrino and γ-ray fluxes to the 6.9 yr Fermi-LAT light curve of Mrk 421. We find that the mean event count above 1 PeV for the full IceCube detector livetime is 3.59 ± 0.60 (2.73 ± 0.38) νμ +νbarμ with (without) major flares included in our analysis. This estimate exceeds, within the uncertainties, the 95% (90%) threshold value for the detection of one or more muon (anti-)neutrinos. Meanwhile, the most conservative scenario, where no correlation of γ-rays and neutrinos is assumed, predicts 1.60 ± 0.16νμ +νbarμ events. We conclude that a non-detection of high-energy neutrinos by IceCube would probe the neutrino/γ-ray flux correlation during major flares or/and the hadronic contribution to the blazar emission.

  19. Theoretical Predictions of Ice Crystal Shape in CO2 Clouds on Mars

    NASA Astrophysics Data System (ADS)

    Wood, S. E.

    2001-11-01

    Carbon dioxide ice crystals that form in the Martian atmosphere play very important roles in the climate of Mars, primarily through their radiative effects. Unlike water ice, small CO2 ice particles are very efficient scatterers of thermal infrared radiation [1]. On present-day Mars, CO2 clouds over the polar regions during winter have been observed to reduce the net cooling rate to space [2]. Theoretical studies have shown that the presence of CO2 clouds in a dense (>=1 bar) CO2 atmosphere on early Mars (≈3.8 Ga) could have had a net warming effect and maintained surface temperatures above the melting point of water [3,4], for certain assumptions regarding the optical depth and areal coverage of the clouds, and the size and shape of the cloud particles. Modeling studies to date have assumed spherical particles in their radiative transfer calculations. While this may be true for evaporating crystals, for growing crystals it is certainly not. In order to predict the actual shapes of crystals in CO2 ice clouds, I have derived values for the surface energy, edge energy, and surface diffusion distance for molecules on each of the singular crystallographic faces [5]. Using these values in a model of crystal growth, I find that CO2 ice crystals in the Martian atmosphere will be cubes, octahedrons, or a combination thereof (truncated octahedrons), depending largely on which crystal growth mechanism is active. The values of these physical parameters are also important for calculating the nucleation and growth rates of cloud particles in a microphysical model. I will present calculations of the scattering phase function for these shapes, at visible and infrared wavelengths, for comparison with the Mie phase functions for spheres. [1] Hansen, G. B., JGR v.102, p.21569, 1997 [2] Kieffer, H. H. and T. Z. Martin, JGR v. 82, p.4249, 1977 [3] Forget, F. and R. T. Pierrehumbert, Science v.278, p.1273, 1997 [4] Mischna, M. A. et al., Icarus v.145, p.546, 2000 [5] Wood, S. E., Ph

  20. Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

    SciTech Connect

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic

  1. nuMap: a web platform for accurate prediction of nucleosome positioning.

    PubMed

    Alharbi, Bader A; Alshammari, Thamir H; Felton, Nathan L; Zhurkin, Victor B; Cui, Feng

    2014-10-01

    Nucleosome positioning is critical for gene expression and of major biological interest. The high cost of experimentally mapping nucleosomal arrangement signifies the need for computational approaches to predict nucleosome positions at high resolution. Here, we present a web-based application to fulfill this need by implementing two models, YR and W/S schemes, for the translational and rotational positioning of nucleosomes, respectively. Our methods are based on sequence-dependent anisotropic bending that dictates how DNA is wrapped around a histone octamer. This application allows users to specify a number of options such as schemes and parameters for threading calculation and provides multiple layout formats. The nuMap is implemented in Java/Perl/MySQL and is freely available for public use at http://numap.rit.edu. The user manual, implementation notes, description of the methodology and examples are available at the site. PMID:25220945

  2. A Foundation for the Accurate Prediction of the Soft Error Vulnerability of Scientific Applications

    SciTech Connect

    Bronevetsky, G; de Supinski, B; Schulz, M

    2009-02-13

    Understanding the soft error vulnerability of supercomputer applications is critical as these systems are using ever larger numbers of devices that have decreasing feature sizes and, thus, increasing frequency of soft errors. As many large scale parallel scientific applications use BLAS and LAPACK linear algebra routines, the soft error vulnerability of these methods constitutes a large fraction of the applications overall vulnerability. This paper analyzes the vulnerability of these routines to soft errors by characterizing how their outputs are affected by injected errors and by evaluating several techniques for predicting how errors propagate from the input to the output of each routine. The resulting error profiles can be used to understand the fault vulnerability of full applications that use these routines.

  3. Simplified versus geometrically accurate models of forefoot anatomy to predict plantar pressures: A finite element study.

    PubMed

    Telfer, Scott; Erdemir, Ahmet; Woodburn, James; Cavanagh, Peter R

    2016-01-25

    Integration of patient-specific biomechanical measurements into the design of therapeutic footwear has been shown to improve clinical outcomes in patients with diabetic foot disease. The addition of numerical simulations intended to optimise intervention design may help to build on these advances, however at present the time and labour required to generate and run personalised models of foot anatomy restrict their routine clinical utility. In this study we developed second-generation personalised simple finite element (FE) models of the forefoot with varying geometric fidelities. Plantar pressure predictions from barefoot, shod, and shod with insole simulations using simplified models were compared to those obtained from CT-based FE models incorporating more detailed representations of bone and tissue geometry. A simplified model including representations of metatarsals based on simple geometric shapes, embedded within a contoured soft tissue block with outer geometry acquired from a 3D surface scan was found to provide pressure predictions closest to the more complex model, with mean differences of 13.3kPa (SD 13.4), 12.52kPa (SD 11.9) and 9.6kPa (SD 9.3) for barefoot, shod, and insole conditions respectively. The simplified model design could be produced in <1h compared to >3h in the case of the more detailed model, and solved on average 24% faster. FE models of the forefoot based on simplified geometric representations of the metatarsal bones and soft tissue surface geometry from 3D surface scans may potentially provide a simulation approach with improved clinical utility, however further validity testing around a range of therapeutic footwear types is required.

  4. Four-protein signature accurately predicts lymph node metastasis and survival in oral squamous cell carcinoma.

    PubMed

    Zanaruddin, Sharifah Nurain Syed; Saleh, Amyza; Yang, Yi-Hsin; Hamid, Sharifah; Mustafa, Wan Mahadzir Wan; Khairul Bariah, A A N; Zain, Rosnah Binti; Lau, Shin Hin; Cheong, Sok Ching

    2013-03-01

    The presence of lymph node (LN) metastasis significantly affects the survival of patients with oral squamous cell carcinoma (OSCC). Successful detection and removal of positive LNs are crucial in the treatment of this disease. Current evaluation methods still have their limitations in detecting the presence of tumor cells in the LNs, where up to a third of clinically diagnosed metastasis-negative (N0) patients actually have metastasis-positive LNs in the neck. We developed a molecular signature in the primary tumor that could predict LN metastasis in OSCC. A total of 211 cores from 55 individuals were included in the study. Eleven proteins were evaluated using immunohistochemical analysis in a tissue microarray. Of the 11 biomarkers evaluated using receiver operating curve analysis, epidermal growth factor receptor (EGFR), v-erb-b2 erythroblastic leukemia viral oncogene homolog 2 (HER-2/neu), laminin, gamma 2 (LAMC2), and ras homolog family member C (RHOC) were found to be significantly associated with the presence of LN metastasis. Unsupervised hierarchical clustering-demonstrated expression patterns of these 4 proteins could be used to differentiate specimens that have positive LN metastasis from those that are negative for LN metastasis. Collectively, EGFR, HER-2/neu, LAMC2, and RHOC have a specificity of 87.5% and a sensitivity of 70%, with a prognostic accuracy of 83.4% for LN metastasis. We also demonstrated that the LN signature could independently predict disease-specific survival (P = .036). The 4-protein LN signature validated in an independent set of samples strongly suggests that it could reliably distinguish patients with LN metastasis from those who were metastasis-free and therefore could be a prognostic tool for the management of patients with OSCC.

  5. Four-protein signature accurately predicts lymph node metastasis and survival in oral squamous cell carcinoma.

    PubMed

    Zanaruddin, Sharifah Nurain Syed; Saleh, Amyza; Yang, Yi-Hsin; Hamid, Sharifah; Mustafa, Wan Mahadzir Wan; Khairul Bariah, A A N; Zain, Rosnah Binti; Lau, Shin Hin; Cheong, Sok Ching

    2013-03-01

    The presence of lymph node (LN) metastasis significantly affects the survival of patients with oral squamous cell carcinoma (OSCC). Successful detection and removal of positive LNs are crucial in the treatment of this disease. Current evaluation methods still have their limitations in detecting the presence of tumor cells in the LNs, where up to a third of clinically diagnosed metastasis-negative (N0) patients actually have metastasis-positive LNs in the neck. We developed a molecular signature in the primary tumor that could predict LN metastasis in OSCC. A total of 211 cores from 55 individuals were included in the study. Eleven proteins were evaluated using immunohistochemical analysis in a tissue microarray. Of the 11 biomarkers evaluated using receiver operating curve analysis, epidermal growth factor receptor (EGFR), v-erb-b2 erythroblastic leukemia viral oncogene homolog 2 (HER-2/neu), laminin, gamma 2 (LAMC2), and ras homolog family member C (RHOC) were found to be significantly associated with the presence of LN metastasis. Unsupervised hierarchical clustering-demonstrated expression patterns of these 4 proteins could be used to differentiate specimens that have positive LN metastasis from those that are negative for LN metastasis. Collectively, EGFR, HER-2/neu, LAMC2, and RHOC have a specificity of 87.5% and a sensitivity of 70%, with a prognostic accuracy of 83.4% for LN metastasis. We also demonstrated that the LN signature could independently predict disease-specific survival (P = .036). The 4-protein LN signature validated in an independent set of samples strongly suggests that it could reliably distinguish patients with LN metastasis from those who were metastasis-free and therefore could be a prognostic tool for the management of patients with OSCC. PMID:23026198

  6. Nonempirically Tuned Range-Separated DFT Accurately Predicts Both Fundamental and Excitation Gaps in DNA and RNA Nucleobases

    PubMed Central

    2012-01-01

    Using a nonempirically tuned range-separated DFT approach, we study both the quasiparticle properties (HOMO–LUMO fundamental gaps) and excitation energies of DNA and RNA nucleobases (adenine, thymine, cytosine, guanine, and uracil). Our calculations demonstrate that a physically motivated, first-principles tuned DFT approach accurately reproduces results from both experimental benchmarks and more computationally intensive techniques such as many-body GW theory. Furthermore, in the same set of nucleobases, we show that the nonempirical range-separated procedure also leads to significantly improved results for excitation energies compared to conventional DFT methods. The present results emphasize the importance of a nonempirically tuned range-separation approach for accurately predicting both fundamental and excitation gaps in DNA and RNA nucleobases. PMID:22904693

  7. A snow and ice melt seasonal prediction modelling system for Alpine reservoirs

    NASA Astrophysics Data System (ADS)

    Förster, Kristian; Oesterle, Felix; Hanzer, Florian; Schöber, Johannes; Huttenlau, Matthias; Strasser, Ulrich

    2016-10-01

    The timing and the volume of snow and ice melt in Alpine catchments are crucial for management operations of reservoirs and hydropower generation. Moreover, a sustainable reservoir operation through reservoir storage and flow control as part of flood risk management is important for downstream communities. Forecast systems typically provide predictions for a few days in advance. Reservoir operators would benefit if lead times could be extended in order to optimise the reservoir management. Current seasonal prediction products such as the NCEP (National Centers for Environmental Prediction) Climate Forecast System version 2 (CFSv2) enable seasonal forecasts up to nine months in advance, with of course decreasing accuracy as lead-time increases. We present a coupled seasonal prediction modelling system that runs at monthly time steps for a small catchment in the Austrian Alps (Gepatschalm). Meteorological forecasts are obtained from the CFSv2 model. Subsequently, these data are downscaled to the Alpine Water balance And Runoff Estimation model AWARE running at monthly time step. Initial conditions are obtained using the physically based, hydro-climatological snow model AMUNDSEN that predicts hourly fields of snow water equivalent and snowmelt at a regular grid with 50 m spacing. Reservoir inflow is calculated taking into account various runs of the CFSv2 model. These simulations are compared with observed inflow volumes for the melting and accumulation period 2015.

  8. Lateral impact validation of a geometrically accurate full body finite element model for blunt injury prediction.

    PubMed

    Vavalle, Nicholas A; Moreno, Daniel P; Rhyne, Ashley C; Stitzel, Joel D; Gayzik, F Scott

    2013-03-01

    This study presents four validation cases of a mid-sized male (M50) full human body finite element model-two lateral sled tests at 6.7 m/s, one sled test at 8.9 m/s, and a lateral drop test. Model results were compared to transient force curves, peak force, chest compression, and number of fractures from the studies. For one of the 6.7 m/s impacts (flat wall impact), the peak thoracic, abdominal and pelvic loads were 8.7, 3.1 and 14.9 kN for the model and 5.2 ± 1.1 kN, 3.1 ± 1.1 kN, and 6.3 ± 2.3 kN for the tests. For the same test setup in the 8.9 m/s case, they were 12.6, 6, and 21.9 kN for the model and 9.1 ± 1.5 kN, 4.9 ± 1.1 kN, and 17.4 ± 6.8 kN for the experiments. The combined torso load and the pelvis load simulated in a second rigid wall impact at 6.7 m/s were 11.4 and 15.6 kN, respectively, compared to 8.5 ± 0.2 kN and 8.3 ± 1.8 kN experimentally. The peak thorax load in the drop test was 6.7 kN for the model, within the range in the cadavers, 5.8-7.4 kN. When analyzing rib fractures, the model predicted Abbreviated Injury Scale scores within the reported range in three of four cases. Objective comparison methods were used to quantitatively compare the model results to the literature studies. The results show a good match in the thorax and abdomen regions while the pelvis results over predicted the reaction loads from the literature studies. These results are an important milestone in the development and validation of this globally developed average male FEA model in lateral impact.

  9. Force Criterion Prediction of Damage for Carbon/Epoxy Composite Panels Impacted by High Velocity Ice

    NASA Astrophysics Data System (ADS)

    Rhymer, Jennifer D.

    The use of advanced fiber-reinforced polymer matrix composites in load-bearing aircraft structures is increasing, as evident by the various composites-intensive transport aircraft presently under development. A major impact source of concern for these structures is hail ice, which affects design and skin-sizing (skin thickness determination) at various locations of the aircraft. Impacts onto composite structures often cause internal damage that is not visually detectable due to the high strength and resiliency of the composite material (unlike impacts onto metallic structures). This internal damage and its effect on the performance of the structure are of great concern to the aircraft industry. The prediction of damage in composite structures due to SHI impact has been accomplished via experimental work, explicit dynamic nonlinear finite element analysis (FEA) and the definition of design oriented relationships. Experiments established the critical threshold and corresponding analysis provided contact force results not readily measurable in high velocity SHI impact experiments. The design oriented relationships summarize the FEA results and experimental database into contact force estimation curves that can be easily applied for damage prediction. Failure thresholds were established for the experimental conditions (panel thickness ranging from 1.56 to 4.66 mm and ice diameters from 38.1 to 61.0 mm). Additionally, the observations made by high-speed video during the impact event, and ultrasonic C-scan post-impact, showed how the ice failed during impact and the overall shape and location of the panel damage. Through analysis, the critical force, the force level where damage occurs above but not below, of a SHI impact onto the panel was found to be dependent only on the target structure. However, the peak force generated during impact was dependent on both the projectile and target. Design-oriented curves were generated allowing the prediction of the allowable

  10. Accurate prediction of the refractive index of polymers using first principles and data modeling

    NASA Astrophysics Data System (ADS)

    Afzal, Mohammad Atif Faiz; Cheng, Chong; Hachmann, Johannes

    Organic polymers with a high refractive index (RI) have recently attracted considerable interest due to their potential application in optical and optoelectronic devices. The ability to tailor the molecular structure of polymers is the key to increasing the accessible RI values. Our work concerns the creation of predictive in silico models for the optical properties of organic polymers, the screening of large-scale candidate libraries, and the mining of the resulting data to extract the underlying design principles that govern their performance. This work was set up to guide our experimentalist partners and allow them to target the most promising candidates. Our model is based on the Lorentz-Lorenz equation and thus includes the polarizability and number density values for each candidate. For the former, we performed a detailed benchmark study of different density functionals, basis sets, and the extrapolation scheme towards the polymer limit. For the number density we devised an exceedingly efficient machine learning approach to correlate the polymer structure and the packing fraction in the bulk material. We validated the proposed RI model against the experimentally known RI values of 112 polymers. We could show that the proposed combination of physical and data modeling is both successful and highly economical to characterize a wide range of organic polymers, which is a prerequisite for virtual high-throughput screening.

  11. Accurate predictions of C-SO2R bond dissociation enthalpies using density functional theory methods.

    PubMed

    Yu, Hai-Zhu; Fu, Fang; Zhang, Liang; Fu, Yao; Dang, Zhi-Min; Shi, Jing

    2014-10-14

    The dissociation of the C-SO2R bond is frequently involved in organic and bio-organic reactions, and the C-SO2R bond dissociation enthalpies (BDEs) are potentially important for understanding the related mechanisms. The primary goal of the present study is to provide a reliable calculation method to predict the different C-SO2R bond dissociation enthalpies (BDEs). Comparing the accuracies of 13 different density functional theory (DFT) methods (such as B3LYP, TPSS, and M05 etc.), and different basis sets (such as 6-31G(d) and 6-311++G(2df,2p)), we found that M06-2X/6-31G(d) gives the best performance in reproducing the various C-S BDEs (and especially the C-SO2R BDEs). As an example for understanding the mechanisms with the aid of C-SO2R BDEs, some primary mechanistic studies were carried out on the chemoselective coupling (in the presence of a Cu-catalyst) or desulfinative coupling reactions (in the presence of a Pd-catalyst) between sulfinic acid salts and boryl/sulfinic acid salts.

  12. Towards Accurate Prediction of Turbulent, Three-Dimensional, Recirculating Flows with the NCC

    NASA Technical Reports Server (NTRS)

    Iannetti, A.; Tacina, R.; Jeng, S.-M.; Cai, J.

    2001-01-01

    The National Combustion Code (NCC) was used to calculate the steady state, nonreacting flow field of a prototype Lean Direct Injection (LDI) swirler. This configuration used nine groups of eight holes drilled at a thirty-five degree angle to induce swirl. These nine groups created swirl in the same direction, or a corotating pattern. The static pressure drop across the holes was fixed at approximately four percent. Computations were performed on one quarter of the geometry, because the geometry is considered rotationally periodic every ninety degrees. The final computational grid used was approximately 2.26 million tetrahedral cells, and a cubic nonlinear k - epsilon model was used to model turbulence. The NCC results were then compared to time averaged Laser Doppler Velocimetry (LDV) data. The LDV measurements were performed on the full geometry, but four ninths of the geometry was measured. One-, two-, and three-dimensional representations of both flow fields are presented. The NCC computations compare both qualitatively and quantitatively well to the LDV data, but differences exist downstream. The comparison is encouraging, and shows that NCC can be used for future injector design studies. To improve the flow prediction accuracy of turbulent, three-dimensional, recirculating flow fields with the NCC, recommendations are given.

  13. An improved method for accurate prediction of mass flows through combustor liner holes

    SciTech Connect

    Adkins, R.C.; Gueroui, D.

    1986-01-01

    The objective of this paper is to present a simple approach to the solution of flow through combustor liner holes which can be used by practicing combustor engineers as well as providing the specialist modeler with a convenient boundary condition. For modeling, suppose that all relevant details of the incoming jets can be readily predicted, then the computational boundary can be limited to the inner wall of the liner and to the jets themselves. The scope of this paper is limited to the derivation of a simple analysis, the development of a reliable test technique, and to the correlation of data for plane holes having a diameter which is large when compared to the liner wall thickness. The effect of internal liner flow on the performance of the holes is neglected; this is considered to be justifiable because the analysis terminates at a short distance downstream of the hole and the significantly lower velocities inside the combustor have had little opportunity to have taken any effect. It is intended to extend the procedure to more complex hole forms and flow configurations in later papers.

  14. Neural network approach to quantum-chemistry data: Accurate prediction of density functional theory energies

    NASA Astrophysics Data System (ADS)

    Balabin, Roman M.; Lomakina, Ekaterina I.

    2009-08-01

    Artificial neural network (ANN) approach has been applied to estimate the density functional theory (DFT) energy with large basis set using lower-level energy values and molecular descriptors. A total of 208 different molecules were used for the ANN training, cross validation, and testing by applying BLYP, B3LYP, and BMK density functionals. Hartree-Fock results were reported for comparison. Furthermore, constitutional molecular descriptor (CD) and quantum-chemical molecular descriptor (QD) were used for building the calibration model. The neural network structure optimization, leading to four to five hidden neurons, was also carried out. The usage of several low-level energy values was found to greatly reduce the prediction error. An expected error, mean absolute deviation, for ANN approximation to DFT energies was 0.6±0.2 kcal mol-1. In addition, the comparison of the different density functionals with the basis sets and the comparison of multiple linear regression results were also provided. The CDs were found to overcome limitation of the QD. Furthermore, the effective ANN model for DFT/6-311G(3df,3pd) and DFT/6-311G(2df,2pd) energy estimation was developed, and the benchmark results were provided.

  15. Line Shape Parameters for CO_2 Transitions: Accurate Predictions from Complex Robert-Bonamy Calculations

    NASA Astrophysics Data System (ADS)

    Lamouroux, Julien; Gamache, Robert R.

    2013-06-01

    A model for the prediction of the vibrational dependence of CO_2 half-widths and line shifts for several broadeners, based on a modification of the model proposed by Gamache and Hartmann, is presented. This model allows the half-widths and line shifts for a ro-vibrational transition to be expressed in terms of the number of vibrational quanta exchanged in the transition raised to a power p and a reference ro-vibrational transition. Complex Robert-Bonamy calculations were made for 24 bands for lower rotational quantum numbers J'' from 0 to 160 for N_2-, O_2-, air-, and self-collisions with CO_2. In the model a Quantum Coordinate is defined by (c_1 Δν_1 + c_2 Δν_2 + c_3 Δν_3)^p where a linear least-squares fit to the data by the model expression is made. The model allows the determination of the slope and intercept as a function of rotational transition, broadening gas, and temperature. From these fit data, the half-width, line shift, and the temperature dependence of the half-width can be estimated for any ro-vibrational transition, allowing spectroscopic CO_2 databases to have complete information for the line shape parameters. R. R. Gamache, J.-M. Hartmann, J. Quant. Spectrosc. Radiat. Transfer. {{83}} (2004), 119. R. R. Gamache, J. Lamouroux, J. Quant. Spectrosc. Radiat. Transfer. {{117}} (2013), 93.

  16. The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

    PubMed Central

    Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke

    2015-01-01

    attributed to phantom setup errors due to the slightly deformable and flexible phantom extremities. The estimated site-specific safety buffer distance with 0.001% probability of collision for (gantry-to-couch, gantry-to-phantom) was (1.23 cm, 3.35 cm), (1.01 cm, 3.99 cm), and (2.19 cm, 5.73 cm) for treatment to the head, lung, and prostate, respectively. Automated delivery to all three treatment sites was completed in 15 min and collision free using a digital Linac. Conclusions: An individualized collision prediction model for the purpose of noncoplanar beam delivery was developed and verified. With the model, the study has demonstrated the feasibility of predicting deliverable beams for an individual patient and then guiding fully automated noncoplanar treatment delivery. This work motivates development of clinical workflows and quality assurance procedures to allow more extensive use and automation of noncoplanar beam geometries. PMID:26520735

  17. The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

    SciTech Connect

    Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke

    2015-11-15

    attributed to phantom setup errors due to the slightly deformable and flexible phantom extremities. The estimated site-specific safety buffer distance with 0.001% probability of collision for (gantry-to-couch, gantry-to-phantom) was (1.23 cm, 3.35 cm), (1.01 cm, 3.99 cm), and (2.19 cm, 5.73 cm) for treatment to the head, lung, and prostate, respectively. Automated delivery to all three treatment sites was completed in 15 min and collision free using a digital Linac. Conclusions: An individualized collision prediction model for the purpose of noncoplanar beam delivery was developed and verified. With the model, the study has demonstrated the feasibility of predicting deliverable beams for an individual patient and then guiding fully automated noncoplanar treatment delivery. This work motivates development of clinical workflows and quality assurance procedures to allow more extensive use and automation of noncoplanar beam geometries.

  18. How Accurate Are the Anthropometry Equations in in Iranian Military Men in Predicting Body Composition?

    PubMed Central

    Shakibaee, Abolfazl; Faghihzadeh, Soghrat; Alishiri, Gholam Hossein; Ebrahimpour, Zeynab; Faradjzadeh, Shahram; Sobhani, Vahid; Asgari, Alireza

    2015-01-01

    Background: The body composition varies according to different life styles (i.e. intake calories and caloric expenditure). Therefore, it is wise to record military personnel’s body composition periodically and encourage those who abide to the regulations. Different methods have been introduced for body composition assessment: invasive and non-invasive. Amongst them, the Jackson and Pollock equation is most popular. Objectives: The recommended anthropometric prediction equations for assessing men’s body composition were compared with dual-energy X-ray absorptiometry (DEXA) gold standard to develop a modified equation to assess body composition and obesity quantitatively among Iranian military men. Patients and Methods: A total of 101 military men aged 23 - 52 years old with a mean age of 35.5 years were recruited and evaluated in the present study (average height, 173.9 cm and weight, 81.5 kg). The body-fat percentages of subjects were assessed both with anthropometric assessment and DEXA scan. The data obtained from these two methods were then compared using multiple regression analysis. Results: The mean and standard deviation of body fat percentage of the DEXA assessment was 21.2 ± 4.3 and body fat percentage obtained from three Jackson and Pollock 3-, 4- and 7-site equations were 21.1 ± 5.8, 22.2 ± 6.0 and 20.9 ± 5.7, respectively. There was a strong correlation between these three equations and DEXA (R² = 0.98). Conclusions: The mean percentage of body fat obtained from the three equations of Jackson and Pollock was very close to that of body fat obtained from DEXA; however, we suggest using a modified Jackson-Pollock 3-site equation for volunteer military men because the 3-site equation analysis method is simpler and faster than other methods. PMID:26715964

  19. The development of a coupled ice-ocean model for forecasting ice conditions in the Arctic

    NASA Astrophysics Data System (ADS)

    Riedlinger, Shelley H.; Preller, Ruth H.

    1991-09-01

    A coupled ice-ocean model has been developed to investigate how a better simulation of ice-ocean interaction can improve sea ice forecasting capabilities. The coupling of the ice and ocean results in improved temporal variability of ocean circulation and heat and salt exchange between ice and ocean. The U.S. Navy's Polar Ice Prediction System is coupled to a diagnostic version of the Bryan-Cox three-dimensional ocean circulation model. A horizontal grid spacing of 127 km was used in the coupled model with 17 vertical levels from the surface to the ocean bottom. Atmospheric data from the Naval Operational Global Atmospheric Prediction System (NOGAPS) for 1986 were used to force the model. The ice-ocean model simulation yielded realistic ice thickness distributions, ice drifts, and ocean currents. The model predicted accurate seasonal trends in ice growth and decay. Excess ice is often grown in the Greenland and Barents seas in fall and winter. This is due, in part, to the model's grid resolution which does not accurately resolve narrow currents, such as the West Spitsbergen Current. A sensitivity study of the heat transfer coefficients used in the ice model showed that the ice edge could be improved by using different coefficient values for thick ice, thin ice, and open water. Other sensitivity studies examined the effect of removing the "distorted" physics frequently used in the Bryan-Cox ocean circulation model and the effect of the vertical eddy momentum coefficient on the surface ocean circulation. An additional simulation was made using 1989 NOGAPS forcing to examine what type of variability could occur when using different years of NOGAPS forcing in the diagnostic ocean model. Significant differences occurred between the 1989 and 1986 ice thickness distributions as well as the oceanic heat fluxes. These differences show that the forecast system, which presently uses an ocean "climatology," can benefit from the variability allowed by the diagnostic ocean model.

  20. Industrial Compositional Streamline Simulation for Efficient and Accurate Prediction of Gas Injection and WAG Processes

    SciTech Connect

    Margot Gerritsen

    2008-10-31

    Gas-injection processes are widely and increasingly used for enhanced oil recovery (EOR). In the United States, for example, EOR production by gas injection accounts for approximately 45% of total EOR production and has tripled since 1986. The understanding of the multiphase, multicomponent flow taking place in any displacement process is essential for successful design of gas-injection projects. Due to complex reservoir geometry, reservoir fluid properties and phase behavior, the design of accurate and efficient numerical simulations for the multiphase, multicomponent flow governing these processes is nontrivial. In this work, we developed, implemented and tested a streamline based solver for gas injection processes that is computationally very attractive: as compared to traditional Eulerian solvers in use by industry it computes solutions with a computational speed orders of magnitude higher and a comparable accuracy provided that cross-flow effects do not dominate. We contributed to the development of compositional streamline solvers in three significant ways: improvement of the overall framework allowing improved streamline coverage and partial streamline tracing, amongst others; parallelization of the streamline code, which significantly improves wall clock time; and development of new compositional solvers that can be implemented along streamlines as well as in existing Eulerian codes used by industry. We designed several novel ideas in the streamline framework. First, we developed an adaptive streamline coverage algorithm. Adding streamlines locally can reduce computational costs by concentrating computational efforts where needed, and reduce mapping errors. Adapting streamline coverage effectively controls mass balance errors that mostly result from the mapping from streamlines to pressure grid. We also introduced the concept of partial streamlines: streamlines that do not necessarily start and/or end at wells. This allows more efficient coverage and avoids

  1. An Accurate Method for Prediction of Protein-Ligand Binding Site on Protein Surface Using SVM and Statistical Depth Function

    PubMed Central

    Wang, Kui; Gao, Jianzhao; Shen, Shiyi; Tuszynski, Jack A.; Ruan, Jishou

    2013-01-01

    Since proteins carry out their functions through interactions with other molecules, accurately identifying the protein-ligand binding site plays an important role in protein functional annotation and rational drug discovery. In the past two decades, a lot of algorithms were present to predict the protein-ligand binding site. In this paper, we introduce statistical depth function to define negative samples and propose an SVM-based method which integrates sequence and structural information to predict binding site. The results show that the present method performs better than the existent ones. The accuracy, sensitivity, and specificity on training set are 77.55%, 56.15%, and 87.96%, respectively; on the independent test set, the accuracy, sensitivity, and specificity are 80.36%, 53.53%, and 92.38%, respectively. PMID:24195070

  2. Deformation, Failure, and Fatigue Life of SiC/Ti-15-3 Laminates Accurately Predicted by MAC/GMC

    NASA Technical Reports Server (NTRS)

    Bednarcyk, Brett A.; Arnold, Steven M.

    2002-01-01

    NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) (ref.1) has been extended to enable fully coupled macro-micro deformation, failure, and fatigue life predictions for advanced metal matrix, ceramic matrix, and polymer matrix composites. Because of the multiaxial nature of the code's underlying micromechanics model, GMC--which allows the incorporation of complex local inelastic constitutive models--MAC/GMC finds its most important application in metal matrix composites, like the SiC/Ti-15-3 composite examined here. Furthermore, since GMC predicts the microscale fields within each constituent of the composite material, submodels for local effects such as fiber breakage, interfacial debonding, and matrix fatigue damage can and have been built into MAC/GMC. The present application of MAC/GMC highlights the combination of these features, which has enabled the accurate modeling of the deformation, failure, and life of titanium matrix composites.

  3. How the Assumed Size Distribution of Dust Minerals Affects the Predicted Ice Forming Nuclei

    NASA Astrophysics Data System (ADS)

    Perlwitz, J. P.; Fridlind, A. M.; Pérez García-Pando, C.; Miller, R. L.; Knopf, D. A.

    2015-12-01

    The formation of ice in clouds depends on the availability of ice forming nuclei (IFN). Dust aerosol particles are considered the most important source of IFN at a global scale. Recent laboratory studies have demonstrated that the mineral feldspar provides the most efficient dust IFN for immersion freezing and together with kaolinite for deposition ice nucleation, and that the phyllosilicates illite and montmorillonite (a member of the smectite group) are of secondary importance.A few studies have applied global models that simulate mineral specific dust to predict the number and geographical distribution of IFN. These studies have been based on the simple assumption that the mineral composition of soil as provided in data sets from the literature translates directly into the mineral composition of the dust aerosols. However, these tables are based on measurements of wet-sieved soil where dust aggregates are destroyed to a large degree. In consequence, the size distribution of dust is shifted to smaller sizes, and phyllosilicates like illite, kaolinite, and smectite are only found in the size range <2 μm. In contrast, in measurements of the mineral composition of dust aerosols, the largest mass fraction of these phyllosilicates is found in the size range >2 μm as part of dust aggregates. Conversely, the mass fraction of feldspar is smaller in this size range, varying with the geographical location. This may have a significant effect on the predicted IFN number and its geographical distribution.An improved mineral specific dust aerosol module has been recently implemented in the NASA GISS Earth System ModelE2. The dust module takes into consideration the disaggregated state of wet-sieved soil, on which the tables of soil mineral fractions are based. To simulate the atmospheric cycle of the minerals, the mass size distribution of each mineral in aggregates that are emitted from undispersed parent soil is reconstructed. In the current study, we test the null

  4. How the Assumed Size Distribution of Dust Minerals Affects the Predicted Ice Forming Nuclei

    NASA Technical Reports Server (NTRS)

    Perlwitz, Jan P.; Fridlind, Ann M.; Garcia-Pando, Carlos Perez; Miller, Ron L.; Knopf, Daniel A.

    2015-01-01

    The formation of ice in clouds depends on the availability of ice forming nuclei (IFN). Dust aerosol particles are considered the most important source of IFN at a global scale. Recent laboratory studies have demonstrated that the mineral feldspar provides the most efficient dust IFN for immersion freezing and together with kaolinite for deposition ice nucleation, and that the phyllosilicates illite and montmorillonite (a member of the smectite group) are of secondary importance.A few studies have applied global models that simulate mineral specific dust to predict the number and geographical distribution of IFN. These studies have been based on the simple assumption that the mineral composition of soil as provided in data sets from the literature translates directly into the mineral composition of the dust aerosols. However, these tables are based on measurements of wet-sieved soil where dust aggregates are destroyed to a large degree. In consequence, the size distribution of dust is shifted to smaller sizes, and phyllosilicates like illite, kaolinite, and smectite are only found in the size range 2 m. In contrast, in measurements of the mineral composition of dust aerosols, the largest mass fraction of these phyllosilicates is found in the size range 2 m as part of dust aggregates. Conversely, the mass fraction of feldspar is smaller in this size range, varying with the geographical location. This may have a significant effect on the predicted IFN number and its geographical distribution.An improved mineral specific dust aerosol module has been recently implemented in the NASA GISS Earth System ModelE2. The dust module takes into consideration the disaggregated state of wet-sieved soil, on which the tables of soil mineral fractions are based. To simulate the atmospheric cycle of the minerals, the mass size distribution of each mineral in aggregates that are emitted from undispersed parent soil is reconstructed. In the current study, we test the null

  5. The sensitivity of a one-dimensional thermodynamic sea ice model to changes in cloudiness

    NASA Technical Reports Server (NTRS)

    Shine, K. P.; Crane, R. G.

    1984-01-01

    A thermodynamic sea ice-lead model is used to assess the importance of cloud cover changes to modeled ice thickness. For regions of either permanent multiyear ice or seasonal sea ice, the cloud amount variations have relatively little impact. However, for regions where the presence of summer ice is variable from year to year, the predicted ice thickness is strongly dependent on cloud cover. In general, with a snow covered surface, decreased cloud leads to surface cooling while increased cloud gives rise to a surface warming. For a melting bare ice surface, the reverse occurs. The ice model response time is too long for interannual variations in cloud amount to explain interannual variations in ice thickness and extent. Nevertheless, the implication of the results is that numerical modeling of sea ice distribution requires accurate cloud data or cloud prediction and that trends in cloud cover may lead to significant perturbations in sea ice extent and thickness.

  6. A cross-race effect in metamemory: Predictions of face recognition are more accurate for members of our own race.

    PubMed

    Hourihan, Kathleen L; Benjamin, Aaron S; Liu, Xiping

    2012-09-01

    The Cross-Race Effect (CRE) in face recognition is the well-replicated finding that people are better at recognizing faces from their own race, relative to other races. The CRE reveals systematic limitations on eyewitness identification accuracy and suggests that some caution is warranted in evaluating cross-race identification. The CRE is a problem because jurors value eyewitness identification highly in verdict decisions. In the present paper, we explore how accurate people are in predicting their ability to recognize own-race and other-race faces. Caucasian and Asian participants viewed photographs of Caucasian and Asian faces, and made immediate judgments of learning during study. An old/new recognition test replicated the CRE: both groups displayed superior discriminability of own-race faces, relative to other-race faces. Importantly, relative metamnemonic accuracy was also greater for own-race faces, indicating that the accuracy of predictions about face recognition is influenced by race. This result indicates another source of concern when eliciting or evaluating eyewitness identification: people are less accurate in judging whether they will or will not recognize a face when that face is of a different race than they are. This new result suggests that a witness's claim of being likely to recognize a suspect from a lineup should be interpreted with caution when the suspect is of a different race than the witness.

  7. A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance.

    PubMed

    Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu

    2015-09-01

    Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed.

  8. A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance.

    PubMed

    Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu

    2015-09-01

    Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed. PMID:26121186

  9. Why don't we learn to accurately forecast feelings? How misremembering our predictions blinds us to past forecasting errors.

    PubMed

    Meyvis, Tom; Ratner, Rebecca K; Levav, Jonathan

    2010-11-01

    Why do affective forecasting errors persist in the face of repeated disconfirming evidence? Five studies demonstrate that people misremember their forecasts as consistent with their experience and thus fail to perceive the extent of their forecasting error. As a result, people do not learn from past forecasting errors and fail to adjust subsequent forecasts. In the context of a Super Bowl loss (Study 1), a presidential election (Studies 2 and 3), an important purchase (Study 4), and the consumption of candies (Study 5), individuals mispredicted their affective reactions to these experiences and subsequently misremembered their predictions as more accurate than they actually had been. The findings indicate that this recall error results from people's tendency to anchor on their current affective state when trying to recall their affective forecasts. Further, those who showed larger recall errors were less likely to learn to adjust their subsequent forecasts and reminding people of their actual forecasts enhanced learning. These results suggest that a failure to accurately recall one's past predictions contributes to the perpetuation of forecasting errors.

  10. Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

    PubMed Central

    Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.

    2016-01-01

    The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally—a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process. PMID:26887592

  11. Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding.

    PubMed

    Nissley, Daniel A; Sharma, Ajeet K; Ahmed, Nabeel; Friedrich, Ulrike A; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P

    2016-01-01

    The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally--a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process. PMID:26887592

  12. Lava heating and loading of ice sheets on early Mars: Predictions for meltwater generation, groundwater recharge, and resulting landforms

    NASA Astrophysics Data System (ADS)

    Cassanelli, James P.; Head, James W.

    2016-06-01

    Recent modeling studies of the early Mars climate predict a predominantly cold climate, characterized by the formation of regional ice sheets across the highland areas of Mars. Formation of the predicted "icy highlands" ice sheets is coincident with a peak in the volcanic flux of Mars involving the emplacement of the Late Noachian - Early Hesperian ridged plains unit. We explore the relationship between the predicted early Mars "icy highlands" ice sheets, and the extensive early flood volcanism to gain insight into the surface conditions prevalent during the Late Noachian to Early Hesperian transition period. Using Hesperia Planum as a type area, we develop an ice sheet lava heating and loading model. We quantitatively assess the thermal and melting processes involved in the lava heating and loading process following the chronological sequence of lava emplacement. We test a broad range of parameters to thoroughly constrain the lava heating and loading process and outline predictions for the formation of resulting geological features. We apply the theoretical model to a study area within the Hesperia Planum region and assess the observed geology against predictions derived from the ice sheet lava heating and loading model. Due to the highly cratered nature of the Noachian highlands terrain onto which the volcanic plains were emplaced, we predict highly asymmetrical lava loading conditions. Crater interiors are predicted to accumulate greater thicknesses of lava over more rapid timescales, while in the intercrater plains, lava accumulation occurs over longer timescales and does not reach great thicknesses. We find that top-down melting due to conductive heat transfer from supraglacial lava flows is generally limited when the emplaced lava flows are less than ∼10 m thick, but is very significant at lava flow thicknesses of ∼100 m or greater. We find that bottom-up cryosphere and ice sheet melting is most likely to occur within crater interiors where lavas

  13. Using Web-based Interspecies Correlation Estimation (Web-ICE) models as a tool for acute toxicity prediction

    EPA Science Inventory

    In order to assess risk of contaminants to taxa with limited or no toxicity data available, Interspecies Correlation Estimation (ICE) models have been developed by the U.S. Environmental Protection Agency to extrapolate contaminant sensitivity predictions based on data from commo...

  14. User's manual for the NASA Lewis ice accretion/heat transfer prediction code with electrothermal deicer input

    NASA Technical Reports Server (NTRS)

    Masiulaniec, Konstanty C.; Wright, William B.

    1994-01-01

    A version of LEWICE has been developed that incorporates a recently developed electrothermal deicer code, developed at the University of Toledo by William B. Wright. This was accomplished, in essence, by replacing a subroutine in LEWICE, called EBAL, which balanced the energies at the ice surface, with a subroutine called UTICE. UTICE performs this same energy balance, as well as handles all the time-timperature transients below the ice surface, for all of the layers of a composite blade as well as the ice layer itself. This new addition is set up in such a fashion that a user may specify any number of heaters, any heater chordwise length, and any heater gap desired. The heaters may be fired in unison, or they may be cycled with periods independent of each other. The heater intensity may also be varied. In addition, the user may specify any number of layers and thicknesses depthwise into the blade. Thus, the new addition has maximum flexibility in modeling virtually any electrothermal deicer installed into any airfoil. It should be noted that the model simulates both shedding and runback. With the runback capability, it can simulate the anti-icing mode of heater performance, as well as detect icing downstream of the heaters due to runback in unprotected portions of the airfoil. This version of LEWICE can be run in three modes. In mode 1, no conduction heat transfer is modeled (which would be equivalent to the original version of LEWICE). In mode 2, all heat transfer is considered due to conduction but no heaters are firing. In mode 3, conduction heat transfer where the heaters are engaged is modeled, with subsequent ice shedding. When run in the first mode, there is virtually identical agreement with the original version of LEWICE in the prediction of accreted ice shapes. The code may be run in the second mode to determine the effects of conduction on the ice accretion process.

  15. User's manual for the NASA Lewis ice accretion/heat transfer prediction code with electrothermal deicer input

    NASA Astrophysics Data System (ADS)

    Masiulaniec, Konstanty C.; Wright, William B.

    1994-07-01

    A version of LEWICE has been developed that incorporates a recently developed electrothermal deicer code, developed at the University of Toledo by William B. Wright. This was accomplished, in essence, by replacing a subroutine in LEWICE, called EBAL, which balanced the energies at the ice surface, with a subroutine called UTICE. UTICE performs this same energy balance, as well as handles all the time-timperature transients below the ice surface, for all of the layers of a composite blade as well as the ice layer itself. This new addition is set up in such a fashion that a user may specify any number of heaters, any heater chordwise length, and any heater gap desired. The heaters may be fired in unison, or they may be cycled with periods independent of each other. The heater intensity may also be varied. In addition, the user may specify any number of layers and thicknesses depthwise into the blade. Thus, the new addition has maximum flexibility in modeling virtually any electrothermal deicer installed into any airfoil. It should be noted that the model simulates both shedding and runback. With the runback capability, it can simulate the anti-icing mode of heater performance, as well as detect icing downstream of the heaters due to runback in unprotected portions of the airfoil. This version of LEWICE can be run in three modes. In mode 1, no conduction heat transfer is modeled (which would be equivalent to the original version of LEWICE). In mode 2, all heat transfer is considered due to conduction but no heaters are firing. In mode 3, conduction heat transfer where the heaters are engaged is modeled, with subsequent ice shedding. When run in the first mode, there is virtually identical agreement with the original version of LEWICE in the prediction of accreted ice shapes. The code may be run in the second mode to determine the effects of conduction on the ice accretion process.

  16. A simple yet accurate correction for winner's curse can predict signals discovered in much larger genome scans

    PubMed Central

    Bigdeli, T. Bernard; Lee, Donghyung; Webb, Bradley Todd; Riley, Brien P.; Vladimirov, Vladimir I.; Fanous, Ayman H.; Kendler, Kenneth S.; Bacanu, Silviu-Alin

    2016-01-01

    Motivation: For genetic studies, statistically significant variants explain far less trait variance than ‘sub-threshold’ association signals. To dimension follow-up studies, researchers need to accurately estimate ‘true’ effect sizes at each SNP, e.g. the true mean of odds ratios (ORs)/regression coefficients (RRs) or Z-score noncentralities. Naïve estimates of effect sizes incur winner’s curse biases, which are reduced only by laborious winner’s curse adjustments (WCAs). Given that Z-scores estimates can be theoretically translated on other scales, we propose a simple method to compute WCA for Z-scores, i.e. their true means/noncentralities. Results:WCA of Z-scores shrinks these towards zero while, on P-value scale, multiple testing adjustment (MTA) shrinks P-values toward one, which corresponds to the zero Z-score value. Thus, WCA on Z-scores scale is a proxy for MTA on P-value scale. Therefore, to estimate Z-score noncentralities for all SNPs in genome scans, we propose FDR Inverse Quantile Transformation (FIQT). It (i) performs the simpler MTA of P-values using FDR and (ii) obtains noncentralities by back-transforming MTA P-values on Z-score scale. When compared to competitors, realistic simulations suggest that FIQT is more (i) accurate and (ii) computationally efficient by orders of magnitude. Practical application of FIQT to Psychiatric Genetic Consortium schizophrenia cohort predicts a non-trivial fraction of sub-threshold signals which become significant in much larger supersamples. Conclusions: FIQT is a simple, yet accurate, WCA method for Z-scores (and ORs/RRs, via simple transformations). Availability and Implementation: A 10 lines R function implementation is available at https://github.com/bacanusa/FIQT. Contact: sabacanu@vcu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27187203

  17. Small-scale field experiments accurately scale up to predict density dependence in reef fish populations at large scales.

    PubMed

    Steele, Mark A; Forrester, Graham E

    2005-09-20

    Field experiments provide rigorous tests of ecological hypotheses but are usually limited to small spatial scales. It is thus unclear whether these findings extrapolate to larger scales relevant to conservation and management. We show that the results of experiments detecting density-dependent mortality of reef fish on small habitat patches scale up to have similar effects on much larger entire reefs that are the size of small marine reserves and approach the scale at which some reef fisheries operate. We suggest that accurate scaling is due to the type of species interaction causing local density dependence and the fact that localized events can be aggregated to describe larger-scale interactions with minimal distortion. Careful extrapolation from small-scale experiments identifying species interactions and their effects should improve our ability to predict the outcomes of alternative management strategies for coral reef fishes and their habitats.

  18. Effects of the inlet conditions and blood models on accurate prediction of hemodynamics in the stented coronary arteries

    NASA Astrophysics Data System (ADS)

    Jiang, Yongfei; Zhang, Jun; Zhao, Wanhua

    2015-05-01

    Hemodynamics altered by stent implantation is well-known to be closely related to in-stent restenosis. Computational fluid dynamics (CFD) method has been used to investigate the hemodynamics in stented arteries in detail and help to analyze the performances of stents. In this study, blood models with Newtonian or non-Newtonian properties were numerically investigated for the hemodynamics at steady or pulsatile inlet conditions respectively employing CFD based on the finite volume method. The results showed that the blood model with non-Newtonian property decreased the area of low wall shear stress (WSS) compared with the blood model with Newtonian property and the magnitude of WSS varied with the magnitude and waveform of the inlet velocity. The study indicates that the inlet conditions and blood models are all important for accurately predicting the hemodynamics. This will be beneficial to estimate the performances of stents and also help clinicians to select the proper stents for the patients.

  19. TIMP2•IGFBP7 biomarker panel accurately predicts acute kidney injury in high-risk surgical patients

    PubMed Central

    Gunnerson, Kyle J.; Shaw, Andrew D.; Chawla, Lakhmir S.; Bihorac, Azra; Al-Khafaji, Ali; Kashani, Kianoush; Lissauer, Matthew; Shi, Jing; Walker, Michael G.; Kellum, John A.

    2016-01-01

    BACKGROUND Acute kidney injury (AKI) is an important complication in surgical patients. Existing biomarkers and clinical prediction models underestimate the risk for developing AKI. We recently reported data from two trials of 728 and 408 critically ill adult patients in whom urinary TIMP2•IGFBP7 (NephroCheck, Astute Medical) was used to identify patients at risk of developing AKI. Here we report a preplanned analysis of surgical patients from both trials to assess whether urinary tissue inhibitor of metalloproteinase 2 (TIMP-2) and insulin-like growth factor–binding protein 7 (IGFBP7) accurately identify surgical patients at risk of developing AKI. STUDY DESIGN We enrolled adult surgical patients at risk for AKI who were admitted to one of 39 intensive care units across Europe and North America. The primary end point was moderate-severe AKI (equivalent to KDIGO [Kidney Disease Improving Global Outcomes] stages 2–3) within 12 hours of enrollment. Biomarker performance was assessed using the area under the receiver operating characteristic curve, integrated discrimination improvement, and category-free net reclassification improvement. RESULTS A total of 375 patients were included in the final analysis of whom 35 (9%) developed moderate-severe AKI within 12 hours. The area under the receiver operating characteristic curve for [TIMP-2]•[IGFBP7] alone was 0.84 (95% confidence interval, 0.76–0.90; p < 0.0001). Biomarker performance was robust in sensitivity analysis across predefined subgroups (urgency and type of surgery). CONCLUSION For postoperative surgical intensive care unit patients, a single urinary TIMP2•IGFBP7 test accurately identified patients at risk for developing AKI within the ensuing 12 hours and its inclusion in clinical risk prediction models significantly enhances their performance. LEVEL OF EVIDENCE Prognostic study, level I. PMID:26816218

  20. A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.

    PubMed

    Ydreborg, Magdalena; Lisovskaja, Vera; Lagging, Martin; Brehm Christensen, Peer; Langeland, Nina; Buhl, Mads Rauning; Pedersen, Court; Mørch, Kristine; Wejstål, Rune; Norkrans, Gunnar; Lindh, Magnus; Färkkilä, Martti; Westin, Johan

    2014-01-01

    Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV) infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred to as Nordic Liver Index (NoLI) in the paper, was based on the model: Log-odds (predicting cirrhosis) = -12.17+ (age × 0.11) + (BMI (kg/m(2)) × 0.23) + (D7-lathosterol (μg/100 mg cholesterol)×(-0.013)) + (Platelet count (x10(9)/L) × (-0.018)) + (Prothrombin-INR × 3.69). The area under the ROC curve (AUROC) for prediction of cirrhosis was 0.91 (95% CI 0.86-0.96). The index was validated in a separate cohort of 83 patients and the AUROC for this cohort was similar (0.90; 95% CI: 0.82-0.98). In conclusion, the new index may complement other methods in diagnosing cirrhosis in patients with chronic HCV infection.

  1. Prenatal maternal stress predicts childhood asthma in girls: project ice storm.

    PubMed

    Turcotte-Tremblay, Anne-Marie; Lim, Robert; Laplante, David P; Kobzik, Lester; Brunet, Alain; King, Suzanne

    2014-01-01

    Little is known about how prenatal maternal stress (PNMS) influences risks of asthma in humans. In this small study, we sought to determine whether disaster-related PNMS would predict asthma risk in children. In June 1998, we assessed severity of objective hardship and subjective distress in women pregnant during the January 1998 Quebec Ice Storm. Lifetime asthma symptoms, diagnoses, and corticosteroid utilization were assessed when the children were 12 years old (N = 68). No effects of objective hardship or timing of the exposure were found. However, we found that, in girls only, higher levels of prenatal maternal subjective distress predicted greater lifetime risk of wheezing (OR = 1.11; 90% CI = 1.01-1.23), doctor-diagnosed asthma (OR = 1.09; 90% CI = 1.00-1.19), and lifetime utilization of corticosteroids (OR = 1.12; 90% CI = 1.01-1.25). Other perinatal and current maternal life events were also associated with asthma outcomes. Findings suggest that stress during pregnancy opens a window for fetal programming of immune functioning. A sex-based approach may be useful to examine how prenatal and postnatal environments combine to program the immune system. This small study needs to be replicated with a larger, more representative sample.

  2. Probing Pluto's Underworld : Predicted Ice Temperatures from Microwave Radiometry Decoupled from Surface Conditions

    NASA Astrophysics Data System (ADS)

    Le Gall, Alice; Lorenz, Ralph; Leyrat, Cedric

    2015-11-01

    The Pluto dwarf planet has been successfully observed in July 2015 by the New Horizons spacecraft (NASA) during a close-targeted flyby which reavealed surprising and fascinating landscapes. While data are still being downlinked on the ground, we propose to present a prediction of the observation of the Radio Science Experiment experiment (REX) that occured on July 14, 2015 and aimed at measuring the microwave brightness temperature of Pluto’s night side.Present models admit a wide range of 2015 surface conditions at Pluto and Charon, where the atmospheric pressure may undergo dramatic seasonal variation and for which measurements have been performed by the New Horizons mission. One anticipated observation is the microwave brightness temperature, heretofore anticipated as indicating surface conditions relevant to surface-atmosphere equilibrium. However, drawing on recent experience with Cassini observations at Iapetus and Titan, we call attention to the large electrical skin depth of outer solar system materials such as methane, nitrogen or water ice, such that this observation may indicate temperatures averaged over depths of several or tens of meters beneath the surface.Using a seasonally-forced thermal model to determine microwave emission we predict that the southern hemisphere observations (in the polar night in July 2015) of New Horizons should display relatively warm effective temperatures of about 40 K. This would reflect the deep heat buried over the last century of summer, even if the atmospheric pressure suggests that the surface nitrogen frost point may be much lower. We will present our predictions and discuss their impact for the interpretation of the REX measurements.

  3. Accurate electrical prediction of memory array through SEM-based edge-contour extraction using SPICE simulation

    NASA Astrophysics Data System (ADS)

    Shauly, Eitan; Rotstein, Israel; Peltinov, Ram; Latinski, Sergei; Adan, Ofer; Levi, Shimon; Menadeva, Ovadya

    2009-03-01

    The continues transistors scaling efforts, for smaller devices, similar (or larger) drive current/um and faster devices, increase the challenge to predict and to control the transistor off-state current. Typically, electrical simulators like SPICE, are using the design intent (as-drawn GDS data). At more sophisticated cases, the simulators are fed with the pattern after lithography and etch process simulations. As the importance of electrical simulation accuracy is increasing and leakage is becoming more dominant, there is a need to feed these simulators, with more accurate information extracted from physical on-silicon transistors. Our methodology to predict changes in device performances due to systematic lithography and etch effects was used in this paper. In general, the methodology consists on using the OPCCmaxTM for systematic Edge-Contour-Extraction (ECE) from transistors, taking along the manufacturing and includes any image distortions like line-end shortening, corner rounding and line-edge roughness. These measurements are used for SPICE modeling. Possible application of this new metrology is to provide a-head of time, physical and electrical statistical data improving time to market. In this work, we applied our methodology to analyze a small and large array's of 2.14um2 6T-SRAM, manufactured using Tower Standard Logic for General Purposes Platform. 4 out of the 6 transistors used "U-Shape AA", known to have higher variability. The predicted electrical performances of the transistors drive current and leakage current, in terms of nominal values and variability are presented. We also used the methodology to analyze an entire SRAM Block array. Study of an isolation leakage and variability are presented.

  4. Predicting the abundance of ice nucleating particles of biological origin in precipitation

    NASA Astrophysics Data System (ADS)

    Stopelli, Emiliano; Conen, Franz; Morris, Cindy; Alewell, Christine

    2016-04-01

    Ice nucleation is a key step for the formation of precipitation on Earth. Ice nucleating particles (INPs) of biological origin catalyse the freezing of supercooled cloud droplets at temperatures warmer than -12 ° C. In order to understand the effective role of these INPs in conditioning precipitation, it is of primary importance to describe and predict their variability in the atmosphere. Over the course of two years, 14 sampling campaigns in precipitating clouds were conducted at the High Altitude Research Station Jungfraujoch, in the Swiss Alps, at 3580 m a.s.l. A total of 106 freshly fallen snow samples were analysed immediately on site for the concentration of INPs active at -8 ° C (INPs-8) by immersion freezing. Values of INPs-8 ranged from 0.21 to 434ṡml-1. Environmental parameters (like temperature of the air, wind speed, the stable oxygen ratio δ18O of snow, the number of particles larger than 0.5 μm) were used as independent variables to build a set of multiple linear regression models to describe and predict the observed variations of INPs-8 over time. The model providing the best results was based on fV (the fraction of remaining vapour in precipitating clouds, derived from δ18O) and on wind speed. It indicates that a coincidence of strong atmospheric turbulence and little prior precipitation from a cloud coincides with large concentrations of INPs-8. These conditions can be frequently encountered when air masses are suddenly forced to rise, for instance by the passage of a cold front, where also meteorological conditions are favourable to the onset of precipitation. To obtain more information on the presence of INPs-8 of biological origin and their relative composition, a set of precipitation samples were progressively filtered through different meshes (5 μm, 1.2 μm, 0.22 μm) followed by heating (40 ° C and 80 ° C). Almost all ice nucleating activity is lost after heating at 80 ° C, and a significant part of INPs-8 is sensitive to warming

  5. Predicting the abundance of ice nucleating particles of biological origin in precipitation

    NASA Astrophysics Data System (ADS)

    Stopelli, Emiliano; Conen, Franz; Morris, Cindy; Alewell, Christine

    2016-04-01

    Ice nucleation is a key step for the formation of precipitation on Earth. Ice nucleating particles (INPs) of biological origin catalyse the freezing of supercooled cloud droplets at temperatures warmer than -12 ° C. In order to understand the effective role of these INPs in conditioning precipitation, it is of primary importance to describe and predict their variability in the atmosphere. Over the course of two years, 14 sampling campaigns in precipitating clouds were conducted at the High Altitude Research Station Jungfraujoch, in the Swiss Alps, at 3580 m a.s.l. A total of 106 freshly fallen snow samples were analysed immediately on site for the concentration of INPs active at -8 ° C (INPs‑8) by immersion freezing. Values of INPs‑8 ranged from 0.21 to 434ṡml‑1. Environmental parameters (like temperature of the air, wind speed, the stable oxygen ratio δ18O of snow, the number of particles larger than 0.5 μm) were used as independent variables to build a set of multiple linear regression models to describe and predict the observed variations of INPs‑8 over time. The model providing the best results was based on fV (the fraction of remaining vapour in precipitating clouds, derived from δ18O) and on wind speed. It indicates that a coincidence of strong atmospheric turbulence and little prior precipitation from a cloud coincides with large concentrations of INPs‑8. These conditions can be frequently encountered when air masses are suddenly forced to rise, for instance by the passage of a cold front, where also meteorological conditions are favourable to the onset of precipitation. To obtain more information on the presence of INPs‑8 of biological origin and their relative composition, a set of precipitation samples were progressively filtered through different meshes (5 μm, 1.2 μm, 0.22 μm) followed by heating (40 ° C and 80 ° C). Almost all ice nucleating activity is lost after heating at 80 ° C, and a significant part of INPs‑8 is

  6. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

    PubMed

    Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J

    2015-09-30

    database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887

  7. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

    PubMed Central

    Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.

    2015-01-01

    database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887

  8. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

    PubMed

    Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J

    2015-09-30

    database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior.

  9. Prenatal maternal stress predicts autism traits in 6½ year-old children: Project Ice Storm.

    PubMed

    Walder, Deborah J; Laplante, David P; Sousa-Pires, Alexandra; Veru, Franz; Brunet, Alain; King, Suzanne

    2014-10-30

    Research implicates prenatal maternal stress (PNMS) as a risk factor for neurodevelopmental disorders; however few studies report PNMS effects on autism risk in offspring. We examined, prospectively, the degree to which objective and subjective elements of PNMS explained variance in autism-like traits among offspring, and tested moderating effects of sex and PNMS timing in utero. Subjects were 89 (46F/43M) children who were in utero during the 1998 Quebec Ice Storm. Soon after the storm, mothers completed questionnaires on objective exposure and subjective distress, and completed the Autism Spectrum Screening Questionnaire (ASSQ) for their children at age 6½. ASSQ scores were higher among boys than girls. Greater objective and subjective PNMS predicted higher ASSQ independent of potential confounds. An objective-by-subjective interaction suggested that when subjective PNMS was high, objective PNMS had little effect; whereas when subjective PNMS was low, objective PNMS strongly affected ASSQ scores. A timing-by-objective stress interaction suggested objective stress significantly affected ASSQ in first-trimester exposed children, though less so with later exposure. The final regression explained 43% of variance in ASSQ scores; the main effect of sex and the sex-by-PNMS interactions were not significant. Findings may help elucidate neurodevelopmental origins of non-clinical autism-like traits from a dimensional perspective.

  10. Comparing predicted and observed spatial boundaries of geologic phenomena: Automated Proximity and Conformity Analysis applied to ice sheet reconstructions

    NASA Astrophysics Data System (ADS)

    Napieralski, Jacob; Li, Yingkui; Harbor, Jon

    2006-02-01

    Comparing predicted with observed geologic data is a central element of many aspects of research in the geosciences, e.g., comparing numerical ice sheet models with geomorphic data to test ice sheet model parameters and accuracy. However, the ability to verify predictions using empirical data has been limited by the lack of objective techniques that provide systematic comparison and statistical assessment of the goodness of correspondence between predictions of spatial and temporal patterns of geologic phenomena and the field evidence. Much of this problem arises from the inability to quantify the level of agreement between straight or curvilinear features, such as between the modeled extent of some geologic phenomenon and the field evidence for the extent of the phenomenon. Automated Proximity and Conformity Analysis (APCA) addresses this challenge using a system of Geographic Information System-based buffering that determines the general proximity and parallel conformity between linear features. APCA results indicate which modeled output fits empirical data, based on the distance and angle between features. As a result, various model outputs can be sorted according to overall level of agreement by comparison with one or multiple features from field evidence, based on proximity and conformity values. In an example application drawn from glacial geomorphology, APCA is integrated into an overall model verification process that includes matching modeled ice sheets to known marginal positions and ice flow directions, among other parameters. APCA is not limited to ice sheet or glacier models, but can be applied to many geoscience areas where the extent or geometry of modeled results need to be compared against field observations, such as debris flows, tsunami run-out, lava flows, or flood extents.

  11. Computational finite element bone mechanics accurately predicts mechanical competence in the human radius of an elderly population.

    PubMed

    Mueller, Thomas L; Christen, David; Sandercott, Steve; Boyd, Steven K; van Rietbergen, Bert; Eckstein, Felix; Lochmüller, Eva-Maria; Müller, Ralph; van Lenthe, G Harry

    2011-06-01

    High-resolution peripheral quantitative computed tomography (HR-pQCT) is clinically available today and provides a non-invasive measure of 3D bone geometry and micro-architecture with unprecedented detail. In combination with microarchitectural finite element (μFE) models it can be used to determine bone strength using a strain-based failure criterion. Yet, images from only a relatively small part of the radius are acquired and it is not known whether the region recommended for clinical measurements does predict forearm fracture load best. Furthermore, it is questionable whether the currently used failure criterion is optimal because of improvements in image resolution, changes in the clinically measured volume of interest, and because the failure criterion depends on the amount of bone present. Hence, we hypothesized that bone strength estimates would improve by measuring a region closer to the subchondral plate, and by defining a failure criterion that would be independent of the measured volume of interest. To answer our hypotheses, 20% of the distal forearm length from 100 cadaveric but intact human forearms was measured using HR-pQCT. μFE bone strength was analyzed for different subvolumes, as well as for the entire 20% of the distal radius length. Specifically, failure criteria were developed that provided accurate estimates of bone strength as assessed experimentally. It was shown that distal volumes were better in predicting bone strength than more proximal ones. Clinically speaking, this would argue to move the volume of interest for the HR-pQCT measurements even more distally than currently recommended by the manufacturer. Furthermore, new parameter settings using the strain-based failure criterion are presented providing better accuracy for bone strength estimates.

  12. More accurate determination of the quantity of ice crystallized at low cooling rates in the glycerol and 1,2-propanediol aqueous solutions: comparison with equilibrium.

    PubMed

    Boutron, P

    1984-04-01

    It is generally assumed that when cells are cooled at rates close to those corresponding to the maximum of survival, once supercooling has ceased, above the eutectic melting temperature the extracellular ice is in equilibrium with the residual solution. This did not seem evident to us due to the difficulty of ice crystallization in cryoprotective solutions. The maximum quantities of ice crystallized in glycerol and 1,2-propanediol solutions have been calculated from the area of the solidification and fusion peaks obtained with a Perkin-Elmer DSC-2 differential scanning calorimeter. The accuracy has been improved by several corrections: better defined baseline, thermal variation of the heat of fusion of the ice, heat of solution of the water from its melting with the residual solution. More ice crystallizes in the glycerol than in the 1,2-propanediol solutions, of which the amorphous residue contains about 40 to 55% 1,2-propanediol. The equilibrium values are unknown in the presence of 1,2-propanediol. With glycerol, in our experiments, the maximum is first lower than the equilibrium but approaches it as the concentration increases. It is not completely determined by the colligative properties of the solutes.

  13. Application of a High-Fidelity Icing Analysis Method to a Model-Scale Rotor in Forward Flight

    NASA Technical Reports Server (NTRS)

    Narducci, Robert; Orr, Stanley; Kreeger, Richard E.

    2012-01-01

    An icing analysis process involving the loose coupling of OVERFLOW-RCAS for rotor performance prediction and with LEWICE3D for thermal analysis and ice accretion is applied to a model-scale rotor for validation. The process offers high-fidelity rotor analysis for the noniced and iced rotor performance evaluation that accounts for the interaction of nonlinear aerodynamics with blade elastic deformations. Ice accumulation prediction also involves loosely coupled data exchanges between OVERFLOW and LEWICE3D to produce accurate ice shapes. Validation of the process uses data collected in the 1993 icing test involving Sikorsky's Powered Force Model. Non-iced and iced rotor performance predictions are compared to experimental measurements as are predicted ice shapes.

  14. A Support Vector Machine model for the prediction of proteotypic peptides for accurate mass and time proteomics

    SciTech Connect

    Webb-Robertson, Bobbie-Jo M.; Cannon, William R.; Oehmen, Christopher S.; Shah, Anuj R.; Gurumoorthi, Vidhya; Lipton, Mary S.; Waters, Katrina M.

    2008-07-01

    Motivation: The standard approach to identifying peptides based on accurate mass and elution time (AMT) compares these profiles obtained from a high resolution mass spectrometer to a database of peptides previously identified from tandem mass spectrometry (MS/MS) studies. It would be advantageous, with respect to both accuracy and cost, to only search for those peptides that are detectable by MS (proteotypic). Results: We present a Support Vector Machine (SVM) model that uses a simple descriptor space based on 35 properties of amino acid content, charge, hydrophilicity, and polarity for the quantitative prediction of proteotypic peptides. Using three independently derived AMT databases (Shewanella oneidensis, Salmonella typhimurium, Yersinia pestis) for training and validation within and across species, the SVM resulted in an average accuracy measure of ~0.8 with a standard deviation of less than 0.025. Furthermore, we demonstrate that these results are achievable with a small set of 12 variables and can achieve high proteome coverage. Availability: http://omics.pnl.gov/software/STEPP.php

  15. Development, sensitivity analysis, and uncertainty quantification of high-fidelity arctic sea ice models.

    SciTech Connect

    Peterson, Kara J.; Bochev, Pavel Blagoveston; Paskaleva, Biliana S.

    2010-09-01

    Arctic sea ice is an important component of the global climate system and due to feedback effects the Arctic ice cover is changing rapidly. Predictive mathematical models are of paramount importance for accurate estimates of the future ice trajectory. However, the sea ice components of Global Climate Models (GCMs) vary significantly in their prediction of the future state of Arctic sea ice and have generally underestimated the rate of decline in minimum sea ice extent seen over the past thirty years. One of the contributing factors to this variability is the sensitivity of the sea ice to model physical parameters. A new sea ice model that has the potential to improve sea ice predictions incorporates an anisotropic elastic-decohesive rheology and dynamics solved using the material-point method (MPM), which combines Lagrangian particles for advection with a background grid for gradient computations. We evaluate the variability of the Los Alamos National Laboratory CICE code and the MPM sea ice code for a single year simulation of the Arctic basin using consistent ocean and atmospheric forcing. Sensitivities of ice volume, ice area, ice extent, root mean square (RMS) ice speed, central Arctic ice thickness, and central Arctic ice speed with respect to ten different dynamic and thermodynamic parameters are evaluated both individually and in combination using the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA). We find similar responses for the two codes and some interesting seasonal variability in the strength of the parameters on the solution.

  16. High IFIT1 expression predicts improved clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma.

    PubMed

    Zhang, Jin-Feng; Chen, Yao; Lin, Guo-Shi; Zhang, Jian-Dong; Tang, Wen-Long; Huang, Jian-Huang; Chen, Jin-Shou; Wang, Xing-Fu; Lin, Zhi-Xiong

    2016-06-01

    Interferon-induced protein with tetratricopeptide repeat 1 (IFIT1) plays a key role in growth suppression and apoptosis promotion in cancer cells. Interferon was reported to induce the expression of IFIT1 and inhibit the expression of O-6-methylguanine-DNA methyltransferase (MGMT).This study aimed to investigate the expression of IFIT1, the correlation between IFIT1 and MGMT, and their impact on the clinical outcome in newly diagnosed glioblastoma. The expression of IFIT1 and MGMT and their correlation were investigated in the tumor tissues from 70 patients with newly diagnosed glioblastoma. The effects on progression-free survival and overall survival were evaluated. Of 70 cases, 57 (81.4%) tissue samples showed high expression of IFIT1 by immunostaining. The χ(2) test indicated that the expression of IFIT1 and MGMT was negatively correlated (r = -0.288, P = .016). Univariate and multivariate analyses confirmed high IFIT1 expression as a favorable prognostic indicator for progression-free survival (P = .005 and .017) and overall survival (P = .001 and .001), respectively. Patients with 2 favorable factors (high IFIT1 and low MGMT) had an improved prognosis as compared with others. The results demonstrated significantly increased expression of IFIT1 in newly diagnosed glioblastoma tissue. The negative correlation between IFIT1 and MGMT expression may be triggered by interferon. High IFIT1 can be a predictive biomarker of favorable clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma. PMID:26980050

  17. Predicting global atmospheric ice nuclei distributions and their impacts on climate.

    PubMed

    DeMott, P J; Prenni, A J; Liu, X; Kreidenweis, S M; Petters, M D; Twohy, C H; Richardson, M S; Eidhammer, T; Rogers, D C

    2010-06-22

    Knowledge of cloud and precipitation formation processes remains incomplete, yet global precipitation is predominantly produced by clouds containing the ice phase. Ice first forms in clouds warmer than -36 degrees C on particles termed ice nuclei. We combine observations from field studies over a 14-year period, from a variety of locations around the globe, to show that the concentrations of ice nuclei active in mixed-phase cloud conditions can be related to temperature and the number concentrations of particles larger than 0.5 microm in diameter. This new relationship reduces unexplained variability in ice nuclei concentrations at a given temperature from approximately 10(3) to less than a factor of 10, with the remaining variability apparently due to variations in aerosol chemical composition or other factors. When implemented in a global climate model, the new parameterization strongly alters cloud liquid and ice water distributions compared to the simple, temperature-only parameterizations currently widely used. The revised treatment indicates a global net cloud radiative forcing increase of approximately 1 W m(-2) for each order of magnitude increase in ice nuclei concentrations, demonstrating the strong sensitivity of climate simulations to assumptions regarding the initiation of cloud glaciation.

  18. A time accurate prediction of the viscous flow in a turbine stage including a rotor in motion

    NASA Astrophysics Data System (ADS)

    Shavalikul, Akamol

    accurate flow characteristics in the NGV domain and the rotor domain with less computational time and computer memory requirements. In contrast, the time accurate flow simulation can predict all unsteady flow characteristics occurring in the turbine stage, but with high computational resource requirements. (Abstract shortened by UMI.)

  19. A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts?

    PubMed Central

    Harris, Adam; Harries, Priscilla

    2016-01-01

    overall accuracy being reported. Data were extracted using a standardised tool, by one reviewer, which could have introduced bias. Devising search terms for prognostic studies is challenging. Every attempt was made to devise search terms that were sufficiently sensitive to detect all prognostic studies; however, it remains possible that some studies were not identified. Conclusion Studies of prognostic accuracy in palliative care are heterogeneous, but the evidence suggests that clinicians’ predictions are frequently inaccurate. No sub-group of clinicians was consistently shown to be more accurate than any other. Implications of Key Findings Further research is needed to understand how clinical predictions are formulated and how their accuracy can be improved. PMID:27560380

  20. Polar predictability: exploring the influence of GCM and regional model uncertainty on future ice sheet climates

    NASA Astrophysics Data System (ADS)

    Reusch, D. B.

    2015-12-01

    Evaluating uncertainty in GCMs and regional-scale forecast models is an essential step in the development of climate change predictions. Polar-region skill is particularly important due to the potential for changes affecting both local (ice sheet) and global (sea level) environments through more frequent/intense surface melting and changes in precipitation type/amount. High-resolution, regional-scale models also use GCMs as a source of boundary/initial conditions in future scenarios, thus inheriting a measure of GCM-derived externally-driven uncertainty. We examine inter- and intramodel uncertainty through statistics from decadal climatologies and analyses of variability based on self-organizing maps (SOMs), a nonlinear data analysis tool. We evaluate a 19-member CMIP5 subset and the 30-member CESM1.0-CAM5-BGC Large Ensemble (CESMLE) during polar melt seasons (boreal/austral summer) for recent (1981-2000) and future (2081-2100, RCP 8.5) decades. Regional-model uncertainty is examined with a subset of these GCMs driving Polar WRF simulations. Decadal climatologies relative to a reference (recent: the ERA-Interim reanalysis; future: a skillful modern GCM) identify model uncertainty in bulk, e.g., BNU-ESM is too warm, CMCC-CM too cold. While quite useful for model screening, diagnostic benefit is often indirect. SOMs extend our diagnostics by providing a concise, objective summary of model variability as a set of generalized patterns. Joint analysis of reference and test models summarizes the variability of multiple realizations of climate (all the models), benchmarks each model versus the reference (frequency analysis helps identify the patterns behind GCM bias), and places each GCM in a common context. Joint SOM analysis of CESMLE members shows how initial conditions contribute to differences in modeled climates, providing useful information about internal variability, such as contributions from each member to overall uncertainty using pattern frequencies. In the

  1. Radar Differential Phase Signatures of Ice Orientation for the Prediction of Lightning Initiation and Cessation

    NASA Technical Reports Server (NTRS)

    Carey, L.D.; Petersen, W.A.; Deierling, W.

    2009-01-01

    The majority of lightning-related casualties typically occur during thunderstorm initiation (e.g., first flash) or dissipation (e.g., last flash). The physics of electrification and lightning production during thunderstorm initiation is fairly well understood. As such, the literature includes a number of studies presenting various radar techniques (using reflectivity and, if available, other dual-polarimetric parameters) for the anticipation of initial electrification and first lightning flash. These radar techniques have shown considerable skill at forecasting first flash. On the other hand, electrical processes and lightning production during thunderstorm dissipation are not nearly as well understood and few, if any, successful techniques have been developed to anticipate the last flash and subsequent cessation of lightning. One promising approach involves the use of dual-polarimetric radar variables to infer the presence of oriented ice crystals in lightning producing storms. In the absence of strong vertical electric fields, ice crystals fall with their largest (semi-major) axis in the horizontal associated with gravitational and aerodynamic forces. In thunderstorms, strong vertical electric fields (100-200 kV m(sup -1)) have been shown to orient small (less than 2 mm) ice crystals such that their semi-major axis is vertical (or nearly vertical). After a lightning flash, the electric field is typically relaxed and prior radar research suggests that ice crystals rapidly resume their preferred horizontal orientation. In active thunderstorms, the vertical electric field quickly recovers and the ice crystals repeat this cycle of orientation for each nearby flash. This change in ice crystal orientation from primarily horizontal to vertical during the development of strong vertical electric fields prior to a lightning flash forms the physical basis for anticipating lightning initiation and, potentially, cessation. Research has shown that radar reflectivity (Z) and

  2. Predicting High Frequency Wind-wave Generated Seismic Noise: a Way to Remotely Monitor Sea-ice Mechanical State.

    NASA Astrophysics Data System (ADS)

    Gimbert, F.; Tsai, V. C.

    2014-12-01

    It is commonly accepted that ambient ground motion within the 1 s to 10 s period range (including the so-called secondary microseism peak) is caused by ocean wave interactions that induce pressure fluctuations at the ocean floor through acoustic waves. In recent years, numerical ocean wave models have successfully predicted the maximum amplitude of the secondary microseism peak in the 4 s to 8 s range, where seismic energy is mainly caused by the interaction of ocean swells of typically 8 s to 16 s of periods, i.e. 100-400 m wavelengths, that travel in opposite directions as they are generated by distant storms, by single but fast moving storms or by coastal reflections. In contrast, little attention has been devoted to the contribution of local wind generated seas characterized by shorter period waves (1 s to 3 s ocean waves, i.e. 1-10 m wavelengths) in the generation of higher frequency seismic noise in coastal regions. While this noise content is becoming increasingly used by seismologists, for example for high resolution ground imaging from dense arrays, its absolute amplitude and frequency dependence has not yet been consistently predicted: this is the purpose of this talk. We present a simple analytical approach that allows the prediction of ambient seismic noise recorded on land in the 0.5 s to 3 s range from knowledge of the local wind field operating on the surrounding ocean. Ocean waves and their interactions are accounted for within hundreds of kilometers from coastal seismic stations, and a realistic ground structure is considered in the generation and propagation of Rayleigh waves. We show that the amplitude and frequency scaling of hourly noise spectra can be systematically predicted, and thus suggest that seismic stations can complement in-situ measurements in inferring wind sea properties in coastal regions. Furthermore, we use our new approach to demonstrate that seismic stations deployed on land can be used to remotely study ocean waves in sea ice

  3. Prediction of Lightning Inception by Large Ice Particles and Extensive Air Showers.

    PubMed

    Dubinova, Anna; Rutjes, Casper; Ebert, Ute; Buitink, Stijn; Scholten, Olaf; Trinh, Gia Thi Ngoc

    2015-07-01

    We derive that lightning can start if the electric field is 15% of the breakdown field, and if elongated ice particles of 6 cm length and 100 free electrons per cm3 are present. This is one particular example set from a parameter range that we discuss as well. Our simulations include the permittivity ε(ω) of ice. 100 free electrons per cm3 exist at 5.5 km altitude in air showers created by cosmic particles of at least 5×10(15)  eV. If the electric field zone is 3 m high and 0.2  km2 in the horizontal direction, at least one discharge per minute can be triggered. The size distribution of the ice particles is crucial for our argument; more detailed measurements would be desirable. PMID:26182101

  4. Ceres: Predictions for near-surface water ice stability and implications for plume generating processes

    NASA Astrophysics Data System (ADS)

    Titus, Timothy N.

    2015-04-01

    This paper will constrain the possible sources and processes for the formation of recently observed H2O vapor plumes above the surface of the dwarf planet Ceres. Two hypotheses have been proposed: (1) cryovolcanism where the water source is the mantle and the heating source is still unknown or (2) comet-like sublimation where near-surface water ice is vaporized by seasonally increasing solar insolation. We test hypothesis 2, comet-like near-surface sublimation, by using a thermal model to examine the stability of water ice in the near surface. For a reasonable range of physical parameters (thermal inertia, surface roughness, and slopes), we find that water ice is only stable at latitudes higher than ~40-60°. These results indicate that either (a) the physical properties of Ceres are unlike our expectations or (b) an alternative to comet-like sublimation, such as the cryovolcanism hypothesis, must be invoked.

  5. Ceres: predictions for near-surface water ice stability and implications for plume generating processes

    USGS Publications Warehouse

    Titus, Timothy N.

    2015-01-01

    This paper will constrain the possible sources and processes for the formation of recently observed H2O vapor plumes above the surface of the dwarf planet Ceres. Two hypotheses have been proposed: (1) cryovolcanism where the water source is the mantle and the heating source is still unknown or (2) comet-like sublimation where near-surface water ice is vaporized by seasonally increasing solar insolation. We test hypothesis #2, comet-like near-surface sublimation, by using a thermal model to examine the stability of water-ice in the near surface. For a reasonable range of physical parameters (thermal inertia, surface roughness, slopes), we find that water ice is only stable at latitudes higher than ~40-60 degrees. These results indicate that either (a) the physical properties of Ceres are unlike our expectations or (b) an alternative to comet-like sublimation, such as the cryovolcanism hypothesis, must be invoked.

  6. Prediction of Lightning Inception by Large Ice Particles and Extensive Air Showers.

    PubMed

    Dubinova, Anna; Rutjes, Casper; Ebert, Ute; Buitink, Stijn; Scholten, Olaf; Trinh, Gia Thi Ngoc

    2015-07-01

    We derive that lightning can start if the electric field is 15% of the breakdown field, and if elongated ice particles of 6 cm length and 100 free electrons per cm3 are present. This is one particular example set from a parameter range that we discuss as well. Our simulations include the permittivity ε(ω) of ice. 100 free electrons per cm3 exist at 5.5 km altitude in air showers created by cosmic particles of at least 5×10(15)  eV. If the electric field zone is 3 m high and 0.2  km2 in the horizontal direction, at least one discharge per minute can be triggered. The size distribution of the ice particles is crucial for our argument; more detailed measurements would be desirable.

  7. Collaborative Project. Understanding the effects of tides and eddies on the ocean dynamics, sea ice cover and decadal/centennial climate prediction using the Regional Arctic Climate Model (RACM)

    SciTech Connect

    Hutchings, Jennifer; Joseph, Renu

    2013-09-14

    The goal of this project is to develop an eddy resolving ocean model (POP) with tides coupled to a sea ice model (CICE) within the Regional Arctic System Model (RASM) to investigate the importance of ocean tides and mesoscale eddies in arctic climate simulations and quantify biases associated with these processes and how their relative contribution may improve decadal to centennial arctic climate predictions. Ocean, sea ice and coupled arctic climate response to these small scale processes will be evaluated with regard to their influence on mass, momentum and property exchange between oceans, shelf-basin, ice-ocean, and ocean-atmosphere. The project will facilitate the future routine inclusion of polar tides and eddies in Earth System Models when computing power allows. As such, the proposed research addresses the science in support of the BER’s Climate and Environmental Sciences Division Long Term Measure as it will improve the ocean and sea ice model components as well as the fully coupled RASM and Community Earth System Model (CESM) and it will make them more accurate and computationally efficient.

  8. Investigating the Effects of Water Ice Cloud Radiative Forcing on the Predicted Patterns and Strength of Dust Lifting on Mars

    NASA Astrophysics Data System (ADS)

    Kahre, Melinda A.; Hollingsworth, Jeffery L.; Haberle, Robert M.

    2014-11-01

    The dust cycle is critical for the current Mars climate system because airborne dust significantly influences the thermal and dynamical structure of the atmosphere. The atmospheric dust loading varies with season and exhibits variability on a range of spatial and temporal scales. Until recently, interactive dust cycle modeling studies that include the lifting, transport, and sedimentation of radiatively active dust have not included the formation or radiative effects of water ice clouds. While the simulated patterns of dust lifting and global dust loading from these investigations of the dust cycle in isolation reproduce some characteristics of the observed dust cycle, there are also marked differences between the predictions and the observations. Water ice clouds can influence when, where, and how much dust is lifted from the surface by altering the thermal structure of the atmosphere and the character and strength of the general circulation. Using an updated version of the NASA Ames Mars Global Climate Model (GCM), we show that including water ice cloud formation and their radiative effects affect the magnitude and spatial extent of dust lifting, particularly in the northern hemisphere during the pre- and post- winter solstitial seasons. Feedbacks between dust lifting, cloud formation, circulation intensification and further dust lifting are isolated and shown to be important for improving the behavior of the simulated dust cycle.

  9. Factors Affecting Ice Nucleation in Plant Tissues

    PubMed Central

    Ashworth, Edward N.; Davis, Glen A.; Anderson, Jeffrey A.

    1985-01-01

    Factors affecting the ice nucleation temperature of plants and plant tissues were examined. The mass of a sample had a marked effect on ice nucleation temperature. Small tissue samples supercooled to −10°C and were not accurate predictors of the nucleation temperature of intact plants in either laboratory or field experiments. This effect was not unique to plant tissues and was observed in autoclaved and control soil samples. Ice nucleation temperatures of bean, corn, cotton, and soybean seedlings were influenced by the length of subzero exposure, presence of ice nucleation active bacteria, and leaf surface wetness. The number of factors influencing ice nucleation temperature suggested that predicting the freezing behavior of plants in the field will be complex. PMID:16664524

  10. Crustal Motion and Gravity Change Predicted from Scenarios of Ice Mass Change in Marie Byrd Land and the Eastern Ross Sea

    NASA Astrophysics Data System (ADS)

    James, T. S.; Ivins, E. R.

    2006-12-01

    GPS observations indicate large (>10 mm/yr) uplift rates at a site in the Rockefeller Mountains in Marie Byrd Land (Donnellan and Luyendyk, 2004) that may have been generated by Late Holocene and present-day ice mass change. Crustal uplift predictions depend strongly on the unknown mantle viscosity profile and affect inferences of ice sheet history. By analogy with geologically similar rifted regions, such as the Basin and Range, mantle viscosity underlying much of the Ross Embayment may be as low as 1018 Pa s, but could also be one or two orders of magnitude larger. At the low end of the viscosity range, present-day uplift rates are largely sensitive to ice mass changes in the past millennium, and the GPS observations would suggest substantial recent ice thinning in the Shirase Coast and regions inland. In contrast, larger viscosity values would be sensitive to mid and Late Holocene ice mass change and would suggest substantial reduction of ice mass at that time. Satellite gravity observations, such as from the Gravity Recovery and Climate Experiment (GRACE), have the potential to help resolve this under-constrained problem, because the two end-member scenarios described above to explain the crustal motion predictions have different gravity signatures. Eventual resolution of this trade-off between mantle viscosity and ice sheet history will come from a combination of further glaciological investigations and better-constrained geodetic observations.

  11. False alarms: How early warning signals falsely predict abrupt sea ice loss

    NASA Astrophysics Data System (ADS)

    Wagner, Till J. W.; Eisenman, Ian

    2016-04-01

    Uncovering universal early warning signals for critical transitions has become a coveted goal in diverse scientific disciplines, ranging from climate science to financial mathematics. There has been a flurry of recent research proposing such signals, with increasing autocorrelation and increasing variance being among the most widely discussed candidates. A number of studies have suggested that increasing autocorrelation alone may suffice to signal an impending transition, although some others have questioned this. Here we consider variance and autocorrelation in the context of sea ice loss in an idealized model of the global climate system. The model features no bifurcation, nor increased rate of retreat, as the ice disappears. Nonetheless, the autocorrelation of summer sea ice area is found to increase in a global warming scenario. The variance, by contrast, decreases. A simple physical mechanism is proposed to explain the occurrence of increasing autocorrelation but not variance when there is no approaching bifurcation. Additionally, a similar mechanism is shown to allow an increase in both indicators with no physically attainable bifurcation. This implies that relying on autocorrelation and variance as early warning signals can raise false alarms in the climate system, warning of "tipping points" that are not actually there.

  12. False alarms: How early warning signals falsely predict abrupt sea ice loss

    NASA Astrophysics Data System (ADS)

    Wagner, Till J. W.; Eisenman, Ian

    2015-12-01

    Uncovering universal early warning signals for critical transitions has become a coveted goal in diverse scientific disciplines, ranging from climate science to financial mathematics. There has been a flurry of recent research proposing such signals, with increasing autocorrelation and increasing variance being among the most widely discussed candidates. A number of studies have suggested that increasing autocorrelation alone may suffice to signal an impending transition, although some others have questioned this. Here we consider variance and autocorrelation in the context of sea ice loss in an idealized model of the global climate system. The model features no bifurcation, nor increased rate of retreat, as the ice disappears. Nonetheless, the autocorrelation of summer sea ice area is found to increase in a global warming scenario. The variance, by contrast, decreases. A simple physical mechanism is proposed to explain the occurrence of increasing autocorrelation but not variance when there is no approaching bifurcation. Additionally, a similar mechanism is shown to allow an increase in both indicators with no physically attainable bifurcation. This implies that relying on autocorrelation and variance as early warning signals can raise false alarms in the climate system, warning of "tipping points" that are not actually there.

  13. PSSP-RFE: Accurate Prediction of Protein Structural Class by Recursive Feature Extraction from PSI-BLAST Profile, Physical-Chemical Property and Functional Annotations

    PubMed Central

    Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

    2014-01-01

    Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets. PMID:24675610

  14. Predicting abundance and variability of ice nucleating particles in precipitation at the high-altitude observatory Jungfraujoch

    NASA Astrophysics Data System (ADS)

    Stopelli, Emiliano; Conen, Franz; Morris, Cindy E.; Herrmann, Erik; Henne, Stephan; Steinbacher, Martin; Alewell, Christine

    2016-07-01

    Nucleation of ice affects the properties of clouds and the formation of precipitation. Quantitative data on how ice nucleating particles (INPs) determine the distribution, occurrence and intensity of precipitation are still scarce. INPs active at -8 °C (INPs-8) were observed for 2 years in precipitation samples at the High-Altitude Research Station Jungfraujoch (Switzerland) at 3580 m a.s.l. Several environmental parameters were scanned for their capability to predict the observed abundance and variability of INPs-8. Those singularly presenting the best correlations with observed number of INPs-8 (residual fraction of water vapour, wind speed, air temperature, number of particles with diameter larger than 0.5 µm, season, and source region of particles) were implemented as potential predictor variables in statistical multiple linear regression models. These models were calibrated with 84 precipitation samples collected during the first year of observations; their predictive power was successively validated on the set of 15 precipitation samples collected during the second year. The model performing best in calibration and validation explains more than 75 % of the whole variability of INPs-8 in precipitation and indicates that a high abundance of INPs-8 is to be expected whenever high wind speed coincides with air masses having experienced little or no precipitation prior to sampling. Such conditions occur during frontal passages, often accompanied by precipitation. Therefore, the circumstances when INPs-8 could be sufficiently abundant to initiate the ice phase in clouds may frequently coincide with meteorological conditions favourable to the onset of precipitation events.

  15. Numerical simulations of iced airfoils and wings

    NASA Astrophysics Data System (ADS)

    Pan, Jianping

    A numerical study was conducted to understand the effects of simulated ridge and leading-edge ice shapes on the aerodynamic performance of airfoils and wings. In the first part of this study, a range of Reynolds numbers and Mach numbers, as well as ice-shape sizes and ice-shape locations were examined for various airfoils with the Reynolds-Averaged Navier-Stokes approach. Comparisons between simulation results and experimental force data showed favorable comparison up to stall conditions. At and past stall condition, the aerodynamic forces were typically not predicted accurately for large upper-surface ice shapes. A lift-break (pseudo-stall) condition was then defined based on the lift curve slope change. The lift-break angles compared reasonably with experimental stall angles, and indicated that the critical ice-shape location tended to be near the location of minimum pressure and the location of the most adverse pressure gradient. With the aim of improving the predictive ability of the stall behavior for iced airfoils, simulations using the Detached Eddy Simulation (DES) approach were conducted in the second part of this numerical investigation. Three-dimensional DES computations were performed for a series of angles of attack around stall for the iced NACA 23012 and NLF 0414 airfoils. The simulations for both iced airfoils provided the maximum lift coefficients and stall behaviors qualitatively consistent with experiments.

  16. Time-dependent neutrino emission from Mrk 421 during flares and predictions for IceCube

    NASA Astrophysics Data System (ADS)

    Petropoulou, Maria; Coenders, Stefan; Dimitrakoudis, Stavros

    2016-07-01

    Blazars, a subclass of active galactic nuclei, are prime candidate sources for the high energy neutrinos recently detected by IceCube. Being one of the brightest sources in the extragalactic X-ray and γ-ray sky as well as one of the nearest blazars to Earth, Mrk 421 is an excellent source for testing the scenario of the blazar-neutrino connection, especially during flares where time-dependent neutrino searches may have a higher detection probability. Here, we model the spectral energy distribution of Mrk 421 during a 13-day flare in 2010 with unprecedented multi-wavelength coverage, and calculate the respective neutrino flux. We find a correlation between the >1 PeV neutrino and photon fluxes, in all energy bands. Using typical IceCube through-going muon event samples with good angular resolution and high statistics, wederive the mean event rate above 100 TeV (∼0.57 evt/yr) and show that it is comparable to that expected from a four-month quiescent period in 2009. Due to the short duration of the flare, an accumulation of similar flares over several years would be necessary to produce a meaningful signal for IceCube. To better assess this, we apply the correlation between the neutrino and γ-ray fluxes to the 6.9 yr Fermi-LAT light curve of Mrk 421. We find that the mean event count above 1 PeV for the full IceCube detector livetime is 3.59 ± 0.60 (2.73 ± 0.38) νμ +νbarμ with (without) major flares included in our analysis. This estimate exceeds, within the uncertainties, the 95% (90%) threshold value for the detection of one or more muon (anti-)neutrinos. Meanwhile, the most conservative scenario, where no correlation of γ-rays and neutrinos is assumed, predicts 1.60 ± 0.16νμ +νbarμ events. We conclude that a non-detection of high-energy neutrinos by IceCube would probe the neutrino/γ-ray flux correlation during major flares or/and the hadronic contribution to the blazar emission.

  17. An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1.

    PubMed

    Kosakovsky Pond, Sergei L; Posada, David; Stawiski, Eric; Chappey, Colombe; Poon, Art F Y; Hughes, Gareth; Fearnhill, Esther; Gravenor, Mike B; Leigh Brown, Andrew J; Frost, Simon D W

    2009-11-01

    Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (approximately 5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate

  18. Conformations of 1,2-dimethoxypropane and 5-methoxy-1,3-dioxane: are ab initio quantum chemistry predictions accurate?

    NASA Astrophysics Data System (ADS)

    Smith, Grant D.; Jaffe, Richard L.; Yoon, Do. Y.

    1998-06-01

    High-level ab initio quantum chemistry calculations are shown to predict conformer populations of 1,2-dimethoxypropane and 5-methoxy-1,3-dioxane that are consistent with gas-phase NMR vicinal coupling constant measurements. The conformational energies of the cyclic ether 5-methoxy-1,3-dioxane are found to be consistent with those predicted by a rotational isomeric state (RIS) model based upon the acyclic analog 1,2-dimethoxypropane. The quantum chemistry and RIS calculations indicate the presence of strong attractive 1,5 C(H 3)⋯O electrostatic interactions in these molecules, similar to those found in 1,2-dimethoxyethane.

  19. A Maximal Graded Exercise Test to Accurately Predict VO2max in 18-65-Year-Old Adults

    ERIC Educational Resources Information Center

    George, James D.; Bradshaw, Danielle I.; Hyde, Annette; Vehrs, Pat R.; Hager, Ronald L.; Yanowitz, Frank G.

    2007-01-01

    The purpose of this study was to develop an age-generalized regression model to predict maximal oxygen uptake (VO sub 2 max) based on a maximal treadmill graded exercise test (GXT; George, 1996). Participants (N = 100), ages 18-65 years, reached a maximal level of exertion (mean plus or minus standard deviation [SD]; maximal heart rate [HR sub…

  20. Survival outcomes scores (SOFT, BAR, and Pedi-SOFT) are accurate in predicting post-liver transplant survival in adolescents.

    PubMed

    Conjeevaram Selvakumar, Praveen Kumar; Maksimak, Brian; Hanouneh, Ibrahim; Youssef, Dalia H; Lopez, Rocio; Alkhouri, Naim

    2016-09-01

    SOFT and BAR scores utilize recipient, donor, and graft factors to predict the 3-month survival after LT in adults (≥18 years). Recently, Pedi-SOFT score was developed to predict 3-month survival after LT in young children (≤12 years). These scoring systems have not been studied in adolescent patients (13-17 years). We evaluated the accuracy of these scoring systems in predicting the 3-month post-LT survival in adolescents through a retrospective analysis of data from UNOS of patients aged 13-17 years who received LT between 03/01/2002 and 12/31/2012. Recipients of combined organ transplants, donation after cardiac death, or living donor graft were excluded. A total of 711 adolescent LT recipients were included with a mean age of 15.2±1.4 years. A total of 100 patients died post-LT including 33 within 3 months. SOFT, BAR, and Pedi-SOFT scores were all found to be good predictors of 3-month post-transplant survival outcome with areas under the ROC curve of 0.81, 0.80, and 0.81, respectively. All three scores provided good accuracy for predicting 3-month survival post-LT in adolescents and may help clinical decision making to optimize survival rate and organ utilization. PMID:27478012

  1. Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset.

    PubMed

    Luo, Wei; Nguyen, Thin; Nichols, Melanie; Tran, Truyen; Rana, Santu; Gupta, Sunil; Phung, Dinh; Venkatesh, Svetha; Allender, Steve

    2015-01-01

    For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

  2. Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

    PubMed Central

    Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

    2014-01-01

    Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

  3. A predictive model for routing of supraglacial meltwater to the bed of glaciers: application to Leverett Glacier, western Greenland Ice Sheet

    NASA Astrophysics Data System (ADS)

    Clason, Caroline; Mair, Douglas; Nienow, Peter

    2010-05-01

    Recent studies have shown that Greenland outlet glacier velocities may be responding to increased meltwater generation (Shepherd et al, 2009; Zwally et al, 2002). Where sufficient supraglacial meltwater is routed into crevasses and moulins it could act to lubricate the bed, resulting in dynamic thinning and accelerated transfer of ice mass to glacier termini. The extent to which this mechanism contributes to mass loss is largely unknown, but may be increasingly important if current trends of warming are to continue, particularly in high northerly latitudes. This study introduces a modelling routine for prediction of moulin formation and quantification of meltwater delivery to the bed from digital elevation models, ice surface velocity data and meteorological input data. Supraglacial meltwater pathways are predicted from ice surface topography using a single flow direction hydrological flow routing algorithm. A temperature-index model driven by measured air temperature is used to produce values of distributed ice surface melt, integrated within stream accumulation to produce estimates of supraglacial stream discharge throughout the predicted network. Ice surface strain rates are calculated from satellite-derived surface velocities acquired using feature tracking. Strain rates are converted to stresses through the constitutive relation for glacier ice, after Nye (1957). Surface tensile stresses are calculated from the resultant principal stresses using the Von Mises criteria for failure of ductile materials, with areas of crevassing predicted where tensile stresses exceed a prescribed value of fracture toughness. Where supraglacial streams and areas of crevassing intersect, surficial moulin locations are predicted. A simple model for propagation of water-filled crevasses is applied to determine where moulins will penetrate through the full ice thickness, delivering meltwater to the bed. Derived from linear elastic fracture mechanics, the model calculates crevasse

  4. Length of sick leave – Why not ask the sick-listed? Sick-listed individuals predict their length of sick leave more accurately than professionals

    PubMed Central

    Fleten, Nils; Johnsen, Roar; Førde, Olav Helge

    2004-01-01

    Background The knowledge of factors accurately predicting the long lasting sick leaves is sparse, but information on medical condition is believed to be necessary to identify persons at risk. Based on the current practice, with identifying sick-listed individuals at risk of long-lasting sick leaves, the objectives of this study were to inquire the diagnostic accuracy of length of sick leaves predicted in the Norwegian National Insurance Offices, and to compare their predictions with the self-predictions of the sick-listed. Methods Based on medical certificates, two National Insurance medical consultants and two National Insurance officers predicted, at day 14, the length of sick leave in 993 consecutive cases of sick leave, resulting from musculoskeletal or mental disorders, in this 1-year follow-up study. Two months later they reassessed 322 cases based on extended medical certificates. Self-predictions were obtained in 152 sick-listed subjects when their sick leave passed 14 days. Diagnostic accuracy of the predictions was analysed by ROC area, sensitivity, specificity, likelihood ratio, and positive predictive value was included in the analyses of predictive validity. Results The sick-listed identified sick leave lasting 12 weeks or longer with an ROC area of 80.9% (95% CI 73.7–86.8), while the corresponding estimates for medical consultants and officers had ROC areas of 55.6% (95% CI 45.6–65.6%) and 56.0% (95% CI 46.6–65.4%), respectively. The predictions of sick-listed males were significantly better than those of female subjects, and older subjects predicted somewhat better than younger subjects. Neither formal medical competence, nor additional medical information, noticeably improved the diagnostic accuracy based on medical certificates. Conclusion This study demonstrates that the accuracy of a prognosis based on medical documentation in sickness absence forms, is lower than that of one based on direct communication with the sick-listed themselves

  5. Accurate and efficient prediction of fine-resolution hydrologic and carbon dynamic simulations from coarse-resolution models

    NASA Astrophysics Data System (ADS)

    Pau, George Shu Heng; Shen, Chaopeng; Riley, William J.; Liu, Yaning

    2016-02-01

    The topography, and the biotic and abiotic parameters are typically upscaled to make watershed-scale hydrologic-biogeochemical models computationally tractable. However, upscaling procedure can produce biases when nonlinear interactions between different processes are not fully captured at coarse resolutions. Here we applied the Proper Orthogonal Decomposition Mapping Method (PODMM) to downscale the field solutions from a coarse (7 km) resolution grid to a fine (220 m) resolution grid. PODMM trains a reduced-order model (ROM) with coarse-resolution and fine-resolution solutions, here obtained using PAWS+CLM, a quasi-3-D watershed processes model that has been validated for many temperate watersheds. Subsequent fine-resolution solutions were approximated based only on coarse-resolution solutions and the ROM. The approximation errors were efficiently quantified using an error estimator. By jointly estimating correlated variables and temporally varying the ROM parameters, we further reduced the approximation errors by up to 20%. We also improved the method's robustness by constructing multiple ROMs using different set of variables, and selecting the best approximation based on the error estimator. The ROMs produced accurate downscaling of soil moisture, latent heat flux, and net primary production with O(1000) reduction in computational cost. The subgrid distributions were also nearly indistinguishable from the ones obtained using the fine-resolution model. Compared to coarse-resolution solutions, biases in upscaled ROM solutions were reduced by up to 80%. This method has the potential to help address the long-standing spatial scaling problem in hydrology and enable long-time integration, parameter estimation, and stochastic uncertainty analysis while accurately representing the heterogeneities.

  6. Prognostic models and risk scores: can we accurately predict postoperative nausea and vomiting in children after craniotomy?

    PubMed

    Neufeld, Susan M; Newburn-Cook, Christine V; Drummond, Jane E

    2008-10-01

    Postoperative nausea and vomiting (PONV) is a problem for many children after craniotomy. Prognostic models and risk scores help identify who is at risk for an adverse event such as PONV to help guide clinical care. The purpose of this article is to assess whether an existing prognostic model or risk score can predict PONV in children after craniotomy. The concepts of transportability, calibration, and discrimination are presented to identify what is required to have a valid tool for clinical use. Although previous work may inform clinical practice and guide future research, existing prognostic models and risk scores do not appear to be options for predicting PONV in children undergoing craniotomy. However, until risk factors are further delineated, followed by the development and validation of prognostic models and risk scores that include children after craniotomy, clinical judgment in the context of current research may serve as a guide for clinical care in this population. PMID:18939320

  7. Predicting movements of female polar bears between summer sea ice foraging habitats and terrestrial denning habitats of Alaska in the 21st century: Proposed methodology and pilot assessment

    USGS Publications Warehouse

    Bergen, Scott; Durner, George M.; Douglas, David C.; Amstrup, Steven C.

    2007-01-01

    Polar bears (Ursus maritimus) require the relative warmth and stability afforded by snow dens for successful reproduction. Pregnant bears must travel from foraging habitats on the sea ice to land in autumn to establish winter dens. Data of sea ice extent and composition from satellite-acquired passive microwave (PMW) imagery show a reduction in summer sea ice extent throughout the Arctic from 1979-2006. Additionally, General Circulation Models (GCM) predict that Arctic sea ice extent will continue to diminish throughout the 21st century. Greater energetic demands will be placed on pregnant polar bears in the future if they travel greater distances from summer forage habitats to traditional denning habitats on land. We developed an approach for estimating how much these distances may change by modeling autumn movement paths of polar bears using the observational PMW record of sea ice distribution and sea ice projections of 5 GCMs during the 21st century. Over the 1979-2006 PMW record, polar bears returning to Alaska to den have experienced an annual increase in travel of > 6 km/year—an increase of >168 km over the 28 year period. Based on GCM sea ice projections during 2001-2060, the average increase in the distance required to reach traditional Alaskan denning regions was estimated to increase > 16 km/year. Distances traveled, and therefore, energetic demands, will likely vary among the different circumpolar sub-populations of polar bears.

  8. How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements.

    PubMed

    Grassi, Lorenzo; Väänänen, Sami P; Ristinmaa, Matti; Jurvelin, Jukka S; Isaksson, Hanna

    2016-03-21

    Subject-specific finite element models have been proposed as a tool to improve fracture risk assessment in individuals. A thorough laboratory validation against experimental data is required before introducing such models in clinical practice. Results from digital image correlation can provide full-field strain distribution over the specimen surface during in vitro test, instead of at a few pre-defined locations as with strain gauges. The aim of this study was to validate finite element models of human femora against experimental data from three cadaver femora, both in terms of femoral strength and of the full-field strain distribution collected with digital image correlation. The results showed a high accuracy between predicted and measured principal strains (R(2)=0.93, RMSE=10%, 1600 validated data points per specimen). Femoral strength was predicted using a rate dependent material model with specific strain limit values for yield and failure. This provided an accurate prediction (<2% error) for two out of three specimens. In the third specimen, an accidental change in the boundary conditions occurred during the experiment, which compromised the femoral strength validation. The achieved strain accuracy was comparable to that obtained in state-of-the-art studies which validated their prediction accuracy against 10-16 strain gauge measurements. Fracture force was accurately predicted, with the predicted failure location being very close to the experimental fracture rim. Despite the low sample size and the single loading condition tested, the present combined numerical-experimental method showed that finite element models can predict femoral strength by providing a thorough description of the local bone mechanical response. PMID:26944687

  9. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing.

    PubMed

    Wang, Ting; He, Quanze; Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing.

  10. Coronary Computed Tomographic Angiography Does Not Accurately Predict the Need of Coronary Revascularization in Patients with Stable Angina

    PubMed Central

    Hong, Sung-Jin; Her, Ae-Young; Suh, Yongsung; Won, Hoyoun; Cho, Deok-Kyu; Cho, Yun-Hyeong; Yoon, Young-Won; Lee, Kyounghoon; Kang, Woong Chol; Kim, Yong Hoon; Kim, Sang-Wook; Shin, Dong-Ho; Kim, Jung-Sun; Kim, Byeong-Keuk; Ko, Young-Guk; Choi, Byoung-Wook; Choi, Donghoon; Jang, Yangsoo

    2016-01-01

    Purpose To evaluate the ability of coronary computed tomographic angiography (CCTA) to predict the need of coronary revascularization in symptomatic patients with stable angina who were referred to a cardiac catheterization laboratory for coronary revascularization. Materials and Methods Pre-angiography CCTA findings were analyzed in 1846 consecutive symptomatic patients with stable angina, who were referred to a cardiac catheterization laboratory at six hospitals and were potential candidates for coronary revascularization between July 2011 and December 2013. The number of patients requiring revascularization was determined based on the severity of coronary stenosis as assessed by CCTA. This was compared to the actual number of revascularization procedures performed in the cardiac catheterization laboratory. Results Based on CCTA findings, coronary revascularization was indicated in 877 (48%) and not indicated in 969 (52%) patients. Of the 877 patients indicated for revascularization by CCTA, only 600 (68%) underwent the procedure, whereas 285 (29%) of the 969 patients not indicated for revascularization, as assessed by CCTA, underwent the procedure. When the coronary arteries were divided into 15 segments using the American Heart Association coronary tree model, the sensitivity, specificity, positive predictive value, and negative predictive value of CCTA for therapeutic decision making on a per-segment analysis were 42%, 96%, 40%, and 96%, respectively. Conclusion CCTA-based assessment of coronary stenosis severity does not sufficiently differentiate between coronary segments requiring revascularization versus those not requiring revascularization. Conventional coronary angiography should be considered to determine the need of revascularization in symptomatic patients with stable angina. PMID:27401637

  11. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing.

    PubMed

    Wang, Ting; He, Quanze; Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing. PMID:27441628

  12. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing

    PubMed Central

    Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing. PMID:27441628

  13. A highly accurate protein structural class prediction approach using auto cross covariance transformation and recursive feature elimination.

    PubMed

    Li, Xiaowei; Liu, Taigang; Tao, Peiying; Wang, Chunhua; Chen, Lanming

    2015-12-01

    Structural class characterizes the overall folding type of a protein or its domain. Many methods have been proposed to improve the prediction accuracy of protein structural class in recent years, but it is still a challenge for the low-similarity sequences. In this study, we introduce a feature extraction technique based on auto cross covariance (ACC) transformation of position-specific score matrix (PSSM) to represent a protein sequence. Then support vector machine-recursive feature elimination (SVM-RFE) is adopted to select top K features according to their importance and these features are input to a support vector machine (SVM) to conduct the prediction. Performance evaluation of the proposed method is performed using the jackknife test on three low-similarity datasets, i.e., D640, 1189 and 25PDB. By means of this method, the overall accuracies of 97.2%, 96.2%, and 93.3% are achieved on these three datasets, which are higher than those of most existing methods. This suggests that the proposed method could serve as a very cost-effective tool for predicting protein structural class especially for low-similarity datasets.

  14. Shallow ice approximation, second order shallow ice approximation, and full Stokes models: A discussion of their roles in palaeo-ice sheet modelling and development

    NASA Astrophysics Data System (ADS)

    Kirchner, N.; Ahlkrona, J.; Gowan, E. J.; Lötstedt, P.; Lea, J. M.; Noormets, R.; von Sydow, L.; Dowdeswell, J. A.; Benham, T.

    2016-09-01

    Full Stokes ice sheet models provide the most accurate description of ice sheet flow, and can therefore be used to reduce existing uncertainties in predicting the contribution of ice sheets to future sea level rise on centennial time-scales. The level of accuracy at which millennial time-scale palaeo-ice sheet simulations resolve ice sheet flow lags the standards set by Full Stokes models, especially, when Shallow Ice Approximation (SIA) models are used. Most models used in paleo-ice sheet modeling were developed at a time when computer power was very limited, and rely on several assumptions. At the time there was no means of verifying the assumptions by other than mathematical arguments. However, with the computer power and refined Full Stokes models available today, it is possible to test these assumptions numerically. In this paper, we review (Ahlkrona et al., 2013a) where such tests were performed and inaccuracies in commonly used arguments were found. We also summarize (Ahlkrona et al., 2013b) where the implications of the inaccurate assumptions are analyzed for two paleo-models - the SIA and the SOSIA. We review these works without resorting to mathematical detail, in order to make them accessible to a wider audience with a general interest in palaeo-ice sheet modelling. Specifically, we discuss two implications of relevance for palaeo-ice sheet modelling. First, classical SIA models are less accurate than assumed in their original derivation. Secondly, and contrary to previous recommendations, the SOSIA model is ruled out as a practicable tool for palaeo-ice sheet simulations. We conclude with an outlook concerning the new Ice Sheet Coupled Approximation Level (ISCAL) method presented in Ahlkrona et al. (2016), that has the potential to match the accuracy standards of full Stokes model on palaeo-timescales of tens of thousands of years, and to become an alternative to hybrid models currently used in palaeo-ice sheet modelling. The method is applied to an ice

  15. Shallow ice approximation, second order shallow ice approximation, and full Stokes models: A discussion of their roles in palaeo-ice sheet modelling and development

    NASA Astrophysics Data System (ADS)

    Kirchner, N.; Ahlkrona, J.; Gowan, E. J.; Lötstedt, P.; Lea, J. M.; Noormets, R.; von Sydow, L.; Dowdeswell, J. A.; Benham, T.

    2016-03-01

    Full Stokes ice sheet models provide the most accurate description of ice sheet flow, and can therefore be used to reduce existing uncertainties in predicting the contribution of ice sheets to future sea level rise on centennial time-scales. The level of accuracy at which millennial time-scale palaeo-ice sheet simulations resolve ice sheet flow lags the standards set by Full Stokes models, especially, when Shallow Ice Approximation (SIA) models are used. Most models used in paleo-ice sheet modeling were developed at a time when computer power was very limited, and rely on several assumptions. At the time there was no means of verifying the assumptions by other than mathematical arguments. However, with the computer power and refined Full Stokes models available today, it is possible to test these assumptions numerically. In this paper, we review (Ahlkrona et al., 2013a) where such tests were performed and inaccuracies in commonly used arguments were found. We also summarize (Ahlkrona et al., 2013b) where the implications of the inaccurate assumptions are analyzed for two paleo-models - the SIA and the SOSIA. We review these works without resorting to mathematical detail, in order to make them accessible to a wider audience with a general interest in palaeo-ice sheet modelling. Specifically, we discuss two implications of relevance for palaeo-ice sheet modelling. First, classical SIA models are less accurate than assumed in their original derivation. Secondly, and contrary to previous recommendations, the SOSIA model is ruled out as a practicable tool for palaeo-ice sheet simulations. We conclude with an outlook concerning the new Ice Sheet Coupled Approximation Level (ISCAL) method presented in Ahlkrona et al. (2016), that has the potential to match the accuracy standards of full Stokes model on palaeo-timescales of tens of thousands of years, and to become an alternative to hybrid models currently used in palaeo-ice sheet modelling. The method is applied to an ice

  16. A hybrid Navier-Stokes/full-potential method for the prediction of iced wing aerodynamics

    NASA Technical Reports Server (NTRS)

    Mello, O. A. F.; Sankar, L. N.

    1994-01-01

    A hybrid method for computing compressible viscous flows is presented. This method divides the computational domain into two zones. In the outer zone, the unsteady full-potential equation (FPE) is solved. In the inner zone, the Navier-Stokes equations are solved. The two zones are tightly coupled so that steady and unsteady flows may be efficiently solved. The resulting CPU times are less than 50 percent of the required for a full-blown Navier-Stokes analysis. Sample applications of the method to an unswept iced wing at 4 deg and 8 deg angle of attack are presented. Surface pressures are in good agreement with the measurements obtained by Bragg et al. at the University of Illinois.

  17. aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events.

    PubMed

    Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B; Ben-Hur, Asa; Boucher, Christina

    2016-01-01

    Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The [Formula: see text] class contains tandem [Formula: see text]-type motif sequences, and the [Formula: see text] class contains alternating [Formula: see text], [Formula: see text] and [Formula: see text] type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a [Formula: see text]-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the [Formula: see text] class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for [Formula: see text]-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

  18. A 3D-CFD code for accurate prediction of fluid flows and fluid forces in seals

    NASA Technical Reports Server (NTRS)

    Athavale, M. M.; Przekwas, A. J.; Hendricks, R. C.

    1994-01-01

    Current and future turbomachinery requires advanced seal configurations to control leakage, inhibit mixing of incompatible fluids and to control the rotodynamic response. In recognition of a deficiency in the existing predictive methodology for seals, a seven year effort was established in 1990 by NASA's Office of Aeronautics Exploration and Technology, under the Earth-to-Orbit Propulsion program, to develop validated Computational Fluid Dynamics (CFD) concepts, codes and analyses for seals. The effort will provide NASA and the U.S. Aerospace Industry with advanced CFD scientific codes and industrial codes for analyzing and designing turbomachinery seals. An advanced 3D CFD cylindrical seal code has been developed, incorporating state-of-the-art computational methodology for flow analysis in straight, tapered and stepped seals. Relevant computational features of the code include: stationary/rotating coordinates, cylindrical and general Body Fitted Coordinates (BFC) systems, high order differencing schemes, colocated variable arrangement, advanced turbulence models, incompressible/compressible flows, and moving grids. This paper presents the current status of code development, code demonstration for predicting rotordynamic coefficients, numerical parametric study of entrance loss coefficients for generic annular seals, and plans for code extensions to labyrinth, damping, and other seal configurations.

  19. aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events

    PubMed Central

    Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B.; Ben-Hur, Asa; Boucher, Christina

    2016-01-01

    Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The P class contains tandem P-type motif sequences, and the PLS class contains alternating P, L and S type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a PLS-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the PLS class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for PLS-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

  20. IrisPlex: a sensitive DNA tool for accurate prediction of blue and brown eye colour in the absence of ancestry information.

    PubMed

    Walsh, Susan; Liu, Fan; Ballantyne, Kaye N; van Oven, Mannis; Lao, Oscar; Kayser, Manfred

    2011-06-01

    A new era of 'DNA intelligence' is arriving in forensic biology, due to the impending ability to predict externally visible characteristics (EVCs) from biological material such as those found at crime scenes. EVC prediction from forensic samples, or from body parts, is expected to help concentrate police investigations towards finding unknown individuals, at times when conventional DNA profiling fails to provide informative leads. Here we present a robust and sensitive tool, termed IrisPlex, for the accurate prediction of blue and brown eye colour from DNA in future forensic applications. We used the six currently most eye colour-informative single nucleotide polymorphisms (SNPs) that previously revealed prevalence-adjusted prediction accuracies of over 90% for blue and brown eye colour in 6168 Dutch Europeans. The single multiplex assay, based on SNaPshot chemistry and capillary electrophoresis, both widely used in forensic laboratories, displays high levels of genotyping sensitivity with complete profiles generated from as little as 31pg of DNA, approximately six human diploid cell equivalents. We also present a prediction model to correctly classify an individual's eye colour, via probability estimation solely based on DNA data, and illustrate the accuracy of the developed prediction test on 40 individuals from various geographic origins. Moreover, we obtained insights into the worldwide allele distribution of these six SNPs using the HGDP-CEPH samples of 51 populations. Eye colour prediction analyses from HGDP-CEPH samples provide evidence that the test and model presented here perform reliably without prior ancestry information, although future worldwide genotype and phenotype data shall confirm this notion. As our IrisPlex eye colour prediction test is capable of immediate implementation in forensic casework, it represents one of the first steps forward in the creation of a fully individualised EVC prediction system for future use in forensic DNA intelligence.

  1. Accurate ab initio prediction of propagation rate coefficients in free-radical polymerization: Acrylonitrile and vinyl chloride

    NASA Astrophysics Data System (ADS)

    Izgorodina, Ekaterina I.; Coote, Michelle L.

    2006-05-01

    A systematic methodology for calculating accurate propagation rate coefficients in free-radical polymerization was designed and tested for vinyl chloride and acrylonitrile polymerization. For small to medium-sized polymer systems, theoretical reaction barriers are calculated using G3(MP2)-RAD. For larger systems, G3(MP2)-RAD barriers can be approximated (to within 1 kJ mol -1) via an ONIOM-based approach in which the core is studied at G3(MP2)-RAD and the substituent effects are modeled with ROMP2/6-311+G(3df,2p). DFT methods (including BLYP, B3LYP, MPWB195, BB1K and MPWB1K) failed to reproduce the correct trends in the reaction barriers and enthalpies with molecular size, though KMLYP showed some promise as a low cost option for very large systems. Reaction rates are calculated via standard transition state theory in conjunction with the one-dimensional hindered rotor model. The harmonic oscillator approximation was shown to introduce an error of a factor of 2-3, and would be suitable for "order-of-magnitude" estimates. A systematic study of chain length effects indicated that rate coefficients had largely converged to their long chain limit at the dimer radical stage, and the inclusion of the primary substituent of the penultimate unit was sufficient for practical purposes. Solvent effects, as calculated using the COSMO model, were found to be relatively minor. The overall methodology reproduced the available experimental data for both of these monomers within a factor of 2.

  2. Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type III secretion systems

    SciTech Connect

    Samudrala, Ram; Heffron, Fred; McDermott, Jason E.

    2009-04-24

    The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates, effector proteins, are not. We have used a machine learning approach to identify new secreted effectors. The method integrates evolutionary measures, such as the pattern of homologs in a range of other organisms, and sequence-based features, such as G+C content, amino acid composition and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from Salmonella typhimurium and validated on a corresponding set of effectors from Pseudomonas syringae, after eliminating effectors with detectable sequence similarity. The method was able to identify all of the known effectors in P. syringae with a specificity of 84% and sensitivity of 82%. The reciprocal validation, training on P. syringae and validating on S. typhimurium, gave similar results with a specificity of 86% when the sensitivity level was 87%. These results show that type III effectors in disparate organisms share common features. We found that maximal performance is attained by including an N-terminal sequence of only 30 residues, which agrees with previous studies indicating that this region contains the secretion signal. We then used the method to define the most important residues in this putative secretion signal. Finally, we present novel predictions of secreted effectors in S. typhimurium, some of which have been experimentally validated, and apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis. This approach is a novel and effective way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal.

  3. Automatic Earthquake Shear Stress Measurement Method Developed for Accurate Time- Prediction Analysis of Forthcoming Major Earthquakes Along Shallow Active Faults

    NASA Astrophysics Data System (ADS)

    Serata, S.

    2006-12-01

    The Serata Stressmeter has been developed to measure and monitor earthquake shear stress build-up along shallow active faults. The development work made in the past 25 years has established the Stressmeter as an automatic stress measurement system to study timing of forthcoming major earthquakes in support of the current earthquake prediction studies based on statistical analysis of seismological observations. In early 1982, a series of major Man-made earthquakes (magnitude 4.5-5.0) suddenly occurred in an area over deep underground potash mine in Saskatchewan, Canada. By measuring underground stress condition of the mine, the direct cause of the earthquake was disclosed. The cause was successfully eliminated by controlling the stress condition of the mine. The Japanese government was interested in this development and the Stressmeter was introduced to the Japanese government research program for earthquake stress studies. In Japan the Stressmeter was first utilized for direct measurement of the intrinsic lateral tectonic stress gradient G. The measurement, conducted at the Mt. Fuji Underground Research Center of the Japanese government, disclosed the constant natural gradients of maximum and minimum lateral stresses in an excellent agreement with the theoretical value, i.e., G = 0.25. All the conventional methods of overcoring, hydrofracturing and deformation, which were introduced to compete with the Serata method, failed demonstrating the fundamental difficulties of the conventional methods. The intrinsic lateral stress gradient determined by the Stressmeter for the Japanese government was found to be the same with all the other measurements made by the Stressmeter in Japan. The stress measurement results obtained by the major international stress measurement work in the Hot Dry Rock Projects conducted in USA, England and Germany are found to be in good agreement with the Stressmeter results obtained in Japan. Based on this broad agreement, a solid geomechanical

  4. Cloud ice caused by atmospheric mineral dust - Part 1: Parameterization of ice nuclei concentration in the NMME-DREAM model

    NASA Astrophysics Data System (ADS)

    Nickovic, Slobodan; Cvetkovic, Bojan; Madonna, Fabio; Rosoldi, Marco; Pejanovic, Goran; Petkovic, Slavko; Nikolic, Jugoslav

    2016-09-01

    Dust aerosols are very efficient ice nuclei, important for heterogeneous cloud glaciation even in regions distant from desert sources. A new generation of ice nucleation parameterizations, including dust as an ice nucleation agent, opens the way towards a more accurate treatment of cold cloud formation in atmospheric models. Using such parameterizations, we have developed a regional dust-atmospheric modelling system capable of predicting, in real time, dust-induced ice nucleation. We executed the model with the added ice nucleation component over the Mediterranean region, exposed to moderate Saharan dust transport, over two periods lasting 15 and 9 days, respectively. The model results were compared against satellite and ground-based cloud-ice-related measurements, provided by SEVIRI (Spinning Enhanced Visible and InfraRed Imager) and the CNR-IMAA Atmospheric Observatory (CIAO) in Potenza, southern Italy. The predicted ice nuclei concentration showed a reasonable level of agreement when compared against the observed spatial and temporal patterns of cloud ice water. The developed methodology permits the use of ice nuclei as input into the cloud microphysics schemes of atmospheric models, assuming that this approach could improve the predictions of cloud formation and associated precipitation.

  5. Mapping Ice with Airborne Lasers

    NASA Video Gallery

    Determining whether polar ice quantities are growing or shrinking requires accurate and detailed measurements, year over year. To help make those measurements, IceBridge mission aircraft fire 3,000...

  6. Predicting College Students' First Year Success: Should Soft Skills Be Taken into Consideration to More Accurately Predict the Academic Achievement of College Freshmen?

    ERIC Educational Resources Information Center

    Powell, Erica Dion

    2013-01-01

    This study presents a survey developed to measure the skills of entering college freshmen in the areas of responsibility, motivation, study habits, literacy, and stress management, and explores the predictive power of this survey as a measure of academic performance during the first semester of college. The survey was completed by 334 incoming…

  7. Predicting Antimicrobial Resistance Prevalence and Incidence from Indicators of Antimicrobial Use: What Is the Most Accurate Indicator for Surveillance in Intensive Care Units?

    PubMed Central

    Fortin, Élise; Platt, Robert W.; Fontela, Patricia S.; Buckeridge, David L.; Quach, Caroline

    2015-01-01

    Objective The optimal way to measure antimicrobial use in hospital populations, as a complement to surveillance of resistance is still unclear. Using respiratory isolates and antimicrobial prescriptions of nine intensive care units (ICUs), this study aimed to identify the indicator of antimicrobial use that predicted prevalence and incidence rates of resistance with the best accuracy. Methods Retrospective cohort study including all patients admitted to three neonatal (NICU), two pediatric (PICU) and four adult ICUs between April 2006 and March 2010. Ten different resistance / antimicrobial use combinations were studied. After adjustment for ICU type, indicators of antimicrobial use were successively tested in regression models, to predict resistance prevalence and incidence rates, per 4-week time period, per ICU. Binomial regression and Poisson regression were used to model prevalence and incidence rates, respectively. Multiplicative and additive models were tested, as well as no time lag and a one 4-week-period time lag. For each model, the mean absolute error (MAE) in prediction of resistance was computed. The most accurate indicator was compared to other indicators using t-tests. Results Results for all indicators were equivalent, except for 1/20 scenarios studied. In this scenario, where prevalence of carbapenem-resistant Pseudomonas sp. was predicted with carbapenem use, recommended daily doses per 100 admissions were less accurate than courses per 100 patient-days (p = 0.0006). Conclusions A single best indicator to predict antimicrobial resistance might not exist. Feasibility considerations such as ease of computation or potential external comparisons could be decisive in the choice of an indicator for surveillance of healthcare antimicrobial use. PMID:26710322

  8. Theoretical predictions of source rates for exospheric CO 2 on icy satellites of the outer planets due to sublimation of deep subsurface CO 2 ice

    NASA Astrophysics Data System (ADS)

    Wood, Stephen E.

    2016-10-01

    The abundances of CO2 observed in the exospheres of Callisto and, more recently, Rhea and Dione are difficult to explain. The previously proposed sources for the CO2 either have production rates well below the expected rates of escape/destruction or should produce other species (e.g. CO) that are not observed.We consider a potential source that has not been previously investigated – CO2 vapor originating from crustal CO2 ice and driven upward by the endogenic heat flux – and have developed a model to make quantitative estimates of the corresponding global subsurface vapor flux.Our model is based on previous theoretical work by Clifford (1993) and Mellon et al. (1997) for equatorial ground ice on Mars, who showed that in times or places where subsurface pore ice is undergoing long-term sublimation and diffusive loss, the ice table (the shallowest depth where any pore ice exists) will not continue to recede indefinitely. Beyond a certain, predictable depth, the linear diffusive profile of vapor density between the ice table and the surface will become supersaturated with respect to the local temperature and recondense as pore ice. This is true for any planetary body with a non-negligible interior heat source (e.g. radiogenic, tidal, etc) and is due to the fact that, while the ice temperature increases ~linearly with depth, the corresponding equilibrium vapor density increases exponentially.Once this occurs, a steady-state profile of ice volume fraction, f_ice(z), develops, with net mass loss only occurring from the retreating pore-filling ice layer. The rate of vapor flux to the surface is then determined only by the vapor density and temperature gradient at the ice table depth. We use a 1-D thermal model coupled with an analytic physical model for regolith thermal conductivity (including its depth- and T-dependence), to calculate the zonally-integrated global CO2 vapor flux corresponding to the range of expected heat flow values. Our preliminary results show

  9. Microdosing of a Carbon-14 Labeled Protein in Healthy Volunteers Accurately Predicts Its Pharmacokinetics at Therapeutic Dosages.

    PubMed

    Vlaming, M L H; van Duijn, E; Dillingh, M R; Brands, R; Windhorst, A D; Hendrikse, N H; Bosgra, S; Burggraaf, J; de Koning, M C; Fidder, A; Mocking, J A J; Sandman, H; de Ligt, R A F; Fabriek, B O; Pasman, W J; Seinen, W; Alves, T; Carrondo, M; Peixoto, C; Peeters, P A M; Vaes, W H J

    2015-08-01

    Preclinical development of new biological entities (NBEs), such as human protein therapeutics, requires considerable expenditure of time and costs. Poor prediction of pharmacokinetics in humans further reduces net efficiency. In this study, we show for the first time that pharmacokinetic data of NBEs in humans can be successfully obtained early in the drug development process by the use of microdosing in a small group of healthy subjects combined with ultrasensitive accelerator mass spectrometry (AMS). After only minimal preclinical testing, we performed a first-in-human phase 0/phase 1 trial with a human recombinant therapeutic protein (RESCuing Alkaline Phosphatase, human recombinant placental alkaline phosphatase [hRESCAP]) to assess its safety and kinetics. Pharmacokinetic analysis showed dose linearity from microdose (53 μg) [(14) C]-hRESCAP to therapeutic doses (up to 5.3 mg) of the protein in healthy volunteers. This study demonstrates the value of a microdosing approach in a very small cohort for accelerating the clinical development of NBEs. PMID:25869840

  10. A new accurate ground-state potential energy surface of ethylene and predictions for rotational and vibrational energy levels

    NASA Astrophysics Data System (ADS)

    Delahaye, Thibault; Nikitin, Andrei; Rey, Michaël; Szalay, Péter G.; Tyuterev, Vladimir G.

    2014-09-01

    In this paper we report a new ground state potential energy surface for ethylene (ethene) C2H4 obtained from extended ab initio calculations. The coupled-cluster approach with the perturbative inclusion of the connected triple excitations CCSD(T) and correlation consistent polarized valence basis set cc-pVQZ was employed for computations of electronic ground state energies. The fit of the surface included 82 542 nuclear configurations using sixth order expansion in curvilinear symmetry-adapted coordinates involving 2236 parameters. A good convergence for variationally computed vibrational levels of the C2H4 molecule was obtained with a RMS(Obs.-Calc.) deviation of 2.7 cm-1 for fundamental bands centers and 5.9 cm-1 for vibrational bands up to 7800 cm-1. Large scale vibrational and rotational calculations for 12C2H4, 13C2H4, and 12C2D4 isotopologues were performed using this new surface. Energy levels for J = 20 up to 6000 cm-1 are in a good agreement with observations. This represents a considerable improvement with respect to available global predictions of vibrational levels of 13C2H4 and 12C2D4 and rovibrational levels of 12C2H4.

  11. Accurate Predictions of Mean Geomagnetic Dipole Excursion and Reversal Frequencies, Mean Paleomagnetic Field Intensity, and the Radius of Earth's Core Using McLeod's Rule

    NASA Technical Reports Server (NTRS)

    Voorhies, Coerte V.; Conrad, Joy

    1996-01-01

    The geomagnetic spatial power spectrum R(sub n)(r) is the mean square magnetic induction represented by degree n spherical harmonic coefficients of the internal scalar potential averaged over the geocentric sphere of radius r. McLeod's Rule for the magnetic field generated by Earth's core geodynamo says that the expected core surface power spectrum (R(sub nc)(c)) is inversely proportional to (2n + 1) for 1 less than n less than or equal to N(sub E). McLeod's Rule is verified by locating Earth's core with main field models of Magsat data; the estimated core radius of 3485 kn is close to the seismologic value for c of 3480 km. McLeod's Rule and similar forms are then calibrated with the model values of R(sub n) for 3 less than or = n less than or = 12. Extrapolation to the degree 1 dipole predicts the expectation value of Earth's dipole moment to be about 5.89 x 10(exp 22) Am(exp 2)rms (74.5% of the 1980 value) and the expected geomagnetic intensity to be about 35.6 (mu)T rms at Earth's surface. Archeo- and paleomagnetic field intensity data show these and related predictions to be reasonably accurate. The probability distribution chi(exp 2) with 2n+1 degrees of freedom is assigned to (2n + 1)R(sub nc)/(R(sub nc). Extending this to the dipole implies that an exceptionally weak absolute dipole moment (less than or = 20% of the 1980 value) will exist during 2.5% of geologic time. The mean duration for such major geomagnetic dipole power excursions, one quarter of which feature durable axial dipole reversal, is estimated from the modern dipole power time-scale and the statistical model of excursions. The resulting mean excursion duration of 2767 years forces us to predict an average of 9.04 excursions per million years, 2.26 axial dipole reversals per million years, and a mean reversal duration of 5533 years. Paleomagnetic data show these predictions to be quite accurate. McLeod's Rule led to accurate predictions of Earth's core radius, mean paleomagnetic field

  12. Integrating metabolic performance, thermal tolerance, and plasticity enables for more accurate predictions on species vulnerability to acute and chronic effects of global warming.

    PubMed

    Magozzi, Sarah; Calosi, Piero

    2015-01-01

    Predicting species vulnerability to global warming requires a comprehensive, mechanistic understanding of sublethal and lethal thermal tolerances. To date, however, most studies investigating species physiological responses to increasing temperature have focused on the underlying physiological traits of either acute or chronic tolerance in isolation. Here we propose an integrative, synthetic approach including the investigation of multiple physiological traits (metabolic performance and thermal tolerance), and their plasticity, to provide more accurate and balanced predictions on species and assemblage vulnerability to both acute and chronic effects of global warming. We applied this approach to more accurately elucidate relative species vulnerability to warming within an assemblage of six caridean prawns occurring in the same geographic, hence macroclimatic, region, but living in different thermal habitats. Prawns were exposed to four incubation temperatures (10, 15, 20 and 25 °C) for 7 days, their metabolic rates and upper thermal limits were measured, and plasticity was calculated according to the concept of Reaction Norms, as well as Q10 for metabolism. Compared to species occupying narrower/more stable thermal niches, species inhabiting broader/more variable thermal environments (including the invasive Palaemon macrodactylus) are likely to be less vulnerable to extreme acute thermal events as a result of their higher upper thermal limits. Nevertheless, they may be at greater risk from chronic exposure to warming due to the greater metabolic costs they incur. Indeed, a trade-off between acute and chronic tolerance was apparent in the assemblage investigated. However, the invasive species P. macrodactylus represents an exception to this pattern, showing elevated thermal limits and plasticity of these limits, as well as a high metabolic control. In general, integrating multiple proxies for species physiological acute and chronic responses to increasing

  13. Creating collaboration opportunities for marine research across the Arctic: The SEARCH-ACCESS partnership and an emerging sea ice prediction research network

    NASA Astrophysics Data System (ADS)

    Eicken, H.; Bitz, C. M.; Gascard, J.; Kaminski, T.; Karcher, M. J.; Kauker, F.; Overland, J. E.; Stroeve, J. C.; Wiggins, H. V.

    2013-12-01

    Rapid Arctic environmental and socio-economic change presents major challenges and opportunities to Arctic residents, government agencies and the private sector. The Arctic Ocean and its ice cover, in particular, are in the midst of transformative change, ranging from declines in sea-ice thickness and summer ice extent to threats to coastal communities and increases in maritime traffic and offshore resource development. The US interagency Study of Environmental Arctic Change (SEARCH) and the European Arctic Climate Change, Economy and Society (ACCESS) project are addressing both scientific research needs and stakeholder information priorities to improve understanding and responses to Arctic change. Capacity building, coordination and integration of activities at the international level and across sectors and stakeholder groups are major challenges that have to be met. ACCESS and SEARCH build on long-standing collaborations with a focus on environmental change in the Arctic ocean-ice-atmosphere system and the most pressing research needs to inform marine policy, resource management and threats to Arctic coastal communities. To illustrate the approach, key results and major conclusions from this international coordination and collaboration effort, we focus on a nascent sea-ice prediction research network. This activity builds on the Arctic Sea Ice Outlook that was initiated by SEARCH and the European DAMOCLES project (a precursor to ACCESS) and has now grown into an international community of practice that synthesizes, evaluates and discusses sea-ice predictions on seasonal to interannual scales. Key goals of the effort which is now entering into a new phase include the comparative evaluation of different prediction approaches, including the combination of different techniques, the compilation of reference datasets and model output, guidance on the design and implementation of observing system efforts to improve predictions and information transfer into private

  14. Ice phases under ambient and high pressure: Insights from density functional theory

    NASA Astrophysics Data System (ADS)

    Fang, Yuan; Xiao, Bing; Tao, Jianmin; Sun, Jianwei; Perdew, John P.

    2013-06-01

    Water is common and plays a crucial role in biological, chemical, and physical processes, but its crystalline or ice state has a complicated structure. In this work, we study the lattice mismatch challenge for ice nucleation on silver iodide, the sublimation energy for different ice phases, and the structural phase-transition pressures of ice, with various density functionals. Our calculations show that the recently developed meta-generalized gradient approximation made simple (MGGA_MS) yields a lattice mismatch (3%) of hexagonal ice (ice Ih) with β-AgI in good agreement with experiment (2%), significantly better than the Perdew-Burke-Ernzerhof (PBE) GGA mismatch (6%). MGGA_MS is a computationally efficient semilocal functional that incorporates intermediate-range van der Waals (vdW) interaction, which, overall, performs well for ice and may be expected to improve upon PBE for liquid water. While MGGA_MS predicts the most realistic volumes and volume changes in the phase transitions of ice Ih to trigonal ice (ice II) and tetragonal ice (ice VIII), a more accurate description of some other properties of the higher-pressure phases (ice II and ice VIII) is provided by some functionals that include long-range vdW corrections (e.g., revised Tao-Perdew-Staroverov-Scuseria+vdW for sublimation energy and optB88-vdW for transition pressure).

  15. Infectious titres of sheep scrapie and bovine spongiform encephalopathy agents cannot be accurately predicted from quantitative laboratory test results.

    PubMed

    González, Lorenzo; Thorne, Leigh; Jeffrey, Martin; Martin, Stuart; Spiropoulos, John; Beck, Katy E; Lockey, Richard W; Vickery, Christopher M; Holder, Thomas; Terry, Linda

    2012-11-01

    It is widely accepted that abnormal forms of the prion protein (PrP) are the best surrogate marker for the infectious agent of prion diseases and, in practice, the detection of such disease-associated (PrP(d)) and/or protease-resistant (PrP(res)) forms of PrP is the cornerstone of diagnosis and surveillance of the transmissible spongiform encephalopathies (TSEs). Nevertheless, some studies question the consistent association between infectivity and abnormal PrP detection. To address this discrepancy, 11 brain samples of sheep affected with natural scrapie or experimental bovine spongiform encephalopathy were selected on the basis of the magnitude and predominant types of PrP(d) accumulation, as shown by immunohistochemical (IHC) examination; contra-lateral hemi-brain samples were inoculated at three different dilutions into transgenic mice overexpressing ovine PrP and were also subjected to quantitative analysis by three biochemical tests (BCTs). Six samples gave 'low' infectious titres (10⁶·⁵ to 10⁶·⁷ LD₅₀ g⁻¹) and five gave 'high titres' (10⁸·¹ to ≥ 10⁸·⁷ LD₅₀ g⁻¹) and, with the exception of the Western blot analysis, those two groups tended to correspond with samples with lower PrP(d)/PrP(res) results by IHC/BCTs. However, no statistical association could be confirmed due to high individual sample variability. It is concluded that although detection of abnormal forms of PrP by laboratory methods remains useful to confirm TSE infection, infectivity titres cannot be predicted from quantitative test results, at least for the TSE sources and host PRNP genotypes used in this study. Furthermore, the near inverse correlation between infectious titres and Western blot results (high protease pre-treatment) argues for a dissociation between infectivity and PrP(res).

  16. A new accurate ground-state potential energy surface of ethylene and predictions for rotational and vibrational energy levels

    SciTech Connect

    Delahaye, Thibault Rey, Michaël Tyuterev, Vladimir G.; Nikitin, Andrei; Szalay, Péter G.

    2014-09-14

    In this paper we report a new ground state potential energy surface for ethylene (ethene) C{sub 2}H{sub 4} obtained from extended ab initio calculations. The coupled-cluster approach with the perturbative inclusion of the connected triple excitations CCSD(T) and correlation consistent polarized valence basis set cc-pVQZ was employed for computations of electronic ground state energies. The fit of the surface included 82 542 nuclear configurations using sixth order expansion in curvilinear symmetry-adapted coordinates involving 2236 parameters. A good convergence for variationally computed vibrational levels of the C{sub 2}H{sub 4} molecule was obtained with a RMS(Obs.–Calc.) deviation of 2.7 cm{sup −1} for fundamental bands centers and 5.9 cm{sup −1} for vibrational bands up to 7800 cm{sup −1}. Large scale vibrational and rotational calculations for {sup 12}C{sub 2}H{sub 4}, {sup 13}C{sub 2}H{sub 4}, and {sup 12}C{sub 2}D{sub 4} isotopologues were performed using this new surface. Energy levels for J = 20 up to 6000 cm{sup −1} are in a good agreement with observations. This represents a considerable improvement with respect to available global predictions of vibrational levels of {sup 13}C{sub 2}H{sub 4} and {sup 12}C{sub 2}D{sub 4} and rovibrational levels of {sup 12}C{sub 2}H{sub 4}.

  17. Predictability of the Barents Sea ice in early winter: Remote effects of oceanic and atmospheric thermal conditions from the North Atlantic

    NASA Astrophysics Data System (ADS)

    Nakanowatari, Takuya; Sato, Kazutoshi; Inoue, Jun

    2015-04-01

    Predictability of sea ice concentrations (SICs) in the Barents Sea in early winter (November-December) is studied using canonical correlation analysis with atmospheric and ocean anomalies from the NCEP Climate Forecast System Reanalysis (NCEP-CFSR) data. We find that the highest prediction skill for a single-predictor model is obtained from the 13-month lead subsurface temperature at 200-m depth (T200) and the in-phase meridional surface wind (Vsfc). T200 skillfully predicts SIC variability in 35% of the Barents Sea, mainly in the eastern side. The T200 for negative sea-ice anomalies exhibits warm anomalies in the subsurface ocean temperature downstream of the Norwegian Atlantic Slope Current (NwASC) on a decadal timescale. The diagnostic analysis of NCEP-CFSR data suggests that the subsurface temperature anomaly stored below the thermocline during summer re-emerges in late autumn by atmospheric cooling and affects the sea-ice. The subsurface temperature anomaly of the NwASC is advected from the North Atlantic subpolar gyre over about 3 years. Vsfc skillfully predicts SIC variability in 32% of the Barents Sea, mainly in the western side. The Vsfc for the negative sea-ice anomalies exhibits southerly wind anomalies. Vsfc is related to the large-scale atmospheric circulation patterns from the subtropical North Atlantic to the Eurasian continent. Our study suggests that both atmospheric and oceanic remote effects have a potential impact on the forecasting accuracy of SIC.

  18. Noncontrast computed tomography can predict the outcome of shockwave lithotripsy via accurate stone measurement and abdominal fat distribution determination.

    PubMed

    Geng, Jiun-Hung; Tu, Hung-Pin; Shih, Paul Ming-Chen; Shen, Jung-Tsung; Jang, Mei-Yu; Wu, Wen-Jen; Li, Ching-Chia; Chou, Yii-Her; Juan, Yung-Shun

    2015-01-01

    Urolithiasis is a common disease of the urinary system. Extracorporeal shockwave lithotripsy (SWL) has become one of the standard treatments for renal and ureteral stones; however, the success rates range widely and failure of stone disintegration may cause additional outlay, alternative procedures, and even complications. We used the data available from noncontrast abdominal computed tomography (NCCT) to evaluate the impact of stone parameters and abdominal fat distribution on calculus-free rates following SWL. We retrospectively reviewed 328 patients who had urinary stones and had undergone SWL from August 2012 to August 2013. All of them received pre-SWL NCCT; 1 month after SWL, radiography was arranged to evaluate the condition of the fragments. These patients were classified into stone-free group and residual stone group. Unenhanced computed tomography variables, including stone attenuation, abdominal fat area, and skin-to-stone distance (SSD) were analyzed. In all, 197 (60%) were classified as stone-free and 132 (40%) as having residual stone. The mean ages were 49.35 ± 13.22 years and 55.32 ± 13.52 years, respectively. On univariate analysis, age, stone size, stone surface area, stone attenuation, SSD, total fat area (TFA), abdominal circumference, serum creatinine, and the severity of hydronephrosis revealed statistical significance between these two groups. From multivariate logistic regression analysis, the independent parameters impacting SWL outcomes were stone size, stone attenuation, TFA, and serum creatinine. [Adjusted odds ratios and (95% confidence intervals): 9.49 (3.72-24.20), 2.25 (1.22-4.14), 2.20 (1.10-4.40), and 2.89 (1.35-6.21) respectively, all p < 0.05]. In the present study, stone size, stone attenuation, TFA and serum creatinine were four independent predictors for stone-free rates after SWL. These findings suggest that pretreatment NCCT may predict the outcomes after SWL. Consequently, we can use these predictors for selecting

  19. The Antarctic Ice.

    ERIC Educational Resources Information Center

    Radok, Uwe

    1985-01-01

    The International Antarctic Glaciological Project has collected information on the East Antarctic ice sheet since 1969. Analysis of ice cores revealed climatic history, and radar soundings helped map bedrock of the continent. Computer models of the ice sheet and its changes over time will aid in predicting the future. (DH)

  20. Antarctic ice-sheet loss driven by basal melting of ice shelves.

    PubMed

    Pritchard, H D; Ligtenberg, S R M; Fricker, H A; Vaughan, D G; van den Broeke, M R; Padman, L

    2012-04-26

    Accurate prediction of global sea-level rise requires that we understand the cause of recent, widespread and intensifying glacier acceleration along Antarctic ice-sheet coastal margins. Atmospheric and oceanic forcing have the potential to reduce the thickness and extent of floating ice shelves, potentially limiting their ability to buttress the flow of grounded tributary glaciers. Indeed, recent ice-shelf collapse led to retreat and acceleration of several glaciers on the Antarctic Peninsula. But the extent and magnitude of ice-shelf thickness change, the underlying causes of such change, and its link to glacier flow rate are so poorly understood that its future impact on the ice sheets cannot yet be predicted. Here we use satellite laser altimetry and modelling of the surface firn layer to reveal the circum-Antarctic pattern of ice-shelf thinning through increased basal melt. We deduce that this increased melt is the primary control of Antarctic ice-sheet loss, through a reduction in buttressing of the adjacent ice sheet leading to accelerated glacier flow. The highest thinning rates occur where warm water at depth can access thick ice shelves via submarine troughs crossing the continental shelf. Wind forcing could explain the dominant patterns of both basal melting and the surface melting and collapse of Antarctic ice shelves, through ocean upwelling in the Amundsen and Bellingshausen seas, and atmospheric warming on the Antarctic Peninsula. This implies that climate forcing through changing winds influences Antarctic ice-sheet mass balance, and hence global sea level, on annual to decadal timescales. PMID:22538614

  1. Antarctic ice-sheet loss driven by basal melting of ice shelves.

    PubMed

    Pritchard, H D; Ligtenberg, S R M; Fricker, H A; Vaughan, D G; van den Broeke, M R; Padman, L

    2012-04-25

    Accurate prediction of global sea-level rise requires that we understand the cause of recent, widespread and intensifying glacier acceleration along Antarctic ice-sheet coastal margins. Atmospheric and oceanic forcing have the potential to reduce the thickness and extent of floating ice shelves, potentially limiting their ability to buttress the flow of grounded tributary glaciers. Indeed, recent ice-shelf collapse led to retreat and acceleration of several glaciers on the Antarctic Peninsula. But the extent and magnitude of ice-shelf thickness change, the underlying causes of such change, and its link to glacier flow rate are so poorly understood that its future impact on the ice sheets cannot yet be predicted. Here we use satellite laser altimetry and modelling of the surface firn layer to reveal the circum-Antarctic pattern of ice-shelf thinning through increased basal melt. We deduce that this increased melt is the primary control of Antarctic ice-sheet loss, through a reduction in buttressing of the adjacent ice sheet leading to accelerated glacier flow. The highest thinning rates occur where warm water at depth can access thick ice shelves via submarine troughs crossing the continental shelf. Wind forcing could explain the dominant patterns of both basal melting and the surface melting and collapse of Antarctic ice shelves, through ocean upwelling in the Amundsen and Bellingshausen seas, and atmospheric warming on the Antarctic Peninsula. This implies that climate forcing through changing winds influences Antarctic ice-sheet mass balance, and hence global sea level, on annual to decadal timescales.

  2. Stochastic ice stream dynamics

    NASA Astrophysics Data System (ADS)

    Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca

    2016-08-01

    Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.

  3. Stochastic ice stream dynamics.

    PubMed

    Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca

    2016-08-01

    Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution. PMID:27457960

  4. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints.

    PubMed

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-02-24

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.

  5. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints

    PubMed Central

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-01-01

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108

  6. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints.

    PubMed

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-01-01

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108

  7. Profile-QSAR: a novel meta-QSAR method that combines activities across the kinase family to accurately predict affinity, selectivity, and cellular activity.

    PubMed

    Martin, Eric; Mukherjee, Prasenjit; Sullivan, David; Jansen, Johanna

    2011-08-22

    Profile-QSAR is a novel 2D predictive model building method for kinases. This "meta-QSAR" method models the activity of each compound against a new kinase target as a linear combination of its predicted activities against a large panel of 92 previously studied kinases comprised from 115 assays. Profile-QSAR starts with a sparse incomplete kinase by compound (KxC) activity matrix, used to generate Bayesian QSAR models for the 92 "basis-set" kinases. These Bayesian QSARs generate a complete "synthetic" KxC activity matrix of predictions. These synthetic activities are used as "chemical descriptors" to train partial-least squares (PLS) models, from modest amounts of medium-throughput screening data, for predicting activity against new kinases. The Profile-QSAR predictions for the 92 kinases (115 assays) gave a median external R²(ext) = 0.59 on 25% held-out test sets. The method has proven accurate enough to predict pairwise kinase selectivities with a median correlation of R²(ext) = 0.61 for 958 kinase pairs with at least 600 common compounds. It has been further expanded by adding a "C(k)XC" cellular activity matrix to the KxC matrix to predict cellular activity for 42 kinase driven cellular assays with median R²(ext) = 0.58 for 24 target modulation assays and R²(ext) = 0.41 for 18 cell proliferation assays. The 2D Profile-QSAR, along with the 3D Surrogate AutoShim, are the foundations of an internally developed iterative medium-throughput screening (IMTS) methodology for virtual screening (VS) of compound archives as an alternative to experimental high-throughput screening (HTS). The method has been applied to 20 actual prospective kinase projects. Biological results have so far been obtained in eight of them. Q² values ranged from 0.3 to 0.7. Hit-rates at 10 uM for experimentally tested compounds varied from 25% to 80%, except in K5, which was a special case aimed specifically at finding "type II" binders, where none of the compounds were predicted to be

  8. Using radar to determine the mechanical and thermodynamic effect of tides on an ice shelf

    NASA Astrophysics Data System (ADS)

    Makinson, K.; Nicholls, K. W.; Østerhus, S.; Lok, L. B.; Brennan, P. V.

    2015-12-01

    Understanding how fast the ocean melts Antarctic ice shelves, which are known to restrain the flow of ice from the continental interior, is important to future ice sheet contributions to global sea level rise. Dependant on oceanographic processes delivering ocean heat from the Southern Ocean to the ice, changing rates of ice shelf basal melting ultimately contribute to variations in ice shelf thickness that can affect the discharge of grounded ice into the ocean. Being able to understanding and then predict the way basal melting responds to a changing ocean, requires ocean models that include fully interactive ice shelves and melting processes within their domain. Although such ocean models exist, their performance in the sub-ice shelf part of the domain is very difficult to optimise and validate. Highly accurate measurements of melt rates can be provided by phase-sensitive radars (e.g. pRES), although these have been limited to long term averages. Recent developments by BAS and UCL however, have provided a lightweight, low-power and relatively low cost radar for year-round autonomous operation (ApRES), delivering long time series of ice thickness changes. At tidal time scales however, ice shelves respond elastically to tilting, with significant fluctuations in vertical strain that will appear as apparent basal melting or even freezing. To determine the true basal melt rate at tidal time scales these radar observed vertical strain fluctuations must be removed. At Site 5 on Ronne Ice Shelf, the combined availability of radar-derived melt rates, independent measurements from oceanographic instruments beneath the ice shelf, and GPS strain observations provide a powerful test of both how the ocean interacts with the ice shelf base and the tidally induced melt rates. Using these data we will discuss our ability to accurately predict the temporal details of melt rates beneath ice shelves using ApRES radar.

  9. Anomalous growth of single ice crystals in solution

    NASA Technical Reports Server (NTRS)

    Gill, W. N.

    1979-01-01

    It is shown that major discrepancies exist between experiments and theory for ice crystal growth from solution. Accurate data, taken in a microgravity environment, approximate analytical models, and exact (probably numerical) models all are needed to advance our understanding of ice crystal growth phenomena. A new approximate semi-empirical theory is presented which predicts that a relatively sharp transition from natural convection control to diffusion control for ice growth in pure water occurs at a subcooling of about 10 C (a reduced temperature difference of about 0.125). No reliable data exist to test this prediction. The theory also predicts qualitatively the growth of ice in NaCl solution in which maxima in the growth rates are observed at various levels of subcooling.

  10. Tests of GCM pressure predictions for water ice stability using Mars Odyssey Neutron Spectrometer data

    NASA Astrophysics Data System (ADS)

    Wilson, J. T.; Eke, V. R.; Massey, R. J.; Elphic, R. C.; Feldman, W. C.; Maurice, S.; Teodoro, L. F. A.

    2015-10-01

    We have used the pixon image reconstruction t e c h n i q u e o n t h e M a r s O d y s s e y N e u t r o n Spectrometer epithermal neutron data to produce an improved global map of the hydrogen abundance on Mars. We will compare this to the predictions for surface hydration from the martian general circulation models, in order to provide both new constraints on, and tests of, the models.

  11. Development of Three-Dimensional Flow Code Package to Predict Performance and Stability of Aircraft with Leading Edge Ice Contamination

    NASA Technical Reports Server (NTRS)

    Strash, D. J.; Summa, J. M.

    1996-01-01

    In the work reported herein, a simplified, uncoupled, zonal procedure is utilized to assess the capability of numerically simulating icing effects on a Boeing 727-200 aircraft. The computational approach combines potential flow plus boundary layer simulations by VSAERO for the un-iced aircraft forces and moments with Navier-Stokes simulations by NPARC for the incremental forces and moments due to iced components. These are compared with wind tunnel force and moment data, supplied by the Boeing Company, examining longitudinal flight characteristics. Grid refinement improved the local flow features over previously reported work with no appreciable difference in the incremental ice effect. The computed lift curve slope with and without empennage ice matches the experimental value to within 1%, and the zero lift angle agrees to within 0.2 of a degree. The computed slope of the un-iced and iced aircraft longitudinal stability curve is within about 2% of the test data. This work demonstrates the feasibility of a zonal method for the icing analysis of complete aircraft or isolated components within the linear angle of attack range. In fact, this zonal technique has allowed for the viscous analysis of a complete aircraft with ice which is currently not otherwise considered tractable.

  12. Unprecedently Large-Scale Kinase Inhibitor Set Enabling the Accurate Prediction of Compound-Kinase Activities: A Way toward Selective Promiscuity by Design?

    PubMed

    Christmann-Franck, Serge; van Westen, Gerard J P; Papadatos, George; Beltran Escudie, Fanny; Roberts, Alexander; Overington, John P; Domine, Daniel

    2016-09-26

    Drug discovery programs frequently target members of the human kinome and try to identify small molecule protein kinase inhibitors, primarily for cancer treatment, additional indications being increasingly investigated. One of the challenges is controlling the inhibitors degree of selectivity, assessed by in vitro profiling against panels of protein kinases. We manually extracted, compiled, and standardized such profiles published in the literature: we collected 356 908 data points corresponding to 482 protein kinases, 2106 inhibitors, and 661 patents. We then analyzed this data set in terms of kinome coverage, results reproducibility, popularity, and degree of selectivity of both kinases and inhibitors. We used the data set to create robust proteochemometric models capable of predicting kinase activity (the ligand-target space was modeled with an externally validated RMSE of 0.41 ± 0.02 log units and R02 0.74 ± 0.03), in order to account for missing or unreliable measurements. The influence on the prediction quality of parameters such as number of measurements, Murcko scaffold frequency or inhibitor type was assessed. Interpretation of the models enabled to highlight inhibitors and kinases properties correlated with higher affinities, and an analysis in the context of kinases crystal structures was performed. Overall, the models quality allows the accurate prediction of kinase-inhibitor activities and their structural interpretation, thus paving the way for the rational design of compounds with a targeted selectivity profile.

  13. Unprecedently Large-Scale Kinase Inhibitor Set Enabling the Accurate Prediction of Compound–Kinase Activities: A Way toward Selective Promiscuity by Design?

    PubMed Central

    2016-01-01

    Drug discovery programs frequently target members of the human kinome and try to identify small molecule protein kinase inhibitors, primarily for cancer treatment, additional indications being increasingly investigated. One of the challenges is controlling the inhibitors degree of selectivity, assessed by in vitro profiling against panels of protein kinases. We manually extracted, compiled, and standardized such profiles published in the literature: we collected 356 908 data points corresponding to 482 protein kinases, 2106 inhibitors, and 661 patents. We then analyzed this data set in terms of kinome coverage, results reproducibility, popularity, and degree of selectivity of both kinases and inhibitors. We used the data set to create robust proteochemometric models capable of predicting kinase activity (the ligand–target space was modeled with an externally validated RMSE of 0.41 ± 0.02 log units and R02 0.74 ± 0.03), in order to account for missing or unreliable measurements. The influence on the prediction quality of parameters such as number of measurements, Murcko scaffold frequency or inhibitor type was assessed. Interpretation of the models enabled to highlight inhibitors and kinases properties correlated with higher affinities, and an analysis in the context of kinases crystal structures was performed. Overall, the models quality allows the accurate prediction of kinase-inhibitor activities and their structural interpretation, thus paving the way for the rational design of compounds with a targeted selectivity profile. PMID:27482722

  14. Unprecedently Large-Scale Kinase Inhibitor Set Enabling the Accurate Prediction of Compound-Kinase Activities: A Way toward Selective Promiscuity by Design?

    PubMed

    Christmann-Franck, Serge; van Westen, Gerard J P; Papadatos, George; Beltran Escudie, Fanny; Roberts, Alexander; Overington, John P; Domine, Daniel

    2016-09-26

    Drug discovery programs frequently target members of the human kinome and try to identify small molecule protein kinase inhibitors, primarily for cancer treatment, additional indications being increasingly investigated. One of the challenges is controlling the inhibitors degree of selectivity, assessed by in vitro profiling against panels of protein kinases. We manually extracted, compiled, and standardized such profiles published in the literature: we collected 356 908 data points corresponding to 482 protein kinases, 2106 inhibitors, and 661 patents. We then analyzed this data set in terms of kinome coverage, results reproducibility, popularity, and degree of selectivity of both kinases and inhibitors. We used the data set to create robust proteochemometric models capable of predicting kinase activity (the ligand-target space was modeled with an externally validated RMSE of 0.41 ± 0.02 log units and R02 0.74 ± 0.03), in order to account for missing or unreliable measurements. The influence on the prediction quality of parameters such as number of measurements, Murcko scaffold frequency or inhibitor type was assessed. Interpretation of the models enabled to highlight inhibitors and kinases properties correlated with higher affinities, and an analysis in the context of kinases crystal structures was performed. Overall, the models quality allows the accurate prediction of kinase-inhibitor activities and their structural interpretation, thus paving the way for the rational design of compounds with a targeted selectivity profile. PMID:27482722

  15. Clouds enhance Greenland ice sheet meltwater runoff

    NASA Astrophysics Data System (ADS)

    Van Tricht, Kristof; Lhermitte, Stef; Lenaerts, Jan T. M.; Gorodetskaya, Irina V.; L'Ecuyer, Tristan S.; Noël, Brice; van den Broeke, Michiel R.; Turner, David D.; van Lipzig, Nicole P. M.

    2016-04-01

    The Greenland ice sheet has become one of the main contributors to global sea level rise, predominantly through increased meltwater runoff. The main drivers of Greenland ice sheet runoff, however, remain poorly understood. Here we show that clouds enhance meltwater runoff by about one-third relative to clear skies, using a unique combination of active satellite observations, climate model data and snow model simulations. This impact results from a cloud radiative effect of 29.5 (±5.2) W m‑2. Contrary to conventional wisdom, however, the Greenland ice sheet responds to this energy through a new pathway by which clouds reduce meltwater refreezing as opposed to increasing surface melt directly, thereby accelerating bare-ice exposure and enhancing meltwater runoff. The high sensitivity of the Greenland ice sheet to both ice-only and liquid-bearing clouds highlights the need for accurate cloud representations in climate models, to better predict future contributions of the Greenland ice sheet to global sea level rise.

  16. Clouds enhance Greenland ice sheet meltwater runoff.

    PubMed

    Van Tricht, K; Lhermitte, S; Lenaerts, J T M; Gorodetskaya, I V; L'Ecuyer, T S; Noël, B; van den Broeke, M R; Turner, D D; van Lipzig, N P M

    2016-01-12

    The Greenland ice sheet has become one of the main contributors to global sea level rise, predominantly through increased meltwater runoff. The main drivers of Greenland ice sheet runoff, however, remain poorly understood. Here we show that clouds enhance meltwater runoff by about one-third relative to clear skies, using a unique combination of active satellite observations, climate model data and snow model simulations. This impact results from a cloud radiative effect of 29.5 (±5.2) W m(-2). Contrary to conventional wisdom, however, the Greenland ice sheet responds to this energy through a new pathway by which clouds reduce meltwater refreezing as opposed to increasing surface melt directly, thereby accelerating bare-ice exposure and enhancing meltwater runoff. The high sensitivity of the Greenland ice sheet to both ice-only and liquid-bearing clouds highlights the need for accurate cloud representations in climate models, to better predict future contributions of the Greenland ice sheet to global sea level rise.

  17. Clouds enhance Greenland ice sheet meltwater runoff

    NASA Astrophysics Data System (ADS)

    Van Tricht, Kristof; Lhermitte, Stef; Lenaerts, Jan T. M.; Gorodetskaya, Irina V.; L'Ecuyer, Tristan S.; Noël, Brice; van den Broeke, Michiel R.; Turner, David D.; van Lipzig, Nicole P. M.

    2016-04-01

    The Greenland ice sheet has become one of the main contributors to global sea level rise, predominantly through increased meltwater runoff. The main drivers of Greenland ice sheet runoff, however, remain poorly understood. Here we show that clouds enhance meltwater runoff by about one-third relative to clear skies, using a unique combination of active satellite observations, climate model data and snow model simulations. This impact results from a cloud radiative effect of 29.5 (±5.2) W m-2. Contrary to conventional wisdom, however, the Greenland ice sheet responds to this energy through a new pathway by which clouds reduce meltwater refreezing as opposed to increasing surface melt directly, thereby accelerating bare-ice exposure and enhancing meltwater runoff. The high sensitivity of the Greenland ice sheet to both ice-only and liquid-bearing clouds highlights the need for accurate cloud representations in climate models, to better predict future contributions of the Greenland ice sheet to global sea level rise.

  18. Clouds enhance Greenland ice sheet meltwater runoff

    NASA Astrophysics Data System (ADS)

    van Tricht, K.; Lhermitte, S.; Lenaerts, J. T. M.; Gorodetskaya, I. V.; L'Ecuyer, T. S.; Noël, B.; van den Broeke, M. R.; Turner, D. D.; van Lipzig, N. P. M.

    2016-01-01

    The Greenland ice sheet has become one of the main contributors to global sea level rise, predominantly through increased meltwater runoff. The main drivers of Greenland ice sheet runoff, however, remain poorly understood. Here we show that clouds enhance meltwater runoff by about one-third relative to clear skies, using a unique combination of active satellite observations, climate model data and snow model simulations. This impact results from a cloud radiative effect of 29.5 (+/-5.2) W m-2. Contrary to conventional wisdom, however, the Greenland ice sheet responds to this energy through a new pathway by which clouds reduce meltwater refreezing as opposed to increasing surface melt directly, thereby accelerating bare-ice exposure and enhancing meltwater runoff. The high sensitivity of the Greenland ice sheet to both ice-only and liquid-bearing clouds highlights the need for accurate cloud representations in climate models, to better predict future contributions of the Greenland ice sheet to global sea level rise.

  19. Clouds enhance Greenland ice sheet meltwater runoff

    PubMed Central

    Van Tricht, K.; Lhermitte, S.; Lenaerts, J. T. M.; Gorodetskaya, I. V.; L'Ecuyer, T. S.; Noël, B.; van den Broeke, M. R.; Turner, D. D.; van Lipzig, N. P. M.

    2016-01-01

    The Greenland ice sheet has become one of the main contributors to global sea level rise, predominantly through increased meltwater runoff. The main drivers of Greenland ice sheet runoff, however, remain poorly understood. Here we show that clouds enhance meltwater runoff by about one-third relative to clear skies, using a unique combination of active satellite observations, climate model data and snow model simulations. This impact results from a cloud radiative effect of 29.5 (±5.2) W m−2. Contrary to conventional wisdom, however, the Greenland ice sheet responds to this energy through a new pathway by which clouds reduce meltwater refreezing as opposed to increasing surface melt directly, thereby accelerating bare-ice exposure and enhancing meltwater runoff. The high sensitivity of the Greenland ice sheet to both ice-only and liquid-bearing clouds highlights the need for accurate cloud representations in climate models, to better predict future contributions of the Greenland ice sheet to global sea level rise. PMID:26756470

  20. SeaRISE: A Multidisciplinary Research Initiative to Predict Rapid Changes in Global Sea Level Caused by Collapse of Marine Ice Sheets

    NASA Technical Reports Server (NTRS)

    Bindschadler, Robert A. (Editor)

    1990-01-01

    The results of a workshop held to discuss the role of the polar ice sheets in global climate change are reported. The participants agreed that the most important aspect of the ice sheets' involvement in climate change is the potential of marine ice sheets to cause a rapid change in global sea level. To address this concern, a research initiative is called for that considers the full complexity of the coupled atmosphere-ocean-cryosphere-lithosphere system. This initiative, called SeaRISE (Sea-level Response to Ice Sheet Evolution) has the goal of predicting the contribution of marine ice sheets to rapid changes in global sea level in the next decade to few centuries. To attain this goal, a coordinated program of multidisciplinary investigations must be launched with the linked objectives of understanding the current state, internal dynamics, interactions, and history of this environmental system. The key questions needed to satisfy these objectives are presented and discussed along with a plan of action to make the SeaRISE project a reality.

  1. Spring Snow Depth on Arctic Sea Ice using the IceBridge Snow Depth Product (Invited)

    NASA Astrophysics Data System (ADS)

    Webster, M.; Rigor, I. G.; Nghiem, S. V.; Kurtz, N. T.; Farrell, S. L.

    2013-12-01

    Snow has dual roles in the growth and decay of Arctic sea ice. In winter, it insulates sea ice from colder air temperatures, slowing its growth. From spring into summer, the albedo of snow determines how much insolation is transmitted through the sea ice and into the underlying ocean, ultimately impacting the progression of the summer ice melt. Knowing the snow thickness and distribution are essential for understanding and modeling sea ice thermodynamics and the surface heat budget. Therefore, an accurate assessment of the snow cover is necessary for identifying its impacts in the changing Arctic. This study assesses springtime snow conditions on Arctic sea ice using airborne snow thickness measurements from Operation IceBridge (2009-2012). The 2012 data were validated with coordinated in situ measurements taken in March 2012 during the BRomine, Ozone, and Mercury EXperiment field campaign. We find a statistically significant correlation coefficient of 0.59 and RMS error of 5.8 cm. The comparison between the IceBridge snow thickness product and the 1937, 1954-1991 Soviet drifting ice station data suggests that the snow cover has thinned by 33% in the western Arctic and 44% in the Beaufort and Chukchi Seas. A rudimentary estimation shows that a thinner snow cover in the Beaufort and Chukchi Seas translates to a mid-December surface heat flux as high as 81 W/m2 compared to 32 W/m2. The relationship between the 2009-2012 thinner snow depth distribution and later sea ice freeze-up is statistically significant, with a correlation coefficient of 0.59. These results may help us better understand the surface energy budget in the changing Arctic, and may improve our ability to predict the future state of the sea ice cover.

  2. ION COMPOSITION ELUCIDATION (ICE)

    EPA Science Inventory



    Ion Composition Elucidation (ICE) utilizes selected ion recording with a double focusing mass spectrometer to simultaneously determine exact masses and relative isotopic abundances from mass peak profiles. These can be determined more accurately and at higher sensitivity ...

  3. PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions.

    PubMed

    Bendl, Jaroslav; Musil, Miloš; Štourač, Jan; Zendulka, Jaroslav; Damborský, Jiří; Brezovský, Jan

    2016-05-01

    An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools' predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To

  4. PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions

    PubMed Central

    Brezovský, Jan

    2016-01-01

    An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools’ predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations

  5. Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients

    PubMed Central

    Ferrari, Clarissa; Uher, Rudolf; Bocchio-Chiavetto, Luisella; Riva, Marco Andrea; Pariante, Carmine M.

    2016-01-01

    Background: Increased levels of inflammation have been associated with a poorer response to antidepressants in several clinical samples, but these findings have had been limited by low reproducibility of biomarker assays across laboratories, difficulty in predicting response probability on an individual basis, and unclear molecular mechanisms. Methods: Here we measured absolute mRNA values (a reliable quantitation of number of molecules) of Macrophage Migration Inhibitory Factor and interleukin-1β in a previously published sample from a randomized controlled trial comparing escitalopram vs nortriptyline (GENDEP) as well as in an independent, naturalistic replication sample. We then used linear discriminant analysis to calculate mRNA values cutoffs that best discriminated between responders and nonresponders after 12 weeks of antidepressants. As Macrophage Migration Inhibitory Factor and interleukin-1β might be involved in different pathways, we constructed a protein-protein interaction network by the Search Tool for the Retrieval of Interacting Genes/Proteins. Results: We identified cutoff values for the absolute mRNA measures that accurately predicted response probability on an individual basis, with positive predictive values and specificity for nonresponders of 100% in both samples (negative predictive value=82% to 85%, sensitivity=52% to 61%). Using network analysis, we identified different clusters of targets for these 2 cytokines, with Macrophage Migration Inhibitory Factor interacting predominantly with pathways involved in neurogenesis, neuroplasticity, and cell proliferation, and interleukin-1β interacting predominantly with pathways involved in the inflammasome complex, oxidative stress, and neurodegeneration. Conclusion: We believe that these data provide a clinically suitable approach to the personalization of antidepressant therapy: patients who have absolute mRNA values above the suggested cutoffs could be directed toward earlier access to more

  6. Dose Addition Models Based on Biologically Relevant Reductions in Fetal Testosterone Accurately Predict Postnatal Reproductive Tract Alterations by a Phthalate Mixture in Rats.

    PubMed

    Howdeshell, Kembra L; Rider, Cynthia V; Wilson, Vickie S; Furr, Johnathan R; Lambright, Christy R; Gray, L Earl

    2015-12-01

    Challenges in cumulative risk assessment of anti-androgenic phthalate mixtures include a lack of data on all the individual phthalates and difficulty determining the biological relevance of reduction in fetal testosterone (T) on postnatal development. The objectives of the current study were 2-fold: (1) to test whether a mixture model of dose addition based on the fetal T production data of individual phthalates would predict the effects of a 5 phthalate mixture on androgen-sensitive postnatal male reproductive tract development, and (2) to determine the biological relevance of the reductions in fetal T to induce abnormal postnatal reproductive tract development using data from the mixture study. We administered a dose range of the mixture (60, 40, 20, 10, and 5% of the top dose used in the previous fetal T production study consisting of 300 mg/kg per chemical of benzyl butyl (BBP), di(n)butyl (DBP), diethyl hexyl phthalate (DEHP), di-isobutyl phthalate (DiBP), and 100 mg dipentyl (DPP) phthalate/kg; the individual phthalates were present in equipotent doses based on their ability to reduce fetal T production) via gavage to Sprague Dawley rat dams on GD8-postnatal day 3. We compared observed mixture responses to predictions of dose addition based on the previously published potencies of the individual phthalates to reduce fetal T production relative to a reference chemical and published postnatal data for the reference chemical (called DAref). In addition, we predicted DA (called DAall) and response addition (RA) based on logistic regression analysis of all 5 individual phthalates when complete data were available. DA ref and DA all accurately predicted the observed mixture effect for 11 of 14 endpoints. Furthermore, reproductive tract malformations were seen in 17-100% of F1 males when fetal T production was reduced by about 25-72%, respectively. PMID:26350170

  7. Comparison of full field and anomaly initialisation for decadal climate prediction: towards an optimal consistency between the ocean and sea-ice anomaly initialisation state

    NASA Astrophysics Data System (ADS)

    Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco J.

    2016-10-01

    Decadal prediction exploits sources of predictability from both the internal variability through the initialisation of the climate model from observational estimates, and the external radiative forcings. When a model is initialised with the observed state at the initial time step (Full Field Initialisation—FFI), the forecast run drifts towards the biased model climate. Distinguishing between the climate signal to be predicted and the model drift is a challenging task, because the application of a-posteriori bias correction has the risk of removing part of the variability signal. The anomaly initialisation (AI) technique aims at addressing the drift issue by answering the following question: if the model is allowed to start close to its own attractor (i.e. its biased world), but the phase of the simulated variability is constrained toward the contemporaneous observed one at the initialisation time, does the prediction skill improve? The relative merits of the FFI and AI techniques applied respectively to the ocean component and the ocean and sea ice components simultaneously in the EC-Earth global coupled model are assessed. For both strategies the initialised hindcasts show better skill than historical simulations for the ocean heat content and AMOC along the first two forecast years, for sea ice and PDO along the first forecast year, while for AMO the improvements are statistically significant for the first two forecast years. The AI in the ocean and sea ice components significantly improves the skill of the Arctic sea surface temperature over the FFI.

  8. Effects of nonlinear rheology and anisotropy on the relationship between age and depth at ice divides

    NASA Astrophysics Data System (ADS)

    Martin, C.; Gudmundsson, G. H.

    2012-04-01

    Ice-cores need to be accurately dated to reveal, in detail, past environmental conditions. The ice-core chronology is always incomplete because of ice stratigraphy thinning and distortion due to flow, and timeline extraction is often reliant on simplified models to predict the age of ice. Through numerical modelling using a full Stokes solver and a non-linear anisotropic rheology, we investigate the effects of ice flow on the age versus depth relationship at ice divides. We compare our results with analytical approximations commonly employed in age-depth prediction. Our main findings are: Firstly, once the ice has developed a significant single maximum or vertical girdle fabric, the analytical approximations tend to underestimate the age of ice. Secondly, ice fabric enhance the effect of the bedrock topography on the ice flow. We show that the presence of single maximum fabric close to the bedrock affects strongly the ice stratigraphy and the age-depth relationship. We also study the coupling between anisotropic viscosity and internal heating. It does produce a warm spot and softer ice at the base of the divide when compared with surrounding areas. Finally we study the age-depth distribution in divides that show double-peaked Raymond bump in their radar stratigraphy. They provide ideal locations fore ice-core drilling as they have been stable for a long time when compared with their characteristic time (ice thickness divide by accumulation). Our model shows that the ice in these areas can be up to one order of magnitude older that ice at the same depth both at the flanks of the divide area or on similar divides that have not been stable for that long.

  9. Discovery of a general method of solving the Schrödinger and dirac equations that opens a way to accurately predictive quantum chemistry.

    PubMed

    Nakatsuji, Hiroshi

    2012-09-18

    Just as Newtonian law governs classical physics, the Schrödinger equation (SE) and the relativistic Dirac equation (DE) rule the world of chemistry. So, if we can solve these equations accurately, we can use computation to predict chemistry precisely. However, for approximately 80 years after the discovery of these equations, chemists believed that they could not solve SE and DE for atoms and molecules that included many electrons. This Account reviews ideas developed over the past decade to further the goal of predictive quantum chemistry. Between 2000 and 2005, I discovered a general method of solving the SE and DE accurately. As a first inspiration, I formulated the structure of the exact wave function of the SE in a compact mathematical form. The explicit inclusion of the exact wave function's structure within the variational space allows for the calculation of the exact wave function as a solution of the variational method. Although this process sounds almost impossible, it is indeed possible, and I have published several formulations and applied them to solve the full configuration interaction (CI) with a very small number of variables. However, when I examined analytical solutions for atoms and molecules, the Hamiltonian integrals in their secular equations diverged. This singularity problem occurred in all atoms and molecules because it originates from the singularity of the Coulomb potential in their Hamiltonians. To overcome this problem, I first introduced the inverse SE and then the scaled SE. The latter simpler idea led to immediate and surprisingly accurate solution for the SEs of the hydrogen atom, helium atom, and hydrogen molecule. The free complement (FC) method, also called the free iterative CI (free ICI) method, was efficient for solving the SEs. In the FC method, the basis functions that span the exact wave function are produced by the Hamiltonian of the system and the zeroth-order wave function. These basis functions are called complement

  10. Tuning of Strouhal number for high propulsive efficiency accurately predicts how wingbeat frequency and stroke amplitude relate and scale with size and flight speed in birds.

    PubMed Central

    Nudds, Robert L.; Taylor, Graham K.; Thomas, Adrian L. R.

    2004-01-01

    The wing kinematics of birds vary systematically with body size, but we still, after several decades of research, lack a clear mechanistic understanding of the aerodynamic selection pressures that shape them. Swimming and flying animals have recently been shown to cruise at Strouhal numbers (St) corresponding to a regime of vortex growth and shedding in which the propulsive efficiency of flapping foils peaks (St approximately fA/U, where f is wingbeat frequency, U is cruising speed and A approximately bsin(theta/2) is stroke amplitude, in which b is wingspan and theta is stroke angle). We show that St is a simple and accurate predictor of wingbeat frequency in birds. The Strouhal numbers of cruising birds have converged on the lower end of the range 0.2 < St < 0.4 associated with high propulsive efficiency. Stroke angle scales as theta approximately 67b-0.24, so wingbeat frequency can be predicted as f approximately St.U/bsin(33.5b-0.24), with St0.21 and St0.25 for direct and intermittent fliers, respectively. This simple aerodynamic model predicts wingbeat frequency better than any other relationship proposed to date, explaining 90% of the observed variance in a sample of 60 bird species. Avian wing kinematics therefore appear to have been tuned by natural selection for high aerodynamic efficiency: physical and physiological constraints upon wing kinematics must be reconsidered in this light. PMID:15451698

  11. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

    PubMed

    Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

    2016-09-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  12. In-situ aircraft observations of ice concentrations within clouds over the Antarctic Peninsula and Larsen Ice Shelf

    NASA Astrophysics Data System (ADS)

    Grosvenor, D. P.; Choularton, T. W.; Lachlan-Cope, T.; Gallagher, M. W.; Crosier, J.; Bower, K. N.; Ladkin, R. S.; Dorsey, J. R.

    2012-07-01

    In-situ aircraft observations of ice crystal concentrations in Antarctic clouds are presented for the first time. Orographic, layer and wave clouds around the Antarctic Peninsula and Larsen Ice shelf regions were penetrated by the British Antarctic Survey's Twin Otter Aircraft, which was equipped with modern cloud physics probes. The clouds studied were mostly in the free troposphere and hence ice crystals blown from the surface are unlikely to have been a major source for the ice phase. The temperature range covered by the experiments was 0 to -21°C. The clouds were found to contain supercooled liquid water in most regions and at heterogeneous ice formation temperatures ice crystal concentrations (60 s averages) were often less than 0.07 l-1, although values up to 0.22 l-1 were observed. Estimates of observed aerosol concentrations were used as input into the DeMott et al., 2010 ice nuclei (IN) parameterisation. The observed ice crystal number concentrations were generally in broad agreement with the IN predictions, although on the whole the predicted values were higher. Possible reasons for this are discussed and include the lack of IN observations in this region with which to characterise the parameterisation, and/or problems in relating ice concentration measurements to IN concentrations. Other IN parameterisations significantly overestimated the number of ice particles. Generally ice particle concentrations were much lower than found in clouds in middle latitudes for a given temperature. Higher ice crystal concentrations were sometimes observed at temperatures warmer than -9 °C, with values of several per litre reached. These were attributable to secondary ice particle production by the Hallett Mossop process. Even in this temperature range it was observed that there were regions with little or no ice that were dominated by supercooled liquid water. It is likely that in some cases this was due to a lack of seeding ice crystals to act as rimers to initiate

  13. In-situ aircraft observations of ice concentrations within clouds over the Antarctic Peninsula and Larsen Ice Shelf

    NASA Astrophysics Data System (ADS)

    Grosvenor, D. P.; Choularton, T. W.; Lachlan-Cope, T.; Gallagher, M. W.; Crosier, J.; Bower, K. N.; Ladkin, R. S.; Dorsey, J. R.

    2012-12-01

    In-situ aircraft observations of ice crystal concentrations in Antarctic clouds are presented for the first time. Orographic, layer and wave clouds around the Antarctic Peninsula and Larsen Ice shelf regions were penetrated by the British Antarctic Survey's Twin Otter aircraft, which was equipped with modern cloud physics probes. The clouds studied were mostly in the free troposphere and hence ice crystals blown from the surface are unlikely to have been a major source for the ice phase. The temperature range covered by the experiments was 0 to -21 °C. The clouds were found to contain supercooled liquid water in most regions and at heterogeneous ice formation temperatures ice crystal concentrations (60 s averages) were often less than 0.07 l-1, although values up to 0.22 l-1 were observed. Estimates of observed aerosol concentrations were used as input into the DeMott et al. (2010) ice nuclei (IN) parameterisation. The observed ice crystal number concentrations were generally in broad agreement with the IN predictions, although on the whole the predicted values were higher. Possible reasons for this are discussed and include the lack of IN observations in this region with which to characterise the parameterisation, and/or problems in relating ice concentration measurements to IN concentrations. Other IN parameterisations significantly overestimated the number of ice particles. Generally ice particle concentrations were much lower than found in clouds in middle latitudes for a given temperature. Higher ice crystal concentrations were sometimes observed at temperatures warmer than -9 °C, with values of several per litre reached. These were attributable to secondary ice particle production by the Hallett Mossop process. Even in this temperature range it was observed that there were regions with little or no ice that were dominated by supercooled liquid water. It is likely that in some cases this was due to a lack of seeding ice crystals to act as rimers to initiate

  14. The Model for End-stage Liver Disease accurately predicts 90-day liver transplant wait-list mortality in Atlantic Canada

    PubMed Central

    Renfrew, Paul Douglas; Quan, Hude; Doig, Christopher James; Dixon, Elijah; Molinari, Michele

    2011-01-01

    OBJECTIVE: To determine the generalizability of the predictions for 90-day mortality generated by Model for End-stage Liver Disease (MELD) and the serum sodium augmented MELD (MELDNa) to Atlantic Canadian adults with end-stage liver disease awaiting liver transplantation (LT). METHODS: The predictive accuracy of the MELD and the MELDNa was evaluated by measurement of the discrimination and calibration of the respective models’ estimates for the occurrence of 90-day mortality in a consecutive cohort of LT candidates accrued over a five-year period. Accuracy of discrimination was measured by the area under the ROC curves. Calibration accuracy was evaluated by comparing the observed and model-estimated incidences of 90-day wait-list failure for the total cohort and within quantiles of risk. RESULTS: The area under the ROC curve for the MELD was 0.887 (95% CI 0.705 to 0.978) – consistent with very good accuracy of discrimination. The area under the ROC curve for the MELDNa was 0.848 (95% CI 0.681 to 0.965). The observed incidence of 90-day wait-list mortality in the validation cohort was 7.9%, which was not significantly different from the MELD estimate of 6.6% (95% CI 4.9% to 8.4%; P=0.177) or the MELDNa estimate of 5.8% (95% CI 3.5% to 8.0%; P=0.065). Global goodness-of-fit testing found no evidence of significant lack of fit for either model (Hosmer-Lemeshow χ2 [df=3] for MELD 2.941, P=0.401; for MELDNa 2.895, P=0.414). CONCLUSION: Both the MELD and the MELDNa accurately predicted the occurrence of 90-day wait-list mortality in the study cohort and, therefore, are generalizable to Atlantic Canadians with end-stage liver disease awaiting LT. PMID:21876856

  15. The VACS Index Accurately Predicts Mortality and Treatment Response among Multi-Drug Resistant HIV Infected Patients Participating in the Options in Management with Antiretrovirals (OPTIMA) Study

    PubMed Central

    Brown, Sheldon T.; Tate, Janet P.; Kyriakides, Tassos C.; Kirkwood, Katherine A.; Holodniy, Mark; Goulet, Joseph L.; Angus, Brian J.; Cameron, D. William; Justice, Amy C.

    2014-01-01

    Objectives The VACS Index is highly predictive of all-cause mortality among HIV infected individuals within the first few years of combination antiretroviral therapy (cART). However, its accuracy among highly treatment experienced individuals and its responsiveness to treatment interventions have yet to be evaluated. We compared the accuracy and responsiveness of the VACS Index with a Restricted Index of age and traditional HIV biomarkers among patients enrolled in the OPTIMA study. Methods Using data from 324/339 (96%) patients in OPTIMA, we evaluated associations between indices and mortality using Kaplan-Meier estimates, proportional hazards models, Harrel’s C-statistic and net reclassification improvement (NRI). We also determined the association between study interventions and risk scores over time, and change in score and mortality. Results Both the Restricted Index (c = 0.70) and VACS Index (c = 0.74) predicted mortality from baseline, but discrimination was improved with the VACS Index (NRI = 23%). Change in score from baseline to 48 weeks was more strongly associated with survival for the VACS Index than the Restricted Index with respective hazard ratios of 0.26 (95% CI 0.14–0.49) and 0.39(95% CI 0.22–0.70) among the 25% most improved scores, and 2.08 (95% CI 1.27–3.38) and 1.51 (95%CI 0.90–2.53) for the 25% least improved scores. Conclusions The VACS Index predicts all-cause mortality more accurately among multi-drug resistant, treatment experienced individuals and is more responsive to changes in risk associated with treatment intervention than an index restricted to age and HIV biomarkers. The VACS Index holds promise as an intermediate outcome for intervention research. PMID:24667813

  16. Modelling the feedbacks between mass balance, ice flow and debris transport to predict the response to climate change of debris-covered glaciers in the Himalaya

    NASA Astrophysics Data System (ADS)

    Rowan, Ann V.; Egholm, David L.; Quincey, Duncan J.; Glasser, Neil F.

    2015-11-01

    Many Himalayan glaciers are characterised in their lower reaches by a rock debris layer. This debris insulates the glacier surface from atmospheric warming and complicates the response to climate change compared to glaciers with clean-ice surfaces. Debris-covered glaciers can persist well below the altitude that would be sustainable for clean-ice glaciers, resulting in much longer timescales of mass loss and meltwater production. The properties and evolution of supraglacial debris present a considerable challenge to understanding future glacier change. Existing approaches to predicting variations in glacier volume and meltwater production rely on numerical models that represent the processes governing glaciers with clean-ice surfaces, and yield conflicting results. We developed a numerical model that couples the flow of ice and debris and includes important feedbacks between debris accumulation and glacier mass balance. To investigate the impact of debris transport on the response of a glacier to recent and future climate change, we applied this model to a large debris-covered Himalayan glacier-Khumbu Glacier in Nepal. Our results demonstrate that supraglacial debris prolongs the response of the glacier to warming and causes lowering of the glacier surface in situ, concealing the magnitude of mass loss when compared with estimates based on glacierised area. Since the Little Ice Age, Khumbu Glacier has lost 34% of its volume while its area has reduced by only 6%. We predict a decrease in glacier volume of 8-10% by AD2100, accompanied by dynamic and physical detachment of the debris-covered tongue from the active glacier within the next 150 yr. This detachment will accelerate rates of glacier decay, and similar changes are likely for other debris-covered glaciers in the Himalaya.

  17. Parameterizing Size Distribution in Ice Clouds

    SciTech Connect

    DeSlover, Daniel; Mitchell, David L.

    2009-09-25

    cloud optical properties formulated in terms of PSD parameters in combination with remote measurements of thermal radiances to characterize the small mode. This is possible since the absorption efficiency (Qabs) of small mode crystals is larger at 12 µm wavelength relative to 11 µm wavelength due to the process of wave resonance or photon tunneling more active at 12 µm. This makes the 12/11 µm absorption optical depth ratio (or equivalently the 12/11 µm Qabs ratio) a means for detecting the relative concentration of small ice particles in cirrus. Using this principle, this project tested and developed PSD schemes that can help characterize cirrus clouds at each of the three ARM sites: SGP, NSA and TWP. This was the main effort of this project. These PSD schemes and ice sedimentation velocities predicted from them have been used to test the new cirrus microphysics parameterization in the GCM known as the Community Climate Systems Model (CCSM) as part of an ongoing collaboration with NCAR. Regarding the second problem, we developed and did preliminary testing on a passive thermal method for retrieving the total water path (TWP) of Arctic mixed phase clouds where TWPs are often in the range of 20 to 130 g m-2 (difficult for microwave radiometers to accurately measure). We also developed a new radar method for retrieving the cloud ice water content (IWC), which can be vertically integrated to yield the ice water path (IWP). These techniques were combined to determine the IWP and liquid water path (LWP) in Arctic clouds, and hence the fraction of ice and liquid water. We have tested this approach using a case study from the ARM field campaign called M-PACE (Mixed-Phase Arctic Cloud Experiment). This research led to a new satellite remote sensing method that appears promising for detecting low levels of liquid water in high clouds typically between -20 and -36 oC. We hope to develop this method in future research.

  18. An Intercomparison of Predicted Sea Ice Concentration from Global Ocean Forecast System & Arctic Cap Nowcast/Forecast System

    NASA Astrophysics Data System (ADS)

    Rosemond, K.

    2015-12-01

    The objective of this research is to provide an evaluation of improvements in marginal ice zone (MIZ) and pack ice estimations from the Global Ocean Forecast System (GOFS) model compared to the current operational model, the Arctic Cap Nowcast/Forecast System (ACNFS). This will be determined by an intercomparison between the subjectively estimated operational ice concentration data from the National Ice Center (NIC) MIZ analysis and the ice concentration estimates from GOFS and ACNFS. This will help ascertain which nowcast from the models compares best to the NIC operational data stream needed for vessel support. It will also provide a quantitative assessment of GOFS and ACNFS performance and be used in the Operational Evaluation (OPEVAL) report from the NIC to NRL. The intercomparison results are based on statistical evaluations through a series of map overlays from both models ACNFS, GOFS with the NIC's MIZ data. All data was transformed to a common grid and difference maps were generated to determine which model had the greatest difference compared to the MIZ ice concentrations. This was provided daily for both the freeze-up and meltout seasons. Results indicated the GOFS model surpassed the ACNFS model, however both models were comparable. These results will help US Navy and NWS Anchorage ice forecasters understand model biases and know which model guidance is likely to provide the best estimate of future ice conditions.The objective of this research is to provide an evaluation of improvements in marginal ice zone (MIZ) and pack ice estimations from the Global Ocean Forecast System (GOFS) model compared to the current operational model, the Arctic Cap Nowcast/Forecast System (ACNFS). This will be determined by an intercomparison between the subjectively estimated operational ice concentration data from the National Ice Center (NIC) MIZ analysis and the ice concentration estimates from GOFS and ACNFS. This will help ascertain which nowcast from the models

  19. Predicting the future distribution of Polar Bear Habitat in the polar basin from resource selection functions applied to 21st century general circulation model projections of sea ice

    USGS Publications Warehouse

    Durner, George M.; Douglas, David C.; Nielson, Ryan M.; Amstrup, Steven C.; McDonald, Trent L.

    2007-01-01

    Predictions of polar bear (Ursus maritimus) habitat distribution in the Arctic polar basin during the 21st century were developed to help understand the likely consequences of anticipated sea ice reductions on polar bear populations. We used location data from satellite-collared polar bears and environmental data (e.g., bathymetry, coastlines, and sea ice) collected between 1985–1995 to build habitat use models called Resource Selection Functions (RSF). The RSFs described habitats polar bears preferred in each of four seasons: summer (ice minimum), autumn (growth), winter (ice maximum) and spring (melt). When applied to the model source data and to independent data (1996–2006), the RSFs consistently identified habitats most frequently used by polar bears. We applied the RSFs to monthly maps of 21st century sea ice concentration predicted by 10 general circulation models (GCM) described in the International Panel of Climate Change Fourth Assessment Report. The 10 GCMs we used had high concordance between their simulations of 20th century summer sea ice extent and the actual ice extent derived from passive microwave satellite observations. Predictions of the amount and rate of change in polar bear habitat varied among GCMs, but all GCMs predicted net habitat losses in the polar basin during the 21st century. Projected losses in the highest-valued RSF habitat (optimal habitat) were greatest in the peripheral seas of the polar basin, especially the Chukchi Sea and Barents Sea. Losses were least in high-latitude regions where RSFs predicted an initial increase in optimal habitat followed by a modest decline. The largest seasonal reductions in habitat were predicted for spring and summer. Average area of optimal polar bear habitat during summer in the polar basin declined from an observed 1.0 million km2 in 1985–1995 (baseline) to a projected multi-model average of 0.58 million km2 in 2045–2054 (-42% change), 0.36 million km2 in 2070–2079 (-64% change), and 0

  20. Toward Relatively General and Accurate Quantum Chemical Predictions of Solid-State 17O NMR Chemical Shifts in Various Biologically Relevant Oxygen-containing Compounds

    PubMed Central

    Rorick, Amber; Michael, Matthew A.; Yang, Liu; Zhang, Yong

    2015-01-01

    Oxygen is an important element in most biologically significant molecules and experimental solid-state 17O NMR studies have provided numerous useful structural probes to study these systems. However, computational predictions of solid-state 17O NMR chemical shift tensor properties are still challenging in many cases and in particular each of the prior computational work is basically limited to one type of oxygen-containing systems. This work provides the first systematic study of the effects of geometry refinement, method and basis sets for metal and non-metal elements in both geometry optimization and NMR property calculations of some biologically relevant oxygen-containing compounds with a good variety of XO bonding groups, X= H, C, N, P, and metal. The experimental range studied is of 1455 ppm, a major part of the reported 17O NMR chemical shifts in organic and organometallic compounds. A number of computational factors towards relatively general and accurate predictions of 17O NMR chemical shifts were studied to provide helpful and detailed suggestions for future work. For the studied various kinds of oxygen-containing compounds, the best computational approach results in a theory-versus-experiment correlation coefficient R2 of 0.9880 and mean absolute deviation of 13 ppm (1.9% of the experimental range) for isotropic NMR shifts and R2 of 0.9926 for all shift tensor properties. These results shall facilitate future computational studies of 17O NMR chemical shifts in many biologically relevant systems, and the high accuracy may also help refinement and determination of active-site structures of some oxygen-containing substrate bound proteins. PMID:26274812

  1. Toward Relatively General and Accurate Quantum Chemical Predictions of Solid-State (17)O NMR Chemical Shifts in Various Biologically Relevant Oxygen-Containing Compounds.

    PubMed

    Rorick, Amber; Michael, Matthew A; Yang, Liu; Zhang, Yong

    2015-09-01

    Oxygen is an important element in most biologically significant molecules, and experimental solid-state (17)O NMR studies have provided numerous useful structural probes to study these systems. However, computational predictions of solid-state (17)O NMR chemical shift tensor properties are still challenging in many cases, and in particular, each of the prior computational works is basically limited to one type of oxygen-containing system. This work provides the first systematic study of the effects of geometry refinement, method, and basis sets for metal and nonmetal elements in both geometry optimization and NMR property calculations of some biologically relevant oxygen-containing compounds with a good variety of XO bonding groups (X = H, C, N, P, and metal). The experimental range studied is of 1455 ppm, a major part of the reported (17)O NMR chemical shifts in organic and organometallic compounds. A number of computational factors toward relatively general and accurate predictions of (17)O NMR chemical shifts were studied to provide helpful and detailed suggestions for future work. For the studied kinds of oxygen-containing compounds, the best computational approach results in a theory-versus-experiment correlation coefficient (R(2)) value of 0.9880 and a mean absolute deviation of 13 ppm (1.9% of the experimental range) for isotropic NMR shifts and an R(2) value of 0.9926 for all shift-tensor properties. These results shall facilitate future computational studies of (17)O NMR chemical shifts in many biologically relevant systems, and the high accuracy may also help the refinement and determination of active-site structures of some oxygen-containing substrate-bound proteins.

  2. Deep vein thrombosis is accurately predicted by comprehensive analysis of the levels of microRNA-96 and plasma D-dimer

    PubMed Central

    Xie, Xuesheng; Liu, Changpeng; Lin, Wei; Zhan, Baoming; Dong, Changjun; Song, Zhen; Wang, Shilei; Qi, Yingguo; Wang, Jiali; Gu, Zengquan

    2016-01-01

    The aim of the present study was to investigate the association between platelet microRNA-96 (miR-96) expression levels and the occurrence of deep vein thrombosis (DVT) in orthopedic patients. A total of consecutive 69 orthopedic patients with DVT and 30 healthy individuals were enrolled. Ultrasonic color Doppler imaging was performed on lower limb veins after orthopedic surgery to determine the occurrence of DVT. An enzyme-linked fluorescent assay was performed to detect the levels of D-dimer in plasma. A quantitative polymerase chain reaction assay was performed to determine the expression levels of miR-96. Expression levels of platelet miR-96 were significantly increased in orthopedic patients after orthopedic surgery. miR-96 expression levels in orthopedic patients with DVT at days 1, 3 and 7 after orthopedic surgery were significantly increased when compared with those in the control group. The increased miR-96 expression levels were correlated with plasma D-dimer levels in orthopedic patients with DVT. However, for the orthopedic patients in the non-DVT group following surgery, miR-96 expression levels were correlated with plasma D-dimer levels. In summary, the present results suggest that the expression levels of miR-96 may be associated with the occurrence of DVT. The occurrence of DVT may be accurately predicted by comprehensive analysis of the levels of miR-96 and plasma D-dimer. PMID:27588107

  3. Satellite remote sensing over ice

    NASA Technical Reports Server (NTRS)

    Thomas, R. H.

    1984-01-01

    Satellite remote sensing provides unique opportunities for observing ice-covered terrain. Passive-microwave data give information on snow extent on land, sea-ice extent and type, and zones of summer melting on the polar ice sheets, with the potential for estimating snow-accumulation rates on these ice sheets. All weather, high-resolution imagery of sea ice is obtained using synthetic aperture radars, and ice-movement vectors can be deduced by comparing sequential images of the same region. Radar-altimetry data provide highly detailed information on ice-sheet topography, with the potential for deducing thickening/thinning rates from repeat surveys. The coastline of Antarctica can be mapped accurately using altimetry data, and the size and spatial distribution of icebergs can be monitored. Altimetry data also distinguish open ocean from pack ice and they give an indication of sea-ice characteristics.

  4. Experimental Studies in Ice Nucleation

    NASA Astrophysics Data System (ADS)

    Wright, Timothy Peter

    Ice nuclei play a critical role in the formation of precipitation in mixed phase clouds. Modification of IN concentrations can lead to changes in cloud lifetimes and precipitation size. Presented in this study are experimental investigations into ice nuclei in an ongoing effort to reduce the uncertainties that ice nuclei have on cloud processes and climate. This research presents a new version of the cold stage drop freezing assay to investigate the time-dependence of heterogeneous nucleation. The temperature range for the instrument spans from the melting point of water to the homogeneous freezing limit of ˜-38 deg C. Temperature stability for the instrument allowed for experimental operation for up to four days while interrogating the same sample. Up to a one hundred fold increase in the number of analyzed drops was accomplished through an in-house written automated drop freezing detection software package. Combined instrument design improvements allow for the analysis of IN concentrations down to ˜10-8 ice nuclei per picoliter of sample water. A new variant of the multiple-component stochastic model for heterogeneous ice nucleation was used to investigate the time dependence of heterogeneous freezing processes. This was accomplished by analyzing how the changes in the cooling rate can impact the observed nucleation rate. The model employed four material-dependent parameters to accurately capture the observed freezing of water drops containing Arizona Test Dust. The parameters were then used to accurately predict the freezing behavior of the drops in time dependent experiments. The time dependence freezing of a wide range of materials was then investigated. These materials included the minerals montmorillonite and kaolinite, the biological proxy ice nuclei contained within the product Icemax, and flame soot generated from the incomplete combustion of ethylene gas. The time dependence for ice nuclei collected from rainwater samples was also investigated. The

  5. Searches for Dark Matter with IceCube and DeepCore : New constraints on theories predicting dark matter particles

    NASA Astrophysics Data System (ADS)

    Danninger, Matthias

    The cubic-kilometer sized IceCube neutrino observatory, constructed in the glacial ice at the South Pole, searches indirectly for dark matter via neutrinos from dark matter self-annihilations. It has a high discovery potential through striking signatures. This thesis presents searches for dark matter annihilations in the center of the Sun using experimental data collected with IceCube. The main physics analysis described here was performed for dark matter in the form of weakly interacting massive particles (WIMPs) with the 79-string configuration of the IceCube neutrino telescope. For the first time, the DeepCore sub-array was included in the analysis, lowering the energy threshold and extending the search to the austral summer. Data from 317 days live-time are consistent with the expected background from atmospheric muons and neutrinos. Upper limits were set on the dark matter annihilation rate, with conversions to limits on the WIMP-proton scattering cross section, which initiates the WIMP capture process in the Sun.These are the most stringent spin-dependent WIMP-proton cross-sections limits to date above 35 GeV for most WIMP models. In addition, a formalism for quickly and directly comparing event-level IceCube data with arbitrary annihilation spectra in detailed model scans, considering not only total event counts but also event directions and energy estimators, is presented. Two analyses were made that show an application of this formalism to both model exclusion and parameter estimation in models of supersymmetry. An analysis was also conducted that extended for the first time indirect dark matter searches with neutrinos using IceCube data, to an alternative dark matter candidate, Kaluza-Klein particles, arising from theories with extra space-time dimensions. The methods developed for the solar dark matter search were applied to look for neutrino emission during a flare of the Crab Nebula in 2010.

  6. Ice accretion simulation on multi-element airfoils using extended Messinger model

    NASA Astrophysics Data System (ADS)

    Özgen, S.; Canıbek, M.

    2009-01-01

    In the current article, the problem of in-flight ice accumulation on multi-element airfoils is studied numerically. The analysis starts with flow field computation using the Hess-Smith panel method. The second step is the calculation of droplet trajectories and droplet collection efficiencies. In the next step, convective heat transfer coefficient distributions around the airfoil elements are calculated using the Integral Boundary-Layer Method. The formulation accounts for the surface roughness due to ice accretion. The fourth step consists of establishing the thermodynamic balance and computing ice accretion rates using the Extended Messinger Model. At low temperatures and low liquid water contents, rime ice occurs for which the ice shape is determined by a simple mass balance. At warmer temperatures and high liquid water contents, glaze ice forms for which the energy and mass conservation equations are combined to yield a single first order ordinary differential equation, solved numerically. Predicted ice shapes are compared with experimental shapes reported in the literature and good agreement is observed both for rime and glaze ice. Ice shapes and masses are also computed for realistic flight scenarios. The results indicate that the smaller elements in multielement configurations accumulate comparable and often greater amount of ice compared to larger elements. The results also indicate that the multi-layer approach yields more accurate results compared to the one-layer approach, especially for glaze ice conditions.

  7. Accurate Prediction of Hyperfine Coupling Constants in Muoniated and Hydrogenated Ethyl Radicals: Ab Initio Path Integral Simulation Study with Density Functional Theory Method.

    PubMed

    Yamada, Kenta; Kawashima, Yukio; Tachikawa, Masanori

    2014-05-13

    We performed ab initio path integral molecular dynamics (PIMD) simulations with a density functional theory (DFT) method to accurately predict hyperfine coupling constants (HFCCs) in the ethyl radical (CβH3-CαH2) and its Mu-substituted (muoniated) compound (CβH2Mu-CαH2). The substitution of a Mu atom, an ultralight isotope of the H atom, with larger nuclear quantum effect is expected to strongly affect the nature of the ethyl radical. The static conventional DFT calculations of CβH3-CαH2 find that the elongation of one Cβ-H bond causes a change in the shape of potential energy curve along the rotational angle via the imbalance of attractive and repulsive interactions between the methyl and methylene groups. Investigation of the methyl-group behavior including the nuclear quantum and thermal effects shows that an unbalanced CβH2Mu group with the elongated Cβ-Mu bond rotates around the Cβ-Cα bond in a muoniated ethyl radical, quite differently from the CβH3 group with the three equivalent Cβ-H bonds in the ethyl radical. These rotations couple with other molecular motions such as the methylene-group rocking motion (inversion), leading to difficulties in reproducing the corresponding barrier heights. Our PIMD simulations successfully predict the barrier heights to be close to the experimental values and provide a significant improvement in muon and proton HFCCs given by the static conventional DFT method. Further investigation reveals that the Cβ-Mu/H stretching motion, methyl-group rotation, methylene-group rocking motion, and HFCC values deeply intertwine with each other. Because these motions are different between the radicals, a proper description of the structural fluctuations reflecting the nuclear quantum and thermal effects is vital to evaluate HFCC values in theory to be comparable to the experimental ones. Accordingly, a fundamental difference in HFCC between the radicals arises from their intrinsic molecular motions at a finite temperature, in

  8. Communication: Thermodynamics of stacking disorder in ice nuclei.

    PubMed

    Quigley, D

    2014-09-28

    A simple Ising-like model for the stacking thermodynamics of ice 1 is constructed for nuclei in supercooled water, and combined with classical nucleation theory. For relative stabilities of cubic and hexagonal ice I within the range of experimental estimates, this predicts critical nuclei are stacking disordered at strong sub-cooling, consistent with recent experiments. At higher temperatures nucleation of pure hexagonal ice is recovered. Lattice-switching Monte-Carlo is applied to accurately compute the relative stability of cubic and hexagonal ice for the popular mW model of water. Results demonstrate that this model fails to adequately capture the relative energetics of the two polytypes, leading to stacking disorder at all temperatures. PMID:25273401

  9. Communication: Thermodynamics of stacking disorder in ice nuclei

    NASA Astrophysics Data System (ADS)

    Quigley, D.

    2014-09-01

    A simple Ising-like model for the stacking thermodynamics of ice 1 is constructed for nuclei in supercooled water, and combined with classical nucleation theory. For relative stabilities of cubic and hexagonal ice I within the range of experimental estimates, this predicts critical nuclei are stacking disordered at strong sub-cooling, consistent with recent experiments. At higher temperatures nucleation of pure hexagonal ice is recovered. Lattice-switching Monte-Carlo is applied to accurately compute the relative stability of cubic and hexagonal ice for the popular mW model of water. Results demonstrate that this model fails to adequately capture the relative energetics of the two polytypes, leading to stacking disorder at all temperatures.

  10. Prospecting for Martian Ice

    NASA Technical Reports Server (NTRS)

    McBride, S. A.; Allen, C. C.; Bell, M. S.

    2005-01-01

    During high Martian obliquity, ice is stable to lower latitudes than predicted by models of present conditions and observed by the Gamma Ray Spectrometer (approx. 60 deg N). An ice-rich layer deposited at mid-latitudes could persist to the present day; ablation of the top 1 m of ice leaving a thin insulating cover could account for lack of its detection by GRS. The presence of an ice-layer in the mid-latitudes is suggested by a network of polygons, interpreted as ice-wedge cracks. This study focuses on an exceptional concentration of polygons in Western Utopia (section of Casius quadrangle, roughly 40 deg - 50 deg N, 255 deg - 300 deg W). We attempt to determine the thickness and age of this ice layer through crater-polygons relations.

  11. Ice stream activity scaled to ice sheet volume during Laurentide Ice Sheet deglaciation

    NASA Astrophysics Data System (ADS)

    Stokes, C. R.; Margold, M.; Clark, C. D.; Tarasov, L.

    2016-02-01

    The contribution of the Greenland and West Antarctic ice sheets to sea level has increased in recent decades, largely owing to the thinning and retreat of outlet glaciers and ice streams. This dynamic loss is a serious concern, with some modelling studies suggesting that the collapse of a major ice sheet could be imminent or potentially underway in West Antarctica, but others predicting a more limited response. A major problem is that observations used to initialize and calibrate models typically span only a few decades, and, at the ice-sheet scale, it is unclear how the entire drainage network of ice streams evolves over longer timescales. This represents one of the largest sources of uncertainty when predicting the contributions of ice sheets to sea-level rise. A key question is whether ice streams might increase and sustain rates of mass loss over centuries or millennia, beyond those expected for a given ocean-climate forcing. Here we reconstruct the activity of 117 ice streams that operated at various times during deglaciation of the Laurentide Ice Sheet (from about 22,000 to 7,000 years ago) and show that as they activated and deactivated in different locations, their overall number decreased, they occupied a progressively smaller percentage of the ice sheet perimeter and their total discharge decreased. The underlying geology and topography clearly influenced ice stream activity, but—at the ice-sheet scale—their drainage network adjusted and was linked to changes in ice sheet volume. It is unclear whether these findings can be directly translated to modern ice sheets. However, contrary to the view that sees ice streams as unstable entities that can accelerate ice-sheet deglaciation, we conclude that ice streams exerted progressively less influence on ice sheet mass balance during the retreat of the Laurentide Ice Sheet.

  12. Ice stream activity scaled to ice sheet volume during Laurentide Ice Sheet deglaciation.

    PubMed

    Stokes, C R; Margold, M; Clark, C D; Tarasov, L

    2016-02-18

    The contribution of the Greenland and West Antarctic ice sheets to sea level has increased in recent decades, largely owing to the thinning and retreat of outlet glaciers and ice streams. This dynamic loss is a serious concern, with some modelling studies suggesting that the collapse of a major ice sheet could be imminent or potentially underway in West Antarctica, but others predicting a more limited response. A major problem is that observations used to initialize and calibrate models typically span only a few decades, and, at the ice-sheet scale, it is unclear how the entire drainage network of ice streams evolves over longer timescales. This represents one of the largest sources of uncertainty when predicting the contributions of ice sheets to sea-level rise. A key question is whether ice streams might increase and sustain rates of mass loss over centuries or millennia, beyond those expected for a given ocean-climate forcing. Here we reconstruct the activity of 117 ice streams that operated at various times during deglaciation of the Laurentide Ice Sheet (from about 22,000 to 7,000 years ago) and show that as they activated and deactivated in different locations, their overall number decreased, they occupied a progressively smaller percentage of the ice sheet perimeter and their total discharge decreased. The underlying geology and topography clearly influenced ice stream activity, but--at the ice-sheet scale--their drainage network adjusted and was linked to changes in ice sheet volume. It is unclear whether these findings can be directly translated to modern ice sheets. However, contrary to the view that sees ice streams as unstable entities that can accelerate ice-sheet deglaciation, we conclude that ice streams exerted progressively less influence on ice sheet mass balance during the retreat of the Laurentide Ice Sheet. PMID:26887494

  13. Modeling Commercial Turbofan Engine Icing Risk With Ice Crystal Ingestion

    NASA Technical Reports Server (NTRS)

    Jorgenson, Philip C. E.; Veres, Joseph P.

    2013-01-01

    flight. The computational tool was utilized to help guide a portion of the PSL testing, and was used to predict ice accretion could also occur at significantly lower altitudes. The predictions were qualitatively verified by subsequent testing of the engine in the PSL. The PSL test has helped to calibrate the engine icing computational tool to assess the risk of ice accretion. The results from the computer simulation identified prevalent trends in wet bulb temperature, ice particle melt ratio, and engine inlet temperature as a function of altitude for predicting engine icing risk due to ice crystal ingestion.

  14. Airframe Icing Research Gaps: NASA Perspective

    NASA Technical Reports Server (NTRS)

    Potapczuk, Mark

    2009-01-01

    qCurrent Airframe Icing Technology Gaps: Development of a full 3D ice accretion simulation model. Development of an improved simulation model for SLD conditions. CFD modeling of stall behavior for ice-contaminated wings/tails. Computational methods for simulation of stability and control parameters. Analysis of thermal ice protection system performance. Quantification of 3D ice shape geometric characteristics Development of accurate ground-based simulation of SLD conditions. Development of scaling methods for SLD conditions. Development of advanced diagnostic techniques for assessment of tunnel cloud conditions. Identification of critical ice shapes for aerodynamic performance degradation. Aerodynamic scaling issues associated with testing scale model ice shape geometries. Development of altitude scaling methods for thermal ice protections systems. Development of accurate parameter identification methods. Measurement of stability and control parameters for an ice-contaminated swept wing aircraft. Creation of control law modifications to prevent loss of control during icing encounters. 3D ice shape geometries. Collection efficiency data for ice shape geometries. SLD ice shape data, in-flight and ground-based, for simulation verification. Aerodynamic performance data for 3D geometries and various icing conditions. Stability and control parameter data for iced aircraft configurations. Thermal ice protection system data for simulation validation.

  15. Response of the ice sheets to fluctuating temperatures

    NASA Astrophysics Data System (ADS)

    Bøgeholm Mikkelsen, Troels; Grinsted, Aslak; Ditlevsen, Peter

    2016-04-01

    Forecasting the future sea level relies on accurate modeling of the response of the Greenland and Antarctic ice sheets to changing tempera- tures. Using coupled climate and ice sheet models long time forecasting is often made computationally feasible by running the ice sheet model in off-line mode, such that the temperature and precipitation fields govern- ing the mass balance of the ice sheets are taken to be constant over time. As the temperature and precipitation fluctuates, the asymmetry in the typical time scales for accumulation and ablation would result in a bias in the resulting mass balance of the ice sheet. We show that the steady state of the ice sheet is biased toward larger size of the ice sheet, if the short time scale fluctuations in temperature are not taken into account. This could potentially imply that the critical global temperature increase for ice sheet collapse is overestimated, thus the risk of collapse in a given climate change scenario underestimated. Our results highlight the need to consider the variability and not only the mean of the forcing of the mass balance of the ice sheet. We estimate that the effect of temperature variability on surface mass balance of the Greenland Ice Sheet in recent ensemble forecasting should be adjusted downward by as much as 10 percent of the present day observed value, if assuming a 2 degree warming. We are thus closer to a potential tipping point, than previously anticipated. Many predicted scenarios of the future climate show an increased variability in temperature over much of the Earth. In light of the findings presented here, it is important to gauge the extent to which this increased variability will further influence climate change.

  16. Consider an Ice Stream.

    NASA Astrophysics Data System (ADS)

    Bindschadler, R.

    2002-12-01

    Forty years ago, John Nye was one of the leaders who introduced the rigors of classical physics to glaciology. His elegant treatments frequently took advantage of the then recent discovery that ice could be approximated as a plastic material. With this viewpoint, Nye was able to explain the shape of ice sheets and glaciers, to predict the expected pattern of stress and velocity within a glacier, and to derive the advance and retreat of a glacier from the record of accumulation and ablation. These advances have given generations of glaciologists tools to interpret the excellent observational record of glacier behavior and variation. In the 1980s, glaciologist, weaned on these works of Nye and of other similarly adept colleagues, carried their lessons to West Antarctica to study ice streams, the vast conveyor belts of ice that discharged nearly as much Antarctic ice as the much larger East Antarctic ice sheet. Ice streams were a glaciological conundrum. Despite the gently sloping surface, these broad features roared along, moving fastest when the gravitational impetus was least. After two decades of research, ice streams still have not given up all their secrets, yet much is now known. Internal deformation is negligible. Basal friction is frequently nil leaving the shattered margins as the primary means to avoid rapid wastage of the ice sheet. Within the margins, the resistive force results from a delicate balance of heat and evolving ice fabrics. Nevertheless, the bed beneath an ice stream cannot be ignored. It is ultimately the state of the underlying marine sediment that determines whether the ice stream can slide at all. There too, the heat balance is critical with an influx of water required to keep the bed wet enough to let the streams glide along. Ice stream research has been the portal through which glaciologists have seen and identified the complexities of West Antarctic ice sheet dynamics. Remarkably, nearly all time scales seem important. Ice stream

  17. Microbial abundance in surface ice on the Greenland Ice Sheet

    PubMed Central

    Stibal, Marek; Gözdereliler, Erkin; Cameron, Karen A.; Box, Jason E.; Stevens, Ian T.; Gokul, Jarishma K.; Schostag, Morten; Zarsky, Jakub D.; Edwards, Arwyn; Irvine-Fynn, Tristram D. L.; Jacobsen, Carsten S.

    2015-01-01

    Measuring microbial abundance in glacier ice and identifying its controls is essential for a better understanding and quantification of biogeochemical processes in glacial ecosystems. However, cell enumeration of glacier ice samples is challenging due to typically low cell numbers and the presence of interfering mineral particles. We quantified for the first time the abundance of microbial cells in surface ice from geographically distinct sites on the Greenland Ice Sheet (GrIS), using three enumeration methods: epifluorescence microscopy (EFM), flow cytometry (FCM), and quantitative polymerase chain reaction (qPCR). In addition, we reviewed published data on microbial abundance in glacier ice and tested the three methods on artificial ice samples of realistic cell (102–107 cells ml−1) and mineral particle (0.1–100 mg ml−1) concentrations, simulating a range of glacial ice types, from clean subsurface ice to surface ice to sediment-laden basal ice. We then used multivariate statistical analysis to identify factors responsible for the variation in microbial abundance on the ice sheet. EFM gave the most accurate and reproducible results of the tested methodologies, and was therefore selected as the most suitable technique for cell enumeration of ice containing dust. Cell numbers in surface ice samples, determined by EFM, ranged from ~ 2 × 103 to ~ 2 × 106 cells ml−1 while dust concentrations ranged from 0.01 to 2 mg ml−1. The lowest abundances were found in ice sampled from the accumulation area of the ice sheet and in samples affected by fresh snow; these samples may be considered as a reference point of the cell abundance of precipitants that are deposited on the ice sheet surface. Dust content was the most significant variable to explain the variation in the abundance data, which suggests a direct association between deposited dust particles and cells and/or by their provision of limited nutrients to microbial communities on the GrIS. PMID:25852678

  18. Microbial abundance in surface ice on the Greenland Ice Sheet.

    PubMed

    Stibal, Marek; Gözdereliler, Erkin; Cameron, Karen A; Box, Jason E; Stevens, Ian T; Gokul, Jarishma K; Schostag, Morten; Zarsky, Jakub D; Edwards, Arwyn; Irvine-Fynn, Tristram D L; Jacobsen, Carsten S

    2015-01-01

    Measuring microbial abundance in glacier ice and identifying its controls is essential for a better understanding and quantification of biogeochemical processes in glacial ecosystems. However, cell enumeration of glacier ice samples is challenging due to typically low cell numbers and the presence of interfering mineral particles. We quantified for the first time the abundance of microbial cells in surface ice from geographically distinct sites on the Greenland Ice Sheet (GrIS), using three enumeration methods: epifluorescence microscopy (EFM), flow cytometry (FCM), and quantitative polymerase chain reaction (qPCR). In addition, we reviewed published data on microbial abundance in glacier ice and tested the three methods on artificial ice samples of realistic cell (10(2)-10(7) cells ml(-1)) and mineral particle (0.1-100 mg ml(-1)) concentrations, simulating a range of glacial ice types, from clean subsurface ice to surface ice to sediment-laden basal ice. We then used multivariate statistical analysis to identify factors responsible for the variation in microbial abundance on the ice sheet. EFM gave the most accurate and reproducible results of the tested methodologies, and was therefore selected as the most suitable technique for cell enumeration of ice containing dust. Cell numbers in surface ice samples, determined by EFM, ranged from ~ 2 × 10(3) to ~ 2 × 10(6) cells ml(-1) while dust concentrations ranged from 0.01 to 2 mg ml(-1). The lowest abundances were found in ice sampled from the accumulation area of the ice sheet and in samples affected by fresh snow; these samples may be considered as a reference point of the cell abundance of precipitants that are deposited on the ice sheet surface. Dust content was the most significant variable to explain the variation in the abundance data, which suggests a direct association between deposited dust particles and cells and/or by their provision of limited nutrients to microbial communities on the GrIS. PMID

  19. Multiwalled ice helixes and ice nanotubes

    PubMed Central

    Bai, Jaeil; Wang, Jun; Zeng, X. C.

    2006-01-01

    We report six phases of high-density nano-ice predicted to form within carbon nanotubes (CNTs) at high pressure. High-density nano-ice self-assembled within smaller-diameter CNT (17,0) exhibits a double-walled helical structure where the outer wall consists of four double-stranded helixes, which resemble a DNA double helix, and the inner wall is a quadruple-stranded helix. Four other double-walled nano-ices, self-assembled respectively in two larger-diameter CNTs (20,0 and 22,0), display tubular structure. Within CNT (24,0), the confined water can freeze spontaneously into a triple-walled helical nano-ice where the outer wall is an 18-stranded helix and the middle and inner walls are hextuple-stranded helixes. PMID:17170136

  20. Accurate prediction of explicit solvent atom distribution in HIV-1 protease and F-ATP synthase by statistical theory of liquids

    NASA Astrophysics Data System (ADS)

    Sindhikara, Daniel; Yoshida, Norio; Hirata, Fumio

    2012-02-01

    We have created a simple algorithm for automatically predicting the explicit solvent atom distribution of biomolecules. The explicit distribution is coerced from the 3D continuous distribution resulting from a 3D-RISM calculation. This procedure predicts optimal location of solvent molecules and ions given a rigid biomolecular structure. We show examples of predicting water molecules near KNI-275 bound form of HIV-1 protease and predicting both sodium ions and water molecules near the rotor ring of F-ATP synthase. Our results give excellent agreement with experimental structure with an average prediction error of 0.45-0.65 angstroms. Further, unlike experimental methods, this method does not suffer from the partial occupancy limit. Our method can be performed directly on 3D-RISM output within minutes. It is useful not only as a location predictor but also as a convenient method for generating initial structures for MD calculations.

  1. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11.

    PubMed

    Lundegaard, Claus; Lamberth, Kasper; Harndahl, Mikkel; Buus, Søren; Lund, Ole; Nielsen, Morten

    2008-07-01

    NetMHC-3.0 is trained on a large number of quantitative peptide data using both affinity data from the Immune Epitope Database and Analysis Resource (IEDB) and elution data from SYFPEITHI. The method generates high-accuracy predictions of major histocompatibility complex (MHC): peptide binding. The predictions are based on artificial neural networks trained on data from 55 MHC alleles (43 Human and 12 non-human), and position-specific scoring matrices (PSSMs) for additional 67 HLA alleles. As only the MHC class I prediction server is available, predictions are possible for peptides of length 8-11 for all 122 alleles. artificial neural network predictions are given as actual IC(50) values whereas PSSM predictions are given as a log-odds likelihood scores. The output is optionally available as download for easy post-processing. The training method underlying the server is the best available, and has been used to predict possible MHC-binding peptides in a series of pathogen viral proteomes including SARS, Influenza and HIV, resulting in an average of 75-80% confirmed MHC binders. Here, the performance is further validated and benchmarked using a large set of newly published affinity data, non-redundant to the training set. The server is free of use and available at: http://www.cbs.dtu.dk/services/NetMHC.

  2. Impacts of alternative fuels in aviation on microphysical aerosol properties and predicted ice nuclei concentration at aircraft cruise altitude

    NASA Astrophysics Data System (ADS)

    Weinzierl, B.; D'Ascoli, E.; Sauer, D. N.; Kim, J.; Scheibe, M.; Schlager, H.; Moore, R.; Anderson, B. E.; Ullrich, R.; Mohler, O.; Hoose, C.

    2015-12-01

    In the past decades air traffic has been substantially growing affecting air quality and climate. According to the International Civil Aviation Authority (ICAO), in the next few years world passenger and freight traffic is expected to increase annually by 6-7% and 4-5%, respectively. One possibility to reduce aviation impacts on the atmosphere and climate might be the replacement of fossil fuels by alternative fuels. However, so far the effects of alternative fuels on particle emissions from aircraft engines and their ability to form contrails remain uncertain. To study the effects of alternative fuels on particle emissions and the formation of contrails, the Alternative Fuel Effects on Contrails and Cruise Emissions (ACCESS) field experiment was conducted in California. In May 2014, the DLR Falcon 20 and the NASA HU-25 jet aircraft were instrumented with an extended aerosol and trace gas payload probing different types of fuels including JP-8 and JP-8 blended with HEFA (Hydroprocessed Esters and Fatty Acids) while the NASA DC8 aircraft acted as the source aircraft for ACCESS-2. Emission measurements were taken in the DC8 exhaust plumes at aircraft cruise level between 9-12 km altitude and at distances between 50 m and 20 km behind the DC8 engines. Here, we will present results from the ACCESS-2 aerosol measurements which show a 30-60% reduction of the non-volatile (mainly black carbon) particle number concentration in the aircraft exhaust for the HEFA-blend compared to conventional JP-8 fuel. Size-resolved particle emission indices show the largest reductions for larger particle sizes suggesting that the HEFA blend contains fewer and smaller black carbon particles. We will combine the airborne measurements with a parameterization of deposition nucleation developed during a number of ice nucleation experiments at the AIDA chamber in Karlsruhe and discuss the impact of alternative fuels on the abundance of potential ice nuclei at cruise conditions.

  3. Cyclic steps on ice

    NASA Astrophysics Data System (ADS)

    Yokokawa, M.; Izumi, N.; Naito, K.; Parker, G.; Yamada, T.; Greve, R.

    2016-05-01

    Boundary waves often form at the interface between ice and fluid flowing adjacent to it, such as ripples under river ice covers, and steps on the bed of supraglacial meltwater channels. They may also be formed by wind, such as the megadunes on the Antarctic ice sheet. Spiral troughs on the polar ice caps of Mars have been interpreted to be cyclic steps formed by katabatic wind blowing over ice. Cyclic steps are relatives of upstream-migrating antidunes. Cyclic step formation on ice is not only a mechanical but also a thermodynamic process. There have been very few studies on the formation of either cyclic steps or upstream-migrating antidunes on ice. In this study, we performed flume experiments to reproduce cyclic steps on ice by flowing water, and found that trains of steps form when the Froude number is larger than unity. The features of those steps allow them to be identified as ice-bed analogs of cyclic steps in alluvial and bedrock rivers. We performed a linear stability analysis and obtained a physical explanation of the formation of upstream-migrating antidunes, i.e., precursors of cyclic steps. We compared the results of experiments with the predictions of the analysis and found the observed steps fall in the range where the analysis predicts interfacial instability. We also found that short antidune-like undulations formed as a precursor to the appearance of well-defined steps. This fact suggests that such antidune-like undulations correspond to the instability predicted by the analysis and are precursors of cyclic steps.

  4. On the Ice Nucleation Spectrum

    NASA Technical Reports Server (NTRS)

    Barahona, D.

    2012-01-01

    This work presents a novel formulation of the ice nucleation spectrum, i.e. the function relating the ice crystal concentration to cloud formation conditions and aerosol properties. The new formulation is physically-based and explicitly accounts for the dependency of the ice crystal concentration on temperature, supersaturation, cooling rate, and particle size, surface area and composition. This is achieved by introducing the concepts of ice nucleation coefficient (the number of ice germs present in a particle) and nucleation probability dispersion function (the distribution of ice nucleation coefficients within the aerosol population). The new formulation is used to generate ice nucleation parameterizations for the homogeneous freezing of cloud droplets and the heterogeneous deposition ice nucleation on dust and soot ice nuclei. For homogeneous freezing, it was found that by increasing the dispersion in the droplet volume distribution the fraction of supercooled droplets in the population increases. For heterogeneous ice nucleation the new formulation consistently describes singular and stochastic behavior within a single framework. Using a fundamentally stochastic approach, both cooling rate independence and constancy of the ice nucleation fraction over time, features typically associated with singular behavior, were reproduced. Analysis of the temporal dependency of the ice nucleation spectrum suggested that experimental methods that measure the ice nucleation fraction over few seconds would tend to underestimate the ice nuclei concentration. It is shown that inferring the aerosol heterogeneous ice nucleation properties from measurements of the onset supersaturation and temperature may carry significant error as the variability in ice nucleation properties within the aerosol population is not accounted for. This work provides a simple and rigorous ice nucleation framework where theoretical predictions, laboratory measurements and field campaign data can be

  5. NASA's program on icing research and technology

    NASA Technical Reports Server (NTRS)

    Reinmann, John J.; Shaw, Robert J.; Ranaudo, Richard J.

    1989-01-01

    NASA's program in aircraft icing research and technology is reviewed. The program relies heavily on computer codes and modern applied physics technology in seeking icing solutions on a finer scale than those offered in earlier programs. Three major goals of this program are to offer new approaches to ice protection, to improve our ability to model the response of an aircraft to an icing encounter, and to provide improved techniques and facilities for ground and flight testing. This paper reviews the following program elements: (1) new approaches to ice protection; (2) numerical codes for deicer analysis; (3) measurement and prediction of ice accretion and its effect on aircraft and aircraft components; (4) special wind tunnel test techniques for rotorcraft icing; (5) improvements of icing wind tunnels and research aircraft; (6) ground de-icing fluids used in winter operation; (7) fundamental studies in icing; and (8) droplet sizing instruments for icing clouds.

  6. Ice thickness in the Northwest Passage

    NASA Astrophysics Data System (ADS)

    Haas, Christian; Howell, Stephen E. L.

    2015-09-01

    Recently, the feasibility of commercial shipping in the ice-prone Northwest Passage (NWP) has attracted a lot of attention. However, very little ice thickness information actually exists. We present results of the first ever airborne electromagnetic ice thickness surveys over the NWP carried out in April and May 2011 and 2015 over first-year and multiyear ice. These show modal thicknesses between 1.8 and 2.0 m in all regions. Mean thicknesses over 3 m and thick, deformed ice were observed over some multiyear ice regimes shown to originate from the Arctic Ocean. Thick ice features more than 100 m wide and thicker than 4 m occurred frequently. Results indicate that even in today's climate, ice conditions must still be considered severe. These results have important implications for the prediction of ice breakup and summer ice conditions, and the assessment of sea ice hazards during the summer shipping season.

  7. NASA's program on icing research and technology

    NASA Technical Reports Server (NTRS)

    Reinmann, John J.; Shaw, Robert J.; Ranaudo, Richard J.

    1989-01-01

    NASA's program in aircraft icing research and technology is reviewed. The program relies heavily on computer codes and modern applied physics technology in seeking icing solutions on a finer scale than those offered in earlier programs. Three major goals of this program are to offer new approaches to ice protection, to improve the ability to model the response of an aircraft to an icing encounter, and to provide improved techniques and facilities for ground and flight testing. The following program elements are reviewed: (1) new approaches to ice protection; (2) numerical codes for deicer analysis; (3) measurement and prediction of ice accretion and its effect on aircraft and aircraft components; (4) special wind tunnel test techniques for rotorcraft icing; (5) improvements of icing wind tunnels and research aircraft; (6) ground de-icing fluids used in winter operation; (7) fundamental studies in icing; and (8) droplet sizing instruments for icing clouds.

  8. Using ice-penetrating radars to date ice-rise formation and Late Holocene ice-sheet retreat in the Ronne Ice Shelf region, West Antarctica

    NASA Astrophysics Data System (ADS)

    Kingslake, Jonathan; Hindmarsh, Richard; King, Edward; Corr, Hugh

    2015-04-01

    The history of the West Antarctic Ice Sheet in the region currently occupied by the Ronne Ice Shelf is poorly known. This reflects a lack of accessible recently deglaciated surfaces, which prohibits conventional paleo glaciological techniques that can provide evidence of past ice-sheet extent and retreat, for example ocean coring or exposure-dating of geological material. We use a glaciological technique, Raymond Effect Dating, to constrain the retreat of the ice sheet through the Ronne Ice Shelf region. During two Antarctic field seasons, we used a pulse-echo ice-penetrating radar to image the base and internal stratigraphy of four ice rises - areas of grounded ice containing ice divides. Towing the radar with skidoos, we conducted over 2000 km of surveys on the Skytrain, Korff, Henry and Fowler Ice Rises and the ice shelf between them. We also used a step-frequency radar called pRES to measure the vertical ice flow in the vicinity of each ice divide. Isochronal ice layers imaged during the surveys deforming in a predictable way with ice flow, meaning that their shape contains information about past ice flow. Directly beneath ice divides the downward motion of the ice is impeded by an ice-dynamical phenomenon called the Raymond Effect. This causes layers beneath the divides to form 'Raymond Arches' that grow over time. We will present the data and simulate the growth of the Raymond Arches using our pRES-measured vertical ice velocities and date the onset of ice-divide flow at each ice rise by comparing the size of simulated arches to the arches imaged during our radar surveys. We consider the main sources of uncertainty associated with these ice-rise formation dates and discuss what they can tell us about the retreat of the West Antarctic Ice Sheet through this region during the last few thousand years.

  9. Sea ice-albedo climate feedback mechanism

    SciTech Connect

    Schramm, J.L.; Curry, J.A.; Ebert, E.E.

    1995-02-01

    The sea ice-albedo feedback mechanism over the Arctic Ocean multiyear sea ice is investigated by conducting a series of experiments using several one-dimensional models of the coupled sea ice-atmosphere system. In its simplest form, ice-albedo feedback is thought to be associated with a decrease in the areal cover of snow and ice and a corresponding increase in the surface temperature, further decreasing the area cover of snow and ice. It is shown that the sea ice-albedo feedback can operate even in multiyear pack ice, without the disappearance of this ice, associated with internal processes occurring within the multiyear ice pack (e.g., duration of the snow cover, ice thickness, ice distribution, lead fraction, and melt pond characteristics). The strength of the ice-albedo feedback mechanism is compared for several different thermodynamic sea ice models: a new model that includes ice thickness distribution., the Ebert and Curry model, the Mayjut and Untersteiner model, and the Semtner level-3 and level-0 models. The climate forcing is chosen to be a perturbation of the surface heat flux, and cloud and water vapor feedbacks are inoperative so that the effects of the sea ice-albedo feedback mechanism can be isolated. The inclusion of melt ponds significantly strengthens the ice-albedo feedback, while the ice thickness distribution decreases the strength of the modeled sea ice-albedo feedback. It is emphasized that accurately modeling present-day sea ice thickness is not adequate for a sea ice parameterization; the correct physical processes must be included so that the sea ice parameterization yields correct sensitivities to external forcing. 22 refs., 6 figs., 1 tab.

  10. [Tail Plane Icing

    NASA Technical Reports Server (NTRS)

    1997-01-01

    The Aviation Safety Program initiated by NASA in 1997 has put greater emphasis in safety related research activities. Ice-contaminated-tailplane stall (ICTS) has been identified by the NASA Lewis Icing Technology Branch as an important activity for aircraft safety related research. The ICTS phenomenon is characterized as a sudden, often uncontrollable aircraft nose- down pitching moment, which occurs due to increased angle-of-attack of the horizontal tailplane resulting in tailplane stall. Typically, this phenomenon occurs when lowering the flaps during final approach while operating in or recently departing from icing conditions. Ice formation on the tailplane leading edge can reduce tailplane angle-of-attack range and cause flow separation resulting in a significant reduction or complete loss of aircraft pitch control. In 1993, the Federal Aviation Authority (FAA) and NASA embarked upon a four-year research program to address the problem of tailplane stall and to quantify the effect of tailplane ice accretion on aircraft performance and handling characteristics. The goals of this program, which was completed in March 1998, were to collect aerodynamic data for an aircraft tail with and without ice contamination and to develop analytical methods for predicting the effects of tailplane ice contamination. Extensive dry air and icing tunnel tests which resulted in a database of the aerodynamic effects associated with tailplane ice contamination. Although the FAA/NASA tailplane icing program generated some answers regarding ice-contaminated-tailplane stall (ICTS) phenomena, NASA researchers have found many open questions that warrant further investigation into ICTS. In addition, several aircraft manufacturers have expressed interest in a second research program to expand the database to other tail configurations and to develop experimental and computational methodologies for evaluating the ICTS phenomenon. In 1998, the icing branch at NASA Lewis initiated a second

  11. Results of the Marine Ice Sheet Model Intercomparison Project, MISMIP

    NASA Astrophysics Data System (ADS)

    Pattyn, F.; Schoof, C.; Perichon, L.; Hindmarsh, R. C. A.; Bueler, E.; de Fleurian, B.; Durand, G.; Gagliardini, O.; Gladstone, R.; Goldberg, D.; Gudmundsson, G. H.; Lee, V.; Nick, F. M.; Payne, A. J.; Pollard, D.; Rybak, O.; Saito, F.; Vieli, A.

    2012-01-01

    Predictions of marine ice-sheet behaviour require models that are able to robustly simulate grounding line migration. We present results of an intercomparison exercise for marine ice-sheet models. Verification is effected by comparison with approximate analytical solutions for flux across the grounding line using simplified geometrical configurations (no lateral variations, no effects of lateral buttressing). Unique steady-state grounding line positions exist for ice sheets on a downward sloping bed, while hysteresis occurs across an overdeepened bed, and stable steady state grounding line positions only occur on the downward-sloping sections. Models based on the shallow ice approximation, which does not resolve extensional stresses, do not reproduce the approximate analytical results unless appropriate parameterizations for ice flux are imposed at the grounding line. For extensional-stress resolving "shelfy stream" models, differences between model results were mainly due to the choice of spatial discretization. Moving grid methods were found to be the most accurate at capturing grounding line evolution, since they track the grounding line explicitly. Adaptive mesh refinement can further improve accuracy, including in fixed-grid models that generally perform poorly at coarse resolution. Fixed grid models with nested grid representations of the grounding line are able to generate accurate steady-state positions, but can be inaccurate over transients. Only one full Stokes model was included in the intercomparison, and consequently the accuracy of shelfy stream models as approximations of full Stokes models remains to be determined in detail, especially during transients.

  12. Results of the Marine Ice Sheet Model Intercomparison Project, MISMIP

    NASA Astrophysics Data System (ADS)

    Pattyn, F.; Schoof, C.; Perichon, L.; Hindmarsh, R. C. A.; Bueler, E.; de Fleurian, B.; Durand, G.; Gagliardini, O.; Gladstone, R.; Goldberg, D.; Gudmundsson, G. H.; Huybrechts, P.; Lee, V.; Nick, F. M.; Payne, A. J.; Pollard, D.; Rybak, O.; Saito, F.; Vieli, A.

    2012-05-01

    Predictions of marine ice-sheet behaviour require models that are able to robustly simulate grounding line migration. We present results of an intercomparison exercise for marine ice-sheet models. Verification is effected by comparison with approximate analytical solutions for flux across the grounding line using simplified geometrical configurations (no lateral variations, no effects of lateral buttressing). Unique steady state grounding line positions exist for ice sheets on a downward sloping bed, while hysteresis occurs across an overdeepened bed, and stable steady state grounding line positions only occur on the downward-sloping sections. Models based on the shallow ice approximation, which does not resolve extensional stresses, do not reproduce the approximate analytical results unless appropriate parameterizations for ice flux are imposed at the grounding line. For extensional-stress resolving "shelfy stream" models, differences between model results were mainly due to the choice of spatial discretization. Moving grid methods were found to be the most accurate at capturing grounding line evolution, since they track the grounding line explicitly. Adaptive mesh refinement can further improve accuracy, including fixed grid models that generally perform poorly at coarse resolution. Fixed grid models, with nested grid representations of the grounding line, are able to generate accurate steady state positions, but can be inaccurate over transients. Only one full-Stokes model was included in the intercomparison, and consequently the accuracy of shelfy stream models as approximations of full-Stokes models remains to be determined in detail, especially during transients.

  13. Sea Ice

    NASA Technical Reports Server (NTRS)

    Parkinson, Claire L.; Cavalieri, Donald J.

    2005-01-01

    Sea ice covers vast areas of the polar oceans, with ice extent in the Northern Hemisphere ranging from approximately 7 x 10(exp 6) sq km in September to approximately 15 x 10(exp 6) sq km in March and ice extent in the Southern Hemisphere ranging from approximately 3 x 10(exp 6) sq km in February to approximately 18 x 10(exp 6) sq km in September. These ice covers have major impacts on the atmosphere, oceans, and ecosystems of the polar regions, and so as changes occur in them there are potential widespread consequences. Satellite data reveal considerable interannual variability in both polar sea ice covers, and many studies suggest possible connections between the ice and various oscillations within the climate system, such as the Arctic Oscillation, North Atlantic Oscillation, and Antarctic Oscillation, or Southern Annular Mode. Nonetheless, statistically significant long-term trends are also apparent, including overall trends of decreased ice coverage in the Arctic and increased ice coverage in the Antarctic from late 1978 through the end of 2003, with the Antarctic ice increases following marked decreases in the Antarctic ice during the 1970s. For a detailed picture of the seasonally varying ice cover at the start of the 21st century, this chapter includes ice concentration maps for each month of 2001 for both the Arctic and the Antarctic, as well as an overview of what the satellite record has revealed about the two polar ice covers from the 1970s through 2003.

  14. Over Ice

    NASA Video Gallery

    All about NASA's IceBridge P-3B plane and its IceBridge retrofit. Upgraded with 21st century "special modifications", the aircraft is less a cold war relic and more like the Space Agency's Millenni...

  15. Mechanisms resulting in accreted ice roughness

    NASA Technical Reports Server (NTRS)

    Bilanin, Alan J.; Chua, Kiat

    1992-01-01

    Icing tests conducted on rotating cylinders in the BF Goodrich's Icing Research Facility indicate that a regular, deterministic, icing roughness pattern is typical. The roughness pattern is similar to kernels of corn on a cob for cylinders of diameter typical of a cob. An analysis is undertaken to determine the mechanisms which result in this roughness to ascertain surface scale and amplitude of roughness. Since roughness and the resulting augmentation of the convected heat transfer coefficient has been determined to most strongly control the accreted ice in ice prediction codes, the ability to predict a priori, location, amplitude and surface scale of roughness would greatly augment the capabilities of current ice accretion models.

  16. Windamper method of galloping control. Pt. II. Prediction of dynamic galloping. Final report. [Ice buildup on windward side

    SciTech Connect

    Richardson, A.S. Jr.

    1983-10-15

    This has been a technical review and extension of the Windamper methodology for controlling galloping (ice buildup on windward side). The new material consists of three main parts. First, there is the review and analysis of single conductor by coupled two-degree-of-freedom analysis. Second, there is the extension of that method to the bundled conductor. Third, there is the report of the new Windamper aerodynamic data (Appendix). The analytical work supports the general hypothesis and theory of Den Hartog. The Windamper appears to act to stabilize conductors which would otherwise become unstable when lift slope is negative. When lift slope is positive, a flutter type of gallop may be identified, owing to lee-side location of the damper c.g. In single conductors, the realization of the flutter gallop requires very large positive lift slope, and the torsion component dominates the motion which also would limit gallop amplitude. In bundled conductors, the realization of the flutter gallop requires only small positive lift slope because of the proximity of the two natural frequencies to each other. Very little torsion is present in the bundle motion, and the Windamper aerodynamic drag produces a net flow of energy to damp the motion.

  17. Use of quantitative shape-activity relationships to model the photoinduced toxicity of polycyclic aromatic hydrocarbons: Electron density shape features accurately predict toxicity

    SciTech Connect

    Mezey, P.G.; Zimpel, Z.; Warburton, P.; Walker, P.D.; Irvine, D.G.; Huang, X.D.; Dixon, D.G.; Greenberg, B.M.

    1998-07-01

    The quantitative shape-activity relationship (QShAR) methodology, based on accurate three-dimensional electron densities and detailed shape analysis methods, has been applied to a Lemna gibba photoinduced toxicity data set of 16 polycyclic aromatic hydrocarbon (PAH) molecules. In the first phase of the studies, a shape fragment QShAR database of PAHs was developed. The results provide a very good match to toxicity based on a combination of the local shape features of single rings in comparison to the central ring of anthracene and a more global shape feature involving larger molecular fragments. The local shape feature appears as a descriptor of the susceptibility of PAHs to photomodification and the global shape feature is probably related to photosensitization activity.

  18. CFD Analysis of the Aerodynamics of a Business-Jet Airfoil with Leading-Edge Ice Accretion

    NASA Technical Reports Server (NTRS)

    Chi, X.; Zhu, B.; Shih, T. I.-P.; Addy, H. E.; Choo, Y. K.

    2004-01-01

    For rime ice - where the ice buildup has only rough and jagged surfaces but no protruding horns - this study shows two dimensional CFD analysis based on the one-equation Spalart-Almaras (S-A) turbulence model to predict accurately the lift, drag, and pressure coefficients up to near the stall angle. For glaze ice - where the ice buildup has two or more protruding horns near the airfoil's leading edge - CFD predictions were much less satisfactory because of the large separated region produced by the horns even at zero angle of attack. This CFD study, based on the WIND and the Fluent codes, assesses the following turbulence models by comparing predictions with available experimental data: S-A, standard k-epsilon, shear-stress transport, v(exp 2)-f, and differential Reynolds stress.

  19. Ice crystal ingestion by turbofans

    NASA Astrophysics Data System (ADS)

    Rios Pabon, Manuel A.

    This Thesis will present the problem of inflight icing in general and inflight icing caused by the ingestion of high altitude ice crystals produced by high energy mesoscale convective complexes in particular, and propose a new device to prevent it based on dielectric barrier discharge plasma. Inflight icing is known to be the cause of 583 air accidents and more than 800 deaths in more than a decade. The new ice crystal ingestion problem has caused more than 100 flights to lose engine power since the 1990's, and the NTSB identified it as one of the causes of the Air France flight 447 accident in 1-Jun2008. The mechanics of inflight icing not caused by ice crystals are well established. Aircraft surfaces exposed to supercooled liquid water droplets will accrete ice in direct proportion of the droplet catch and the freezing heat transfer process. The multiphase flow droplet catch is predicted by the simple sum of forces on each spherical droplet and a droplet trajectory calculation based on Lagrangian or Eulerian analysis. The most widely used freezing heat transfer model for inflight icing caused by supercooled droplets was established by Messinger. Several computer programs implement these analytical models to predict inflight icing, with LEWICE being based on Lagrangian analysis and FENSAP being based on Eulerian analysis as the best representatives among them. This Thesis presents the multiphase fluid mechanics particular to ice crystals, and explains how it differs from the established droplet multiphase flow, and the obstacles in implementing the former in computational analysis. A new modification of the Messinger thermal model is proposed to account for ice accretion produced by ice crystal impingement. Because there exist no computational and experimental ways to fully replicate ice crystal inflight icing, and because existing ice protections systems consume vast amounts of energy, a new ice protection device based on dielectric barrier discharge plasma is

  20. Use of dose-dependent absorption into target tissues to more accurately predict cancer risk at low oral doses of hexavalent chromium.

    PubMed

    Haney, J

    2015-02-01

    The mouse dose at the lowest water concentration used in the National Toxicology Program hexavalent chromium (CrVI) drinking water study (NTP, 2008) is about 74,500 times higher than the approximate human dose corresponding to the 35-city geometric mean reported in EWG (2010) and over 1000 times higher than that based on the highest reported tap water concentration. With experimental and environmental doses differing greatly, it is a regulatory challenge to extrapolate high-dose results to environmental doses orders of magnitude lower in a meaningful and toxicologically predictive manner. This seems particularly true for the low-dose extrapolation of results for oral CrVI-induced carcinogenesis since dose-dependent differences in the dose fraction absorbed by mouse target tissues are apparent (Kirman et al., 2012). These data can be used for a straightforward adjustment of the USEPA (2010) draft oral slope factor (SFo) to be more predictive of risk at environmentally-relevant doses. More specifically, the evaluation of observed and modeled differences in the fraction of dose absorbed by target tissues at the point-of-departure for the draft SFo calculation versus lower doses suggests that the draft SFo be divided by a dose-specific adjustment factor of at least an order of magnitude to be less over-predictive of risk at more environmentally-relevant doses.

  1. PredPPCrys: Accurate Prediction of Sequence Cloning, Protein Production, Purification and Crystallization Propensity from Protein Sequences Using Multi-Step Heterogeneous Feature Fusion and Selection

    PubMed Central

    Wang, Huilin; Wang, Mingjun; Tan, Hao; Li, Yuan; Zhang, Ziding; Song, Jiangning

    2014-01-01

    X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed ‘PredPPCrys’ using the support vector machine (SVM). Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I). Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II), which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization targets of

  2. Normal Tissue Complication Probability Estimation by the Lyman-Kutcher-Burman Method Does Not Accurately Predict Spinal Cord Tolerance to Stereotactic Radiosurgery

    SciTech Connect

    Daly, Megan E.; Luxton, Gary; Choi, Clara Y.H.; Gibbs, Iris C.; Chang, Steven D.; Adler, John R.; Soltys, Scott G.

    2012-04-01

    Purpose: To determine whether normal tissue complication probability (NTCP) analyses of the human spinal cord by use of the Lyman-Kutcher-Burman (LKB) model, supplemented by linear-quadratic modeling to account for the effect of fractionation, predict the risk of myelopathy from stereotactic radiosurgery (SRS). Methods and Materials: From November 2001 to July 2008, 24 spinal hemangioblastomas in 17 patients were treated with SRS. Of the tumors, 17 received 1 fraction with a median dose of 20 Gy (range, 18-30 Gy) and 7 received 20 to 25 Gy in 2 or 3 sessions, with cord maximum doses of 22.7 Gy (range, 17.8-30.9 Gy) and 22.0 Gy (range, 20.2-26.6 Gy), respectively. By use of conventional values for {alpha}/{beta}, volume parameter n, 50% complication probability dose TD{sub 50}, and inverse slope parameter m, a computationally simplified implementation of the LKB model was used to calculate the biologically equivalent uniform dose and NTCP for each treatment. Exploratory calculations were performed with alternate values of {alpha}/{beta} and n. Results: In this study 1 case (4%) of myelopathy occurred. The LKB model using radiobiological parameters from Emami and the logistic model with parameters from Schultheiss overestimated complication rates, predicting 13 complications (54%) and 18 complications (75%), respectively. An increase in the volume parameter (n), to assume greater parallel organization, improved the predictive value of the models. Maximum-likelihood LKB fitting of {alpha}/{beta} and n yielded better predictions (0.7 complications), with n = 0.023 and {alpha}/{beta} = 17.8 Gy. Conclusions: The spinal cord tolerance to the dosimetry of SRS is higher than predicted by the LKB model using any set of accepted parameters. Only a high {alpha}/{beta} value in the LKB model and only a large volume effect in the logistic model with Schultheiss data could explain the low number of complications observed. This finding emphasizes that radiobiological models

  3. An experimental and theoretical study of the ice accretion process during artificial and natural icing conditions

    NASA Technical Reports Server (NTRS)

    Kirby, Mark S.; Hansman, R. John

    1988-01-01

    Real-time measurements of ice growth during artificial and natural icing conditions were conducted using an ultrasonic pulse-echo technique. This technique allows ice thickness to be measured with an accuracy of + or - 0.5 mm; in addition, the ultrasonic signal characteristics may be used to detect the presence of liquid on the ice surface and hence discern wet and dry ice growth behavior. Ice growth was measured on the stagnation line of a cylinder exposed to artificial icing conditions in the NASA Lewis Icing Research Tunnel (IRT), and similarly for a cylinder exposed in flight to natural icing conditions. Ice thickness was observed to increase approximately linearly with exposure time during the initial icing period. The ice accretion rate was found to vary with cloud temperature during wet ice growth, and liquid runback from the stagnation region was inferred. A steady-state energy balance model for the icing surface was used to compare heat transfer characteristics for IRT and natural icing conditions. Ultrasonic measurements of wet and dry ice growth observed in the IRT and in flight were compared with icing regimes predicted by a series of heat transfer coefficients. The heat transfer magnitude was generally inferred to be higher for the IRT than for the natural icing conditions encountered in flight. An apparent variation in the heat transfer magnitude was also observed for flights conducted through different natural icing-cloud formations.

  4. The CUPIC algorithm: an accurate model for the prediction of sustained viral response under telaprevir or boceprevir triple therapy in cirrhotic patients.

    PubMed

    Boursier, J; Ducancelle, A; Vergniol, J; Veillon, P; Moal, V; Dufour, C; Bronowicki, J-P; Larrey, D; Hézode, C; Zoulim, F; Fontaine, H; Canva, V; Poynard, T; Allam, S; De Lédinghen, V

    2015-12-01

    Triple therapy using boceprevir or telaprevir remains the reference treatment for genotype 1 chronic hepatitis C in countries where new interferon-free regimens have not yet become available. Antiviral treatment is highly required in cirrhotic patients, but they represent a difficult-to-treat population. We aimed to develop a simple algorithm for the prediction of sustained viral response (SVR) in cirrhotic patients treated with triple therapy. A total of 484 cirrhotic patients from the ANRS CO20 CUPIC cohort treated with triple therapy were randomly distributed into derivation and validation sets. A total of 52.1% of patients achieved SVR. In the derivation set, a D0 score for the prediction of SVR before treatment initiation included the following independent predictors collected at day 0: prior treatment response, gamma-GT, platelets, telaprevir treatment, viral load. To refine the prediction at the early phase of the treatment, a W4 score included as additional parameter the viral load collected at week 4. The D0 and W4 scores were combined in the CUPIC algorithm defining three subgroups: 'no treatment initiation or early stop at week 4', 'undetermined' and 'SVR highly probable'. In the validation set, the rates of SVR in these three subgroups were, respectively, 11.1%, 50.0% and 82.2% (P < 0.001). By replacing the variable 'prior treatment response' with 'IL28B genotype', another algorithm was derived for treatment-naïve patients with similar results. The CUPIC algorithm is an easy-to-use tool that helps physicians weigh their decision between immediately treating cirrhotic patients using boceprevir/telaprevir triple therapy or waiting for new drugs to become available in their country. PMID:26216230

  5. The role of sediment supply in esker formation and ice tunnel evolution

    NASA Astrophysics Data System (ADS)

    Burke, Matthew J.; Brennand, Tracy A.; Sjogren, Darren B.

    2015-05-01

    Meltwater is an important part of the glacier system as it can directly influence ice sheet dynamics. Although it is important that ice sheet models incorporate accurate information about subglacial meltwater processes, the relative inaccessibility of contemporary ice sheet beds makes direct investigation challenging. Former ice sheet beds contain a wealth of meltwater landforms such as eskers that, if accurately interpreted, can provide detailed insight into the hydrology of former ice sheets. Eskers are the casts of ice-walled channels and are a common landform within the footprint of the last Laurentide and Cordilleran Ice Sheets. In south-western Alberta, esker distribution suggests that both water and sediment supply may have been important controls; the longest esker ridge segments are located within meltwater valleys partially filled by glaciofluvial sediments, whereas the shortest esker ridge segments are located in areas dominated by clast-poor till. Through detailed esker ridge planform and crest-type mapping, and near surface geophysics we reveal morpho-sedimentary relationships that suggest esker sedimentation was dynamic, but that esker distribution and architecture were primarily governed by sediment supply. Through comparison of these data with data from eskers elsewhere, we suggest three formative scenarios: 1) where sediment supply and flow powers were high, coarse sediment loads result in rapid deposition, and rates of thermo-mechanical ice tunnel growth is exceeded by the rate of ice tunnel closure due to sediment infilling. High sedimentation rates reduce ice tunnel cross-sectional area, cause an increase in meltwater flow velocity and force ice tunnel growth. Thus, ice tunnel growth is fastest where sedimentation rate is highest; this positive feedback results in a non-uniform ice tunnel geometry, and favours macroform development and non-uniform ridge geometry. 2) Where sediment supply is limited, but flow power high, the rate of sedimentation

  6. Ab initio molecular dynamics of liquid water using embedded-fragment second-order many-body perturbation theory towards its accurate property prediction

    PubMed Central

    Willow, Soohaeng Yoo; Salim, Michael A.; Kim, Kwang S.; Hirata, So

    2015-01-01

    A direct, simultaneous calculation of properties of a liquid using an ab initio electron-correlated theory has long been unthinkable. Here we present structural, dynamical, and response properties of liquid water calculated by ab initio molecular dynamics using the embedded-fragment spin-component-scaled second-order many-body perturbation method with the aug-cc-pVDZ basis set. This level of theory is chosen as it accurately and inexpensively reproduces the water dimer potential energy surface from the coupled-cluster singles, doubles, and noniterative triples with the aug-cc-pVQZ basis set, which is nearly exact. The calculated radial distribution function, self-diffusion coefficient, coordinate number, and dipole moment, as well as the infrared and Raman spectra are in excellent agreement with experimental results. The shapes and widths of the OH stretching bands in the infrared and Raman spectra and their isotropic-anisotropic Raman noncoincidence, which reflect the diverse local hydrogen-bond environment, are also reproduced computationally. The simulation also reveals intriguing dynamic features of the environment, which are difficult to probe experimentally, such as a surprisingly large fluctuation in the coordination number and the detailed mechanism by which the hydrogen donating water molecules move across the first and second shells, thereby causing this fluctuation. PMID:26400690

  7. Ab initio molecular dynamics of liquid water using embedded-fragment second-order many-body perturbation theory towards its accurate property prediction.

    PubMed

    Willow, Soohaeng Yoo; Salim, Michael A; Kim, Kwang S; Hirata, So

    2015-01-01

    A direct, simultaneous calculation of properties of a liquid using an ab initio electron-correlated theory has long been unthinkable. Here we present structural, dynamical, and response properties of liquid water calculated by ab initio molecular dynamics using the embedded-fragment spin-component-scaled second-order many-body perturbation method with the aug-cc-pVDZ basis set. This level of theory is chosen as it accurately and inexpensively reproduces the water dimer potential energy surface from the coupled-cluster singles, doubles, and noniterative triples with the aug-cc-pVQZ basis set, which is nearly exact. The calculated radial distribution function, self-diffusion coefficient, coordinate number, and dipole moment, as well as the infrared and Raman spectra are in excellent agreement with experimental results. The shapes and widths of the OH stretching bands in the infrared and Raman spectra and their isotropic-anisotropic Raman noncoincidence, which reflect the diverse local hydrogen-bond environment, are also reproduced computationally. The simulation also reveals intriguing dynamic features of the environment, which are difficult to probe experimentally, such as a surprisingly large fluctuation in the coordination number and the detailed mechanism by which the hydrogen donating water molecules move across the first and second shells, thereby causing this fluctuation.

  8. Stable, high-order SBP-SAT finite difference operators to enable accurate simulation of compressible turbulent flows on curvilinear grids, with application to predicting turbulent jet noise

    NASA Astrophysics Data System (ADS)

    Byun, Jaeseung; Bodony, Daniel; Pantano, Carlos

    2014-11-01

    Improved order-of-accuracy discretizations often require careful consideration of their numerical stability. We report on new high-order finite difference schemes using Summation-By-Parts (SBP) operators along with the Simultaneous-Approximation-Terms (SAT) boundary condition treatment for first and second-order spatial derivatives with variable coefficients. In particular, we present a highly accurate operator for SBP-SAT-based approximations of second-order derivatives with variable coefficients for Dirichlet and Neumann boundary conditions. These terms are responsible for approximating the physical dissipation of kinetic and thermal energy in a simulation, and contain grid metrics when the grid is curvilinear. Analysis using the Laplace transform method shows that strong stability is ensured with Dirichlet boundary conditions while weaker stability is obtained for Neumann boundary conditions. Furthermore, the benefits of the scheme is shown in the direct numerical simulation (DNS) of a Mach 1.5 compressible turbulent supersonic jet using curvilinear grids and skew-symmetric discretization. Particularly, we show that the improved methods allow minimization of the numerical filter often employed in these simulations and we discuss the qualities of the simulation.

  9. Analysis of iced wings

    NASA Technical Reports Server (NTRS)

    Cebeci, T.; Chen, H. H.; Kaups, K.; Schimke, S.; Shin, J.

    1992-01-01

    A method for computing ice shapes along the leading edge of a wing and a method for predicting its aerodynamic performance degradation due to icing is described. Ice shapes are computed using an extension of the LEWICE code which was developed for airfoils. The aerodynamic properties of the iced wing are determined with an interactive scheme in which the solutions of the inviscid flow equations are obtained from a panel method and the solutions of the viscous flow equations are obtained from an inverse three-dimensional finite-difference boundary-layer method. A new interaction law is used to couple the inviscid and viscous flow solutions. The application of the LEWICE wing code to the calculation of ice shapes on a MS-317 swept wing shows good agreement with measurements. The interactive boundary-layer method is applied to a tapered ice wing in order to study the effect of icing on the aerodynamic properties of the wing at several angles of attack.

  10. Accurate prediction of diradical chemistry from a single-reference density-matrix method: Model application to the bicyclobutane to gauche-1,3-butadiene isomerization

    SciTech Connect

    Bertels, Luke W.; Mazziotti, David A.

    2014-07-28

    Multireference correlation in diradical molecules can be captured by a single-reference 2-electron reduced-density-matrix (2-RDM) calculation with only single and double excitations in the 2-RDM parametrization. The 2-RDM parametrization is determined by N-representability conditions that are non-perturbative in their treatment of the electron correlation. Conventional single-reference wave function methods cannot describe the entanglement within diradical molecules without employing triple- and potentially even higher-order excitations of the mean-field determinant. In the isomerization of bicyclobutane to gauche-1,3-butadiene the parametric 2-RDM (p2-RDM) method predicts that the diradical disrotatory transition state is 58.9 kcal/mol above bicyclobutane. This barrier is in agreement with previous multireference calculations as well as recent Monte Carlo and higher-order coupled cluster calculations. The p2-RDM method predicts the Nth natural-orbital occupation number of the transition state to be 0.635, revealing its diradical character. The optimized geometry from the p2-RDM method differs in important details from the complete-active-space self-consistent-field geometry used in many previous studies including the Monte Carlo calculation.

  11. Regional seasonal forecasts of the Arctic sea ice in two coupled climate models

    NASA Astrophysics Data System (ADS)

    Chevallier, Matthieu; Guémas, Virginie; Salas y Mélia, David; Doblas-Reyes, Francisco

    2015-04-01

    The predictive capabilities of two state-of-the-art coupled atmosphere-ocean global climate models (CNRM-CM5.1 and EC-Earth v2.3) in seasonal forecasting of the Arctic sea ice will be presented with a focus on regional skill. 5-month hindcasts of September sea ice area in the Arctic peripherial seas (Barents-Kara seas, Laptev-East Siberian seas, Chukchi sea and Beaufort sea) and March sea ice area in the marginal ice zones (Barents, Greenland, Labrador, Bering and Okhotsk sea) have been produced over the period 1990-2009. Systems mainly differ with respect to the initialization strategy, the ensemble generation techniques and the sea ice components. Predictive skill, assessed in terms of actual and potential predictability, is comparable in the two systems for both summer and winter hindcasts. Most interestingly, the multi-model prediction is often better than individual predictions in several sub-basins, including the Barents sea in the winter and most shelf seas in the summer. Systematic biases are also reduced using the multi-model predictions. Results from this study show that a regional zoom of global seasonal forecasts could be useful for operational needs. This study also show that the multi-model approach may be the step forward in producing accurate and reliable seasonal forecasts based on coupled global climate models.

  12. SNP development from RNA-seq data in a nonmodel fish: how many individuals are needed for accurate allele frequency prediction?

    PubMed

    Schunter, C; Garza, J C; Macpherson, E; Pascual, M

    2014-01-01

    Single nucleotide polymorphisms (SNPs) are rapidly becoming the marker of choice in population genetics due to a variety of advantages relative to other markers, including higher genomic density, data quality, reproducibility and genotyping efficiency, as well as ease of portability between laboratories. Advances in sequencing technology and methodologies to reduce genomic representation have made the isolation of SNPs feasible for nonmodel organisms. RNA-seq is one such technique for the discovery of SNPs and development of markers for large-scale genotyping. Here, we report the development of 192 validated SNP markers for parentage analysis in Tripterygion delaisi (the black-faced blenny), a small rocky-shore fish from the Mediterranean Sea. RNA-seq data for 15 individual samples were used for SNP discovery by applying a series of selection criteria. Genotypes were then collected from 1599 individuals from the same population with the resulting loci. Differences in heterozygosity and allele frequencies were found between the two data sets. Heterozygosity was lower, on average, in the population sample, and the mean difference between the frequencies of particular alleles in the two data sets was 0.135 ± 0.100. We used bootstrap resampling of the sequence data to predict appropriate sample sizes for SNP discovery. As cDNA library production is time-consuming and expensive, we suggest that using seven individuals for RNA sequencing reduces the probability of discarding highly informative SNP loci, due to lack of observed polymorphism, whereas use of more than 12 samples does not considerably improve prediction of true allele frequencies.

  13. Is scoring system of computed tomography based metric parameters can accurately predicts shock wave lithotripsy stone-free rates and aid in the development of treatment strategies?

    PubMed Central

    Badran, Yasser Ali; Abdelaziz, Alsayed Saad; Shehab, Mohamed Ahmed; Mohamed, Hazem Abdelsabour Dief; Emara, Absel-Aziz Ali; Elnabtity, Ali Mohamed Ali; Ghanem, Maged Mohammed; ELHelaly, Hesham Abdel Azim

    2016-01-01

    Objective: The objective was to determine the predicting success of shock wave lithotripsy (SWL) using a combination of computed tomography based metric parameters to improve the treatment plan. Patients and Methods: Consecutive 180 patients with symptomatic upper urinary tract calculi 20 mm or less were enrolled in our study underwent extracorporeal SWL were divided into two main groups, according to the stone size, Group A (92 patients with stone ≤10 mm) and Group B (88 patients with stone >10 mm). Both groups were evaluated, according to the skin to stone distance (SSD) and Hounsfield units (≤500, 500–1000 and >1000 HU). Results: Both groups were comparable in baseline data and stone characteristics. About 92.3% of Group A rendered stone-free, whereas 77.2% were stone-free in Group B (P = 0.001). Furthermore, in both group SWL success rates was a significantly higher for stones with lower attenuation <830 HU than with stones >830 HU (P < 0.034). SSD were statistically differences in SWL outcome (P < 0.02). Simultaneous consideration of three parameters stone size, stone attenuation value, and SSD; we found that stone-free rate (SFR) was 100% for stone attenuation value <830 HU for stone <10 mm or >10 mm but total number SWL sessions and shock waves required for the larger stone group were higher than in the smaller group (P < 0.01). Furthermore, SFR was 83.3% and 37.5% for stone <10 mm, mean HU >830, SSD 90 mm and SSD >120 mm, respectively. On the other hand, SFR was 52.6% and 28.57% for stone >10 mm, mean HU >830, SSD <90 mm and SSD >120 mm, respectively. Conclusion: Stone size, stone density (HU), and SSD is simple to calculate and can be reported by radiologists to applying combined score help to augment predictive power of SWL, reduce cost, and improving of treatment strategies. PMID:27141192

  14. Ice Fog and Light Snow Measurements Using a High-Resolution Camera System

    NASA Astrophysics Data System (ADS)

    Kuhn, Thomas; Gultepe, Ismail

    2016-07-01

    Ice fog, diamond dust, and light snow usually form over extremely cold weather conditions, and they affect both visibility and Earth's radiative energy budget. Prediction of these hydrometeors using models is difficult because of limited knowledge of the microphysical properties at the small size ranges due to measurement issues. These phenomena need to be better represented in forecast and climate models; therefore, in addition to remote sensing accurate measurements using ground-based instrumentation are required. An imaging instrument, aimed at measuring ice fog and light snow particles, has been built and is presented here. The ice crystal imaging (ICI) probe samples ice particles into a vertical, tapered inlet with an inlet flow rate of 11 L min-1. A laser beam across the vertical air flow containing the ice crystals allows for their detection by a photodetector collecting the scattered light. Detected particles are then imaged with high optical resolution. An illuminating LED flash and image capturing are triggered by the photodetector. In this work, ICI measurements collected during the fog remote sensing and modeling (FRAM) project, which took place during Winter of 2010-2011 in Yellowknife, NWT, Canada, are summarized and challenges related to measuring small ice particles are described. The majority of ice particles during the 2-month-long campaign had sizes between 300 and 800 μm. During ice fog events the size distribution measured had a lower mode diameter of 300 μm compared to the overall campaign average with mode at 500 μm.

  15. Slush Fund: Ice's Multiphase Evolution and Its Role in Shaping Europa

    NASA Astrophysics Data System (ADS)

    Buffo, Jacob; Schmidt, Britney E.

    2016-10-01

    The role of Europa's ice shell in mediating ocean-surface interaction, constraining potential habitability of the underlying hydrosphere, and dictating the surface morphology of the moon has been discussed in the literature for years, yet the dynamics and characteristics of the shell itself remain largely unconstrained. These discrepancies likely arise from underrepresented physics and varying a priori assumptions built into the current ice shell models. Presented here is a two-phase reactive porous media model of Europa's ice shell evolution, inspired by successful contemporary sea ice models, designed to capture the multiphase nature of forming ice as well as eliminate the need for a priori assumptions about ice shell structure and properties. The design of the model is such that it temporally and spatially constructs the ice shell from a first principles approach, allowing for accurate simulation of the shell's thermodynamic and compositional properties from the beginning of its formation up to its current state. This methodology provides explicit predictions of the ice's two-phase behavior, including heat and mass transfer, which ultimately dictate the shell's composition, density, and eutectic properties. All of which have been suggested as key factors in facilitating ocean-surface interaction, understanding the ocean's potential habitability, and shaping the moons surface. Preliminary results and their potential impact on how we understand Europa's evolution and dynamics will be discussed.

  16. Ice Fog and Light Snow Measurements Using a High-Resolution Camera System

    NASA Astrophysics Data System (ADS)

    Kuhn, Thomas; Gultepe, Ismail

    2016-09-01

    Ice fog, diamond dust, and light snow usually form over extremely cold weather conditions, and they affect both visibility and Earth's radiative energy budget. Prediction of these hydrometeors using models is difficult because of limited knowledge of the microphysical properties at the small size ranges due to measurement issues. These phenomena need to be better represented in forecast and climate models; therefore, in addition to remote sensing accurate measurements using ground-based instrumentation are required. An imaging instrument, aimed at measuring ice fog and light snow particles, has been built and is presented here. The ice crystal imaging (ICI) probe samples ice particles into a vertical, tapered inlet with an inlet flow rate of 11 L min-1. A laser beam across the vertical air flow containing the ice crystals allows for their detection by a photodetector collecting the scattered light. Detected particles are then imaged with high optical resolution. An illuminating LED flash and image capturing are triggered by the photodetector. In this work, ICI measurements collected during the fog remote sensing and modeling (FRAM) project, which took place during Winter of 2010-2011 in Yellowknife, NWT, Canada, are summarized and challenges related to measuring small ice particles are described. The majority of ice particles during the 2-month-long campaign had sizes between 300 and 800 μm. During ice fog events the size distribution measured had a lower mode diameter of 300 μm compared to the overall campaign average with mode at 500 μm.

  17. Arctic sea-ice diffusion from observed and simulated Lagrangian trajectories

    NASA Astrophysics Data System (ADS)

    Rampal, Pierre; Bouillon, Sylvain; Bergh, Jon; Ólason, Einar

    2016-07-01

    We characterize sea-ice drift by applying a Lagrangian diffusion analysis to buoy trajectories from the International Arctic Buoy Programme (IABP) dataset and from two different models: the standalone Lagrangian sea-ice model neXtSIM and the Eulerian coupled ice-ocean model used for the TOPAZ reanalysis. By applying the diffusion analysis to the IABP buoy trajectories over the period 1979-2011, we confirm that sea-ice diffusion follows two distinct regimes (ballistic and Brownian) and we provide accurate values for the diffusivity and integral timescale that could be used in Eulerian or Lagrangian passive tracers models to simulate the transport and diffusion of particles moving with the ice. We discuss how these values are linked to the evolution of the fluctuating displacements variance and how this information could be used to define the size of the search area around the position predicted by the mean drift. By comparing observed and simulated sea-ice trajectories for three consecutive winter seasons (2007-2011), we show how the characteristics of the simulated motion may differ from or agree well with observations. This comparison illustrates the usefulness of first applying a diffusion analysis to evaluate the output of modeling systems that include a sea-ice model before using these in, e.g., oil spill trajectory models or, more generally, to simulate the transport of passive tracers in sea ice.

  18. Additional Arctic observations improve weather and sea-ice forecasts for the Northern Sea Route

    NASA Astrophysics Data System (ADS)

    Inoue, Jun; Yamazaki, Akira; Ono, Jun; Dethloff, Klaus; Maturilli, Marion; Neuber, Roland; Edwards, Patti; Yamaguchi, Hajime

    2015-11-01

    During ice-free periods, the Northern Sea Route (NSR) could be an attractive shipping route. The decline in Arctic sea-ice extent, however, could be associated with an increase in the frequency of the causes of severe weather phenomena, and high wind-driven waves and the advection of sea ice could make ship navigation along the NSR difficult. Accurate forecasts of weather and sea ice are desirable for safe navigation, but large uncertainties exist in current forecasts, partly owing to the sparse observational network over the Arctic Ocean. Here, we show that the incorporation of additional Arctic observations improves the initial analysis and enhances the skill of weather and sea-ice forecasts, the application of which has socioeconomic benefits. Comparison of 63-member ensemble atmospheric forecasts, using different initial data sets, revealed that additional Arctic radiosonde observations were useful for predicting a persistent strong wind event. The sea-ice forecast, initialised by the wind fields that included the effects of the observations, skilfully predicted rapid wind-driven sea-ice advection along the NSR.

  19. Additional Arctic observations improve weather and sea-ice forecasts for the Northern Sea Route.

    PubMed

    Inoue, Jun; Yamazaki, Akira; Ono, Jun; Dethloff, Klaus; Maturilli, Marion; Neuber, Roland; Edwards, Patti; Yamaguchi, Hajime

    2015-01-01

    During ice-free periods, the Northern Sea Route (NSR) could be an attractive shipping route. The decline in Arctic sea-ice extent, however, could be associated with an increase in the frequency of the causes of severe weather phenomena, and high wind-driven waves and the advection of sea ice could make ship navigation along the NSR difficult. Accurate forecasts of weather and sea ice are desirable for safe navigation, but large uncertainties exist in current forecasts, partly owing to the sparse observational network over the Arctic Ocean. Here, we show that the incorporation of additional Arctic observations improves the initial analysis and enhances the skill of weather and sea-ice forecasts, the application of which has socioeconomic benefits. Comparison of 63-member ensemble atmospheric forecasts, using different initial data sets, revealed that additional Arctic radiosonde observations were useful for predicting a persistent strong wind event. The sea-ice forecast, initialised by the wind fields that included the effects of the observations, skilfully predicted rapid wind-driven sea-ice advection along the NSR. PMID:26585690

  20. Additional Arctic observations improve weather and sea-ice forecasts for the Northern Sea Route

    PubMed Central

    Inoue, Jun; Yamazaki, Akira; Ono, Jun; Dethloff, Klaus; Maturilli, Marion; Neuber, Roland; Edwards, Patti; Yamaguchi, Hajime

    2015-01-01

    During ice-free periods, the Northern Sea Route (NSR) could be an attractive shipping route. The decline in Arctic sea-ice extent, however, could be associated with an increase in the frequency of the causes of severe weather phenomena, and high wind-driven waves and the advection of sea ice could make ship navigation along the NSR difficult. Accurate forecasts of weather and sea ice are desirable for safe navigation, but large uncertainties exist in current forecasts, partly owing to the sparse observational network over the Arctic Ocean. Here, we show that the incorporation of additional Arctic observations improves the initial analysis and enhances the skill of weather and sea-ice forecasts, the application of which has socioeconomic benefits. Comparison of 63-member ensemble atmospheric forecasts, using different initial data sets, revealed that additional Arctic radiosonde observations were useful for predicting a persistent strong wind event. The sea-ice forecast, initialised by the wind fields that included the effects of the observations, skilfully predicted rapid wind-driven sea-ice advection along the NSR. PMID:26585690

  1. Comparison of LEWICE and GlennICE in the SLD Regime

    NASA Technical Reports Server (NTRS)

    Wright, William B.; Potapczuk, Mark G.; Levinson, Laurie H.

    2008-01-01

    A research project is underway at the NASA Glenn Research Center (GRC) to produce computer software that can accurately predict ice growth under any meteorological conditions for any aircraft surface. This report will present results from two different computer programs. The first program, LEWICE version 3.2.2, has been reported on previously. The second program is GlennICE version 0.1. An extensive comparison of the results in a quantifiable manner against the database of ice shapes that have been generated in the GRC Icing Research Tunnel (IRT) has also been performed, including additional data taken to extend the database in the Super-cooled Large Drop (SLD) regime. This paper will show the differences in ice shape between LEWICE 3.2.2, GlennICE, and experimental data. This report will also provide a description of both programs. Comparisons are then made to recent additions to the SLD database and selected previous cases. Quantitative comparisons are shown for horn height, horn angle, icing limit, area, and leading edge thickness. The results show that the predicted results for both programs are within the accuracy limits of the experimental data for the majority of cases.

  2. Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

    NASA Astrophysics Data System (ADS)

    Urrego-Blanco, Jorge R.; Urban, Nathan M.; Hunke, Elizabeth C.; Turner, Adrian K.; Jeffery, Nicole

    2016-04-01

    Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. It is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.

  3. Additional Arctic observations improve weather and sea-ice forecasts for the Northern Sea Route.

    PubMed

    Inoue, Jun; Yamazaki, Akira; Ono, Jun; Dethloff, Klaus; Maturilli, Marion; Neuber, Roland; Edwards, Patti; Yamaguchi, Hajime

    2015-01-01

    During ice-free periods, the Northern Sea Route (NSR) could be an attractive shipping route. The decline in Arctic sea-ice extent, however, could be associated with an increase in the frequency of the causes of severe weather phenomena, and high wind-driven waves and the advection of sea ice could make ship navigation along the NSR difficult. Accurate forecasts of weather and sea ice are desirable for safe navigation, but large uncertainties exist in current forecasts, partly owing to the sparse observational network over the Arctic Ocean. Here, we show that the incorporation of additional Arctic observations improves the initial analysis and enhances the skill of weather and sea-ice forecasts, the application of which has socioeconomic benefits. Comparison of 63-member ensemble atmospheric forecasts, using different initial data sets, revealed that additional Arctic radiosonde observations were useful for predicting a persistent strong wind event. The sea-ice forecast, initialised by the wind fields that included the effects of the observations, skilfully predicted rapid wind-driven sea-ice advection along the NSR.

  4. Influence of Aerosol Chemical Composition on Heterogeneous Ice Formation under Mid-Upper Troposphere Conditions

    NASA Astrophysics Data System (ADS)

    Kanji, Z. A.; Niemand, M.; Saathoff, H.; Möhler, O.; Chou, C.; Abbatt, J.; Stetzer, O.

    2011-12-01

    Aerosols are involved in cooling/warming the atmosphere directly via interaction with incoming solar radiation (aerosol direct effect), or via their ability to act as cloud condensation or ice nuclei (IN) and thus play a role in cloud formation (indirect effect). In particular, the physical properties of aerosols such as size and solubility and chemical composition can influence their behavior and fate in the atmosphere. Ice nucleation taking place via IN is termed as heterogeneous ice nucleation and can take place with via deposition (ice forming on IN directly from the vapor phase), condensation/immersion (freezing via formation of the liquid phase on IN) or condensation (IN colliding with supercooled liquid drops). This presentation shows how the chemical composition and surface area of various tropospherically relevant aerosols influence conditions of temperature (T) and relative humidity (RH) required for heterogeneous ice formation conditions in the mid-upper troposphere regime (253 - 220K)? Motivation for this comes first from, the importance of being able to predict ice formation accurately so as to understand the hydrological cycle since the ice is the primary initiator of precipitation forming clouds. Second, the tropospheric budget of water vapour, an especially active greenhouse gas is strongly influenced by ice nucleation and growth. Third, ice surfaces in the atmosphere act as heterogeneous surfaces for chemical reactions of trace gases (e.g., SO2, O3, NOx and therefore being able to accurately estimate ice formation rates and quantify ice surface concentrations will allow a more accurate calculation of trace gas budgets in the troposphere. Ice nucleation measurements were conducted using a self-developed continuous flow diffusion chamber and static chamber. A number of tropospherically relevant particulates with naturally-varying and laboratory-modified surface chemistry/structure were investigated for their ice formation efficiency based on highest

  5. Accurate prediction of hard-sphere virial coefficients B6 to B12 from a compressibility-based equation of state

    NASA Astrophysics Data System (ADS)

    Hansen-Goos, Hendrik

    2016-04-01

    We derive an analytical equation of state for the hard-sphere fluid that is within 0.01% of computer simulations for the whole range of the stable fluid phase. In contrast, the commonly used Carnahan-Starling equation of state deviates by up to 0.3% from simulations. The derivation uses the functional form of the isothermal compressibility from the Percus-Yevick closure of the Ornstein-Zernike relation as a starting point. Two additional degrees of freedom are introduced, which are constrained by requiring the equation of state to (i) recover the exact fourth virial coefficient B4 and (ii) involve only integer coefficients on the level of the ideal gas, while providing best possible agreement with the numerical result for B5. Virial coefficients B6 to B10 obtained from the equation of state are within 0.5% of numerical computations, and coefficients B11 and B12 are within the error of numerical results. We conjecture that even higher virial coefficients are reliably predicted.

  6. Accurate predictions of spectroscopic and molecular properties of 27 Λ-S and 73 Ω states of AsS radical.

    PubMed

    Shi, Deheng; Song, Ziyue; Niu, Xianghong; Sun, Jinfeng; Zhu, Zunlue

    2016-01-15

    The PECs are calculated for the 27 Λ-S states and their corresponding 73 Ω states of AsS radical. Of these Λ-S states, only the 2(2)Δ and 5(4)Π states are replulsive. The 1(2)Σ(+), 2(2)Σ(+), 4(2)Π, 3(4)Δ, 3(4)Σ(+), and 4(4)Π states possess double wells. The 3(2)Σ(+) state possesses three wells. The A(2)Π, 3(2)Π, 1(2)Φ, 2(4)Π, 3(4)Π, 2(4)Δ, 3(4)Δ, 1(6)Σ(+), and 1(6)Π states are inverted with the SO coupling effect included. The 1(4)Σ(+), 2(4)Σ(+), 2(4)Σ(-), 2(4)Δ, 1(4)Φ, 1(6)Σ(+), and 1(6)Π states, the second wells of 1(2)Σ(+), 3(4)Σ(+), 4(2)Π, 4(4)Π, and 3(4)Δ states, and the third well of 3(2)Σ(+) state are very weakly-bound states. The PECs are extrapolated to the CBS limit. The effect of SO coupling on the PECs is discussed. The spectroscopic parameters are evaluated, and compared with available measurements and other theoretical ones. The vibrational properties of several weakly-bound states are determined. The spectroscopic properties reported here can be expected to be reliably predicted ones.

  7. Accurate predictions of spectroscopic and molecular properties of 27 Λ-S and 73 Ω states of AsS radical

    NASA Astrophysics Data System (ADS)

    Shi, Deheng; Song, Ziyue; Niu, Xianghong; Sun, Jinfeng; Zhu, Zunlue

    2016-01-01

    The PECs are calculated for the 27 Λ-S states and their corresponding 73 Ω states of AsS radical. Of these Λ-S states, only the 22Δ and 54Π states are replulsive. The 12Σ+, 22Σ+, 42Π, 34Δ, 34Σ+, and 44Π states possess double wells. The 32Σ+ state possesses three wells. The A2Π, 32Π, 12Φ, 24Π, 34Π, 24Δ, 34Δ, 16Σ+, and 16Π states are inverted with the SO coupling effect included. The 14Σ+, 24Σ+, 24Σ-, 24Δ, 14Φ, 16Σ+, and 16Π states, the second wells of 12Σ+, 34Σ+, 42Π, 44Π, and 34Δ states, and the third well of 32Σ+ state are very weakly-bound states. The PECs are extrapolated to the CBS limit. The effect of SO coupling on the PECs is discussed. The spectroscopic parameters are evaluated, and compared with available measurements and other theoretical ones. The vibrational properties of several weakly-bound states are determined. The spectroscopic properties reported here can be expected to be reliably predicted ones.

  8. The Value of Accurate Magnetic Resonance Characterization of Posterior Cruciate Ligament Tears in the Setting of Multiligament Knee Injury: Imaging Features Predictive of Early Repair vs Reconstruction.

    PubMed

    Goiney, Christoper C; Porrino, Jack; Twaddle, Bruce; Richardson, Michael L; Mulcahy, Hyojeong; Chew, Felix S

    2016-01-01

    Multiligament knee injury (MLKI) represents a complex set of pathologies treated with a wide variety of surgical approaches. If early surgical intervention is performed, the disrupted posterior cruciate ligament (PCL) can be treated with primary repair or reconstruction. The purpose of our study was to retrospectively identify a critical length of the distal component of the torn PCL on magnetic resonance imaging (MRI) that may predict the ability to perform early proximal femoral repair of the ligament, as opposed to reconstruction. A total of 50 MLKIs were managed at Harborview Medical Center from May 1, 2013, through July 15, 2014, by an orthopedic surgeon. Following exclusions, there were 27 knees with complete disruption of the PCL that underwent either early reattachment to the femoral insertion or reconstruction and were evaluated using preoperative MRI. In a consensus fashion, 2 radiologists measured the proximal and distal fragments of each disrupted PCL using preoperative MRI in multiple planes, as needed. MRI findings were correlated with what was performed at surgery. Those knees with a distal fragment PCL length of ≥41mm were capable of, and underwent, early proximal femoral repair. With repair, the distal stump was attached to the distal femur. Alternatively, those with a distal PCL length of ≤32mm could not undergo repair because of insufficient length and as such, were reconstructed. If early surgical intervention for an MLKI involving disruption of the PCL is considered, attention should be given to the length of the distal PCL fragment on MRI to plan appropriately for proximal femoral reattachment vs reconstruction. If the distal PCL fragment measures ≥41mm, surgical repair is achievable and can be considered as a surgical option.

  9. Sea Ice

    NASA Technical Reports Server (NTRS)

    Perovich, D.; Gerland, S.; Hendricks, S.; Meier, Walter N.; Nicolaus, M.; Richter-Menge, J.; Tschudi, M.

    2013-01-01

    During 2013, Arctic sea ice extent remained well below normal, but the September 2013 minimum extent was substantially higher than the record-breaking minimum in 2012. Nonetheless, the minimum was still much lower than normal and the long-term trend Arctic September extent is -13.7 per decade relative to the 1981-2010 average. The less extreme conditions this year compared to 2012 were due to cooler temperatures and wind patterns that favored retention of ice through the summer. Sea ice thickness and volume remained near record-low levels, though indications are of slightly thicker ice compared to the record low of 2012.

  10. A direct evidence of vibrationally delocalized response at ice surface

    SciTech Connect

    Ishiyama, Tatsuya; Morita, Akihiro

    2014-11-14

    Surface-specific vibrational spectroscopic responses at isotope diluted ice and amorphous ice are investigated by molecular dynamics (MD) simulations combined with quantum mechanics/molecular mechanics calculations. The intense response specific to the ordinary crystal ice surface is predicted to be significantly suppressed in the isotopically diluted and amorphous ices, demonstrating the vibrational delocalization at the ordinary ice surface. The collective vibration at the ice surface is also analyzed with varying temperature by the MD simulation.

  11. Experimental methodologies to support aircraft icing analysis

    NASA Technical Reports Server (NTRS)

    Hansman, R. John, Jr.; Kirby, Mark S.

    1987-01-01

    The experimental methodologies are illustrated by graphs, charts and line drawings. Typical ultrasonic echo signals for dry and wet ice growth, ice accretion rates for various tunnel configurations, the experimental configuration for flight tests of the ultrasonic measuring system and heat balance models used to predict ice growth are among the topics that are illustrated and briefly discussed.

  12. Icing modelling in NSMB with chimera overset grids

    SciTech Connect

    Pena, D.; Deloze, T.; Laurendeau, E.; Hoarau, Y.

    2015-03-10

    In aerospace Engineering, the accurate simulation of ice accretion is a key element to increase flight safety and avoid accidents related to icing effects. The icing code developed in the NSMB solver is based on an Eulerian formulation for droplets tracking, an iterative Messinger model using a modified water runback scheme for ice thickness calculation and mesh deformation to track the ice/air interface through time. The whole process is parallelized with MPI and applied with chimera grids.

  13. Comprehensive mollusk acute toxicity database improves the use of Interspecies Correlation Estimation (ICE) models to predict toxicity of untested freshwater and endangered mussel species

    EPA Science Inventory

    Interspecies correlation estimation (ICE) models extrapolate acute toxicity data from surrogate test species to untested taxa. A suite of ICE models developed from a comprehensive database is available on the US Environmental Protection Agency’s web-based application, Web-I...

  14. Generalisation of Levine's prediction for the distribution of freezing temperatures of droplets: a general singular model for ice nucleation

    NASA Astrophysics Data System (ADS)

    Sear, R. P.

    2013-04-01

    Models without an explicit time dependence, called singular models, are widely used for fitting the distribution of temperatures at which water droplets freeze. In 1950 Levine developed the original singular model. His key assumption was that each droplet contained many nucleation sites, and that freezing occurred due to the nucleation site with the highest freezing temperature. The fact that freezing occurs due to the maximum value out of large number of nucleation temperatures, means that we can apply the results of what is called extreme-value statistics. This is the statistics of the extreme, i.e., maximum or minimum, value of a large number of random variables. Here we use the results of extreme-value statistics to show that we can generalise Levine's model to produce the most general singular model possible. We show that when a singular model is a good approximation, the distribution of freezing temperatures should always be given by what is called the generalised extreme-value distribution. In addition, we also show that the distribution of freezing temperatures for droplets of one size, can be used to make predictions for the scaling of the median nucleation temperature with droplet size, and vice versa.

  15. Generalisation of Levine's prediction for the distribution of freezing temperatures of droplets: a general singular model for ice nucleation

    NASA Astrophysics Data System (ADS)

    Sear, R. P.

    2013-07-01

    Models without an explicit time dependence, called singular models, are widely used for fitting the distribution of temperatures at which water droplets freeze. In 1950 Levine developed the original singular model. His key assumption was that each droplet contained many nucleation sites, and that freezing occurred due to the nucleation site with the highest freezing temperature. The fact that freezing occurs due to the maximum value out of a large number of nucleation temperatures, means that we can apply the results of what is called extreme-value statistics. This is the statistics of the extreme, i.e. maximum or minimum, value of a large number of random variables. Here we use the results of extreme-value statistics to show that we can generalise Levine's model to produce the most general singular model possible. We show that when a singular model is a good approximation, the distribution of freezing temperatures should always be given by what is called the generalised extreme-value distribution. In addition, we also show that the distribution of freezing temperatures for droplets of one size, can be used to make predictions for the scaling of the median nucleation temperature with droplet size, and vice versa.

  16. Accurate quantum chemical calculations

    NASA Technical Reports Server (NTRS)

    Bauschlicher, Charles W., Jr.; Langhoff, Stephen R.; Taylor, Peter R.

    1989-01-01

    An important goal of quantum chemical calculations is to provide an understanding of chemical bonding and molecular electronic structure. A second goal, the prediction of energy differences to chemical accuracy, has been much harder to attain. First, the computational resources required to achieve such accuracy are very large, and second, it is not straightforward to demonstrate that an apparently accurate result, in terms of agreement with experiment, does not result from a cancellation of errors. Recent advances in electronic structure methodology, coupled with the power of vector supercomputers, have made it possible to solve a number of electronic structure problems exactly using the full configuration interaction (FCI) method within a subspace of the complete Hilbert space. These exact results can be used to benchmark approximate techniques that are applicable to a wider range of chemical and physical problems. The methodology of many-electron quantum chemistry is reviewed. Methods are considered in detail for performing FCI calculations. The application of FCI methods to several three-electron problems in molecular physics are discussed. A number of benchmark applications of FCI wave functions are described. Atomic basis sets and the development of improved methods for handling very large basis sets are discussed: these are then applied to a number of chemical and spectroscopic problems; to transition metals; and to problems involving potential energy surfaces. Although the experiences described give considerable grounds for optimism about the general ability to perform accurate calculations, there are several problems that have proved less tractable, at least with current computer resources, and these and possible solutions are discussed.

  17. Revisiting the Potential of Melt Pond Fraction as a Predictor for the Seasonal Arctic Sea Ice Extent Minimum

    NASA Technical Reports Server (NTRS)

    Liu, Jiping; Song, Mirong; Horton, Radley M.; Hu, Yongyun

    2015-01-01

    The rapid change in Arctic sea ice in recent decades has led to a rising demand for seasonal sea ice prediction. A recent modeling study that employed a prognostic melt pond model in a stand-alone sea ice model found that September Arctic sea ice extent can be accurately predicted from the melt pond fraction in May. Here we show that satellite observations show no evidence of predictive skill in May. However, we find that a significantly strong relationship (high predictability) first emerges as the melt pond fraction is integrated from early May to late June, with a persistent strong relationship only occurring after late July. Our results highlight that late spring to mid summer melt pond information is required to improve the prediction skill of the seasonal sea ice minimum. Furthermore, satellite observations indicate a much higher percentage of melt pond formation in May than does the aforementioned model simulation, which points to the need to reconcile model simulations and observations, in order to better understand key mechanisms of melt pond formation and evolution and their influence on sea ice state.

  18. Mars Express MARSIS Radar: A Prediction of the Effect of Overlying Ice on Detecting Polar Basal Lakes and Inter-Glacial Aquifers

    NASA Technical Reports Server (NTRS)

    Farrell, W. M.; Plaut, J. J.; Gurnett, D. A.; Picardi, G.

    2004-01-01

    The penetration of the MARSIS radar signal into the polar ice mass is modeled to determine the capability of the instrument to locate sub-glacial aquifers. As a ground penetrating radar, the orbiting MARSIS transmits a signal greater than 1 W between 1-5 MHz. In this work we will investigate the effect of ice conductive losses on the radar-detection of subsurface aquifers. Based on wave propagation analysis, it is found that for a bulk ice conductivity below 10-5 S/m, conductive losses in the medium are not significant. However, if the bulk ice conductivity is relatively large (greater than 10-5 S/m), the reflected signal from any deep aquifer will be absorbed as it propagates in the lossy ice medium limiting the probing depth.

  19. Airborne Tomographic Swath Ice Sounding Processing System

    NASA Technical Reports Server (NTRS)

    Wu, Xiaoqing; Rodriquez, Ernesto; Freeman, Anthony; Jezek, Ken

    2013-01-01

    Glaciers and ice sheets modulate global sea level by storing water deposited as snow on the surface, and discharging water back into the ocean through melting. Their physical state can be characterized in terms of their mass balance and dynamics. To estimate the current ice mass balance, and to predict future changes in the motion of the Greenland and Antarctic ice sheets, it is necessary to know the ice sheet thickness and the physical conditions of the ice sheet surface and bed. This information is required at fine resolution and over extensive portions of the ice sheets. A tomographic algorithm has been developed to take raw data collected by a multiple-channel synthetic aperture sounding radar system over a polar ice sheet and convert those data into two-dimensional (2D) ice thickness measurements. Prior to this work, conventional processing techniques only provided one-dimensional ice thickness measurements along profiles.

  20. Two new ways of mapping sea ice thickness using ocean waves

    NASA Astrophysics Data System (ADS)

    Wadhams, P.

    2010-12-01

    TWO NEW METHODS OF MAPPING SEA ICE THICKNESS USING OCEAN WAVES. P. Wadhams (1,2), Martin Doble (1,2) and F. Parmiggiani (3) (1) Dept. of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge CB3 0WA, UK. (2) Laboratoire d’Océanographie de Villefranche, Université Pierre et Marie Curie, 06234 Villefranche-sur-Mer, France (2) ISAC-CNR, Bologna, Italy Two new methods of mapping ice thickness have been recently developed and tested, both making use of the dispersion relation of ocean waves in ice of radically different types. In frazil-pancake ice, a young ice type in which cakes less than 5 m across float in a suspension of individual ice crystals, the propagation of waves has been successfully modelled by treating the ice layer as a highly viscous fluid. The model predicts a shortening of wavelengths within the ice. Two-dimensional Fourier analysis of successive SAR subscenes to track the directional spectrum of a wave field as it enters an ice edge shows that waves do indeed shorten within the ice, and the change has been successfully used to predict the thickness of the frazil-pancake layer. Concurrent shipborne sampling in the Antarctic has shown that the method is accurate, and we now propose its use throughout the important frazil-pancake regimes in the world ocean (Antarctic circumpolar ice edge zone, Greenland Sea, Bering Sea and others). A radically different type of dispersion occurs when ocean waves enter the continuous icefields of the central Arctic, when they couple with the elastic ice cover to propagate as a flexural-gravity wave. A two-axis tiltmeter array has been used to measure the resulting change in the dispersion relation for long ocean swell (15-30 s) originating from storms in the Greenland Sea. The dispersion relation is slightly different from swell in the open ocean, so if two such arrays are placed a substantial distance (100s of km) apart and used to observe the changing wave period of arrivals from a given

  1. Wave effects on ocean-ice interaction in the marginal ice zone

    NASA Technical Reports Server (NTRS)

    Liu, Antony K.; Hakkinen, Sirpa; Peng, Chih Y.

    1993-01-01

    The effects of wave train on ice-ocean interaction in the marginal ice zone are studied through numerical modeling. A coupled two-dimensional ice-ocean model has been developed to include wave effects and wind stress for the predictions of ice edge dynamics. The sea ice model is coupled to the reduced-gravity ocean model through interfacial stresses. The main dynamic balance in the ice momentum is between water-ice stress, wind stress, and wave radiation stresses. By considering the exchange of momentum between waves and ice pack through radiation stress for decaying waves, a parametric study of the effects of wave stress and wind stress on ice edge dynamics has been performed. The numerical results show significant effects from wave action. The ice edge is sharper, and ice edge meanders form in the marginal ice zone owing to forcing by wave action and refraction of swell system after a couple of days. Upwelling at the ice edge and eddy formation can be enhanced by the nonlinear effects of wave action; wave action sharpens the ice edge and can produce ice meandering, which enhances local Ekman pumping and pycnocline anomalies. The resulting ice concentration, pycnocline changes, and flow velocity field are shown to be consistent with previous observations.

  2. Can Selforganizing Maps Accurately Predict Photometric Redshifts?

    NASA Technical Reports Server (NTRS)

    Way, Michael J.; Klose, Christian

    2012-01-01

    We present an unsupervised machine-learning approach that can be employed for estimating photometric redshifts. The proposed method is based on a vector quantization called the self-organizing-map (SOM) approach. A variety of photometrically derived input values were utilized from the Sloan Digital Sky Survey's main galaxy sample, luminous red galaxy, and quasar samples, along with the PHAT0 data set from the Photo-z Accuracy Testing project. Regression results obtained with this new approach were evaluated in terms of root-mean-square error (RMSE) to estimate the accuracy of the photometric redshift estimates. The results demonstrate competitive RMSE and outlier percentages when compared with several other popular approaches, such as artificial neural networks and Gaussian process regression. SOM RMSE results (using delta(z) = z(sub phot) - z(sub spec)) are 0.023 for the main galaxy sample, 0.027 for the luminous red galaxy sample, 0.418 for quasars, and 0.022 for PHAT0 synthetic data. The results demonstrate that there are nonunique solutions for estimating SOM RMSEs. Further research is needed in order to find more robust estimation techniques using SOMs, but the results herein are a positive indication of their capabilities when compared with other well-known methods

  3. Bacterial ice nucleation: significance and molecular basis.

    PubMed

    Gurian-Sherman, D; Lindow, S E

    1993-11-01

    Several bacterial species are able to catalyze ice formation at temperatures as warm as -2 degrees C. These microorganisms efficiently catalyze ice formation at temperatures much higher than most organic or inorganic substances. Because of their ubiquity on the surfaces of frost-sensitive plants, they are responsible for initiating ice formation, which results in frost injury. The high temperature of ice catalysis conferred by bacterial ice nuclei makes them useful in ice nucleation-limited processes such as artificial snow production, the freezing of some food products, and possibly in future whether modification schemes. The rarity of other ice nuclei active at high subfreezing temperature, and the ease and sensitivity with which ice nuclei can be quantified, have made the use of a promoterless bacterial ice nucleation gene valuable as a reporter of transcription. Target genes to which this promoter is fused can be used in cells in natural habitats. Warm-temperature ice nucleation sites have also been extensively studied at a molecular level. Nucleation sites active at high temperatures (above -5 degrees C) are probably composed of bacterial ice nucleation protein molecules that form functionally aligned aggregates. Models of ice nucleation proteins predict that they form a planar array of hydrogen binding groups that closely complement that of an ice crystal face. Moreover, interdigitation of these molecules may produce a large contiguous template for ice formation.

  4. Bacterial ice nucleation: significance and molecular basis.

    PubMed

    Gurian-Sherman, D; Lindow, S E

    1993-11-01

    Several bacterial species are able to catalyze ice formation at temperatures as warm as -2 degrees C. These microorganisms efficiently catalyze ice formation at temperatures much higher than most organic or inorganic substances. Because of their ubiquity on the surfaces of frost-sensitive plants, they are responsible for initiating ice formation, which results in frost injury. The high temperature of ice catalysis conferred by bacterial ice nuclei makes them useful in ice nucleation-limited processes such as artificial snow production, the freezing of some food products, and possibly in future whether modification schemes. The rarity of other ice nuclei active at high subfreezing temperature, and the ease and sensitivity with which ice nuclei can be quantified, have made the use of a promoterless bacterial ice nucleation gene valuable as a reporter of transcription. Target genes to which this promoter is fused can be used in cells in natural habitats. Warm-temperature ice nucleation sites have also been extensively studied at a molecular level. Nucleation sites active at high temperatures (above -5 degrees C) are probably composed of bacterial ice nucleation protein molecules that form functionally aligned aggregates. Models of ice nucleation proteins predict that they form a planar array of hydrogen binding groups that closely complement that of an ice crystal face. Moreover, interdigitation of these molecules may produce a large contiguous template for ice formation. PMID:8224607

  5. Statistical analysis of accurate prediction of local atmospheric optical attenuation with a new model according to weather together with beam wandering compensation system: a season-wise experimental investigation

    NASA Astrophysics Data System (ADS)

    Arockia Bazil Raj, A.; Padmavathi, S.

    2016-07-01

    Atmospheric parameters strongly affect the performance of Free Space Optical Communication (FSOC) system when the optical wave is propagating through the inhomogeneous turbulent medium. Developing a model to get an accurate prediction of optical attenuation according to meteorological parameters becomes significant to understand the behaviour of FSOC channel during different seasons. A dedicated free space optical link experimental set-up is developed for the range of 0.5 km at an altitude of 15.25 m. The diurnal profile of received power and corresponding meteorological parameters are continuously measured using the developed optoelectronic assembly and weather station, respectively, and stored in a data logging computer. Measured meteorological parameters (as input factors) and optical attenuation (as response factor) of size [177147 × 4] are used for linear regression analysis and to design the mathematical model that is more suitable to predict the atmospheric optical attenuation at our test field. A model that exhibits the R2 value of 98.76% and average percentage deviation of 1.59% is considered for practical implementation. The prediction accuracy of the proposed model is investigated along with the comparative results obtained from some of the existing models in terms of Root Mean Square Error (RMSE) during different local seasons in one-year period. The average RMSE value of 0.043-dB/km is obtained in the longer range dynamic of meteorological parameters variations.

  6. MIZEX East 1987: Winter Marginal Ice Zone Program in the Fram Strait and Greenland Sea

    NASA Astrophysics Data System (ADS)

    MIZEX'87 Group

    The overall objective o f MIZEX is to gain a better understanding of the mesoscale physical and biological processes by which atmosphere, ice, and ocean interact in the marginal ice zones (MIZ) that are found at the boundaries between ice-covered and open oceans. Improved modeling and better prediction of ice-edge position, ice concentration, and ice type in these regions would be a major step toward expanding human activities, for example, seaborne commerce, fishing, oil exploration and production, and naval operations. In addition, when more accurate parameterizations of mesoscale physical processes are available for inclusion in large-scale models, the result will be a major improvement in hemispherical climatological studies.Winter MIZEX '87 was conducted during March and April 1987 in the Fram Strait and Greenland Sea (see cover) and extended along the MIZ from about 75°N-79°N and 5°W-5°E. The experiment included an intensive 2-day investigation of the Barents Sea MIZ carried out between the southern tip of Svalbard and Bear Island. Two Norwegian ships, R/V Håakon Mosby and the ice-strengthened R/V Polar Circle, and the R/V Valdivia of the Federal Republic of Germany participated in the experiment. Flight operations were carried out by two Canadian aircraft equipped with Synthetic Aperature Radar (SAR), a U.S. plane equipped with passive microwave sensors, a Norwegian P3 aircraft, and a helicopter based on the Polar Circle.

  7. Ice fog and light snow measurements using a high resolution camera system

    NASA Astrophysics Data System (ADS)

    Kuhn, Thomas; Gultepe, Ismail

    2016-04-01

    In this presentation, measurements collected by the ice crystal imaging (ICI) probe employed during FRAM (Fog Remote Sensing and Modeling) project for the Winter of 2010-2011 in Yellowknife, NWT, Canada are analysed to study small ice crystal impact on aviation operations. Ice fog, diamond dust, and light snow form during cold weather conditions and they affect aviation operations through visibility and deposition over the surfaces. In addition, these events influence the local heat budget through radiative cooling. Prediction of these hydrometeors using models is difficult because of limited knowledge of the microphysical properties at the small size ranges. These phenomena need to be better represented in forecast and climate models and this can only be done using accurate measurements from ground-based instrumentation. Imaging of ice particles' properties can complement other in-situ measurements being collected routinely. The newly developed ICI probe, aimed at measuring ice fog and light snow particles, is presented here. The ICI probe samples ice particles through a vertical inlet, where a laser beam and photodetector detect ice crystals contained in the flow. The detected particles are then imaged with high optical resolution between 10 to 1000 micron size range. An illuminating LED flash and image capturing for measurements are triggered by the photodetector. The results suggested that the majority of ice particles during the two-month long campaign were small with sizes between 300 μm and 800 μm. During ice fog events, the size distribution measured had a lower mode diameter of 300 μm compared to the overall campaign average with mode at 500 μm. In this presentation, challenges and issues related to small ice crystals are described and their importance for aviation operations and climate change are discussed.

  8. Population structure of ice-breeding seals.

    PubMed

    Davis, Corey S; Stirling, Ian; Strobeck, Curtis; Coltman, David W

    2008-07-01

    The development of population genetic structure in ice-breeding seal species is likely to be shaped by a combination of breeding habitat and life-history characteristics. Species that return to breed on predictable fast-ice locations are more likely to exhibit natal fidelity than pack-ice-breeding species, which in turn facilitates the development of genetic differentiation between subpopulations. Other aspects of life history such as geographically distinct vocalizations, female gregariousness, and the potential for polygynous breeding may also facilitate population structure. Based on these factors, we predicted that fast-ice-breeding seal species (the Weddell and ringed seal) would show elevated genetic differentiation compared to pack-ice-breeding species (the leopard, Ross, crabeater and bearded seals). We tested this prediction using microsatellite analysis to examine population structure of these six ice-breeding species. Our results did not support this prediction. While none of the Antarctic pack-ice species showed statistically significant population structure, the bearded seal of the Arctic pack ice showed strong differentiation between subpopulations. Again in contrast, the fast-ice-breeding Weddell seal of the Antarctic showed clear evidence for genetic differentiation while the ringed seal, breeding in similar habitat in the Arctic, did not. These results suggest that the development of population structure in ice-breeding phocid seals is a more complex outcome of the interplay of phylogenetic and ecological factors than can be predicted on the basis of breeding substrate and life-history characteristics.

  9. Prediction of {sup 2}D Rydberg energy levels of {sup 6}Li and {sup 7}Li based on very accurate quantum mechanical calculations performed with explicitly correlated Gaussian functions

    SciTech Connect

    Bubin, Sergiy; Sharkey, Keeper L.; Adamowicz, Ludwik

    2013-04-28

    Very accurate variational nonrelativistic finite-nuclear-mass calculations employing all-electron explicitly correlated Gaussian basis functions are carried out for six Rydberg {sup 2}D states (1s{sup 2}nd, n= 6, Horizontal-Ellipsis , 11) of the {sup 7}Li and {sup 6}Li isotopes. The exponential parameters of the Gaussian functions are optimized using the variational method with the aid of the analytical energy gradient determined with respect to these parameters. The experimental results for the lower states (n= 3, Horizontal-Ellipsis , 6) and the calculated results for the higher states (n= 7, Horizontal-Ellipsis , 11) fitted with quantum-defect-like formulas are used to predict the energies of {sup 2}D 1s{sup 2}nd states for {sup 7}Li and {sup 6}Li with n up to 30.

  10. Determining the ice seasons severity during 1982-2015 using the ice extents sum as a new characteristic

    NASA Astrophysics Data System (ADS)

    Rjazin, Jevgeni; Pärn, Ove

    2016-04-01

    Sea ice is a key climate factor and it restricts considerably the winter navigation in sever seasons on the Baltic Sea. So determining ice conditions severity and describing ice cover behaviour at severe seasons interests scientists, engineers and navigation managers. The present study is carried out to determine the ice seasons severity degree basing on the ice seasons 1982 to 2015. A new integrative characteristic is introduced to describe the ice season severity. It is the sum of ice extents of the ice season id est the daily ice extents of the season are summed. The commonly used procedure to determine the ice season severity degree by the maximal ice extent is in this research compared to the new characteristic values. The remote sensing data on the ice concentrations on the Baltic Sea published in the European Copernicus Programme are used to obtain the severity characteristic values. The ice extents are calculated on these ice concentration data. Both the maximal ice extent of the season and a newly introduced characteristic - the ice extents sum are used to classify the winters with respect of severity. The most severe winter of the reviewed period is 1986/87. Also the ice seasons 1981/82, 1984/85, 1985/86, 1995/96 and 2002/03 are classified as severe. Only three seasons of this list are severe by both the criteria. They are 1984/85, 1985/86 and 1986/87. We interpret this coincidence as the evidence of enough-during extensive ice cover in these three seasons. In several winters, for example 2010/11 ice cover extended enough for some time, but did not endure. At few other ice seasons as 2002/03 the Baltic Sea was ice-covered in moderate extent, but the ice cover stayed long time. At 11 winters the ice extents sum differed considerably (> 10%) from the maximal ice extent. These winters yield one third of the studied ice seasons. The maximal ice extent of the season is simple to use and enables to reconstruct the ice cover history and to predict maximal ice

  11. What Determines the Ice Polymorph in Clouds?

    PubMed

    Hudait, Arpa; Molinero, Valeria

    2016-07-20

    Ice crystals in the atmosphere nucleate from supercooled liquid water and grow by vapor uptake. The structure of the ice polymorph grown has strong impact on the morphology and light scattering of the ice crystals, modulates the amount of water vapor in ice clouds, and can impact the molecular uptake and reactivity of atmospheric aerosols. Experiments and molecular simulations indicate that ice nucleated and grown from deeply supercooled liquid water is metastable stacking disordered ice. The ice polymorph grown from vapor has not yet been determined. Here we use large-scale molecular simulations to determine the structure of ice that grows as a result of uptake of water vapor in the temperature range relevant to cirrus and mixed-phase clouds, elucidate the molecular mechanism of the formation of ice at the vapor interface, and compute the free energy difference between cubic and hexagonal ice interfaces with vapor. We find that vapor deposition results in growth of stacking disordered ice only under conditions of extreme super