Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits

PubMed Central

Vesk, Peter A.

2017-01-01

Plant functional traits are increasingly used to generalize across species, however few examples exist of predictions from trait-based models being evaluated in new species or new places. Can we use functional traits to predict growth of unknown species in different areas? We used three independently collected datasets, each containing data on heights of individuals from non-resprouting species over a chronosquence of time-since-fire sites from three ecosystems in south-eastern Australia. We examined the influence of specific leaf area, woody density, seed size and leaf nitrogen content on three aspects of plant growth; maximum relative growth rate, age at maximum growth and asymptotic height. We tested our capacity to perform out-of-sample prediction of growth trajectories between ecosystems using species functional traits. We found strong trait-growth relationships in one of the datasets; whereby species with low SLA achieved the greatest asymptotic heights, species with high leaf-nitrogen content achieved relatively fast growth rates, and species with low seed mass reached their time of maximum growth early. However these same growth-trait relationships did not hold across the two other datasets, making accurate prediction from one dataset to another unachievable. We believe there is evidence to suggest that growth trajectories themselves may be fundamentally different between ecosystems and that trait-height-growth relationships may change over environmental gradients. PMID:28486535

Development and application of Geobacillus stearothermophilus growth model for predicting spoilage of evaporated milk.

PubMed

Kakagianni, Myrsini; Gougouli, Maria; Koutsoumanis, Konstantinos P

2016-08-01

The presence of Geobacillus stearothermophilus spores in evaporated milk constitutes an important quality problem for the milk industry. This study was undertaken to provide an approach in modelling the effect of temperature on G. stearothermophilus ATCC 7953 growth and in predicting spoilage of evaporated milk. The growth of G. stearothermophilus was monitored in tryptone soy broth at isothermal conditions (35-67 °C). The data derived were used to model the effect of temperature on G. stearothermophilus growth with a cardinal type model. The cardinal values of the model for the maximum specific growth rate were Tmin = 33.76 °C, Tmax = 68.14 °C, Topt = 61.82 °C and μopt = 2.068/h. The growth of G. stearothermophilus was assessed in evaporated milk at Topt in order to adjust the model to milk. The efficiency of the model in predicting G. stearothermophilus growth at non-isothermal conditions was evaluated by comparing predictions with observed growth under dynamic conditions and the results showed a good performance of the model. The model was further used to predict the time-to-spoilage (tts) of evaporated milk. The spoilage of this product caused by acid coagulation when the pH approached a level around 5.2, eight generations after G. stearothermophilus reached the maximum population density (Nmax). Based on the above, the tts was predicted from the growth model as the sum of the time required for the microorganism to multiply from the initial to the maximum level ( [Formula: see text] ), plus the time required after the [Formula: see text] to complete eight generations. The observed tts was very close to the predicted one indicating that the model is able to describe satisfactorily the growth of G. stearothermophilus and to provide realistic predictions for evaporated milk spoilage. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-timescale power and energy assessment of lithium-ion battery and supercapacitor hybrid system using extended Kalman filter

NASA Astrophysics Data System (ADS)

Wang, Yujie; Zhang, Xu; Liu, Chang; Pan, Rui; Chen, Zonghai

2018-06-01

The power capability and maximum charge and discharge energy are key indicators for energy management systems, which can help the energy storage devices work in a suitable area and prevent them from over-charging and over-discharging. In this work, a model based power and energy assessment approach is proposed for the lithium-ion battery and supercapacitor hybrid system. The model framework of the lithium-ion battery and supercapacitor hybrid system is developed based on the equivalent circuit model, and the model parameters are identified by regression method. Explicit analyses of the power capability and maximum charge and discharge energy prediction with multiple constraints are elaborated. Subsequently, the extended Kalman filter is employed for on-board power capability and maximum charge and discharge energy prediction to overcome estimation error caused by system disturbance and sensor noise. The charge and discharge power capability, and the maximum charge and discharge energy are quantitatively assessed under both the dynamic stress test and the urban dynamometer driving schedule. The maximum charge and discharge energy prediction of the lithium-ion battery and supercapacitor hybrid system with different time scales are explored and discussed.

On the Importance of Cycle Minimum in Sunspot Cycle Prediction

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.; Reichmann, Edwin J.

1996-01-01

The characteristics of the minima between sunspot cycles are found to provide important information for predicting the amplitude and timing of the following cycle. For example, the time of the occurrence of sunspot minimum sets the length of the previous cycle, which is correlated by the amplitude-period effect to the amplitude of the next cycle, with cycles of shorter (longer) than average length usually being followed by cycles of larger (smaller) than average size (true for 16 of 21 sunspot cycles). Likewise, the size of the minimum at cycle onset is correlated with the size of the cycle's maximum amplitude, with cycles of larger (smaller) than average size minima usually being associated with larger (smaller) than average size maxima (true for 16 of 22 sunspot cycles). Also, it was found that the size of the previous cycle's minimum and maximum relates to the size of the following cycle's minimum and maximum with an even-odd cycle number dependency. The latter effect suggests that cycle 23 will have a minimum and maximum amplitude probably larger than average in size (in particular, minimum smoothed sunspot number Rm = 12.3 +/- 7.5 and maximum smoothed sunspot number RM = 198.8 +/- 36.5, at the 95-percent level of confidence), further suggesting (by the Waldmeier effect) that it will have a faster than average rise to maximum (fast-rising cycles have ascent durations of about 41 +/- 7 months). Thus, if, as expected, onset for cycle 23 will be December 1996 +/- 3 months, based on smoothed sunspot number, then the length of cycle 22 will be about 123 +/- 3 months, inferring that it is a short-period cycle and that cycle 23 maximum amplitude probably will be larger than average in size (from the amplitude-period effect), having an RM of about 133 +/- 39 (based on the usual +/- 30 percent spread that has been seen between observed and predicted values), with maximum amplitude occurrence likely sometime between July 1999 and October 2000.

Water quality management using statistical analysis and time-series prediction model

NASA Astrophysics Data System (ADS)

Parmar, Kulwinder Singh; Bhardwaj, Rashmi

2014-12-01

This paper deals with water quality management using statistical analysis and time-series prediction model. The monthly variation of water quality standards has been used to compare statistical mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation at Yamuna River. Model validated using R-squared, root mean square error, mean absolute percentage error, maximum absolute percentage error, mean absolute error, maximum absolute error, normalized Bayesian information criterion, Ljung-Box analysis, predicted value and confidence limits. Using auto regressive integrated moving average model, future water quality parameters values have been estimated. It is observed that predictive model is useful at 95 % confidence limits and curve is platykurtic for potential of hydrogen (pH), free ammonia, total Kjeldahl nitrogen, dissolved oxygen, water temperature (WT); leptokurtic for chemical oxygen demand, biochemical oxygen demand. Also, it is observed that predicted series is close to the original series which provides a perfect fit. All parameters except pH and WT cross the prescribed limits of the World Health Organization /United States Environmental Protection Agency, and thus water is not fit for drinking, agriculture and industrial use.

Ultimate pier and contraction scour prediction in cohesive soils at selected bridges in Illinois.

DOT National Transportation Integrated Search

2013-09-01

The Scour Rate In COhesive Soils-Erosion Function Apparatus (SRICOS-EFA) method includes an ultimate scour prediction that is : the equilibrium maximum pier and contraction scour of cohesive soils over time. The purpose of this report is to present t...

Analyzing Flows In Rocket Nuclear Reactors

NASA Technical Reports Server (NTRS)

Clark, J. S.; Walton, J. T.; Mcguire, M.

1994-01-01

CAC is analytical prediction program to study heat-transfer and fluid-flow characteristics of circular coolant passage. Predicts, as function of time, axial and radial fluid conditions, temperatures of passage walls, rates of flow in each coolant passage, and approximate maximum material temperatures. Written in ANSI standard FORTRAN 77.

A fluctuating plume dispersion model for the prediction of odour-impact frequencies from continuous stationary sources

NASA Astrophysics Data System (ADS)

Mussio, P.; Gnyp, A. W.; Henshaw, P. F.

A fluctuating plume dispersion model has been developed to facilitate the prediction of odour-impact frequencies in the communities surrounding elevated point sources. The model was used to predict the frequencies of occurrence of odours of various magnitudes for 1 h periods. In addition, the model predicted the maximum odour level. The model was tested with an extensive set of data collected in the residential areas surrounding the paint shop of an automotive assembly plant. Most of the perceived odours in the vicinity of the 64, 46 m high stacks ranged between 2 and 7 odour units and generally persisted for less than 30 s. Ninety-eight different field determinations of odour impact frequencies within 1 km of the plant were conducted during the course of the study. To simplify evaluation, the frequencies of occurrence of different odour levels were summed to give the total frequency of occurrence of all readily detectable (>2 OU) odours. The model provided excellent simulation of the total frequencies of occurrence where the odour was frequent (i.e . readily detectable more than 30% of the time). At lower frequencies of occurrence the model prediction was poor. The stability class did not seem to affect the model's ability to predict field frequency values. However, the model provided excellent predictions of the maximum odour levels without being sensitive to either stability class or distance from the source. Ninety-five percent of the predicted maximum values were within a factor of two of the measured field maximum values.

Optical and magneto-optical properties of AuMnSn

NASA Astrophysics Data System (ADS)

Lee, S. J.; Janssen, Y.; Park, J. M.; Cho, B. K.

2006-03-01

We have measured room-temperature magneto-optical properties of AuMnSn on a single-crystalline sample. The maximum polar Kerr rotation was predicted to be very large, about -0.7° at 1.2eV [L. Offernes, P. Ravindran, and A. Kjekshus, Appl. Phys. Lett. 82, 2862 (2003)]. We found the experimental maximum Kerr rotation and ellipticity were about three times smaller than predicted and appeared at energies about 0.6eV higher than predicted, which is possibly due to inaccurate handling of the theory based on the local spin-density approximation to density-function theory for the localized 4d and 5d orbitals in AuMnSn.

Maximum swimming speeds of sailfish and three other large marine predatory fish species based on muscle contraction time and stride length: a myth revisited

PubMed Central

Svendsen, Morten B. S.; Domenici, Paolo; Marras, Stefano; Krause, Jens; Boswell, Kevin M.; Rodriguez-Pinto, Ivan; Wilson, Alexander D. M.; Kurvers, Ralf H. J. M.; Viblanc, Paul E.; Finger, Jean S.; Steffensen, John F.

2016-01-01

ABSTRACT Billfishes are considered to be among the fastest swimmers in the oceans. Previous studies have estimated maximum speed of sailfish and black marlin at around 35 m s−1 but theoretical work on cavitation predicts that such extreme speed is unlikely. Here we investigated maximum speed of sailfish, and three other large marine pelagic predatory fish species, by measuring the twitch contraction time of anaerobic swimming muscle. The highest estimated maximum swimming speeds were found in sailfish (8.3±1.4 m s−1), followed by barracuda (6.2±1.0 m s−1), little tunny (5.6±0.2 m s−1) and dorado (4.0±0.9 m s−1); although size-corrected performance was highest in little tunny and lowest in sailfish. Contrary to previously reported estimates, our results suggest that sailfish are incapable of exceeding swimming speeds of 10-15 m s−1, which corresponds to the speed at which cavitation is predicted to occur, with destructive consequences for fin tissues. PMID:27543056

Load reduction test method of similarity theory and BP neural networks of large cranes

NASA Astrophysics Data System (ADS)

Yang, Ruigang; Duan, Zhibin; Lu, Yi; Wang, Lei; Xu, Gening

2016-01-01

Static load tests are an important means of supervising and detecting a crane's lift capacity. Due to space restrictions, however, there are difficulties and potential danger when testing large bridge cranes. To solve the loading problems of large-tonnage cranes during testing, an equivalency test is proposed based on the similarity theory and BP neural networks. The maximum stress and displacement of a large bridge crane is tested in small loads, combined with the training neural network of a similar structure crane through stress and displacement data which is collected by a physics simulation progressively loaded to a static load test load within the material scope of work. The maximum stress and displacement of a crane under a static load test load can be predicted through the relationship of stress, displacement, and load. By measuring the stress and displacement of small tonnage weights, the stress and displacement of large loads can be predicted, such as the maximum load capacity, which is 1.25 times the rated capacity. Experimental study shows that the load reduction test method can reflect the lift capacity of large bridge cranes. The load shedding predictive analysis for Sanxia 1200 t bridge crane test data indicates that when the load is 1.25 times the rated lifting capacity, the predicted displacement and actual displacement error is zero. The method solves the problem that lifting capacities are difficult to obtain and testing accidents are easily possible when 1.25 times related weight loads are tested for large tonnage cranes.

Predicting one repetition maximum equations accuracy in paralympic rowers with motor disabilities.

PubMed

Schwingel, Paulo A; Porto, Yuri C; Dias, Marcelo C M; Moreira, Mônica M; Zoppi, Cláudio C

2009-05-01

Predicting one repetition maximum equations accuracy in paralympic rowers Resistance training intensity is prescribed using percentiles of the maximum strength, defined as the maximum tension generated for a muscle or muscular group. This value is found through the application of the one maximal repetition (1RM) test. One maximal repetition test demands time and still is not appropriate for some populations because of the risk it offers. In recent years, the prediction of maximal strength, through predicting equations, has been used to prevent the inconveniences of the 1RM test. The purpose of this study was to verify the accuracy of 12 1RM predicting equations for disabled rowers. Nine male paralympic rowers (7 one-leg amputated rowers and 2 cerebral paralyzed rowers; age, 30 +/- 7.9 years; height, 175.1 +/- 5.9 cm; weight, 69 +/- 13.6 kg) performed 1RM test for lying T-bar row and flat barbell bench press exercises to determine upper-body strength and leg press exercise to determine lower-body strength. One maximal repetition test was performed, and based on submaximal repetitions loads, several linear and exponential equations models were tested with regard of their accuracy. We did not find statistical differences for lying T-bar row and bench press exercises between measured and predicted 1RM values (p = 0.84 and 0.23 for lying T-bar row and flat barbell bench press, respectively); however, leg press exercise reached a high significant difference between measured and predicted values (p < 0.01). In conclusion, rowers with motor disabilities tolerate 1RM testing procedures, and predicting 1RM equations are accurate for bench press and lying T-bar row, but not for leg press, in this kind of athlete.

Direct Methods for Predicting Movement Biomechanics Based Upon Optimal Control Theory with Implementation in OpenSim.

PubMed

Porsa, Sina; Lin, Yi-Chung; Pandy, Marcus G

2016-08-01

The aim of this study was to compare the computational performances of two direct methods for solving large-scale, nonlinear, optimal control problems in human movement. Direct shooting and direct collocation were implemented on an 8-segment, 48-muscle model of the body (24 muscles on each side) to compute the optimal control solution for maximum-height jumping. Both algorithms were executed on a freely-available musculoskeletal modeling platform called OpenSim. Direct collocation converged to essentially the same optimal solution up to 249 times faster than direct shooting when the same initial guess was assumed (3.4 h of CPU time for direct collocation vs. 35.3 days for direct shooting). The model predictions were in good agreement with the time histories of joint angles, ground reaction forces and muscle activation patterns measured for subjects jumping to their maximum achievable heights. Both methods converged to essentially the same solution when started from the same initial guess, but computation time was sensitive to the initial guess assumed. Direct collocation demonstrates exceptional computational performance and is well suited to performing predictive simulations of movement using large-scale musculoskeletal models.

Sunspot variation and selected associated phenomena: A look at solar cycle 21 and beyond

NASA Technical Reports Server (NTRS)

Wilson, R. M.

1982-01-01

Solar sunspot cycles 8 through 21 are reviewed. Mean time intervals are calculated for maximum to maximum, minimum to minimum, minimum to maximum, and maximum to minimum phases for cycles 8 through 20 and 8 through 21. Simple cosine functions with a period of 132 years are compared to, and found to be representative of, the variation of smoothed sunspot numbers at solar maximum and minimum. A comparison of cycles 20 and 21 is given, leading to a projection for activity levels during the Spacelab 2 era (tentatively, November 1984). A prediction is made for cycle 22. Major flares are observed to peak several months subsequent to the solar maximum during cycle 21 and to be at minimum level several months after the solar minimum. Additional remarks are given for flares, gradual rise and fall radio events and 2800 MHz radio emission. Certain solar activity parameters, especially as they relate to the near term Spacelab 2 time frame are estimated.

Service-Oriented Architecture (SOA) Instantiation within a Hard Real-Time, Deterministic Combat System Environment

ERIC Educational Resources Information Center

Moreland, James D., Jr

2013-01-01

This research investigates the instantiation of a Service-Oriented Architecture (SOA) within a hard real-time (stringent time constraints), deterministic (maximum predictability) combat system (CS) environment. There are numerous stakeholders across the U.S. Department of the Navy who are affected by this development, and therefore the system…

Prediction of Normal Organ Absorbed Doses for [177Lu]Lu-PSMA-617 Using [44Sc]Sc-PSMA-617 Pharmacokinetics in Patients With Metastatic Castration Resistant Prostate Carcinoma.

PubMed

Khawar, Ambreen; Eppard, Elisabeth; Sinnes, Jean Phlippe; Roesch, Frank; Ahmadzadehfar, Hojjat; Kürpig, Stefan; Meisenheimer, Michael; Gaertner, Florian C; Essler, Markus; Bundschuh, Ralph A

2018-04-23

In vivo pharmacokinetic analysis of [Sc]Sc-PSMA-617 was used to determine the normal organ-absorbed doses that may result from therapeutic activity of [Lu]Lu-PSMA-617 and to predict the maximum permissible activity of [Lu]Lu-PSMA-617 for patients with metastatic castration-resistant prostate carcinoma. Pharmacokinetics of [Sc]Sc-PSMA-617 was evaluated in 5 patients with metastatic castration-resistant prostate carcinoma using dynamic PET/CT, followed by 3 static PET/CT acquisitions and blood sample collection over 19.5 hours, as well as urine sample collection at 2 time points. Total activity measured in source organs by PET imaging, as well as counts per milliliter measured in blood and urine samples, was decay corrected back to the time of injection using the half-life of Sc. Afterward, forward decay correction using the half-life of Lu was performed, extrapolating the pharmacokinetics of [Sc]Sc-PSMA-617 to that of [Lu]Lu-PSMA-617. Source organs residence times and organ-absorbed doses for [Lu]Lu-PSMA-617 were calculated using OLINDA/EXM software. Bone marrow self-dose was determined with indirect blood-based method, and urinary bladder contents residence time was estimated by trapezoidal approximation. The maximum permissible activity of [Lu]Lu-PSMA-617 was calculated for each patient considering external beam radiotherapy toxicity limits for radiation absorbed doses to kidneys, bone marrow, salivary glands, and whole body. The predicted mean organ-absorbed doses were highest in the kidneys (0.44 mSv/MBq), followed by the salivary glands (0.23 mSv/MBq). The maximum permissible activity was highly variable among patients; limited by whole body-absorbed dose (1 patient), marrow-absorbed dose (1 patient), and kidney-absorbed dose (3 patients). [Sc]Sc-PSMA-617 PET/CT imaging is feasible and allows theoretical extrapolation of the pharmacokinetics of [Sc]Sc-PSMA-617 to that of [Lu]Lu-PSMA-617, with the intent of predicting normal organ-absorbed doses and maximum permissible activity in patients scheduled for therapy with [Lu]Lu-PSMA-617.

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

Blijderveen, Maarten van; University of Twente, Department of Thermal Engineering, Drienerlolaan 5, 7522 NB Enschede; Bramer, Eddy A.

Highlights: Black-Right-Pointing-Pointer We model piloted ignition times of wood and plastics. Black-Right-Pointing-Pointer The model is applied on a packed bed. Black-Right-Pointing-Pointer When the air flow is above a critical level, no ignition can take place. - Abstract: To gain insight in the startup of an incinerator, this article deals with piloted ignition. A newly developed model is described to predict the piloted ignition times of wood, PMMA and PVC. The model is based on the lower flammability limit and the adiabatic flame temperature at this limit. The incoming radiative heat flux, sample thickness and moisture content are some of themore » used variables. Not only the ignition time can be calculated with the model, but also the mass flux and surface temperature at ignition. The ignition times for softwoods and PMMA are mainly under-predicted. For hardwoods and PVC the predicted ignition times agree well with experimental results. Due to a significant scatter in the experimental data the mass flux and surface temperature calculated with the model are hard to validate. The model is applied on the startup of a municipal waste incineration plant. For this process a maximum allowable primary air flow is derived. When the primary air flow is above this maximum air flow, no ignition can be obtained.« less

Comparison of Observed and Predicted Abutment Scour at Selected Bridges in Maine

USGS Publications Warehouse

Lombard, Pamela J.; Hodgkins, Glenn A.

2008-01-01

Maximum abutment-scour depths predicted with five different methods were compared to maximum abutment-scour depths observed at 100 abutments at 50 bridge sites in Maine with a median bridge age of 66 years. Prediction methods included the Froehlich/Hire method, the Sturm method, and the Maryland method published in Federal Highway Administration Hydraulic Engineering Circular 18 (HEC-18); the Melville method; and envelope curves. No correlation was found between scour calculated using any of the prediction methods and observed scour. Abutment scour observed in the field ranged from 0 to 6.8 feet, with an average observed scour of less than 1.0 foot. Fifteen of the 50 bridge sites had no observable scour. Equations frequently overpredicted scour by an order of magnitude and in some cases by two orders of magnitude. The equations also underpredicted scour 4 to 14 percent of the time.

Factors affecting the estimate of primary production from space

NASA Technical Reports Server (NTRS)

Balch, W. M.; Byrne, C. F.

1994-01-01

Remote sensing of primary production in the euphotic zone has been based mostly on visible-band and water-leaving radiance measured with the coastal zone color scanner. There are some robust, simple relationships for calculating integral production based on surface measurements, but they also require knowledge for photoadaptive parameters such as maximum photosynthesis which currently cannot be obtained from spave. A 17,000-station data set is used to show that space-based estimates of maximum photosynthesis could improve predictions of psi, the water column light utiliztion index, which is an important term in many primary productivity models. Temperature is also examined as a factor for predicting hydrographic structure and primary production. A simple model is used to relate temperature and maximum photosynthesis; the model incorporates (1) the positive relationship between maximum photosynthesis and temperature and (2) the strongly negative relationship between temperature and nitrate in the ocean (which directly affects maximum growth rates via nitrogen limitation). Since these two factors relate to carbon and nitrogen, 'balanced carbon/nitrogen assimilation' was calculated using the Redfield ratio, It is expected that the relationship between maximum balanced carbon assimilation versus temperature is concave-down, with the peak dependent on nitrate uptake kinetics, temperature-nitrate relationships,a nd the carbon chlorophyll ration. These predictions were compared with the sea truth data. The minimum turnover time for nitrate was also calculated using this approach. Lastly, sea surface temperature gradients were used to predict the slope of isotherms (a proxy for the slope of isopycnals in many waters). Sea truth data show that at size scales of several hundred kilometers, surface temperature gradients can provide information on the slope of isotherms in the top 200 m of the water column. This is directly relevant to the supply of nutrients into the surface mixed layer, which is useful for predicting integral biomass and primary production.

Predicting critical transitions in dynamical systems from time series using nonstationary probability density modeling.

PubMed

Kwasniok, Frank

2013-11-01

A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.

Universal inverse power-law distribution for temperature and rainfall in the UK region

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2014-06-01

Meteorological parameters, such as temperature, rainfall, pressure, etc., exhibit selfsimilar space-time fractal fluctuations generic to dynamical systems in nature such as fluid flows, spread of forest fires, earthquakes, etc. The power spectra of fractal fluctuations display inverse power-law form signifying long-range correlations. A general systems theory model predicts universal inverse power-law form incorporating the golden mean for the fractal fluctuations. The model predicted distribution was compared with observed distribution of fractal fluctuations of all size scales (small, large and extreme values) in the historic month-wise temperature (maximum and minimum) and total rainfall for the four stations Oxford, Armagh, Durham and Stornoway in the UK region, for data periods ranging from 92 years to 160 years. For each parameter, the two cumulative probability distributions, namely cmax and cmin starting from respectively maximum and minimum data value were used. The results of the study show that (i) temperature distributions (maximum and minimum) follow model predicted distribution except for Stornowy, minimum temperature cmin. (ii) Rainfall distribution for cmin follow model predicted distribution for all the four stations. (iii) Rainfall distribution for cmax follows model predicted distribution for the two stations Armagh and Stornoway. The present study suggests that fractal fluctuations result from the superimposition of eddy continuum fluctuations.

Soil and Water Assessment Tool model predictions of annual maximum pesticide concentrations in high vulnerability watersheds.

PubMed

Winchell, Michael F; Peranginangin, Natalia; Srinivasan, Raghavan; Chen, Wenlin

2018-05-01

Recent national regulatory assessments of potential pesticide exposure of threatened and endangered species in aquatic habitats have led to increased need for watershed-scale predictions of pesticide concentrations in flowing water bodies. This study was conducted to assess the ability of the uncalibrated Soil and Water Assessment Tool (SWAT) to predict annual maximum pesticide concentrations in the flowing water bodies of highly vulnerable small- to medium-sized watersheds. The SWAT was applied to 27 watersheds, largely within the midwest corn belt of the United States, ranging from 20 to 386 km 2 , and evaluated using consistent input data sets and an uncalibrated parameterization approach. The watersheds were selected from the Atrazine Ecological Exposure Monitoring Program and the Heidelberg Tributary Loading Program, both of which contain high temporal resolution atrazine sampling data from watersheds with exceptionally high vulnerability to atrazine exposure. The model performance was assessed based upon predictions of annual maximum atrazine concentrations in 1-d and 60-d durations, predictions critical in pesticide-threatened and endangered species risk assessments when evaluating potential acute and chronic exposure to aquatic organisms. The simulation results showed that for nearly half of the watersheds simulated, the uncalibrated SWAT model was able to predict annual maximum pesticide concentrations within a narrow range of uncertainty resulting from atrazine application timing patterns. An uncalibrated model's predictive performance is essential for the assessment of pesticide exposure in flowing water bodies, the majority of which have insufficient monitoring data for direct calibration, even in data-rich countries. In situations in which SWAT over- or underpredicted the annual maximum concentrations, the magnitude of the over- or underprediction was commonly less than a factor of 2, indicating that the model and uncalibrated parameterization approach provide a capable method for predicting the aquatic exposure required to support pesticide regulatory decision making. Integr Environ Assess Manag 2018;14:358-368. © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Validation of Model-Based Prognostics for Pneumatic Valves in a Demonstration Testbed

DTIC Science & Technology

2014-10-02

predict end of life ( EOL ) and remaining useful life (RUL). The approach still follows the general estimation-prediction framework devel- oped in the...atmosphere, with linearly increasing leak area. kA2leak = Cleak (16) We define valve end of life ( EOL ) through open/close time limits of the valves, as in...represents end of life ( EOL ), and ∆kE represents remaining useful life (RUL). For valves, timing requirements are provided that de- fine the maximum

Prediction Analysis for Measles Epidemics

NASA Astrophysics Data System (ADS)

Sumi, Ayako; Ohtomo, Norio; Tanaka, Yukio; Sawamura, Sadashi; Olsen, Lars Folke; Kobayashi, Nobumichi

2003-12-01

A newly devised procedure of prediction analysis, which is a linearized version of the nonlinear least squares method combined with the maximum entropy spectral analysis method, was proposed. This method was applied to time series data of measles case notification in several communities in the UK, USA and Denmark. The dominant spectral lines observed in each power spectral density (PSD) can be safely assigned as fundamental periods. The optimum least squares fitting (LSF) curve calculated using these fundamental periods can essentially reproduce the underlying variation of the measles data. An extension of the LSF curve can be used to predict measles case notification quantitatively. Some discussions including a predictability of chaotic time series are presented.

Predicting the magnetic vectors within coronal mass ejections arriving at Earth: 2. Geomagnetic response

NASA Astrophysics Data System (ADS)

Savani, N. P.; Vourlidas, A.; Richardson, I. G.; Szabo, A.; Thompson, B. J.; Pulkkinen, A.; Mays, M. L.; Nieves-Chinchilla, T.; Bothmer, V.

2017-02-01

This is a companion to Savani et al. (2015) that discussed how a first-order prediction of the internal magnetic field of a coronal mass ejection (CME) may be made from observations of its initial state at the Sun for space weather forecasting purposes (Bothmer-Schwenn scheme (BSS) model). For eight CME events, we investigate how uncertainties in their predicted magnetic structure influence predictions of the geomagnetic activity. We use an empirical relationship between the solar wind plasma drivers and Kp index together with the inferred magnetic vectors, to make a prediction of the time variation of Kp (Kp(BSS)). We find a 2σ uncertainty range on the magnetic field magnitude (|B|) provides a practical and convenient solution for predicting the uncertainty in geomagnetic storm strength. We also find the estimated CME velocity is a major source of error in the predicted maximum Kp. The time variation of Kp(BSS) is important for predicting periods of enhanced and maximum geomagnetic activity, driven by southerly directed magnetic fields, and periods of lower activity driven by northerly directed magnetic field. We compare the skill score of our model to a number of other forecasting models, including the NOAA/Space Weather Prediction Center (SWPC) and Community Coordinated Modeling Center (CCMC)/SWRC estimates. The BSS model was the most unbiased prediction model, while the other models predominately tended to significantly overforecast. The True skill score of the BSS prediction model (TSS = 0.43 ± 0.06) exceeds the results of two baseline models and the NOAA/SWPC forecast. The BSS model prediction performed equally with CCMC/SWRC predictions while demonstrating a lower uncertainty.

Model evaluation of plant metal content and biomass yield for the phytoextraction of heavy metals by switchgrass.

PubMed

Chen, Bo-Ching; Lai, Hung-Yu; Juang, Kai-Wei

2012-06-01

To better understand the ability of switchgrass (Panicum virgatum L.), a perennial grass often relegated to marginal agricultural areas with minimal inputs, to remove cadmium, chromium, and zinc by phytoextraction from contaminated sites, the relationship between plant metal content and biomass yield is expressed in different models to predict the amount of metals switchgrass can extract. These models are reliable in assessing the use of switchgrass for phytoremediation of heavy-metal-contaminated sites. In the present study, linear and exponential decay models are more suitable for presenting the relationship between plant cadmium and dry weight. The maximum extractions of cadmium using switchgrass, as predicted by the linear and exponential decay models, approached 40 and 34 μg pot(-1), respectively. The log normal model was superior in predicting the relationship between plant chromium and dry weight. The predicted maximum extraction of chromium by switchgrass was about 56 μg pot(-1). In addition, the exponential decay and log normal models were better than the linear model in predicting the relationship between plant zinc and dry weight. The maximum extractions of zinc by switchgrass, as predicted by the exponential decay and log normal models, were about 358 and 254 μg pot(-1), respectively. To meet the maximum removal of Cd, Cr, and Zn, one can adopt the optimal timing of harvest as plant Cd, Cr, and Zn approach 450 and 526 mg kg(-1), 266 mg kg(-1), and 3022 and 5000 mg kg(-1), respectively. Due to the well-known agronomic characteristics of cultivation and the high biomass production of switchgrass, it is practicable to use switchgrass for the phytoextraction of heavy metals in situ. Copyright © 2012 Elsevier Inc. All rights reserved.

Predicting the Maximum Earthquake Magnitude from Seismic Data in Israel and Its Neighboring Countries.

PubMed

Last, Mark; Rabinowitz, Nitzan; Leonard, Gideon

2016-01-01

This paper explores several data mining and time series analysis methods for predicting the magnitude of the largest seismic event in the next year based on the previously recorded seismic events in the same region. The methods are evaluated on a catalog of 9,042 earthquake events, which took place between 01/01/1983 and 31/12/2010 in the area of Israel and its neighboring countries. The data was obtained from the Geophysical Institute of Israel. Each earthquake record in the catalog is associated with one of 33 seismic regions. The data was cleaned by removing foreshocks and aftershocks. In our study, we have focused on ten most active regions, which account for more than 80% of the total number of earthquakes in the area. The goal is to predict whether the maximum earthquake magnitude in the following year will exceed the median of maximum yearly magnitudes in the same region. Since the analyzed catalog includes only 28 years of complete data, the last five annual records of each region (referring to the years 2006-2010) are kept for testing while using the previous annual records for training. The predictive features are based on the Gutenberg-Richter Ratio as well as on some new seismic indicators based on the moving averages of the number of earthquakes in each area. The new predictive features prove to be much more useful than the indicators traditionally used in the earthquake prediction literature. The most accurate result (AUC = 0.698) is reached by the Multi-Objective Info-Fuzzy Network (M-IFN) algorithm, which takes into account the association between two target variables: the number of earthquakes and the maximum earthquake magnitude during the same year.

Predicting the Maximum Earthquake Magnitude from Seismic Data in Israel and Its Neighboring Countries

PubMed Central

2016-01-01

This paper explores several data mining and time series analysis methods for predicting the magnitude of the largest seismic event in the next year based on the previously recorded seismic events in the same region. The methods are evaluated on a catalog of 9,042 earthquake events, which took place between 01/01/1983 and 31/12/2010 in the area of Israel and its neighboring countries. The data was obtained from the Geophysical Institute of Israel. Each earthquake record in the catalog is associated with one of 33 seismic regions. The data was cleaned by removing foreshocks and aftershocks. In our study, we have focused on ten most active regions, which account for more than 80% of the total number of earthquakes in the area. The goal is to predict whether the maximum earthquake magnitude in the following year will exceed the median of maximum yearly magnitudes in the same region. Since the analyzed catalog includes only 28 years of complete data, the last five annual records of each region (referring to the years 2006–2010) are kept for testing while using the previous annual records for training. The predictive features are based on the Gutenberg-Richter Ratio as well as on some new seismic indicators based on the moving averages of the number of earthquakes in each area. The new predictive features prove to be much more useful than the indicators traditionally used in the earthquake prediction literature. The most accurate result (AUC = 0.698) is reached by the Multi-Objective Info-Fuzzy Network (M-IFN) algorithm, which takes into account the association between two target variables: the number of earthquakes and the maximum earthquake magnitude during the same year. PMID:26812351

A Probabilistic Strategy for Understanding Action Selection

PubMed Central

Kim, Byounghoon; Basso, Michele A.

2010-01-01

Brain regions involved in transforming sensory signals into movement commands are the likely sites where decisions are formed. Once formed, a decision must be read-out from the activity of populations of neurons to produce a choice of action. How this occurs remains unresolved. We recorded from four superior colliculus (SC) neurons simultaneously while monkeys performed a target selection task. We implemented three models to gain insight into the computational principles underlying population coding of action selection. We compared the population vector average (PVA), winner-takes-all (WTA) and a Bayesian model, maximum a posteriori estimate (MAP) to determine which predicted choices most often. The probabilistic model predicted more trials correctly than both the WTA and the PVA. The MAP model predicted 81.88% whereas WTA predicted 71.11% and PVA/OLE predicted the least number of trials at 55.71 and 69.47%. Recovering MAP estimates using simulated, non-uniform priors that correlated with monkeys’ choice performance, improved the accuracy of the model by 2.88%. A dynamic analysis revealed that the MAP estimate evolved over time and the posterior probability of the saccade choice reached a maximum at the time of the saccade. MAP estimates also scaled with choice performance accuracy. Although there was overlap in the prediction abilities of all the models, we conclude that movement choice from populations of neurons may be best understood by considering frameworks based on probability. PMID:20147560

Electronic and thermoelectric analysis of phases in the In 2O 3(ZnO) k system

DOE PAGES

Hopper, E. Mitchell; Zhu, Qimin; Song, Jung-Hwan; ...

2011-01-01

The high-temperature electrical conductivity and thermopower of several compounds in the In 2O 3(ZnO) k system (k = 3, 5, 7, and 9) were measured, and the band structures of the k = 1, 2, and 3 structures were predicted based on first-principles calculations. These phases exhibit highly dispersed conduction bands consistent with transparent conducting oxide behavior. Jonker plots (Seebeck coefficient vs. natural logarithm of conductivity) were used to obtain the product of the density of states and mobility for these phases, which were related to the maximum achievable power factor (thermopower squared times conductivity) for each phase by Ioffemore » analysis (maximum power factor vs. Jonker plot intercept). With the exception of the k = 9 phase, all other phases were found to have maximum predicted power factors comparable to other thermoelectric oxides if suitably doped.« less

Time variation of galactic cosmic rays

NASA Technical Reports Server (NTRS)

Evenson, Paul

1988-01-01

Time variations in the flux of galactic cosmic rays are the result of changing conditions in the solar wind. Maximum cosmic ray fluxes, which occur when solar activity is at a minimum, are well defined. Reductions from this maximum level are typically systematic and predictable but on occasion are rapid and unexpected. Models relating the flux level at lower energy to that at neutron monitor energy are typically accurate to 20 percent of the total excursion at that energy. Other models, relating flux to observables such as sunspot number, flare frequency, and current sheet tilt are phenomenological but nevertheless can be quite accurate.

Design of teleoperation system with a force-reflecting real-time simulator

NASA Technical Reports Server (NTRS)

Hirata, Mitsunori; Sato, Yuichi; Nagashima, Fumio; Maruyama, Tsugito

1994-01-01

We developed a force-reflecting teleoperation system that uses a real-time graphic simulator. This system eliminates the effects of communication time delays in remote robot manipulation. The simulator provides the operator with predictive display and feedback of computed contact forces through a six-degree of freedom (6-DOF) master arm on a real-time basis. With this system, peg-in-hole tasks involving round-trip communication time delays of up to a few seconds were performed at three support levels: a real image alone, a predictive display with a real image, and a real-time graphic simulator with computed-contact-force reflection and a predictive display. The experimental results indicate the best teleoperation efficiency was achieved by using the force-reflecting simulator with two images. The shortest work time, lowest sensor maximum, and a 100 percent success rate were obtained. These results demonstrate the effectiveness of simulated-force-reflecting teleoperation efficiency.

Maximum of a Fractional Brownian Motion: Analytic Results from Perturbation Theory.

PubMed

Delorme, Mathieu; Wiese, Kay Jörg

2015-11-20

Fractional Brownian motion is a non-Markovian Gaussian process X_{t}, indexed by the Hurst exponent H. It generalizes standard Brownian motion (corresponding to H=1/2). We study the probability distribution of the maximum m of the process and the time t_{max} at which the maximum is reached. They are encoded in a path integral, which we evaluate perturbatively around a Brownian, setting H=1/2+ϵ. This allows us to derive analytic results beyond the scaling exponents. Extensive numerical simulations for different values of H test these analytical predictions and show excellent agreement, even for large ϵ.

Experimental and modeling results of creep fatigue life of Inconel 617 and Haynes 230 at 850 C

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

Chen, Xiang; Sokolov, Mikhail A; Sham, Sam

Creep fatigue testing of Ni-based superalloy Inconel 617 and Haynes 230 were conducted in the air at 850 C. Tests were performed with fully reversed axial strain control at a total strain range of 0.5%, 1.0% or 1.5% and hold time at maximum tensile strain for 3, 10 or 30 min. In addition, two creep fatigue life prediction methods, i.e. linear damage summation and frequency-modified tensile hysteresis energy modeling, were evaluated and compared with experimental results. Under all creep fatigue tests, Haynes 230 performed better than Inconel 617. Compared to the low cycle fatigue life, the cycles to failure formore » both materials decreased under creep fatigue test conditions. Longer hold time at maximum tensile strain would cause a further reduction in both material creep fatigue life. The linear damage summation could predict the creep fatigue life of Inconel 617 for limited test conditions, but considerably underestimated the creep fatigue life of Haynes 230. In contrast, frequency-modified tensile hysteresis energy modeling showed promising creep fatigue life prediction results for both materials.« less

Experimental and modeling results of creep-fatigue life of Inconel 617 and Haynes 230 at 850 °C

NASA Astrophysics Data System (ADS)

Chen, Xiang; Sokolov, Mikhail A.; Sham, Sam; Erdman, Donald L., III; Busby, Jeremy T.; Mo, Kun; Stubbins, James F.

2013-01-01

Creep-fatigue testing of Ni-based superalloy Inconel 617 and Haynes 230 were conducted in the air at 850 °C. Tests were performed with fully reversed axial strain control at a total strain range of 0.5%, 1.0% or 1.5% and hold time at maximum tensile strain for 3, 10 or 30 min. In addition, two creep-fatigue life prediction methods, i.e. linear damage summation and frequency-modified tensile hysteresis energy modeling, were evaluated and compared with experimental results. Under all creep-fatigue tests, Haynes 230 performed better than Inconel 617. Compared to the low cycle fatigue life, the cycles to failure for both materials decreased under creep-fatigue test conditions. Longer hold time at maximum tensile strain would cause a further reduction in both material creep-fatigue life. The linear damage summation could predict the creep-fatigue life of Inconel 617 for limited test conditions, but considerably underestimated the creep-fatigue life of Haynes 230. In contrast, frequency-modified tensile hysteresis energy modeling showed promising creep-fatigue life prediction results for both materials.

Utilization of waste heat in trucks for increased fuel economy

NASA Technical Reports Server (NTRS)

Leising, C. J.; Purohit, G. P.; Degrey, S. P.; Finegold, J. G.

1978-01-01

The waste heat utilization concepts include preheating, regeneration, turbocharging, turbocompounding, and Rankine engine compounding. Predictions are based on fuel-air cycle analyses, computer simulation, and engine test data. All options are evaluated in terms of maximum theoretical improvements, but the Diesel and adiabatic Diesel are also compared on the basis of maximum expected improvement and expected improvement over a driving cycle. The study indicates that Diesels should be turbocharged and aftercooled to the maximum possible level. The results reveal that Diesel driving cycle performance can be increased by 20% through increased turbocharging, turbocompounding, and Rankine engine compounding. The Rankine engine compounding provides about three times as much improvement as turbocompounding but also costs about three times as much. Performance for either can be approximately doubled if applied to an adiabatic Diesel.

Perturbative expansion for the maximum of fractional Brownian motion.

PubMed

Delorme, Mathieu; Wiese, Kay Jörg

2016-07-01

Brownian motion is the only random process which is Gaussian, scale invariant, and Markovian. Dropping the Markovian property, i.e., allowing for memory, one obtains a class of processes called fractional Brownian motion, indexed by the Hurst exponent H. For H=1/2, Brownian motion is recovered. We develop a perturbative approach to treat the nonlocality in time in an expansion in ɛ=H-1/2. This allows us to derive analytic results beyond scaling exponents for various observables related to extreme value statistics: the maximum m of the process and the time t_{max} at which this maximum is reached, as well as their joint distribution. We test our analytical predictions with extensive numerical simulations for different values of H. They show excellent agreement, even for H far from 1/2.

Transient response to three-phase faults on a wind turbine generator. Ph.D. Thesis - Toledo Univ.

NASA Technical Reports Server (NTRS)

Gilbert, L. J.

1978-01-01

In order to obtain a measure of its responses to short circuits a large horizontal axis wind turbine generator was modeled and its performance was simulated on a digital computer. Simulation of short circuit faults on the synchronous alternator of a wind turbine generator, without resort to the classical assumptions generally made for that analysis, indicates that maximum clearing times for the system tied to an infinite bus are longer than the typical clearing times for equivalent capacity conventional machines. Also, maximum clearing times are independent of tower shadow and wind shear. Variation of circuit conditions produce the modifications in the transient response predicted by analysis.

Epileptic Seizures Prediction Using Machine Learning Methods

PubMed Central

Usman, Syed Muhammad

2017-01-01

Epileptic seizures occur due to disorder in brain functionality which can affect patient's health. Prediction of epileptic seizures before the beginning of the onset is quite useful for preventing the seizure by medication. Machine learning techniques and computational methods are used for predicting epileptic seizures from Electroencephalograms (EEG) signals. However, preprocessing of EEG signals for noise removal and features extraction are two major issues that have an adverse effect on both anticipation time and true positive prediction rate. Therefore, we propose a model that provides reliable methods of both preprocessing and feature extraction. Our model predicts epileptic seizures' sufficient time before the onset of seizure starts and provides a better true positive rate. We have applied empirical mode decomposition (EMD) for preprocessing and have extracted time and frequency domain features for training a prediction model. The proposed model detects the start of the preictal state, which is the state that starts few minutes before the onset of the seizure, with a higher true positive rate compared to traditional methods, 92.23%, and maximum anticipation time of 33 minutes and average prediction time of 23.6 minutes on scalp EEG CHB-MIT dataset of 22 subjects. PMID:29410700

Examining impulse-variability in overarm throwing.

PubMed

Urbin, M A; Stodden, David; Boros, Rhonda; Shannon, David

2012-01-01

The purpose of this study was to examine variability in overarm throwing velocity and spatial output error at various percentages of maximum to test the prediction of an inverted-U function as predicted by impulse-variability theory and a speed-accuracy trade-off as predicted by Fitts' Law Thirty subjects (16 skilled, 14 unskilled) were instructed to throw a tennis ball at seven percentages of their maximum velocity (40-100%) in random order (9 trials per condition) at a target 30 feet away. Throwing velocity was measured with a radar gun and interpreted as an index of overall systemic power output. Within-subject throwing velocity variability was examined using within-subjects repeated-measures ANOVAs (7 repeated conditions) with built-in polynomial contrasts. Spatial error was analyzed using mixed model regression. Results indicated a quadratic fit with variability in throwing velocity increasing from 40% up to 60%, where it peaked, and then decreasing at each subsequent interval to maximum (p < .001, η2 = .555). There was no linear relationship between speed and accuracy. Overall, these data support the notion of an inverted-U function in overarm throwing velocity variability as both skilled and unskilled subjects approach maximum effort. However, these data do not support the notion of a speed-accuracy trade-off. The consistent demonstration of an inverted-U function associated with systemic power output variability indicates an enhanced capability to regulate aspects of force production and relative timing between segments as individuals approach maximum effort, even in a complex ballistic skill.

Are Subject-Specific Musculoskeletal Models Robust to the Uncertainties in Parameter Identification?

PubMed Central

Valente, Giordano; Pitto, Lorenzo; Testi, Debora; Seth, Ajay; Delp, Scott L.; Stagni, Rita; Viceconti, Marco; Taddei, Fulvia

2014-01-01

Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312) across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force predictions could be affected by an uncertainty in the same order of magnitude of its value, although this condition has low probability to occur. PMID:25390896

Relationships between static foot alignment and dynamic plantar loads in runners with acute and chronic stages of plantar fasciitis: a cross-sectional study

PubMed Central

Ribeiro, Ana P.; Sacco, Isabel C. N.; Dinato, Roberto C.; João, Silvia M. A.

2016-01-01

BACKGROUND: The risk factors for the development of plantar fasciitis (PF) have been associated with the medial longitudinal arch (MLA), rearfoot alignment and calcaneal overload. However, the relationships between the biomechanical variables have yet to be determined. OBJECTIVE: The goal of this study was to investigate the relationships between the MLA, rearfoot alignment, and dynamic plantar loads in runners with unilateral PF in acute and chronic phases. METHOD: Cross-sectional study which thirty-five runners with unilateral PF were evaluated: 20 in the acute phase (with pain) and 15 with previous chronic PF (without pain). The MLA index and rearfoot alignment were calculated using digital images. The contact area, maximum force, peak pressure, and force-time integral over three plantar areas were acquired with Pedar X insoles while running at 12 km/h, and the loading rates were calculated from the vertical forces. RESULTS: The multiple regression analyses indicated that both the force-time integral (R 2=0.15 for acute phase PF; R 2=0.17 for chronic PF) and maximum force (R 2=0.35 for chronic PF) over the forefoot were predicted by an elevated MLA index. The rearfoot valgus alignment predicted the maximum force over the rearfoot in both PF groups: acute (R 2=0.18) and chronic (R 2=0.45). The rearfoot valgus alignment also predicted higher loading rates in the PF groups: acute (R 2=0.19) and chronic (R 2=0.40). CONCLUSION: The MLA index and the rearfoot alignment were good predictors of plantar loads over the forefoot and rearfoot areas in runners with PF. However, rearfoot valgus was demonstrated to be an important clinical measure, since it was able to predict the maximum force and both loading rates over the rearfoot. PMID:26786073

Interpreting the Strongly Lensed Supernova iPTF16geu: Time Delay Predictions, Microlensing, and Lensing Rates

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

More, Anupreeta; Oguri, Masamune; More, Surhud

2017-02-01

We present predictions for time delays between multiple images of the gravitationally lensed supernova, iPTF16geu, which was recently discovered from the intermediate Palomar Transient Factory (iPTF). As the supernova is of Type Ia where the intrinsic luminosity is usually well known, accurately measured time delays of the multiple images could provide tight constraints on the Hubble constant. According to our lens mass models constrained by the Hubble Space Telescope F814W image, we expect the maximum relative time delay to be less than a day, which is consistent with the maximum of 100 hr reported by Goobar et al. but placesmore » a stringent upper limit. Furthermore, the fluxes of most of the supernova images depart from expected values suggesting that they are affected by microlensing. The microlensing timescales are small enough that they may pose significant problems to measure the time delays reliably. Our lensing rate calculation indicates that the occurrence of a lensed SN in iPTF is likely. However, the observed total magnification of iPTF16geu is larger than expected, given its redshift. This may be a further indication of ongoing microlensing in this system.« less

Forecast simulation of rapidly-intensified typhoon in the Eddy-Rich Northwest Pacific region

NASA Astrophysics Data System (ADS)

Kim, Kyeong Ok; Yuk, Jin-Hee; Jung, Kyung Tae; Kuh Kang, Suk

2017-04-01

The real-time typhoon predictions in the Northwest Pacific (NWP) are being distributed by various agencies (for example, KMA, JMA, JTWC, NMC, CWB, HKO and PAGASA). Currently the movement of the typhoon can be predicted with an error of less than 100 km in 48 hours, however it is difficult to the predict of the intensity of the typhoon especially the Rapidly Intensified (RI) Typhoons. The mean occurrence of RI typhoon amounts to 5.4 times a year during 39 years (1977-2015), occupying 21% of typhoons in NWP. Especially the RI typhoon in the Eddy-Rich Northwest Pacific (ER-NWP) occurred 1.8 times a year, covering 29% of typhoons in ER-NWP. A RI typhoon, NEPARTAK (T201601), occurred in July 2016. It was formed in Caroline Islands and moved northwest, straightly heading for Taiwan. However, at the beginning stage many forecasting agencies predicts as move to the Yellow Sea. The accuracy of prediction data of the Typhoon NEPARTAK (T201601) from KMA, JMA and JTWC was compared with the adjusted best-track data from Digital-Typhoon (JMA-RSMC). The sequential prediction data are summarized with 6-hour interval from 3th to 10th July 2016.The JMA prediction of the typhoon track and the JTWC predictions of the maximum wind speed were found to be best. The numerical simulations using WRF model forced with NCEP GFS prediction data and microwave SST is compared. The simulations using one domain (D1), two domains (D2) using a moving nest scheme, and with or without the spectral nudging (-SN) are compared. Comparison of the errors on the track shows the differences of 100 km in 48-hour prediction and200 km in 72-hour prediction on average. The best results on the track prediction are shown in the D2 case of WRF model. However, underestimation of the maximum wind speed of WRF prediction still exists, obviously requiring better understanding of RI-related processes to improve the model prediction.

Delayed right atrial lateral electromechanical coupling relative to the septal one can be associated with paroxysmal atrial fibrillation.

PubMed

Karapinar, H; Acar, G; Kirma, C; Kaya, Z; Karavelioglu, Y; Kucukdurmaz, Z; Esen, O; Alizade, E; Dasli, T; Sirma, D; Esen, A M

2013-08-01

Non-invasive prediction of paroxysmal atrial fibrillation (PAF) is one of the most recent interests of cardiology. The current study investigates the relationship between the atrial electromechanical coupling time (EMCT) and PAF. A group of 35 patients with PAF was compared with a group of 37 subjects without PAF. Pulsed wave tissue Doppler evaluations of atrial walls were performed from apical four chambers view under ECG monitoring. The time intervals from the onset of P wave to the onset of late diastolic wave (A') at right atrial wall (P-RA), interatrial septum (P-IAS), and left atrial wall (P-LA, maximum EMCT) were measured. The right atrial EMCT (P-RA minus P-IAS), left atrial EMCT (P-LA minus P-IAS) and interatrial EMCT (P-LA minus P-RA) were computed. A' wave velocities were measured from each atrial wall. RA (16.0±13.1 vs. -8.7±18.6 ms, p < 0.001) and maximum (91.5±32.6 vs. 72.0±23.1 ms, p = 0.001) EMCT were longer, RA A' velocity was higher in the patient group. There were no differences between the groups in LA and interatrial EMCT, and septal and LA A' velocities. Regression analysis revealed that only RA [OR: 1.148 (1.041-1.267), p = 0.006] and maximum [OR: 1.099 (1.009-1.197), p = 0.031] EMCT were independent variables for PAF. In order to predict patients with PAF, we have chosen +7.5 msn for the RA EMCT which yielded 69% sensitivity and 71.4% specificity to predict patients. Delayed RA lateral EMCT relative to septal one and delayed maximum EMCT detected by tissue Doppler could be a valuable method for identifying patients with PAF.

Germination parameterization and development of an after-ripening thermal-time model for primary dormancy release of Lithospermum arvense seeds.

PubMed

Chantre, Guillermo R; Batlla, Diego; Sabbatini, Mario R; Orioli, Gustavo

2009-06-01

Models based on thermal-time approaches have been a useful tool for characterizing and predicting seed germination and dormancy release in relation to time and temperature. The aims of the present work were to evaluate the relative accuracy of different thermal-time approaches for the description of germination in Lithospermum arvense and to develop an after-ripening thermal-time model for predicting seed dormancy release. Seeds were dry-stored at constant temperatures of 5, 15 or 24 degrees C for up to 210 d. After different storage periods, batches of 50 seeds were incubated at eight constant temperature regimes of 5, 8, 10, 13, 15, 17, 20 or 25 degrees C. Experimentally obtained cumulative-germination curves were analysed using a non-linear regression procedure to obtain optimal population thermal parameters for L. arvense. Changes in these parameters were described as a function of after-ripening thermal-time and storage temperature. The most accurate approach for simulating the thermal-germination response of L. arvense was achieved by assuming a normal distribution of both base and maximum germination temperatures. The results contradict the widely accepted assumption of a single T(b) value for the entire seed population. The after-ripening process was characterized by a progressive increase in the mean maximum germination temperature and a reduction in the thermal-time requirements for germination at sub-optimal temperatures. The after-ripening thermal-time model developed here gave an acceptable description of the observed field emergence patterns, thus indicating its usefulness as a predictive tool to enhance weed management tactics.

[Predictive factors of contamination in a blood culture with bacterial growth in an Emergency Department].

PubMed

Hernández-Bou, S; Trenchs Sainz de la Maza, V; Esquivel Ojeda, J N; Gené Giralt, A; Luaces Cubells, C

2015-06-01

The aim of this study is to identify predictive factors of bacterial contamination in positive blood cultures (BC) collected in an emergency department. A prospective, observational and analytical study was conducted on febrile children aged on to 36 months, who had no risk factors of bacterial infection, and had a BC collected in the Emergency Department between November 2011 and October 2013 in which bacterial growth was detected. The potential BC contamination predicting factors analysed were: maximum temperature, time to positivity, initial Gram stain result, white blood cell count, absolute neutrophil count, band count, and C-reactive protein (CRP). Bacteria grew in 169 BC. Thirty (17.8%) were finally considered true positives and 139 (82.2%) false positives. All potential BC contamination predicting factors analysed, except maximum temperature, showed significant differences between true positives and false positives. CRP value, time to positivity, and initial Gram stain result are the best predictors of false positives in BC. The positive predictive values of a CRP value≤30mg/L, BC time to positivity≥16h, and initial Gram stain suggestive of a contaminant in predicting a FP, are 95.1, 96.9 and 97.5%, respectively. When all 3 conditions are applied, their positive predictive value is 100%. Four (8.3%) patients with a false positive BC and discharged to home were revaluated in the Emergency Department. The majority of BC obtained in the Emergency Department that showed positive were finally considered false positives. Initial Gram stain, time to positivity, and CRP results are valuable diagnostic tests in distinguishing between true positives and false positives in BC. The early detection of false positives will allow minimising their negative consequences. Copyright © 2014 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.

Conserved actions, maximum entropy and dark matter haloes

NASA Astrophysics Data System (ADS)

Pontzen, Andrew; Governato, Fabio

2013-03-01

We use maximum entropy arguments to derive the phase-space distribution of a virialized dark matter halo. Our distribution function gives an improved representation of the end product of violent relaxation. This is achieved by incorporating physically motivated dynamical constraints (specifically on orbital actions) which prevent arbitrary redistribution of energy. We compare the predictions with three high-resolution dark matter simulations of widely varying mass. The numerical distribution function is accurately predicted by our argument, producing an excellent match for the vast majority of particles. The remaining particles constitute the central cusp of the halo (≲4 per cent of the dark matter). They can be accounted for within the presented framework once the short dynamical time-scales of the centre are taken into account.

Igniter adapter-to-igniter chamber deflection test

NASA Technical Reports Server (NTRS)

Cook, M.

1990-01-01

Testing was performed to determine the maximum RSRM igniter adapter-to-igniter chamber joint deflection at the crown of the inner joint primary seal. The deflection data was gathered to support igniter inner joint gasket resiliency predictions which led to launch commit criteria temperature determinations. The proximity (deflection) gage holes for the first test (Test No. 1) were incorrectly located; therefore, the test was declared a non-test. Prior to Test No. 2, test article configuration was modified with the correct proximity gage locations. Deflection data were successfully acquired during Test No. 2. However, the proximity gage deflection measurements were adversely affected by temperature increases. Deflections measured after the temperature rise at the proximity gages were considered unreliable. An analysis was performed to predict the maximum deflections based on the reliable data measured before the detectable temperature rise. Deflections to the primary seal crown location were adjusted to correspond to the time of maximum expected operating pressure (2,159 psi) to account for proximity gage bias, and to account for maximum attach and special bolt relaxation. The maximum joint deflection for the igniter inner joint at the crown of the primary seal, accounting for all significant correction factors, was 0.0031 in. (3.1 mil). Since the predicted (0.003 in.) and tested maximum deflection values were sufficiently close, the launch commit criteria was not changed as a result of this test. Data from this test should be used to determine if the igniter inner joint gasket seals are capable of maintaining sealing capability at a joint displacement of (1.4) x (0.0031 in.) = 0.00434 inches. Additional testing should be performed to increase the database on igniter deflections and address launch commit criteria temperatures.

Scaling Analysis of Alloy Solidification and Fluid Flow in a Rectangular Cavity

NASA Astrophysics Data System (ADS)

Plotkowski, A.; Fezi, K.; Krane, M. J. M.

A scaling analysis was performed to predict trends in alloy solidification in a side-cooled rectangular cavity. The governing equations for energy and momentum were scaled in order to determine the dependence of various aspects of solidification on the process parameters for a uniform initial temperature and an isothermal boundary condition. This work improved on previous analyses by adding considerations for the cooling bulk fluid flow. The analysis predicted the time required to extinguish the superheat, the maximum local solidification time, and the total solidification time. The results were compared to a numerical simulation for a Al-4.5 wt.% Cu alloy with various initial and boundary conditions. Good agreement was found between the simulation results and the trends predicted by the scaling analysis.

Lifetime predictions for the Solar Maximum Mission (SMM) and San Marco spacecraft

NASA Technical Reports Server (NTRS)

Smith, E. A.; Ward, D. T.; Schmitt, M. W.; Phenneger, M. C.; Vaughn, F. J.; Lupisella, M. L.

1989-01-01

Lifetime prediction techniques developed by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) are described. These techniques were developed to predict the Solar Maximum Mission (SMM) spacecraft orbit, which is decaying due to atmospheric drag, with reentry predicted to occur before the end of 1989. Lifetime predictions were also performed for the Long Duration Exposure Facility (LDEF), which was deployed on the 1984 SMM repair mission and is scheduled for retrieval on another Space Transportation System (STS) mission later this year. Concepts used in the lifetime predictions were tested on the San Marco spacecraft, which reentered the Earth's atmosphere on December 6, 1988. Ephemerides predicting the orbit evolution of the San Marco spacecraft until reentry were generated over the final 90 days of the mission when the altitude was less than 380 kilometers. The errors in the predicted ephemerides are due to errors in the prediction of atmospheric density variations over the lifetime of the satellite. To model the time dependence of the atmospheric densities, predictions of the solar flux at the 10.7-centimeter wavelength were used in conjunction with Harris-Priester (HP) atmospheric density tables. Orbital state vectors, together with the spacecraft mass and area, are used as input to the Goddard Trajectory Determination System (GTDS). Propagations proceed in monthly segments, with the nominal atmospheric drag model scaled for each month according to the predicted monthly average value of F10.7. Calibration propagations are performed over a period of known orbital decay to obtain the effective ballistic coefficient. Progagations using plus or minus 2 sigma solar flux predictions are also generated to estimate the despersion in expected reentry dates. Definitive orbits are compared with these predictions as time expases. As updated vectors are received, these are also propagated to reentryto continually update the lifetime predictions.

Estimation of typhoon rainfall in GaoPing River: A Multivariate Maximum Entropy Method

NASA Astrophysics Data System (ADS)

Pei-Jui, Wu; Hwa-Lung, Yu

2016-04-01

The heavy rainfall from typhoons is the main factor of the natural disaster in Taiwan, which causes the significant loss of human lives and properties. Statistically average 3.5 typhoons invade Taiwan every year, and the serious typhoon, Morakot in 2009, impacted Taiwan in recorded history. Because the duration, path and intensity of typhoon, also affect the temporal and spatial rainfall type in specific region , finding the characteristics of the typhoon rainfall type is advantageous when we try to estimate the quantity of rainfall. This study developed a rainfall prediction model and can be divided three parts. First, using the EEOF(extended empirical orthogonal function) to classify the typhoon events, and decompose the standard rainfall type of all stations of each typhoon event into the EOF and PC(principal component). So we can classify the typhoon events which vary similarly in temporally and spatially as the similar typhoon types. Next, according to the classification above, we construct the PDF(probability density function) in different space and time by means of using the multivariate maximum entropy from the first to forth moment statistically. Therefore, we can get the probability of each stations of each time. Final we use the BME(Bayesian Maximum Entropy method) to construct the typhoon rainfall prediction model , and to estimate the rainfall for the case of GaoPing river which located in south of Taiwan.This study could be useful for typhoon rainfall predictions in future and suitable to government for the typhoon disaster prevention .

An artificial intelligence approach to Bacillus amyloliquefaciens CCMI 1051 cultures: application to the production of anti-fungal compounds.

PubMed

Caldeira, A Teresa; Arteiro, José M; Roseiro, José C; Neves, José; Vicente, H

2011-01-01

The combined effect of incubation time (IT) and aspartic acid concentration (AA) on the predicted biomass concentration (BC), Bacillus sporulation (BS) and anti-fungal activity of compounds (AFA) produced by Bacillus amyloliquefaciens CCMI 1051, was studied using Artificial Neural Networks (ANNs). The values predicted by ANN were in good agreement with experimental results, and were better than those obtained when using Response Surface Methodology. The database used to train and validate ANNs contains experimental data of B. amyloliquefaciens cultures (AFA, BS and BC) with different incubation times (1-9 days) using aspartic acid (3-42 mM) as nitrogen source. After the training and validation stages, the 2-7-6-3 neural network results showed that maximum AFA can be achieved with 19.5 mM AA on day 9; however, maximum AFA can also be obtained with an incubation time as short as 6 days with 36.6 mM AA. Furthermore, the model results showed two distinct behaviors for AFA, depending on IT. Copyright © 2010 Elsevier Ltd. All rights reserved.

Classification of change detection and change blindness from near-infrared spectroscopy signals

NASA Astrophysics Data System (ADS)

Tanaka, Hirokazu; Katura, Takusige

2011-08-01

Using a machine-learning classification algorithm applied to near-infrared spectroscopy (NIRS) signals, we classify a success (change detection) or a failure (change blindness) in detecting visual changes for a change-detection task. Five subjects perform a change-detection task, and their brain activities are continuously monitored. A support-vector-machine algorithm is applied to classify the change-detection and change-blindness trials, and correct classification probability of 70-90% is obtained for four subjects. Two types of temporal shapes in classification probabilities are found: one exhibiting a maximum value after the task is completed (postdictive type), and another exhibiting a maximum value during the task (predictive type). As for the postdictive type, the classification probability begins to increase immediately after the task completion and reaches its maximum in about the time scale of neuronal hemodynamic response, reflecting a subjective report of change detection. As for the predictive type, the classification probability shows an increase at the task initiation and is maximal while subjects are performing the task, predicting the task performance in detecting a change. We conclude that decoding change detection and change blindness from NIRS signal is possible and argue some future applications toward brain-machine interfaces.

Optimal design criteria - prediction vs. parameter estimation

NASA Astrophysics Data System (ADS)

Waldl, Helmut

2014-05-01

G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

First assembly times and equilibration in stochastic coagulation-fragmentation

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

D’Orsogna, Maria R.; Department of Mathematics, CSUN, Los Angeles, California 91330-8313; Lei, Qi

2015-07-07

We develop a fully stochastic theory for coagulation and fragmentation (CF) in a finite system with a maximum cluster size constraint. The process is modeled using a high-dimensional master equation for the probabilities of cluster configurations. For certain realizations of total mass and maximum cluster sizes, we find exact analytical results for the expected equilibrium cluster distributions. If coagulation is fast relative to fragmentation and if the total system mass is indivisible by the mass of the largest allowed cluster, we find a mean cluster-size distribution that is strikingly broader than that predicted by the corresponding mass-action equations. Combinations ofmore » total mass and maximum cluster size under which equilibration is accelerated, eluding late-stage coarsening, are also delineated. Finally, we compute the mean time it takes particles to first assemble into a maximum-sized cluster. Through careful state-space enumeration, the scaling of mean assembly times is derived for all combinations of total mass and maximum cluster size. We find that CF accelerates assembly relative to monomer kinetic only in special cases. All of our results hold in the infinite system limit and can be only derived from a high-dimensional discrete stochastic model, highlighting how classical mass-action models of self-assembly can fail.« less

Watershed Regressions for Pesticides (WARP) for Predicting Annual Maximum and Annual Maximum Moving-Average Concentrations of Atrazine in Streams

USGS Publications Warehouse

Stone, Wesley W.; Gilliom, Robert J.; Crawford, Charles G.

2008-01-01

Regression models were developed for predicting annual maximum and selected annual maximum moving-average concentrations of atrazine in streams using the Watershed Regressions for Pesticides (WARP) methodology developed by the National Water-Quality Assessment Program (NAWQA) of the U.S. Geological Survey (USGS). The current effort builds on the original WARP models, which were based on the annual mean and selected percentiles of the annual frequency distribution of atrazine concentrations. Estimates of annual maximum and annual maximum moving-average concentrations for selected durations are needed to characterize the levels of atrazine and other pesticides for comparison to specific water-quality benchmarks for evaluation of potential concerns regarding human health or aquatic life. Separate regression models were derived for the annual maximum and annual maximum 21-day, 60-day, and 90-day moving-average concentrations. Development of the regression models used the same explanatory variables, transformations, model development data, model validation data, and regression methods as those used in the original development of WARP. The models accounted for 72 to 75 percent of the variability in the concentration statistics among the 112 sampling sites used for model development. Predicted concentration statistics from the four models were within a factor of 10 of the observed concentration statistics for most of the model development and validation sites. Overall, performance of the models for the development and validation sites supports the application of the WARP models for predicting annual maximum and selected annual maximum moving-average atrazine concentration in streams and provides a framework to interpret the predictions in terms of uncertainty. For streams with inadequate direct measurements of atrazine concentrations, the WARP model predictions for the annual maximum and the annual maximum moving-average atrazine concentrations can be used to characterize the probable levels of atrazine for comparison to specific water-quality benchmarks. Sites with a high probability of exceeding a benchmark for human health or aquatic life can be prioritized for monitoring.

A basin-scale approach to estimating stream temperatures of tributaries to the lower Klamath River, California

USGS Publications Warehouse

Flint, L.E.; Flint, A.L.

2008-01-01

Stream temperature is an important component of salmonid habitat and is often above levels suitable for fish survival in the Lower Klamath River in northern California. The objective of this study was to provide boundary conditions for models that are assessing stream temperature on the main stem for the purpose of developing strategies to manage stream conditions using Total Maximum Daily Loads. For model input, hourly stream temperatures for 36 tributaries were estimated for 1 Jan. 2001 through 31 Oct. 2004. A basin-scale approach incorporating spatially distributed energy balance data was used to estimate the stream temperatures with measured air temperature and relative humidity data and simulated solar radiation, including topographic shading and corrections for cloudiness. Regression models were developed on the basis of available stream temperature data to predict temperatures for unmeasured periods of time and for unmeasured streams. The most significant factor in matching measured minimum and maximum stream temperatures was the seasonality of the estimate. Adding minimum and maximum air temperature to the regression model improved the estimate, and air temperature data over the region are available and easily distributed spatially. The addition of simulated solar radiation and vapor saturation deficit to the regression model significantly improved predictions of maximum stream temperature but was not required to predict minimum stream temperature. The average SE in estimated maximum daily stream temperature for the individual basins was 0.9 ?? 0.6??C at the 95% confidence interval. Copyright ?? 2008 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Chest wall mobility is related to respiratory muscle strength and lung volumes in healthy subjects.

PubMed

Lanza, Fernanda de Cordoba; de Camargo, Anderson Alves; Archija, Lilian Rocha Ferraz; Selman, Jessyca Pachi Rodrigues; Malaguti, Carla; Dal Corso, Simone

2013-12-01

Chest wall mobility is often measured in clinical practice, but the correlations between chest wall mobility and respiratory muscle strength and lung volumes are unknown. We investigate the associations between chest wall mobility, axillary and thoracic cirtometry values, respiratory muscle strength (maximum inspiratory pressure and maximum expiratory pressure), and lung volumes (expiratory reserve volume, FEV(1), inspiratory capacity, FEV(1)/FVC), and the determinants of chest mobility in healthy subjects. In 64 healthy subjects we measured inspiratory capacity, FVC, FEV(1), expiratory reserve volume, maximum inspiratory pressure, and maximum expiratory pressure, and chest wall mobility via axillary and thoracic cirtometry. We used linear regression to evaluate the influence of the measured variables on chest wall mobility. The subjects' mean ± SD values were: age 24 ± 3 years, axillary cirtometry 6.3 ± 2.0 cm, thoracic cirtometry 7.5 ± 2.3 cm; maximum inspiratory pressure 90.4 ± 10.6% of predicted, maximum expiratory pressure 92.8 ± 13.5% of predicted, inspiratory capacity 99.7 ± 8.6% of predicted, FVC 101.9 ± 10.6% of predicted, FEV(1) 98.2 ± 10.3% of predicted, expiratory reserve volume 90.9 ± 19.9% of predicted. There were significant correlations between axillary cirtometry and FVC (r = 0.32), FEV(1) (r = 0.30), maximum inspiratory pressure (r = 0.48), maximum expiratory pressure (r = 0.25), and inspiratory capacity (r = 0.24), and between thoracic cirtometry and FVC (r = 0.50), FEV(1) (r = 0.48), maximum inspiratory pressure (r = 0.46), maximum expiratory pressure (r = 0.37), inspiratory capacity (r = 0.39), and expiratory reserve volume (r = 0.47). In multiple regression analysis the variable that best explained the axillary cirtometry variation was maximum inspiratory pressure (R(2) 0.23), and for thoracic cirtometry it was FVC and maximum inspiratory pressure (R(2) 0.32). Chest mobility in healthy subjects is related to respiratory muscle strength and lung function; the higher the axillary cirtometry and thoracic cirtometry values, the greater the maximum inspiratory pressure, maximum expiratory pressure, and lung volumes in healthy subjects.

Predicting apricot phenology using meteorological data.

PubMed

Ruml, Mirjana; Milatović, Dragan; Vulić, Todor; Vuković, Ana

2011-09-01

The main objective of this study was to develop feasible, easy to apply models for early prediction of full flowering (FF) and maturing (MA) in apricot (Prunus armeniaca L.). Phenological data for 20 apricot cultivars grown in the Belgrade region were modeled against averages of daily temperature records over ten seasons for FF and eight seasons for MA. A much stronger correlation was found between the phenological timing and temperature at the very beginning than at the end of phenophases. Also, the length of developmental periods were better correlated to daily maximum than to daily minimum and mean air temperatures. Using prediction models based on daily maximum temperatures averaged over 30-, 45- and 60-day periods, starting from 1 January for FF prediction and from the date of FF for MA prediction, the onset of examined phenophases in apricot cultivars could be predicted from a few weeks to up to 2 months ahead with acceptable accuracy. The mean absolute differences between the observations and cross-validated predictions obtained by 30-, 45- and 60-day models were 8.6, 6.9 and 5.7 days for FF and 6.1, 3.6 and 2.8 days for MA, respectively. The validity of the results was confirmed using an independent data set for the year 2009.

Predicting apricot phenology using meteorological data

NASA Astrophysics Data System (ADS)

Ruml, Mirjana; Milatović, Dragan; Vulić, Todor; Vuković, Ana

2011-09-01

The main objective of this study was to develop feasible, easy to apply models for early prediction of full flowering (FF) and maturing (MA) in apricot ( Prunus armeniaca L.). Phenological data for 20 apricot cultivars grown in the Belgrade region were modeled against averages of daily temperature records over ten seasons for FF and eight seasons for MA. A much stronger correlation was found between the phenological timing and temperature at the very beginning than at the end of phenophases. Also, the length of developmental periods were better correlated to daily maximum than to daily minimum and mean air temperatures. Using prediction models based on daily maximum temperatures averaged over 30-, 45- and 60-day periods, starting from 1 January for FF prediction and from the date of FF for MA prediction, the onset of examined phenophases in apricot cultivars could be predicted from a few weeks to up to 2 months ahead with acceptable accuracy. The mean absolute differences between the observations and cross-validated predictions obtained by 30-, 45- and 60-day models were 8.6, 6.9 and 5.7 days for FF and 6.1, 3.6 and 2.8 days for MA, respectively. The validity of the results was confirmed using an independent data set for the year 2009.

Germination parameterization and development of an after-ripening thermal-time model for primary dormancy release of Lithospermum arvense seeds

PubMed Central

Chantre, Guillermo R.; Batlla, Diego; Sabbatini, Mario R.; Orioli, Gustavo

2009-01-01

Background and Aims Models based on thermal-time approaches have been a useful tool for characterizing and predicting seed germination and dormancy release in relation to time and temperature. The aims of the present work were to evaluate the relative accuracy of different thermal-time approaches for the description of germination in Lithospermum arvense and to develop an after-ripening thermal-time model for predicting seed dormancy release. Methods Seeds were dry-stored at constant temperatures of 5, 15 or 24 °C for up to 210 d. After different storage periods, batches of 50 seeds were incubated at eight constant temperature regimes of 5, 8, 10, 13, 15, 17, 20 or 25 °C. Experimentally obtained cumulative-germination curves were analysed using a non-linear regression procedure to obtain optimal population thermal parameters for L. arvense. Changes in these parameters were described as a function of after-ripening thermal-time and storage temperature. Key Results The most accurate approach for simulating the thermal-germination response of L. arvense was achieved by assuming a normal distribution of both base and maximum germination temperatures. The results contradict the widely accepted assumption of a single Tb value for the entire seed population. The after-ripening process was characterized by a progressive increase in the mean maximum germination temperature and a reduction in the thermal-time requirements for germination at sub-optimal temperatures. Conclusions The after-ripening thermal-time model developed here gave an acceptable description of the observed field emergence patterns, thus indicating its usefulness as a predictive tool to enhance weed management tactics. PMID:19332426

Nonlinear Prediction As A Tool For Determining Parameters For Phase Space Reconstruction In Meteorology

NASA Astrophysics Data System (ADS)

Miksovsky, J.; Raidl, A.

Time delays phase space reconstruction represents one of useful tools of nonlinear time series analysis, enabling number of applications. Its utilization requires the value of time delay to be known, as well as the value of embedding dimension. There are sev- eral methods how to estimate both these parameters. Typically, time delay is computed first, followed by embedding dimension. Our presented approach is slightly different - we reconstructed phase space for various combinations of mentioned parameters and used it for prediction by means of the nearest neighbours in the phase space. Then some measure of prediction's success was computed (correlation or RMSE, e.g.). The position of its global maximum (minimum) should indicate the suitable combination of time delay and embedding dimension. Several meteorological (particularly clima- tological) time series were used for the computations. We have also created a MS- Windows based program in order to implement this approach - its basic features will be presented as well.

Effects of lightning on trees: A predictive model based on in situ electrical resistivity.

PubMed

Gora, Evan M; Bitzer, Phillip M; Burchfield, Jeffrey C; Schnitzer, Stefan A; Yanoviak, Stephen P

2017-10-01

The effects of lightning on trees range from catastrophic death to the absence of observable damage. Such differences may be predictable among tree species, and more generally among plant life history strategies and growth forms. We used field-collected electrical resistivity data in temperate and tropical forests to model how the distribution of power from a lightning discharge varies with tree size and identity, and with the presence of lianas. Estimated heating density (heat generated per volume of tree tissue) and maximum power (maximum rate of heating) from a standardized lightning discharge differed 300% among tree species. Tree size and morphology also were important; the heating density of a hypothetical 10 m tall Alseis blackiana was 49 times greater than for a 30 m tall conspecific, and 127 times greater than for a 30 m tall Dipteryx panamensis . Lianas may protect trees from lightning by conducting electric current; estimated heating and maximum power were reduced by 60% (±7.1%) for trees with one liana and by 87% (±4.0%) for trees with three lianas. This study provides the first quantitative mechanism describing how differences among trees can influence lightning-tree interactions, and how lianas can serve as natural lightning rods for trees.

The calculation of transport properties in quantum liquids using the maximum entropy numerical analytic continuation method: Application to liquid para-hydrogen

PubMed Central

Rabani, Eran; Reichman, David R.; Krilov, Goran; Berne, Bruce J.

2002-01-01

We present a method based on augmenting an exact relation between a frequency-dependent diffusion constant and the imaginary time velocity autocorrelation function, combined with the maximum entropy numerical analytic continuation approach to study transport properties in quantum liquids. The method is applied to the case of liquid para-hydrogen at two thermodynamic state points: a liquid near the triple point and a high-temperature liquid. Good agreement for the self-diffusion constant and for the real-time velocity autocorrelation function is obtained in comparison to experimental measurements and other theoretical predictions. Improvement of the methodology and future applications are discussed. PMID:11830656

Maximum-entropy description of animal movement.

PubMed

Fleming, Chris H; Subaşı, Yiğit; Calabrese, Justin M

2015-03-01

We introduce a class of maximum-entropy states that naturally includes within it all of the major continuous-time stochastic processes that have been applied to animal movement, including Brownian motion, Ornstein-Uhlenbeck motion, integrated Ornstein-Uhlenbeck motion, a recently discovered hybrid of the previous models, and a new model that describes central-place foraging. We are also able to predict a further hierarchy of new models that will emerge as data quality improves to better resolve the underlying continuity of animal movement. Finally, we also show that Langevin equations must obey a fluctuation-dissipation theorem to generate processes that fall from this class of maximum-entropy distributions when the constraints are purely kinematic.

Short-term load forecasting of power system

NASA Astrophysics Data System (ADS)

Xu, Xiaobin

2017-05-01

In order to ensure the scientific nature of optimization about power system, it is necessary to improve the load forecasting accuracy. Power system load forecasting is based on accurate statistical data and survey data, starting from the history and current situation of electricity consumption, with a scientific method to predict the future development trend of power load and change the law of science. Short-term load forecasting is the basis of power system operation and analysis, which is of great significance to unit combination, economic dispatch and safety check. Therefore, the load forecasting of the power system is explained in detail in this paper. First, we use the data from 2012 to 2014 to establish the partial least squares model to regression analysis the relationship between daily maximum load, daily minimum load, daily average load and each meteorological factor, and select the highest peak by observing the regression coefficient histogram Day maximum temperature, daily minimum temperature and daily average temperature as the meteorological factors to improve the accuracy of load forecasting indicators. Secondly, in the case of uncertain climate impact, we use the time series model to predict the load data for 2015, respectively, the 2009-2014 load data were sorted out, through the previous six years of the data to forecast the data for this time in 2015. The criterion for the accuracy of the prediction is the average of the standard deviations for the prediction results and average load for the previous six years. Finally, considering the climate effect, we use the BP neural network model to predict the data in 2015, and optimize the forecast results on the basis of the time series model.

Population pharmacokinetics and maximum a posteriori probability Bayesian estimator of abacavir: application of individualized therapy in HIV-infected infants and toddlers.

PubMed

Zhao, Wei; Cella, Massimo; Della Pasqua, Oscar; Burger, David; Jacqz-Aigrain, Evelyne

2012-04-01

Abacavir is used to treat HIV infection in both adults and children. The recommended paediatric dose is 8 mg kg(-1) twice daily up to a maximum of 300 mg twice daily. Weight was identified as the central covariate influencing pharmacokinetics of abacavir in children. A population pharmacokinetic model was developed to describe both once and twice daily pharmacokinetic profiles of abacavir in infants and toddlers. Standard dosage regimen is associated with large interindividual variability in abacavir concentrations. A maximum a posteriori probability Bayesian estimator of AUC(0-) (t) based on three time points (0, 1 or 2, and 3 h) is proposed to support area under the concentration-time curve (AUC) targeted individualized therapy in infants and toddlers. To develop a population pharmacokinetic model for abacavir in HIV-infected infants and toddlers, which will be used to describe both once and twice daily pharmacokinetic profiles, identify covariates that explain variability and propose optimal time points to optimize the area under the concentration-time curve (AUC) targeted dosage and individualize therapy. The pharmacokinetics of abacavir was described with plasma concentrations from 23 patients using nonlinear mixed-effects modelling (NONMEM) software. A two-compartment model with first-order absorption and elimination was developed. The final model was validated using bootstrap, visual predictive check and normalized prediction distribution errors. The Bayesian estimator was validated using the cross-validation and simulation-estimation method. The typical population pharmacokinetic parameters and relative standard errors (RSE) were apparent systemic clearance (CL) 13.4 () h−1 (RSE 6.3%), apparent central volume of distribution 4.94 () (RSE 28.7%), apparent peripheral volume of distribution 8.12 () (RSE14.2%), apparent intercompartment clearance 1.25 () h−1 (RSE 16.9%) and absorption rate constant 0.758 h−1 (RSE 5.8%). The covariate analysis identified weight as the individual factor influencing the apparent oral clearance: CL = 13.4 × (weight/12)1.14. The maximum a posteriori probability Bayesian estimator, based on three concentrations measured at 0, 1 or 2, and 3 h after drug intake allowed predicting individual AUC0–t. The population pharmacokinetic model developed for abacavir in HIV-infected infants and toddlers accurately described both once and twice daily pharmacokinetic profiles. The maximum a posteriori probability Bayesian estimator of AUC(0-) (t) was developed from the final model and can be used routinely to optimize individual dosing. © 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.

Nearshore Tsunami Inundation Model Validation: Toward Sediment Transport Applications

USGS Publications Warehouse

Apotsos, Alex; Buckley, Mark; Gelfenbaum, Guy; Jaffe, Bruce; Vatvani, Deepak

2011-01-01

Model predictions from a numerical model, Delft3D, based on the nonlinear shallow water equations are compared with analytical results and laboratory observations from seven tsunami-like benchmark experiments, and with field observations from the 26 December 2004 Indian Ocean tsunami. The model accurately predicts the magnitude and timing of the measured water levels and flow velocities, as well as the magnitude of the maximum inundation distance and run-up, for both breaking and non-breaking waves. The shock-capturing numerical scheme employed describes well the total decrease in wave height due to breaking, but does not reproduce the observed shoaling near the break point. The maximum water levels observed onshore near Kuala Meurisi, Sumatra, following the 26 December 2004 tsunami are well predicted given the uncertainty in the model setup. The good agreement between the model predictions and the analytical results and observations demonstrates that the numerical solution and wetting and drying methods employed are appropriate for modeling tsunami inundation for breaking and non-breaking long waves. Extension of the model to include sediment transport may be appropriate for long, non-breaking tsunami waves. Using available sediment transport formulations, the sediment deposit thickness at Kuala Meurisi is predicted generally within a factor of 2.

Solar prediction analysis

NASA Technical Reports Server (NTRS)

Smith, Jesse B.

1992-01-01

Solar Activity prediction is essential to definition of orbital design and operational environments for space flight. This task provides the necessary research to better understand solar predictions being generated by the solar community and to develop improved solar prediction models. The contractor shall provide the necessary manpower and facilities to perform the following tasks: (1) review, evaluate, and assess the time evolution of the solar cycle to provide probable limits of solar cycle behavior near maximum end during the decline of solar cycle 22, and the forecasts being provided by the solar community and the techniques being used to generate these forecasts; and (2) develop and refine prediction techniques for short-term solar behavior flare prediction within solar active regions, with special emphasis on the correlation of magnetic shear with flare occurrence.

One repetition maximum bench press performance: a new approach for its evaluation in inexperienced males and females: a pilot study.

PubMed

Bianco, Antonino; Filingeri, Davide; Paoli, Antonio; Palma, Antonio

2015-04-01

The aim of this study was to evaluate a new method to perform the one repetition maximum (1RM) bench press test, by combining previously validated predictive and practical procedures. Eight young male and 7 females participants, with no previous experience of resistance training, performed a first set of repetitions to fatigue (RTF) with a workload corresponding to ⅓ of their body mass (BM) for a maximum of 25 repetitions. Following a 5-min recovery period, a second set of RTF was performed with a workload corresponding to ½ of participants' BM. The number of repetitions performed in this set was then used to predict the workload to be used for the 1RM bench press test using Mayhew's equation. Oxygen consumption, heart rate and blood lactate were monitored before, during and after each 1RM attempt. A significant effect of gender was found on the maximum number of repetitions achieved during the RTF set performed with ½ of participants' BM (males: 25.0 ± 6.3; females: 11.0x± 10.6; t = 6.2; p < 0.001). The 1RM attempt performed with the workload predicted by Mayhew's equation resulted in females performing 1.2 ± 0.7 repetitions, while males performed 4.8 ± 1.9 repetitions. All participants reached their 1RM performance within 3 attempts, thus resulting in a maximum of 5 sets required to successfully perform the 1RM bench press test. We conclude that, by combining previously validated predictive equations with practical procedures (i.e. using a fraction of participants' BM to determine the workload for an RTF set), the new method we tested appeared safe, accurate (particularly in females) and time-effective in the practical evaluation of 1RM performance in inexperienced individuals. Copyright © 2014 Elsevier Ltd. All rights reserved.

Impact of climate change on runoff in Lake Urmia basin, Iran

NASA Astrophysics Data System (ADS)

Sanikhani, Hadi; Kisi, Ozgur; Amirataee, Babak

2018-04-01

Investigation of the impact of climate change on water resources is very necessary in dry and arid regions. In the first part of this paper, the climate model Long Ashton Research Station Weather Generator (LARS-WG) was used for downscaling climate data including rainfall, solar radiation, and minimum and maximum temperatures. Two different case studies including Aji-Chay and Mahabad-Chay River basins as sub-basins of Lake Urmia in the northwest part of Iran were considered. The results indicated that the LARS-WG successfully downscaled the climatic variables. By application of different emission scenarios (i.e., A1B, A2, and B1), an increasing trend in rainfall and a decreasing trend in temperature were predicted for both the basins over future time periods. In the second part of this paper, gene expression programming (GEP) was applied for simulating runoff of the basins in the future time periods including 2020, 2055, and 2090. The input combination including rainfall, solar radiation, and minimum and maximum temperatures in current and prior time was selected as the best input combination with highest predictive power for runoff prediction. The results showed that the peak discharge will decrease by 50 and 55.9% in 2090 comparing with the baseline period for the Aji-Chay and Mahabad-Chay basins, respectively. The results indicated that the sustainable adaptation strategies are necessary for these basins for protection of water resources in future.

Recent Studies of the Behavior of the Sun's White-Light Corona Over Time

NASA Technical Reports Server (NTRS)

SaintCyr, O. C.; Young, D. E.; Pesnell, W. D.; Lecinski, A.; Eddy, J.

2008-01-01

Predictions of upcoming solar cycles are often related to the nature and dynamics of the Sun's polar magnetic field and its influence on the corona. For the past 30 years we have a more-or-less continuous record of the Sun's white-light corona from groundbased and spacebased coronagraphs. Over that interval, the large scale features of the corona have varied in what we now consider a 'predictable' fashion--complex, showing multiple streamers at all latitudes during solar activity maximum; and a simple dipolar shape aligned with the rotational pole during solar minimum. Over the past three decades the white-light corona appears to be a better indicator of 'true' solar minimum than sunspot number since sunspots disappear for months (even years) at solar minimum. Since almost all predictions of the timing of the next solar maximum depend on the timing of solar minimum, the white-light corona is a potentially important observational discriminator for future predictors. In this contribution we describe recent work quantifying the large-scale appearance of the Sun's corona to correlate it with the sunspot record, especially around solar minimum. These three decades can be expanded with the HAO archive of eclipse photographs which, although sparse compared to the coronagraphic coverage, extends back to 1869. A more extensive understanding of this proxy would give researchers confidence in using the white-light corona as an indicator of solar minimum conditions.

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

NASA Technical Reports Server (NTRS)

Potter, C. S.

1997-01-01

This study describes the use of satellite data to calibrate a new climate-vegetation greenness function for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes of the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980s in order to refine our empirical understanding of intraannual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global l(sup o) gridded data sets suggest that three climate indexes: growing degree days, annual precipitation total, and an annual moisture index together can account to 70-80 percent of the variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same climate index values from the previous year explained no significant additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes was closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from l(sup o) grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes were not accurately predicted are mainly high latitude ecosystems and other remote locations where climate station data are sparse.

Correlation of Descriptive Analysis and Instrumental Puncture Testing of Watermelon Cultivars.

PubMed

Shiu, J W; Slaughter, D C; Boyden, L E; Barrett, D M

2016-06-01

The textural properties of 5 seedless watermelon cultivars were assessed by descriptive analysis and the standard puncture test using a hollow probe with increased shearing properties. The use of descriptive analysis methodology was an effective means of quantifying watermelon sensory texture profiles for characterizing specific cultivars' characteristics. Of the 10 cultivars screened, 71% of the variation in the sensory attributes was measured using the 1st 2 principal components. Pairwise correlation of the hollow puncture probe and sensory parameters determined that initial slope, maximum force, and work after maximum force measurements all correlated well to the sensory attributes crisp and firm. These findings confirm that maximum force correlates well with not only firmness in watermelon, but crispness as well. The initial slope parameter also captures the sensory crispness of watermelon, but is not as practical to measure in the field as maximum force. The work after maximum force parameter is thought to reflect cellular arrangement and membrane integrity that in turn impact sensory firmness and crispness. Watermelon cultivar types were correctly predicted by puncture test measurements in heart tissue 87% of the time, although descriptive analysis was correct 54% of the time. © 2016 Institute of Food Technologists®

Optimization of ultrasound-assisted extraction of phenolic compounds, antioxidants, and anthocyanins from grape (Vitis vinifera) seeds.

PubMed

Ghafoor, Kashif; Choi, Yong Hee; Jeon, Ju Yeong; Jo, In Hee

2009-06-10

Important functional components from Campbell Early grape seed were extracted by ultrasound-assisted extraction (UAE) technology. The experiments were carried out according to a five level, three variable central composite rotatable design (CCRD). The best possible combinations of ethanol concentration, extraction temperature, and extraction time with the application of ultrasound were obtained for the maximum extraction of phenolic compounds, antioxidant activities, and anthocyanins from grape seed by using response surface methodology (RSM). Process variables had significant effect on the extraction of functional components with extraction time being highly significant for the extraction of phenolics and antioxidants. The optimal conditions obtained by RSM for UAE from grape seed include 53.15% ethanol, 56.03 degrees C temperature, and 29.03 min time for the maximum total phenolic compounds (5.44 mg GAE/100 mL); 53.06% ethanol, 60.65 degrees C temperature, and 30.58 min time for the maximum antioxidant activity (12.31 mg/mL); and 52.35% ethanol, 55.13 degrees C temperature, and 29.49 min time for the maximum total anthocyanins (2.28 mg/mL). Under the above-mentioned conditions, the experimental total phenolics were 5.41 mg GAE/100 mL, antioxidant activity was 12.28 mg/mL, and total anthocyanins were 2.29 mg/mL of the grape seed extract, which is well matched with the predicted values.

Predicting physiological capacity of human load carriage - a review.

PubMed

Drain, Jace; Billing, Daniel; Neesham-Smith, Daniel; Aisbett, Brad

2016-01-01

This review article aims to evaluate a proposed maximum acceptable work duration model for load carriage tasks. It is contended that this concept has particular relevance to physically demanding occupations such as military and firefighting. Personnel in these occupations are often required to perform very physically demanding tasks, over varying time periods, often involving load carriage. Previous research has investigated concepts related to physiological workload limits in occupational settings (e.g. industrial). Evidence suggests however, that existing (unloaded) workload guidelines are not appropriate for load carriage tasks. The utility of this model warrants further work to enable prediction of load carriage durations across a range of functional workloads for physically demanding occupations. If the maximum duration for which personnel can physiologically sustain a load carriage task could be accurately predicted, commanders and supervisors could better plan for and manage tasks to ensure operational imperatives were met whilst minimising health risks for their workers. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Metadata Creation Tool Content Template For Data Stewards

EPA Science Inventory

A space-time Bayesian fusion model (McMillan, Holland, Morara, and Feng, 2009) is used to provide daily, gridded predictive PM_2.5 (daily average) and O₃ (daily 8-hr maximum) surfaces for 2001-2005. The fusion model uses both air quality monitoring data from ...

The needs for prediction and real-time monitoring for the flare build-up study

NASA Technical Reports Server (NTRS)

Svestka, Z.

1979-01-01

Similarities between plasma instabilities occurring in the magnetospheric tail and in active regions on the Sun are discussed. Intense observations of the flare build-up processes on the Sun planned for May and June 1980 as a part of the Solar Maximum Year are described.

Correlation of clinical predictions and surgical results in maxillary superior repositioning.

PubMed

Tabrizi, Reza; Zamiri, Barbad; Kazemi, Hamidreza

2014-05-01

This is a prospective study to evaluate the accuracy of clinical predictions related to surgical results in subjects who underwent maxillary superior repositioning without anterior-posterior movement. Surgeons' predictions according to clinical (tooth show at rest and at the maximum smile) and cephalometric evaluation were documented for the amount of maxillary superior repositioning. Overcorrection or undercorrection was documented for every subject 1 year after the operations. Receiver operating characteristic curve test was used to find a cutoff point in prediction errors and to determine positive predictive value (PPV) and negative predictive value. Forty subjects (14 males and 26 females) were studied. Results showed a significant difference between changes in the tooth show at rest and at the maximum smile line before and after surgery. Analysis of the data demonstrated no correlation between the predictive data and the surgical results. The incidence of undercorrection (25%) was more common than overcorrection (7.5%). The cutoff point for errors in predictions was 5 mm for tooth show at rest and 15 mm at the maximum smile. When the amount of the presurgical tooth show at rest was more than 5 mm, 50.5% of clinical predictions did not match the clinical results (PPV), and 75% of clinical predictions showed the same results when the tooth show was less than 5 mm (negative predictive value). When the amount of presurgical tooth shown in the maximum smile line was more than 15 mm, 75% of clinical predictions did not match with clinical results (PPV), and 25% of the predictions had the same results because the tooth show at the maximum smile was lower than 15 mm. Clinical predictions according to the tooth show at rest and at the maximum smile have a poor correlation with clinical results in maxillary superior repositioning for vertical maxillary excess. The risk of errors in predictions increased when the amount of superior repositioning of the maxilla increased. Generally, surgeons have a tendency to undercorrect rather than overcorrect, although clinical prediction is an original guideline for surgeons, and it may be associated with variable clinical results.

Maximum predictive power and the superposition principle

NASA Technical Reports Server (NTRS)

Summhammer, Johann

1994-01-01

In quantum physics the direct observables are probabilities of events. We ask how observed probabilities must be combined to achieve what we call maximum predictive power. According to this concept the accuracy of a prediction must only depend on the number of runs whose data serve as input for the prediction. We transform each probability to an associated variable whose uncertainty interval depends only on the amount of data and strictly decreases with it. We find that for a probability which is a function of two other probabilities maximum predictive power is achieved when linearly summing their associated variables and transforming back to a probability. This recovers the quantum mechanical superposition principle.

Prediction of the Ultraviolet-Visible Absorption Spectra of Polycyclic Aromatic Hydrocarbons (Dibenzo and Naphtho) Derivatives of Fluoranthene.

PubMed

Oña-Ruales, Jorge O; Ruiz-Morales, Yosadara

2017-06-01

The annellation theory method has been used to predict the locations of maximum absorbance (LMA) of the ultraviolet-visible (UV-Vis) spectral bands in the group of polycyclic aromatic hydrocarbons (PAHs) C 24 H 14 (dibenzo and naphtho) derivatives of fluoranthene (DBNFl). In this group of 21 PAHs, ten PAHs present a sextet migration pattern with four or more benzenoid rings that is potentially related to a high molecular reactivity and high mutagenic conduct. This is the first time that the locations of maximum absorbance in the UV-Vis spectra of naphth[1,2- a]aceanthrylene, dibenz[ a,l]aceanthrylene, indeno[1,2,3- de]naphthacene, naphtho[1,2- j]fluoranthene, naphth[2,1- e]acephenanthrylene, naphth[2,1- a]aceanthrylene, dibenz[ a,j]aceanthrylene, naphth[1,2- e]acephenanthrylene, and naphtho[2,1- j]fluoranthene have been predicted. Also, this represents the first report about the application of the annellation theory for the calculation of the locations of maximum absorbance in the UV-Vis spectra of PAHs with five-membered rings. Furthermore, this study constitutes the premier investigation beyond the pure benzenoid classical approach toward the establishment of a generalized annellation theory that will encompass not only homocyclic benzenoid and non-benzenoid PAHs, but also heterocyclic compounds.

Comparison of observed and predicted abutment scour at selected bridges in Maine.

DOT National Transportation Integrated Search

2008-01-01

Maximum abutment-scour depths predicted with five different methods were compared to : maximum abutment-scour depths observed at 100 abutments at 50 bridge sites in Maine with a : median bridge age of 66 years. Prediction methods included the Froehli...

Geomagnetic storm forecasting service StormFocus: 5 years online

NASA Astrophysics Data System (ADS)

Podladchikova, Tatiana; Petrukovich, Anatoly; Yermolaev, Yuri

2018-04-01

Forecasting geomagnetic storms is highly important for many space weather applications. In this study, we review performance of the geomagnetic storm forecasting service StormFocus during 2011-2016. The service was implemented in 2011 at SpaceWeather.Ru and predicts the expected strength of geomagnetic storms as measured by Dst index several hours ahead. The forecast is based on L1 solar wind and IMF measurements and is updated every hour. The solar maximum of cycle 24 is weak, so most of the statistics are on rather moderate storms. We verify quality of selection criteria, as well as reliability of real-time input data in comparison with the final values, available in archives. In real-time operation 87% of storms were correctly predicted while the reanalysis running on final OMNI data predicts successfully 97% of storms. Thus the main reasons for prediction errors are discrepancies between real-time and final data (Dst, solar wind and IMF) due to processing errors, specifics of datasets.

Evidence for the Role of Proton Shell Closure in Quasifission Reactions from X-Ray Fluorescence of Mass-Identified Fragments

NASA Astrophysics Data System (ADS)

Morjean, M.; Hinde, D. J.; Simenel, C.; Jeung, D. Y.; Airiau, M.; Cook, K. J.; Dasgupta, M.; Drouart, A.; Jacquet, D.; Kalkal, S.; Palshetkar, C. S.; Prasad, E.; Rafferty, D.; Simpson, E. C.; Tassan-Got, L.; Vo-Phuoc, K.; Williams, E.

2017-12-01

The atomic numbers and the masses of fragments formed in quasifission reactions are simultaneously measured at scission in 48Ti + 238U reactions at a laboratory energy of 286 MeV. The atomic numbers are determined from measured characteristic fluorescence x rays, whereas the masses are obtained from the emission angles and times of flight of the two emerging fragments. For the first time, thanks to this full identification of the quasifission fragments on a broad angular range, the important role of the proton shell closure at Z =82 is evidenced by the associated maximum production yield, a maximum predicted by time-dependent Hartree-Fock calculations. This new experimental approach gives now access to precise studies of the time dependence of the N /Z (neutron over proton ratios of the fragments) evolution in quasifission reactions.

Maximum spectral demands in the near-fault region

USGS Publications Warehouse

Huang, Yin-Nan; Whittaker, Andrew S.; Luco, Nicolas

2008-01-01

The Next Generation Attenuation (NGA) relationships for shallow crustal earthquakes in the western United States predict a rotated geometric mean of horizontal spectral demand, termed GMRotI50, and not maximum spectral demand. Differences between strike-normal, strike-parallel, geometric-mean, and maximum spectral demands in the near-fault region are investigated using 147 pairs of records selected from the NGA strong motion database. The selected records are for earthquakes with moment magnitude greater than 6.5 and for closest site-to-fault distance less than 15 km. Ratios of maximum spectral demand to NGA-predicted GMRotI50 for each pair of ground motions are presented. The ratio shows a clear dependence on period and the Somerville directivity parameters. Maximum demands can substantially exceed NGA-predicted GMRotI50 demands in the near-fault region, which has significant implications for seismic design, seismic performance assessment, and the next-generation seismic design maps. Strike-normal spectral demands are a significantly unconservative surrogate for maximum spectral demands for closest distance greater than 3 to 5 km. Scale factors that transform NGA-predicted GMRotI50 to a maximum spectral demand in the near-fault region are proposed.

Maximum spectral demands in the near-fault region

USGS Publications Warehouse

Huang, Y.-N.; Whittaker, A.S.; Luco, N.

2008-01-01

The Next Generation Attenuation (NGA) relationships for shallow crustal earthquakes in the western United States predict a rotated geometric mean of horizontal spectral demand, termed GMRotI50, and not maximum spectral demand. Differences between strike-normal, strike-parallel, geometric-mean, and maximum spectral demands in the near-fault region are investigated using 147 pairs of records selected from the NGA strong motion database. The selected records are for earthquakes with moment magnitude greater than 6.5 and for closest site-to-fault distance less than 15 km. Ratios of maximum spectral demand to NGA-predicted GMRotI50 for each pair of ground motions are presented. The ratio shows a clear dependence on period and the Somerville directivity parameters. Maximum demands can substantially exceed NGA-predicted GMRotI50 demands in the near-fault region, which has significant implications for seismic design, seismic performance assessment, and the next-generation seismic design maps. Strike-normal spectral demands are a significantly unconservative surrogate for maximum spectral demands for closest distance greater than 3 to 5 km. Scale factors that transform NGA-predicted GMRotI50 to a maximum spectral demand in the near-fault region are proposed. ?? 2008, Earthquake Engineering Research Institute.

Demand theory of gene regulation. II. Quantitative application to the lactose and maltose operons of Escherichia coli.

PubMed Central

Savageau, M A

1998-01-01

Induction of gene expression can be accomplished either by removing a restraining element (negative mode of control) or by providing a stimulatory element (positive mode of control). According to the demand theory of gene regulation, which was first presented in qualitative form in the 1970s, the negative mode will be selected for the control of a gene whose function is in low demand in the organism's natural environment, whereas the positive mode will be selected for the control of a gene whose function is in high demand. This theory has now been further developed in a quantitative form that reveals the importance of two key parameters: cycle time C, which is the average time for a gene to complete an ON/OFF cycle, and demand D, which is the fraction of the cycle time that the gene is ON. Here we estimate nominal values for the relevant mutation rates and growth rates and apply the quantitative demand theory to the lactose and maltose operons of Escherichia coli. The results define regions of the C vs. D plot within which selection for the wild-type regulatory mechanisms is realizable, and these in turn provide the first estimates for the minimum and maximum values of demand that are required for selection of the positive and negative modes of gene control found in these systems. The ratio of mutation rate to selection coefficient is the most relevant determinant of the realizable region for selection, and the most influential parameter is the selection coefficient that reflects the reduction in growth rate when there is superfluous expression of a gene. The quantitative theory predicts the rate and extent of selection for each mode of control. It also predicts three critical values for the cycle time. The predicted maximum value for the cycle time C is consistent with the lifetime of the host. The predicted minimum value for C is consistent with the time for transit through the intestinal tract without colonization. Finally, the theory predicts an optimum value of C that is in agreement with the observed frequency for E. coli colonizing the human intestinal tract. PMID:9691028

Financial time series prediction using spiking neural networks.

PubMed

Reid, David; Hussain, Abir Jaafar; Tawfik, Hissam

2014-01-01

In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments.

Mars surface radiation exposure for solar maximum conditions and 1989 solar proton events

NASA Technical Reports Server (NTRS)

Simonsen, Lisa C.; Nealy, John E.

1992-01-01

The Langley heavy-ion/nucleon transport code, HZETRN, and the high-energy nucleon transport code, BRYNTRN, are used to predict the propagation of galactic cosmic rays (GCR's) and solar flare protons through the carbon dioxide atmosphere of Mars. Particle fluences and the resulting doses are estimated on the surface of Mars for GCR's during solar maximum conditions and the Aug., Sep., and Oct. 1989 solar proton events. These results extend previously calculated surface estimates for GCR's at solar minimum conditions and the Feb. 1956, Nov. 1960, and Aug. 1972 solar proton events. Surface doses are estimated with both a low-density and a high-density carbon dioxide model of the atmosphere for altitudes of 0, 4, 8, and 12 km above the surface. A solar modulation function is incorporated to estimate the GCR dose variation between solar minimum and maximum conditions over the 11-year solar cycle. By using current Mars mission scenarios, doses to the skin, eye, and blood-forming organs are predicted for short- and long-duration stay times on the Martian surface throughout the solar cycle.

Forecasting electricity usage using univariate time series models

NASA Astrophysics Data System (ADS)

Hock-Eam, Lim; Chee-Yin, Yip

2014-12-01

Electricity is one of the important energy sources. A sufficient supply of electricity is vital to support a country's development and growth. Due to the changing of socio-economic characteristics, increasing competition and deregulation of electricity supply industry, the electricity demand forecasting is even more important than before. It is imperative to evaluate and compare the predictive performance of various forecasting methods. This will provide further insights on the weakness and strengths of each method. In literature, there are mixed evidences on the best forecasting methods of electricity demand. This paper aims to compare the predictive performance of univariate time series models for forecasting the electricity demand using a monthly data of maximum electricity load in Malaysia from January 2003 to December 2013. Results reveal that the Box-Jenkins method produces the best out-of-sample predictive performance. On the other hand, Holt-Winters exponential smoothing method is a good forecasting method for in-sample predictive performance.

Maximum magnitude estimations of induced earthquakes at Paradox Valley, Colorado, from cumulative injection volume and geometry of seismicity clusters

NASA Astrophysics Data System (ADS)

Yeck, William L.; Block, Lisa V.; Wood, Christopher K.; King, Vanessa M.

2015-01-01

The Paradox Valley Unit (PVU), a salinity control project in southwest Colorado, disposes of brine in a single deep injection well. Since the initiation of injection at the PVU in 1991, earthquakes have been repeatedly induced. PVU closely monitors all seismicity in the Paradox Valley region with a dense surface seismic network. A key factor for understanding the seismic hazard from PVU injection is the maximum magnitude earthquake that can be induced. The estimate of maximum magnitude of induced earthquakes is difficult to constrain as, unlike naturally occurring earthquakes, the maximum magnitude of induced earthquakes changes over time and is affected by injection parameters. We investigate temporal variations in maximum magnitudes of induced earthquakes at the PVU using two methods. First, we consider the relationship between the total cumulative injected volume and the history of observed largest earthquakes at the PVU. Second, we explore the relationship between maximum magnitude and the geometry of individual seismicity clusters. Under the assumptions that: (i) elevated pore pressures must be distributed over an entire fault surface to initiate rupture and (ii) the location of induced events delineates volumes of sufficiently high pore-pressure to induce rupture, we calculate the largest allowable vertical penny-shaped faults, and investigate the potential earthquake magnitudes represented by their rupture. Results from both the injection volume and geometrical methods suggest that the PVU has the potential to induce events up to roughly MW 5 in the region directly surrounding the well; however, the largest observed earthquake to date has been about a magnitude unit smaller than this predicted maximum. In the seismicity cluster surrounding the injection well, the maximum potential earthquake size estimated by these methods and the observed maximum magnitudes have remained steady since the mid-2000s. These observations suggest that either these methods overpredict maximum magnitude for this area or that long time delays are required for sufficient pore-pressure diffusion to occur to cause rupture along an entire fault segment. We note that earthquake clusters can initiate and grow rapidly over the course of 1 or 2 yr, thus making it difficult to predict maximum earthquake magnitudes far into the future. The abrupt onset of seismicity with injection indicates that pore-pressure increases near the well have been sufficient to trigger earthquakes under pre-existing tectonic stresses. However, we do not observe remote triggering from large teleseismic earthquakes, which suggests that the stress perturbations generated from those events are too small to trigger rupture, even with the increased pore pressures.

Actividad solar del ciclo 23. Predicción del máximo y fase decreciente utilizando redes neuronales

NASA Astrophysics Data System (ADS)

Parodi, M. A.; Ceccatto, H. A.; Piacentini, R. D.; García, P. J.

Different methods have been proposed in order to predict the maximum amplitude of solar cycles, either as a consequence of the intrinsic importance of this event and because of its relation with solar storms and possible effects upon satellites, communication systems, etc. In this work, a neural network solar activity prediction is presented, measured through the sunspot number (SSN). The 16-units neural network, with a 12:3:1 architecture, was trained in a ``feed-forward" propagation way and learning by the so called ``back propagation rule". The annual mean SSN data in the 1700-1975 and 1987-1998 periods were used as the training set. The solar cycle 21 (1976-1986) was taken as the cross-validation data set. After performing the network training we obtained a prediction of the maximum annual mean for the current solar cycle 23, SSNmax= 135 ±17 at the year 2000, which is 13% smaller than the International Consensus Commitee's mean maximum prediction obtained through ``precursor techniques". On the other hand, our prediction is only about 4% smaller than the Consensus's neural network mean prediction. A ``multiple step" prediction technique was also performed and SSN annual mean predicted values for the near-maximum (from the present year 1999 to beyond the maximum) and the declining activity of solar cycle 23 are presented in this work. The sensibility of predictions is also tested. To do so, we changed the interval width and comparated our results with those of a previous neural network prediction and those of others authors using differents methods.

Variation and Grey GM(1, 1) Prediction of Melting Peak Temperature of Polypropylene During Ultraviolet Radiation Aging

NASA Astrophysics Data System (ADS)

Chen, K.; Y Zhang, T.; Zhang, F.; Zhang, Z. R.

2017-12-01

Grey system theory regards uncertain system in which information is known partly and unknown partly as research object, extracts useful information from part known, and thereby revealing the potential variation rule of the system. In order to research the applicability of data-driven modelling method in melting peak temperature (T m) fitting and prediction of polypropylene (PP) during ultraviolet radiation aging, the T m of homo-polypropylene after different ultraviolet radiation exposure time investigated by differential scanning calorimeter was fitted and predicted by grey GM(1, 1) model based on grey system theory. The results show that the T m of PP declines with the prolong of aging time, and fitting and prediction equation obtained by grey GM(1, 1) model is T m = 166.567472exp(-0.00012t). Fitting effect of the above equation is excellent and the maximum relative error between prediction value and actual value of T m is 0.32%. Grey system theory needs less original data, has high prediction accuracy, and can be used to predict aging behaviour of PP.

Characterization of Neutropenia in Advanced Cancer Patients Following Palbociclib Treatment Using a Population Pharmacokinetic-Pharmacodynamic Modeling and Simulation Approach.

PubMed

Sun, Wan; O'Dwyer, Peter J; Finn, Richard S; Ruiz-Garcia, Ana; Shapiro, Geoffrey I; Schwartz, Gary K; DeMichele, Angela; Wang, Diane

2017-09-01

Neutropenia is the most commonly reported hematologic toxicity following treatment with palbociclib, a cyclin-dependent kinase 4/6 inhibitor approved for metastatic breast cancer. Using data from 185 advanced cancer patients receiving palbociclib in 3 clinical trials, a pharmacokinetic-pharmacodynamic model was developed to describe the time course of absolute neutrophil count (ANC) and quantify the exposure-response relationship for neutropenia. These analyses help in understanding neutropenia associated with palbociclib and its comparison with chemotherapy-induced neutropenia. In the model, palbociclib plasma concentration was related to its antiproliferative effect on precursor cells through drug-related parameters (ie, maximum estimated drug effect and concentration corresponding to 50% of the maximum effect), and neutrophil physiology was mimicked through system-related parameters (ie, mean transit time, baseline ANC, and feedback parameter). Sex and baseline albumin level were significant covariates for baseline ANC. It was demonstrated by different model evaluation approaches (eg, prediction-corrected visual predictive check and standardized visual predictive check) that the final model adequately described longitudinal ANC with good predictive capability. The established model suggested that higher palbociclib exposure was associated with lower longitudinal neutrophil counts. The ANC nadir was reached approximately 21 days after palbociclib treatment initiation. Consistent with their mechanisms of action, neutropenia associated with palbociclib (cytostatic) was rapidly reversible and noncumulative, with a notably weaker antiproliferative effect on precursor cells relative to chemotherapies (cytotoxic). This pharmacokinetic-pharmacodynamic model aids in predicting neutropenia and optimizing dosing for future palbociclib trials with different dosing regimen combinations. © 2017, The American College of Clinical Pharmacology.

Applications of a New England stream temperature model to evaluate distribution of thermal regimes and sensitivity to change in riparian condition

EPA Science Inventory

We have applied a statistical stream network (SSN) model to predict stream thermal metrics (summer monthly medians, growing season maximum magnitude and timing, and daily rates of change) across New England nontidal streams and rivers, excluding northern Maine watersheds that ext...

Spatio-temporal observations of tertiary ozone maximum

NASA Astrophysics Data System (ADS)

Sofieva, V. F.; Kyrölä, E.; Verronen, P. T.; Seppälä, A.; Tamminen, J.; Marsh, D. R.; Smith, A. K.; Bertaux, J.-L.; Hauchecorne, A.; Dalaudier, F.; Fussen, D.; Vanhellemont, F.; Fanton D'Andon, O.; Barrot, G.; Guirlet, M.; Fehr, T.; Saavedra, L.

2009-03-01

We present spatio-temporal distributions of tertiary ozone maximum (TOM), based on GOMOS (Global Ozone Monitoring by Occultation of Stars) ozone measurements in 2002-2006. The tertiary ozone maximum is typically observed in the high-latitude winter mesosphere at altitude ~72 km. Although the explanation for this phenomenon has been found recently - low concentrations of odd-hydrogen cause the subsequent decrease in odd-oxygen losses - models have had significant deviations from existing observations until recently. Good coverage of polar night regions by GOMOS data has allowed for the first time obtaining spatial and temporal observational distributions of night-time ozone mixing ratio in the mesosphere. The distributions obtained from GOMOS data have specific features, which are variable from year to year. In particular, due to a long lifetime of ozone in polar night conditions, the downward transport of polar air by the meridional circulation is clearly observed in the tertiary ozone maximum time series. Although the maximum tertiary ozone mixing ratio is achieved close to the polar night terminator (as predicted by the theory), TOM can be observed also at very high latitudes, not only in the beginning and at the end, but also in the middle of winter. We have compared the observational spatio-temporal distributions of tertiary ozone maximum with that obtained using WACCM (Whole Atmosphere Community Climate Model) and found that the specific features are reproduced satisfactorily by the model. Since ozone in the mesosphere is very sensitive to HOx concentrations, energetic particle precipitation can significantly modify the shape of the ozone profiles. In particular, GOMOS observations have shown that the tertiary ozone maximum was temporarily destroyed during the January 2005 and December 2006 solar proton events as a result of the HOx enhancement from the increased ionization.

Spatio-temporal observations of the tertiary ozone maximum

NASA Astrophysics Data System (ADS)

Sofieva, V. F.; Kyrölä, E.; Verronen, P. T.; Seppälä, A.; Tamminen, J.; Marsh, D. R.; Smith, A. K.; Bertaux, J.-L.; Hauchecorne, A.; Dalaudier, F.; Fussen, D.; Vanhellemont, F.; Fanton D'Andon, O.; Barrot, G.; Guirlet, M.; Fehr, T.; Saavedra, L.

2009-07-01

We present spatio-temporal distributions of the tertiary ozone maximum (TOM), based on GOMOS (Global Ozone Monitoring by Occultation of Stars) ozone measurements in 2002-2006. The tertiary ozone maximum is typically observed in the high-latitude winter mesosphere at an altitude of ~72 km. Although the explanation for this phenomenon has been found recently - low concentrations of odd-hydrogen cause the subsequent decrease in odd-oxygen losses - models have had significant deviations from existing observations until recently. Good coverage of polar night regions by GOMOS data has allowed for the first time to obtain spatial and temporal observational distributions of night-time ozone mixing ratio in the mesosphere. The distributions obtained from GOMOS data have specific features, which are variable from year to year. In particular, due to a long lifetime of ozone in polar night conditions, the downward transport of polar air by the meridional circulation is clearly observed in the tertiary ozone maximum time series. Although the maximum tertiary ozone mixing ratio is achieved close to the polar night terminator (as predicted by the theory), TOM can be observed also at very high latitudes, not only in the beginning and at the end, but also in the middle of winter. We have compared the observational spatio-temporal distributions of the tertiary ozone maximum with that obtained using WACCM (Whole Atmosphere Community Climate Model) and found that the specific features are reproduced satisfactorily by the model. Since ozone in the mesosphere is very sensitive to HOx concentrations, energetic particle precipitation can significantly modify the shape of the ozone profiles. In particular, GOMOS observations have shown that the tertiary ozone maximum was temporarily destroyed during the January 2005 and December 2006 solar proton events as a result of the HOx enhancement from the increased ionization.

Maximum Likelihood Time-of-Arrival Estimation of Optical Pulses via Photon-Counting Photodetectors

NASA Technical Reports Server (NTRS)

Erkmen, Baris I.; Moision, Bruce E.

2010-01-01

Many optical imaging, ranging, and communications systems rely on the estimation of the arrival time of an optical pulse. Recently, such systems have been increasingly employing photon-counting photodetector technology, which changes the statistics of the observed photocurrent. This requires time-of-arrival estimators to be developed and their performances characterized. The statistics of the output of an ideal photodetector, which are well modeled as a Poisson point process, were considered. An analytical model was developed for the mean-square error of the maximum likelihood (ML) estimator, demonstrating two phenomena that cause deviations from the minimum achievable error at low signal power. An approximation was derived to the threshold at which the ML estimator essentially fails to provide better than a random guess of the pulse arrival time. Comparing the analytic model performance predictions to those obtained via simulations, it was verified that the model accurately predicts the ML performance over all regimes considered. There is little prior art that attempts to understand the fundamental limitations to time-of-arrival estimation from Poisson statistics. This work establishes both a simple mathematical description of the error behavior, and the associated physical processes that yield this behavior. Previous work on mean-square error characterization for ML estimators has predominantly focused on additive Gaussian noise. This work demonstrates that the discrete nature of the Poisson noise process leads to a distinctly different error behavior.

Predicting Long-term Temperature Increase for Time-Dependent SAR Levels with a Single Short-term Temperature Response

PubMed Central

Carluccio, Giuseppe; Bruno, Mary; Collins, Christopher M.

2015-01-01

Purpose Present a novel method for rapid prediction of temperature in vivo for a series of pulse sequences with differing levels and distributions of specific energy absorption rate (SAR). Methods After the temperature response to a brief period of heating is characterized, a rapid estimate of temperature during a series of periods at different heating levels is made using a linear heat equation and Impulse-Response (IR) concepts. Here the initial characterization and long-term prediction for a complete spine exam are made with the Pennes’ bioheat equation where, at first, core body temperature is allowed to increase and local perfusion is not. Then corrections through time allowing variation in local perfusion are introduced. Results The fast IR-based method predicted maximum temperature increase within 1% of that with a full finite difference simulation, but required less than 3.5% of the computation time. Even higher accelerations are possible depending on the time step size chosen, with loss in temporal resolution. Correction for temperature-dependent perfusion requires negligible additional time, and can be adjusted to be more or less conservative than the corresponding finite difference simulation. Conclusion With appropriate methods, it is possible to rapidly predict temperature increase throughout the body for actual MR examinations. (200/200 words) PMID:26096947

Predicting long-term temperature increase for time-dependent SAR levels with a single short-term temperature response.

PubMed

Carluccio, Giuseppe; Bruno, Mary; Collins, Christopher M

2016-05-01

Present a novel method for rapid prediction of temperature in vivo for a series of pulse sequences with differing levels and distributions of specific energy absorption rate (SAR). After the temperature response to a brief period of heating is characterized, a rapid estimate of temperature during a series of periods at different heating levels is made using a linear heat equation and impulse-response (IR) concepts. Here the initial characterization and long-term prediction for a complete spine exam are made with the Pennes' bioheat equation where, at first, core body temperature is allowed to increase and local perfusion is not. Then corrections through time allowing variation in local perfusion are introduced. The fast IR-based method predicted maximum temperature increase within 1% of that with a full finite difference simulation, but required less than 3.5% of the computation time. Even higher accelerations are possible depending on the time step size chosen, with loss in temporal resolution. Correction for temperature-dependent perfusion requires negligible additional time and can be adjusted to be more or less conservative than the corresponding finite difference simulation. With appropriate methods, it is possible to rapidly predict temperature increase throughout the body for actual MR examinations. © 2015 Wiley Periodicals, Inc.

CEDAR-GEM Challenge for Systematic Assessment of Ionosphere/Thermosphere Models in Predicting TEC During the 2006 December Storm Event

NASA Astrophysics Data System (ADS)

Shim, J. S.; Rastätter, L.; Kuznetsova, M.; Bilitza, D.; Codrescu, M.; Coster, A. J.; Emery, B. A.; Fedrizzi, M.; Förster, M.; Fuller-Rowell, T. J.; Gardner, L. C.; Goncharenko, L.; Huba, J.; McDonald, S. E.; Mannucci, A. J.; Namgaladze, A. A.; Pi, X.; Prokhorov, B. E.; Ridley, A. J.; Scherliess, L.; Schunk, R. W.; Sojka, J. J.; Zhu, L.

2017-10-01

In order to assess current modeling capability of reproducing storm impacts on total electron content (TEC), we considered quantities such as TEC, TEC changes compared to quiet time values, and the maximum value of the TEC and TEC changes during a storm. We compared the quantities obtained from ionospheric models against ground-based GPS TEC measurements during the 2006 AGU storm event (14-15 December 2006) in the selected eight longitude sectors. We used 15 simulations obtained from eight ionospheric models, including empirical, physics-based, coupled ionosphere-thermosphere, and data assimilation models. To quantitatively evaluate performance of the models in TEC prediction during the storm, we calculated skill scores such as RMS error, Normalized RMS error (NRMSE), ratio of the modeled to observed maximum increase (Yield), and the difference between the modeled peak time and observed peak time. Furthermore, to investigate latitudinal dependence of the performance of the models, the skill scores were calculated for five latitude regions. Our study shows that RMSE of TEC and TEC changes of the model simulations range from about 3 TECU (total electron content unit, 1 TECU = 1016 el m-2) (in high latitudes) to about 13 TECU (in low latitudes), which is larger than latitudinal average GPS TEC error of about 2 TECU. Most model simulations predict TEC better than TEC changes in terms of NRMSE and the difference in peak time, while the opposite holds true in terms of Yield. Model performance strongly depends on the quantities considered, the type of metrics used, and the latitude considered.

Weather variability and the incidence of cryptosporidiosis: comparison of time series poisson regression and SARIMA models.

PubMed

Hu, Wenbiao; Tong, Shilu; Mengersen, Kerrie; Connell, Des

2007-09-01

Few studies have examined the relationship between weather variables and cryptosporidiosis in Australia. This paper examines the potential impact of weather variability on the transmission of cryptosporidiosis and explores the possibility of developing an empirical forecast system. Data on weather variables, notified cryptosporidiosis cases, and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics for the period of January 1, 1996-December 31, 2004, respectively. Time series Poisson regression and seasonal auto-regression integrated moving average (SARIMA) models were performed to examine the potential impact of weather variability on the transmission of cryptosporidiosis. Both the time series Poisson regression and SARIMA models show that seasonal and monthly maximum temperature at a prior moving average of 1 and 3 months were significantly associated with cryptosporidiosis disease. It suggests that there may be 50 more cases a year for an increase of 1 degrees C maximum temperature on average in Brisbane. Model assessments indicated that the SARIMA model had better predictive ability than the Poisson regression model (SARIMA: root mean square error (RMSE): 0.40, Akaike information criterion (AIC): -12.53; Poisson regression: RMSE: 0.54, AIC: -2.84). Furthermore, the analysis of residuals shows that the time series Poisson regression appeared to violate a modeling assumption, in that residual autocorrelation persisted. The results of this study suggest that weather variability (particularly maximum temperature) may have played a significant role in the transmission of cryptosporidiosis. A SARIMA model may be a better predictive model than a Poisson regression model in the assessment of the relationship between weather variability and the incidence of cryptosporidiosis.

A spatiotemporal dengue fever early warning model accounting for nonlinear associations with meteorological factors: a Bayesian maximum entropy approach

NASA Astrophysics Data System (ADS)

Lee, Chieh-Han; Yu, Hwa-Lung; Chien, Lung-Chang

2014-05-01

Dengue fever has been identified as one of the most widespread vector-borne diseases in tropical and sub-tropical. In the last decade, dengue is an emerging infectious disease epidemic in Taiwan especially in the southern area where have annually high incidences. For the purpose of disease prevention and control, an early warning system is urgently needed. Previous studies have showed significant relationships between climate variables, in particular, rainfall and temperature, and the temporal epidemic patterns of dengue cases. However, the transmission of the dengue fever is a complex interactive process that mostly understated the composite space-time effects of dengue fever. This study proposes developing a one-week ahead warning system of dengue fever epidemics in the southern Taiwan that considered nonlinear associations between weekly dengue cases and meteorological factors across space and time. The early warning system based on an integration of distributed lag nonlinear model (DLNM) and stochastic Bayesian Maximum Entropy (BME) analysis. The study identified the most significant meteorological measures including weekly minimum temperature and maximum 24-hour rainfall with continuous 15-week lagged time to dengue cases variation under condition of uncertainty. Subsequently, the combination of nonlinear lagged effects of climate variables and space-time dependence function is implemented via a Bayesian framework to predict dengue fever occurrences in the southern Taiwan during 2012. The result shows the early warning system is useful for providing potential outbreak spatio-temporal prediction of dengue fever distribution. In conclusion, the proposed approach can provide a practical disease control tool for environmental regulators seeking more effective strategies for dengue fever prevention.

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

NASA Technical Reports Server (NTRS)

Potter, C. S.; Brooks, V.

1997-01-01

This paper describes the use of satellite data to calibrate a new climate-vegetation greenness relationship for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes If the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980's in order to refine our understanding of intra-annual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global 1o gridded data sets suggest that three climate indexes: degree days (growing/chilling), annual precipitation total, and an annual moisture index together can account to 70-80 percent of the geographic variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same annual climate index values from the previous year explains no substantial additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes is closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from lo grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI for several different years at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes are not accurately predicted are mainly high latitude zones, mixed and disturbed vegetation types, and other remote locations where climate station data are sparse.

Assessment of umbilical artery flow and fetal heart rate to predict delivery time in bitches.

PubMed

Giannico, Amália Turner; Garcia, Daniela Aparecida Ayres; Gil, Elaine Mayumi Ueno; Sousa, Marlos Gonçalves; Froes, Tilde Rodrigues

2016-10-15

The aim of this study was to quantitatively investigate the oscillation of the fetal heart rate (HR) in advance of normal delivery and whether this index could be used to indicate impending delivery. In addition, fetal HR oscillation and umbilical artery resistive index (RI) were correlated to determine if the combination of these parameters provided a more accurate prediction of the time of delivery. Sonographic evaluation was performed in 11 pregnant bitches to evaluate the fetal HR and umbilical artery RI at the following antepartum times: 120 to 96 hours, 72 to 48 hours, 24 to 12 hours, and 12 to 1 hours. Statistical analysis indicated a correlation between the oscillation of fetal HR and the umbilical artery RI. As delivery approached a considerable reduction in the umbilical artery RI was documented and greater oscillations between maximum and minimum HRs occurred. We conclude that the quantitative analysis of fetal HR oscillations may be used to predict the time of delivery in bitches. The combination of fetal HR and umbilical artery RI together may provide more accurate predictions of time of delivery. Copyright © 2016 Elsevier Inc. All rights reserved.

Optimization of radiation treatment of ginger ( Zingiber officinale) rhizomes using response surface methodology

NASA Astrophysics Data System (ADS)

Nketsia-Tabiri, Josephine

1998-06-01

The effects of pre-irradiation storage time (7-21 days), radiation dose (0-75 Gy) and post-irradiation storage time (2-20 weeks) on sprouting, wrinkling and weight loss of ginger was investigated using a central composite rotatable design. Predictive models developed for all three responses were highly significant. Weight loss and wrinkling decreased as pre-irradiation storage time increased. Dose and post-irradiation storage time had significant interactive effects on weight loss and sprouting. Processing conditions for achieving minimal sprouting resulted in maximum weight loss and wrinkling.

Population pharmacokinetics and maximum a posteriori probability Bayesian estimator of abacavir: application of individualized therapy in HIV-infected infants and toddlers

PubMed Central

Zhao, Wei; Cella, Massimo; Della Pasqua, Oscar; Burger, David; Jacqz-Aigrain, Evelyne

2012-01-01

AIMS To develop a population pharmacokinetic model for abacavir in HIV-infected infants and toddlers, which will be used to describe both once and twice daily pharmacokinetic profiles, identify covariates that explain variability and propose optimal time points to optimize the area under the concentration–time curve (AUC) targeted dosage and individualize therapy. METHODS The pharmacokinetics of abacavir was described with plasma concentrations from 23 patients using nonlinear mixed-effects modelling (NONMEM) software. A two-compartment model with first-order absorption and elimination was developed. The final model was validated using bootstrap, visual predictive check and normalized prediction distribution errors. The Bayesian estimator was validated using the cross-validation and simulation–estimation method. RESULTS The typical population pharmacokinetic parameters and relative standard errors (RSE) were apparent systemic clearance (CL) 13.4 l h−1 (RSE 6.3%), apparent central volume of distribution 4.94 l (RSE 28.7%), apparent peripheral volume of distribution 8.12 l (RSE14.2%), apparent intercompartment clearance 1.25 l h−1 (RSE 16.9%) and absorption rate constant 0.758 h−1 (RSE 5.8%). The covariate analysis identified weight as the individual factor influencing the apparent oral clearance: CL = 13.4 × (weight/12)1.14. The maximum a posteriori probability Bayesian estimator, based on three concentrations measured at 0, 1 or 2, and 3 h after drug intake allowed predicting individual AUC0–t. CONCLUSIONS The population pharmacokinetic model developed for abacavir in HIV-infected infants and toddlers accurately described both once and twice daily pharmacokinetic profiles. The maximum a posteriori probability Bayesian estimator of AUC0–t was developed from the final model and can be used routinely to optimize individual dosing. PMID:21988586

Real time identification of the internal combustion engine combustion parameters based on the vibration velocity signal

NASA Astrophysics Data System (ADS)

Zhao, Xiuliang; Cheng, Yong; Wang, Limei; Ji, Shaobo

2017-03-01

Accurate combustion parameters are the foundations of effective closed-loop control of engine combustion process. Some combustion parameters, including the start of combustion, the location of peak pressure, the maximum pressure rise rate and its location, can be identified from the engine block vibration signals. These signals often include non-combustion related contributions, which limit the prompt acquisition of the combustion parameters computationally. The main component in these non-combustion related contributions is considered to be caused by the reciprocating inertia force excitation (RIFE) of engine crank train. A mathematical model is established to describe the response of the RIFE. The parameters of the model are recognized with a pattern recognition algorithm, and the response of the RIFE is predicted and then the related contributions are removed from the measured vibration velocity signals. The combustion parameters are extracted from the feature points of the renovated vibration velocity signals. There are angle deviations between the feature points in the vibration velocity signals and those in the cylinder pressure signals. For the start of combustion, a system bias is adopted to correct the deviation and the error bound of the predicted parameters is within 1.1°. To predict the location of the maximum pressure rise rate and the location of the peak pressure, algorithms based on the proportion of high frequency components in the vibration velocity signals are introduced. Tests results show that the two parameters are able to be predicted within 0.7° and 0.8° error bound respectively. The increase from the knee point preceding the peak value point to the peak value in the vibration velocity signals is used to predict the value of the maximum pressure rise rate. Finally, a monitoring frame work is inferred to realize the combustion parameters prediction. Satisfactory prediction for combustion parameters in successive cycles is achieved, which validates the proposed methods.

Predicting the mortality from asbestos-related diseases based on the amount of asbestos used and the effects of slate buildings in Korea.

PubMed

Kim, Su-Young; Kim, Young-Chan; Kim, Yongku; Hong, Won-Hwa

2016-01-15

Asbestos has been used since ancient times, owing to its heat-resistant, rot-proof, and insulating qualities, and its usage rapidly increased after the industrial revolution. In Korea, all slates were previously manufactured in a mixture of about 90% cement and 10% chrysotile (white asbestos). This study used a Generalized Poisson regression (GPR) model after creating databases of the mortality from asbestos-related diseases and of the amount of asbestos used in Korea as a means to predict the future mortality of asbestos-related diseases and mesothelioma in Korea. Moreover, to predict the future mortality according to the effects of slate buildings, a comparative analysis based on the result of the GPR model was conducted after creating databases of the amount of asbestos used in Korea and of the amount of asbestos used in making slates. We predicted the mortality from asbestos-related diseases by year, from 2014 to 2036, according to the amount of asbestos used. As a result, it was predicted that a total of 1942 people (maximum, 3476) will die by 2036. Moreover, based on the comparative analysis according to the influence index, it was predicted that a maximum of 555 people will die from asbestos-related diseases by 2031 as a result of the effects of asbestos-containing slate buildings, and the mortality was predicted to peak in 2021, with 53 cases. Although mesothelioma and pulmonary asbestosis were considered as asbestos-related diseases, these are not the only two diseases caused by asbestos. However the results of this study are highly important and relevant, as, for the first time in Korea, the future mortality from asbestos-related diseases was predicted. These findings are expected to contribute greatly to the Korean government's policies related to the compensation for asbestos victims. Copyright © 2015 Elsevier B.V. All rights reserved.

Prediction of Maximum Oxygen Consumption from Walking, Jogging, or Running.

ERIC Educational Resources Information Center

Larsen, Gary E.; George, James D.; Alexander, Jeffrey L.; Fellingham, Gilbert W.; Aldana, Steve G.; Parcell, Allen C.

2002-01-01

Developed a cardiorespiratory endurance test that retained the inherent advantages of submaximal testing while eliminating reliance on heart rate measurement in predicting maximum oxygen uptake (VO2max). College students completed three exercise tests. The 1.5-mile endurance test predicted VO2max from submaximal exercise without requiring heart…

Modeling of drop breakup in the bag breakup regime

NASA Astrophysics Data System (ADS)

Wang, C.; Chang, S.; Wu, H.; Xu, J.

2014-04-01

Several analytic models for predicting the drop deformation and breakup have been developed over the last three decades, but modeling drop breakup in the bag-type regime is less reported. In this Letter, a breakup model has been proposed to predict the drop deformation length and breakup time in the bag-type breakup regime in a more accurate manner. In the present model, the drop deformation which is approximately as the displacement of the centre of mass (c. m.) along the axis located at the centre of the drop, and the movement of c. m. is obtained by solving the pressure balance equation. The effects of the drop deformation on the drop external aerodynamic force are considered in this model. Drop breakup occurs when the deformation length reaches the maximum value and the maximum deformation length is a function of Weber number. The performance and applicability of the proposed breakup model are tested against the published experimental data.

An increased rectal maximum tolerable volume and long anal canal are associated with poor short-term response to biofeedback therapy for patients with anismus with decreased bowel frequency and normal colonic transit time.

PubMed

Rhee, P L; Choi, M S; Kim, Y H; Son, H J; Kim, J J; Koh, K C; Paik, S W; Rhee, J C; Choi, K W

2000-10-01

Biofeedback is an effective therapy for a majority of patients with anismus. However, a significant proportion of patients still failed to respond to biofeedback, and little has been known about the factors that predict response to biofeedback. We evaluated the factors associated with poor response to biofeedback. Biofeedback therapy was offered to 45 patients with anismus with decreased bowel frequency (less than three times per week) and normal colonic transit time. Any differences in demographics, symptoms, and parameters of anorectal physiologic tests were sought between responders (in whom bowel frequency increased up to three times or more per week after biofeedback) and nonresponders (in whom bowel frequency remained less than three times per week). Thirty-one patients (68.9 percent) responded to biofeedback and 14 patients (31.1 percent) did not. Anal canal length was longer in nonresponders than in responders (4.53 +/- 0.5 vs. 4.08 +/- 0.56 cm; P = 0.02), and rectal maximum tolerable volume was larger in nonresponders than in responders. (361 +/- 87 vs. 302 +/- 69 ml; P = 0.02). Anal canal length and rectal maximum tolerable volume showed significant differences between responders and nonresponders on multivariate analysis (P = 0.027 and P = 0.034, respectively). This study showed that a long anal canal and increased rectal maximum tolerable volume are associated with poor short-term response to biofeedback for patients with anismus with decreased bowel frequency and normal colonic transit time.

In-flight thrust determination on a real-time basis

NASA Technical Reports Server (NTRS)

Ray, R. J.; Carpenter, T.; Sandlin, T.

1984-01-01

A real time computer program was implemented on a F-15 jet fighter to monitor in-flight engine performance of a Digital Electronic Engine Controlled (DEES) F-100 engine. The application of two gas generator methods to calculate in-flight thrust real time is described. A comparison was made between the actual results and those predicted by an engine model simulation. The percent difference between the two methods was compared to the predicted uncertainty based on instrumentation and model uncertainty and agreed closely with the results found during altitude facility testing. Data was obtained from acceleration runs of various altitudes at maximum power settings with and without afterburner. Real time in-flight thrust measurement was a major advancement to flight test productivity and was accomplished with no loss in accuracy over previous post flight methods.

Prediction of three sigma maximum dispersed density for aerospace applications

NASA Technical Reports Server (NTRS)

Charles, Terri L.; Nitschke, Michael D.

1993-01-01

Free molecular heating (FMH) is caused by the transfer of energy during collisions between the upper atmosphere molecules and a space vehicle. The dispersed free molecular heating on a surface is an important constraint for space vehicle thermal analyses since it can be a significant source of heating. To reduce FMH to a spacecraft, the parking orbit is often designed to a higher altitude at the expense of payload capability. Dispersed FMH is a function of both space vehicle velocity and atmospheric density, however, the space vehicle velocity variations are insignificant when compared to the atmospheric density variations. The density of the upper atmosphere molecules is a function of altitude, but also varies with other environmental factors, such as solar activity, geomagnetic activity, location, and time. A method has been developed to predict three sigma maximum dispersed density for up to 15 years into the future. This method uses a state-of-the-art atmospheric density code, MSIS 86, along with 50 years of solar data, NASA and NOAA solar activity predictions for the next 15 years, and an Aerospace Corporation correlation to account for density code inaccuracies to generate dispersed maximum density ratios denoted as 'K-factors'. The calculated K-factors can be used on a mission unique basis to calculate dispersed density, and hence dispersed free molecular heating rates. These more accurate K-factors can allow lower parking orbit altitudes, resulting in increased payload capability.

Hydrometeorological model for streamflow prediction

USGS Publications Warehouse

Tangborn, Wendell V.

1979-01-01

The hydrometeorological model described in this manual was developed to predict seasonal streamflow from water in storage in a basin using streamflow and precipitation data. The model, as described, applies specifically to the Skokomish, Nisqually, and Cowlitz Rivers, in Washington State, and more generally to streams in other regions that derive seasonal runoff from melting snow. Thus the techniques demonstrated for these three drainage basins can be used as a guide for applying this method to other streams. Input to the computer program consists of daily averages of gaged runoff of these streams, and daily values of precipitation collected at Longmire, Kid Valley, and Cushman Dam. Predictions are based on estimates of the absolute storage of water, predominately as snow: storage is approximately equal to basin precipitation less observed runoff. A pre-forecast test season is used to revise the storage estimate and improve the prediction accuracy. To obtain maximum prediction accuracy for operational applications with this model , a systematic evaluation of several hydrologic and meteorologic variables is first necessary. Six input options to the computer program that control prediction accuracy are developed and demonstrated. Predictions of streamflow can be made at any time and for any length of season, although accuracy is usually poor for early-season predictions (before December 1) or for short seasons (less than 15 days). The coefficient of prediction (CP), the chief measure of accuracy used in this manual, approaches zero during the late autumn and early winter seasons and reaches a maximum of about 0.85 during the spring snowmelt season. (Kosco-USGS)

Glutamate receptor-channel gating. Maximum likelihood analysis of gigaohm seal recordings from locust muscle.

PubMed Central

Bates, S E; Sansom, M S; Ball, F G; Ramsey, R L; Usherwood, P N

1990-01-01

Gigaohm recordings have been made from glutamate receptor channels in excised, outside-out patches of collagenase-treated locust muscle membrane. The channels in the excised patches exhibit the kinetic state switching first seen in megaohm recordings from intact muscle fibers. Analysis of channel dwell time distributions reveals that the gating mechanism contains at least four open states and at least four closed states. Dwell time autocorrelation function analysis shows that there are at least three gateways linking the open states of the channel with the closed states. A maximum likelihood procedure has been used to fit six different gating models to the single channel data. Of these models, a cooperative model yields the best fit, and accurately predicts most features of the observed channel gating kinetics. PMID:1696510

Variation of the low level winds during the passage of a thunderstorm gust front

NASA Technical Reports Server (NTRS)

Sinclair, R. W.; Anthes, R. A.; Panofsky, H. A.

1973-01-01

Three time histories of wind profiles in thunderstorm gust fronts at Cape Kennedy and three at Oklahoma City are analyzed. Wind profiles at maximum wind strength below 100 m follow logarithmic laws, so that winds above the surface layer can be estimated from surface winds once the roughness length is known. A statistical analysis of 81 cases of surface winds during thunderstorms at Tampa revealed no predictor with skill to predict the time of maximum gust. Some 34% of the variance of the strength of the gust is accounted for by a stability index and surface wind prior to the gust; the regression equations for these variables are given. The coherence between microscale wind speed variations at the different levels has the same proportions as in non-thunderstorm cases.

Sunspot Time Series - Relations Inferred from the Location of the Longest Spotless Segments

NASA Astrophysics Data System (ADS)

Zięba, Stanisław; Nieckarz, Zenon

2012-06-01

Spotless days ( i.e., days when no sunspots are observed on the Sun) occur during the interval between the declining phase of the old sunspot cycle and the rising phase of the new sunspot cycle, being greatest in number and of longest continuous length near a new cycle minimum. In this paper, we introduce the concept of the longest spotless segment (LSS) and examine its statistical relation to selected characteristic points in the sunspot time series (STS), such as the occurrences of first spotless day and sunspot maximum. The analysis has revealed statistically significant relations that appear to be of predictive value. For example, for Cycle 24 the last spotless day during its rising phase should be about August 2012 (± 9.1 months), the daily maximum sunspot number should be about 227 (± 50; occurring about January 2014±9.5 months), and the maximum Gaussian smoothed sunspot number should be about 87 (± 25; occurring about July 2014). Using the Gaussian-filtered values, slightly earlier dates of August 2011 and March 2013 are indicated for the last spotless day and sunspot maximum for Cycle 24, respectively.

Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data.

PubMed

Kolovos, Alexander; Skupin, André; Jerrett, Michael; Christakos, George

2010-09-01

Space-time data analysis and assimilation techniques in atmospheric sciences typically consider input from monitoring measurements. The input is often processed in a manner that acknowledges characteristics of the measurements (e.g., underlying patterns, fluctuation features) under conditions of uncertainty; it also leads to the derivation of secondary information that serves study-oriented goals, and provides input to space-time prediction techniques. We present a novel approach that blends a rigorous space-time prediction model (Bayesian maximum entropy, BME) with a cognitively informed visualization of high-dimensional data (spatialization). The combined BME and spatialization approach (BME-S) is used to study monthly averaged NO2 and mean annual SO4 measurements in California over the 15-year period 1988-2002. Using the original scattered measurements of these two pollutants BME generates spatiotemporal predictions on a regular grid across the state. Subsequently, the prediction network undergoes the spatialization transformation into a lower-dimensional geometric representation, aimed at revealing patterns and relationships that exist within the input data. The proposed BME-S provides a powerful spatiotemporal framework to study a variety of air pollution data sources.

Calcite Phase Conversion Prediction Model for CaO-Al2O3-SiO2 Slag: An Aqueous Carbonation Process at Ambient Pressure

NASA Astrophysics Data System (ADS)

Zhang, Huining; Dong, Jianhong; Li, Hui; Xiong, Huihui; Xu, Anjun

2018-06-01

To evaluate the effect of the mineralogical phase on carbonation efficiency for CaO-Al2O3-SiO2 slag, a calcite phase conversion prediction model is proposed. This model combines carbon dioxide solubility with carbonation reaction kinetic analysis to improve the prediction capability. The effect of temperature and carbonation time on the carbonation degree is studied in detail. Results show that the reaction rate constant ranges from 0.0135 h-1 to 0.0458 h-1 and that the mineralogical phase contribution sequence for the carbonation degree is C2S, CaO, C3A and CS. The model accurately predicts the effect of temperature and carbonation time on the simulated calcite conversion, and the results agree with the experimental data. The optimal carbonation temperature and reaction time are 333 K and 90 min, respectively. The maximum carbonation efficiency is about 184.3 g/kg slag, and the simulation result of the calcite phase content in carbonated slag is about 20%.

Near Field Modeling for the Maule Tsunami from DART, GPS and Finite Fault Solutions (Invited)

NASA Astrophysics Data System (ADS)

Arcas, D.; Chamberlin, C.; Lagos, M.; Ramirez-Herrera, M.; Tang, L.; Wei, Y.

2010-12-01

The earthquake and tsunami of February, 27, 2010 in central Chile has rekindled an interest in developing techniques to predict the impact of near field tsunamis along the Chilean coastline. Following the earthquake, several initiatives were proposed to increase the density of seismic, pressure and motion sensors along the South American trench, in order to provide field data that could be used to estimate tsunami impact on the coast. However, the precise use of those data in the elaboration of a quantitative assessment of coastal tsunami damage has not been clarified. The present work makes use of seismic, Deep-ocean Assessment and Reporting of Tsunamis (DART®) systems, and GPS measurements obtained during the Maule earthquake to initiate a number of tsunami inundation models along the rupture area by expressing different versions of the seismic crustal deformation in terms of NOAA’s tsunami unit source functions. Translation of all available real-time data into a feasible tsunami source is essential in near-field tsunami impact prediction in which an impact assessment must be generated under very stringent time constraints. Inundation results from each different source are then contrasted with field and tide gauge data by comparing arrival time, maximum wave height, maximum inundation and tsunami decay rate, using field data collected by the authors.

Estimating Controller Intervention Probabilities for Optimized Profile Descent Arrivals

NASA Technical Reports Server (NTRS)

Meyn, Larry A.; Erzberger, Heinz; Huynh, Phu V.

2011-01-01

Simulations of arrival traffic at Dallas/Fort-Worth and Denver airports were conducted to evaluate incorporating scheduling and separation constraints into advisories that define continuous descent approaches. The goal was to reduce the number of controller interventions required to ensure flights maintain minimum separation distances of 5 nmi horizontally and 1000 ft vertically. It was shown that simply incorporating arrival meter fix crossing-time constraints into the advisory generation could eliminate over half of the all predicted separation violations and more than 80% of the predicted violations between two arrival flights. Predicted separation violations between arrivals and non-arrivals were 32% of all predicted separation violations at Denver and 41% at Dallas/Fort-Worth. A probabilistic analysis of meter fix crossing-time errors is included which shows that some controller interventions will still be required even when the predicted crossing-times of the advisories are set to add a 1 or 2 nmi buffer above the minimum in-trail separation of 5 nmi. The 2 nmi buffer was shown to increase average flight delays by up to 30 sec when compared to the 1 nmi buffer, but it only resulted in a maximum decrease in average arrival throughput of one flight per hour.

Financial Time Series Prediction Using Spiking Neural Networks

PubMed Central

Reid, David; Hussain, Abir Jaafar; Tawfik, Hissam

2014-01-01

In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two “traditional”, rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments. PMID:25170618

Ares I-X Launch Abort System, Crew Module, and Upper Stage Simulator Vibroacoustic Flight Data Evaluation, Comparison to Predictions, and Recommendations for Adjustments to Prediction Methodology and Assumptions

NASA Technical Reports Server (NTRS)

Smith, Andrew; Harrison, Phil

2010-01-01

The National Aeronautics and Space Administration (NASA) Constellation Program (CxP) has identified a series of tests to provide insight into the design and development of the Crew Launch Vehicle (CLV) and Crew Exploration Vehicle (CEV). Ares I-X was selected as the first suborbital development flight test to help meet CxP objectives. The Ares I-X flight test vehicle (FTV) is an early operational model of CLV, with specific emphasis on CLV and ground operation characteristics necessary to meet Ares I-X flight test objectives. The in-flight part of the test includes a trajectory to simulate maximum dynamic pressure during flight and perform a stage separation of the Upper Stage Simulator (USS) from the First Stage (FS). The in-flight test also includes recovery of the FS. The random vibration response from the ARES 1-X flight will be reconstructed for a few specific locations that were instrumented with accelerometers. This recorded data will be helpful in validating and refining vibration prediction tools and methodology. Measured vibroacoustic environments associated with lift off and ascent phases of the Ares I-X mission will be compared with pre-flight vibration predictions. The measured flight data was given as time histories which will be converted into power spectral density plots for comparison with the maximum predicted environments. The maximum predicted environments are documented in the Vibroacoustics and Shock Environment Data Book, AI1-SYS-ACOv4.10 Vibration predictions made using statistical energy analysis (SEA) VAOne computer program will also be incorporated in the comparisons. Ascent and lift off measured acoustics will also be compared to predictions to assess whether any discrepancies between the predicted vibration levels and measured vibration levels are attributable to inaccurate acoustic predictions. These comparisons will also be helpful in assessing whether adjustments to prediction methodologies are needed to improve agreement between the predicted and measured flight data. Future assessment will incorporate hybrid methods in VAOne analysis (i.e., boundary element methods, BEM and finite element methods, FEM). These hybrid methods will enable the ability to import NASTRAN models providing much more detailed modeling of the underlying beams and support structure of the ARES 1-X test vehicle. Measured acoustic data will be incorporated into these analyses to improve correlation for additional post flight analysis.

Multi-time-scale heat transfer modeling of turbid tissues exposed to short-pulsed irradiations.

PubMed

Kim, Kyunghan; Guo, Zhixiong

2007-05-01

A combined hyperbolic radiation and conduction heat transfer model is developed to simulate multi-time-scale heat transfer in turbid tissues exposed to short-pulsed irradiations. An initial temperature response of a tissue to an ultrashort pulse irradiation is analyzed by the volume-average method in combination with the transient discrete ordinates method for modeling the ultrafast radiation heat transfer. This response is found to reach pseudo steady state within 1 ns for the considered tissues. The single pulse result is then utilized to obtain the temperature response to pulse train irradiation at the microsecond/millisecond time scales. After that, the temperature field is predicted by the hyperbolic heat conduction model which is solved by the MacCormack's scheme with error terms correction. Finally, the hyperbolic conduction is compared with the traditional parabolic heat diffusion model. It is found that the maximum local temperatures are larger in the hyperbolic prediction than the parabolic prediction. In the modeled dermis tissue, a 7% non-dimensional temperature increase is found. After about 10 thermal relaxation times, thermal waves fade away and the predictions between the hyperbolic and parabolic models are consistent.

An online spatio-temporal prediction model for dengue fever epidemic in Kaohsiung,Taiwan

NASA Astrophysics Data System (ADS)

Cheng, Ming-Hung; Yu, Hwa-Lung; Angulo, Jose; Christakos, George

2013-04-01

Dengue Fever (DF) is one of the most serious vector-borne infectious diseases in tropical and subtropical areas. DF epidemics occur in Taiwan annually especially during summer and fall seasons. Kaohsiung city has been one of the major DF hotspots in decades. The emergence and re-emergence of the DF epidemic is complex and can be influenced by various factors including space-time dynamics of human and vector populations and virus serotypes as well as the associated uncertainties. This study integrates a stochastic space-time "Susceptible-Infected-Recovered" model under Bayesian maximum entropy framework (BME-SIR) to perform real-time prediction of disease diffusion across space-time. The proposed model is applied for spatiotemporal prediction of the DF epidemic at Kaohsiung city during 2002 when the historical series of high DF cases was recorded. The online prediction by BME-SIR model updates the parameters of SIR model and infected cases across districts over time. Results show that the proposed model is rigorous to initial guess of unknown model parameters, i.e. transmission and recovery rates, which can depend upon the virus serotypes and various human interventions. This study shows that spatial diffusion can be well characterized by BME-SIR model, especially at the district surrounding the disease outbreak locations. The prediction performance at DF hotspots, i.e. Cianjhen and Sanmin, can be degraded due to the implementation of various disease control strategies during the epidemics. The proposed online disease prediction BME-SIR model can provide the governmental agency with a valuable reference to timely identify, control, and efficiently prevent DF spread across space-time.

Another baryon miracle? Testing solutions to the `missing dwarfs' problem

NASA Astrophysics Data System (ADS)

Trujillo-Gomez, Sebastian; Schneider, Aurel; Papastergis, Emmanouil; Reed, Darren S.; Lake, George

2018-04-01

The dearth of dwarf galaxies in the local Universe is hard to reconcile with the large number of low-mass haloes expected within the concordance Λ cold dark matter (ΛCDM) paradigm. In this paper, we perform a systematic evaluation of the uncertainties affecting the measurement of dark matter halo abundance using galaxy kinematics. Using a large sample of dwarf galaxies with spatially resolved kinematics, we derive a correction to obtain the abundance of galaxies as a function of maximum circular velocity - a direct probe of halo mass - from the line-of-sight velocity function in the Local Volume. This method provides a direct means of comparing the predictions of theoretical models and simulations (including non-standard cosmologies and novel galaxy formation physics) to the observational constraints. The new `galactic Vmax' function is steeper than the line-of-sight velocity function but still shallower than the theoretical CDM expectation, implying that unaccounted baryonic physics may be necessary to reduce the predicted abundance of galaxies. Using the galactic Vmax function, we investigate the theoretical effects of feedback-powered outflows and photoevaporation of gas due to reionization. At the 3σ confidence level, we find that feedback and reionization are not effective enough to reconcile the disagreement. In the case of maximum baryonic effects, the theoretical prediction still deviates significantly from the observations for Vmax < 60 km s-1. CDM predicts at least 1.8 times more galaxies with Vmax = 50 km s-1 and 2.5 times more than observed at 30 km s-1. Recent hydrodynamic simulations seem to resolve the discrepancy but disagree with the properties of observed galaxies with spatially resolved kinematics. This abundance problem might point to the need to modify cosmological predictions at small scales.

{sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Can Quantify and Predict Esophageal Injury During Radiation Therapy

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

Niedzielski, Joshua S., E-mail: jsniedzielski@mdanderson.org; University of Texas Houston Graduate School of Biomedical Science, Houston, Texas; Yang, Jinzhong

Purpose: We sought to investigate the ability of mid-treatment {sup 18}F-fluorodeoxyglucose positron emission tomography (PET) studies to objectively and spatially quantify esophageal injury in vivo from radiation therapy for non-small cell lung cancer. Methods and Materials: This retrospective study was approved by the local institutional review board, with written informed consent obtained before enrollment. We normalized {sup 18}F-fluorodeoxyglucose PET uptake to each patient's low-irradiated region (<5 Gy) of the esophagus, as a radiation response measure. Spatially localized metrics of normalized uptake (normalized standard uptake value [nSUV]) were derived for 79 patients undergoing concurrent chemoradiation therapy for non-small cell lung cancer. We usedmore » nSUV metrics to classify esophagitis grade at the time of the PET study, as well as maximum severity by treatment completion, according to National Cancer Institute Common Terminology Criteria for Adverse Events, using multivariate least absolute shrinkage and selection operator (LASSO) logistic regression and repeated 3-fold cross validation (training, validation, and test folds). This 3-fold cross-validation LASSO model procedure was used to predict toxicity progression from 43 asymptomatic patients during the PET study. Dose-volume metrics were also tested in both the multivariate classification and the symptom progression prediction analyses. Classification performance was quantified with the area under the curve (AUC) from receiver operating characteristic analysis on the test set from the 3-fold analyses. Results: Statistical analysis showed increasing nSUV is related to esophagitis severity. Axial-averaged maximum nSUV for 1 esophageal slice and esophageal length with at least 40% of axial-averaged nSUV both had AUCs of 0.85 for classifying grade 2 or higher esophagitis at the time of the PET study and AUCs of 0.91 and 0.92, respectively, for maximum grade 2 or higher by treatment completion. Symptom progression was predicted with an AUC of 0.75. Dose metrics performed poorly at classifying esophagitis (AUC of 0.52, grade 2 or higher mid treatment) or predicting symptom progression (AUC of 0.67). Conclusions: Normalized uptake can objectively, locally, and noninvasively quantify esophagitis during radiation therapy and predict eventual symptoms from asymptomatic patients. Normalized uptake may provide patient-specific dose-response information not discernible from dose.« less

(18)F-Fluorodeoxyglucose Positron Emission Tomography Can Quantify and Predict Esophageal Injury During Radiation Therapy.

PubMed

Niedzielski, Joshua S; Yang, Jinzhong; Liao, Zhongxing; Gomez, Daniel R; Stingo, Francesco; Mohan, Radhe; Martel, Mary K; Briere, Tina M; Court, Laurence E

2016-11-01

We sought to investigate the ability of mid-treatment (18)F-fluorodeoxyglucose positron emission tomography (PET) studies to objectively and spatially quantify esophageal injury in vivo from radiation therapy for non-small cell lung cancer. This retrospective study was approved by the local institutional review board, with written informed consent obtained before enrollment. We normalized (18)F-fluorodeoxyglucose PET uptake to each patient's low-irradiated region (<5 Gy) of the esophagus, as a radiation response measure. Spatially localized metrics of normalized uptake (normalized standard uptake value [nSUV]) were derived for 79 patients undergoing concurrent chemoradiation therapy for non-small cell lung cancer. We used nSUV metrics to classify esophagitis grade at the time of the PET study, as well as maximum severity by treatment completion, according to National Cancer Institute Common Terminology Criteria for Adverse Events, using multivariate least absolute shrinkage and selection operator (LASSO) logistic regression and repeated 3-fold cross validation (training, validation, and test folds). This 3-fold cross-validation LASSO model procedure was used to predict toxicity progression from 43 asymptomatic patients during the PET study. Dose-volume metrics were also tested in both the multivariate classification and the symptom progression prediction analyses. Classification performance was quantified with the area under the curve (AUC) from receiver operating characteristic analysis on the test set from the 3-fold analyses. Statistical analysis showed increasing nSUV is related to esophagitis severity. Axial-averaged maximum nSUV for 1 esophageal slice and esophageal length with at least 40% of axial-averaged nSUV both had AUCs of 0.85 for classifying grade 2 or higher esophagitis at the time of the PET study and AUCs of 0.91 and 0.92, respectively, for maximum grade 2 or higher by treatment completion. Symptom progression was predicted with an AUC of 0.75. Dose metrics performed poorly at classifying esophagitis (AUC of 0.52, grade 2 or higher mid treatment) or predicting symptom progression (AUC of 0.67). Normalized uptake can objectively, locally, and noninvasively quantify esophagitis during radiation therapy and predict eventual symptoms from asymptomatic patients. Normalized uptake may provide patient-specific dose-response information not discernible from dose. Copyright © 2016 Elsevier Inc. All rights reserved.

An online spatiotemporal prediction model for dengue fever epidemic in Kaohsiung (Taiwan).

PubMed

Yu, Hwa-Lung; Angulo, José M; Cheng, Ming-Hung; Wu, Jiaping; Christakos, George

2014-05-01

The emergence and re-emergence of disease epidemics is a complex question that may be influenced by diverse factors, including the space-time dynamics of human populations, environmental conditions, and associated uncertainties. This study proposes a stochastic framework to integrate space-time dynamics in the form of a Susceptible-Infected-Recovered (SIR) model, together with uncertain disease observations, into a Bayesian maximum entropy (BME) framework. The resulting model (BME-SIR) can be used to predict space-time disease spread. Specifically, it was applied to obtain a space-time prediction of the dengue fever (DF) epidemic that took place in Kaohsiung City (Taiwan) during 2002. In implementing the model, the SIR parameters were continually updated and information on new cases of infection was incorporated. The results obtained show that the proposed model is rigorous to user-specified initial values of unknown model parameters, that is, transmission and recovery rates. In general, this model provides a good characterization of the spatial diffusion of the DF epidemic, especially in the city districts proximal to the location of the outbreak. Prediction performance may be affected by various factors, such as virus serotypes and human intervention, which can change the space-time dynamics of disease diffusion. The proposed BME-SIR disease prediction model can provide government agencies with a valuable reference for the timely identification, control, and prevention of DF spread in space and time. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Relationship between occlusal force and falls among community-dwelling elderly in Japan: a cross-sectional correlative study.

PubMed

Eto, Maki; Miyauchi, Shinji

2018-05-09

Falls may cause serious health conditions among older population. Fall-related physical factors are thought to be associated with occlusal conditions. However, few studies examined the relationship between occlusal force and falls. To identify the association between occlusal force and falls among community-dwelling elderly individuals in Japan, public health nurses conducted a cross-sectional descriptive study. We performed extensive physical assessments of five items: maximum occlusal force, handgrip strength, maximal knee extensor strength, one-leg standing time with eyes open and body sway. We also conducted a questionnaire survey concerning the participants' demographic characteristics, health status and fall experience during the past year. Mean scores and standard deviations were calculated for age and the total points of the index of activities of daily living. Associations were examined using Mann-Whitney tests and logistic regression. We examined 159 community-dwelling people aged ≥65 years, who were independent and active, including 38 participants (24.5%) with experience of falls in the past year. Maximum occlusal force had significant correlation with handgrip strength, maximal knee extensor strength, and one-leg standing time and body sway (P < .05, respectively). We found weak associations between participants with and without a history of falls in terms of the five physical measurements. Logistic regression analysis showed that fall experience was significantly associated with maximum occlusal force (P = 0.004). This is the first study, led by public health nursing researchers, to examine the associations between maximum occlusal force and falls among community-dwelling elderly in Japan. The results showed that maximum occlusal force was significantly related to the other four extensive physical assessments, and might also suggest that maximum occlusal force assessment by public health nurses could contribute to more sophisticated and precise prediction of fall risks among the community-dwelling elderly. The latest occlusal force measurement device is non-invasive and easy to use. Public health nurses can introduce it at periodical community health checkup assembly events, which might contribute to raising awareness among community-dwelling elderly individuals and public health nurses about fall prevention and prediction.

Modelling of composting process of different organic waste at pilot scale: Biodegradability and odor emissions.

PubMed

Gutiérrez, M C; Siles, J A; Diz, J; Chica, A F; Martín, M A

2017-01-01

The composting process of six different compostable substrates and one of these with the addition of bacterial inoculums carried out in a dynamic respirometer was evaluated. Despite the heterogeneity of the compostable substrates, cumulative oxygen demand (OD, mgO 2 kgVS) was fitted adequately to an exponential regression growing until reaching a maximum in all cases. According to the kinetic constant of the reaction (K) values obtained, the wastes that degraded more slowly were those containing lignocellulosic material (green wastes) or less biodegradable wastes (sewage sludge). The odor emissions generated during the composting processes were also fitted in all cases to a Gaussian regression with R 2 values within the range 0.8-0.9. The model was validated representing real odor concentration near the maximum value against predicted odor concentration of each substrate, (R 2 =0.9314; 95% prediction interval). The variables of maximum odor concentration (ou E /m 3 ) and the time (h) at which the maximum was reached were also evaluated statistically using ANOVA and a post-hoc Tukey test taking the substrate as a factor, which allowed homogeneous groups to be obtained according to one or both of these variables. The maximum oxygen consumption rate or organic matter degradation during composting was directly related to the maximum odor emission generation rate (R 2 =0.9024, 95% confidence interval) when only the organic wastes with a low content in lignocellulosic materials and no inoculated waste (HRIO) were considered. Finally, the composting of OFMSW would produce a higher odor impact than the other substrates if this process was carried out without odor control or open systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling the distribution of extreme share return in Malaysia using Generalized Extreme Value (GEV) distribution

NASA Astrophysics Data System (ADS)

Hasan, Husna; Radi, Noor Fadhilah Ahmad; Kassim, Suraiya

2012-05-01

Extreme share return in Malaysia is studied. The monthly, quarterly, half yearly and yearly maximum returns are fitted to the Generalized Extreme Value (GEV) distribution. The Augmented Dickey Fuller (ADF) and Phillips Perron (PP) tests are performed to test for stationarity, while Mann-Kendall (MK) test is for the presence of monotonic trend. Maximum Likelihood Estimation (MLE) is used to estimate the parameter while L-moments estimate (LMOM) is used to initialize the MLE optimization routine for the stationary model. Likelihood ratio test is performed to determine the best model. Sherman's goodness of fit test is used to assess the quality of convergence of the GEV distribution by these monthly, quarterly, half yearly and yearly maximum. Returns levels are then estimated for prediction and planning purposes. The results show all maximum returns for all selection periods are stationary. The Mann-Kendall test indicates the existence of trend. Thus, we ought to model for non-stationary model too. Model 2, where the location parameter is increasing with time is the best for all selection intervals. Sherman's goodness of fit test shows that monthly, quarterly, half yearly and yearly maximum converge to the GEV distribution. From the results, it seems reasonable to conclude that yearly maximum is better for the convergence to the GEV distribution especially if longer records are available. Return level estimates, which is the return level (in this study return amount) that is expected to be exceeded, an average, once every t time periods starts to appear in the confidence interval of T = 50 for quarterly, half yearly and yearly maximum.

Impact Damage and Strain Rate Effects for Toughened Epoxy Composite Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Minnetyan, Levon

2006-01-01

Structural integrity of composite systems under dynamic impact loading is investigated herein. The GENOA virtual testing software environment is used to implement the effects of dynamic loading on fracture progression and damage tolerance. Combinations of graphite and glass fibers with a toughened epoxy matrix are investigated. The effect of a ceramic coating for the absorption of impact energy is also included. Impact and post impact simulations include verification and prediction of (1) Load and Impact Energy, (2) Impact Damage Size, (3) Maximum Impact Peak Load, (4) Residual Strength, (5) Maximum Displacement, (6) Contribution of Failure Modes to Failure Mechanisms, (7) Prediction of Impact Load Versus Time, and (8) Damage, and Fracture Pattern. A computer model is utilized for the assessment of structural response, progressive fracture, and defect/damage tolerance characteristics. Results show the damage progression sequence and the changes in the structural response characteristics due to dynamic impact. The fundamental premise of computational simulation is that the complete evaluation of composite fracture requires an assessment of ply and subply level damage/fracture processes as the structure is subjected to loads. Simulation results for the graphite/epoxy composite were compared with the impact and tension failure test data, correlation and verification was obtained that included: (1) impact energy, (2) damage size, (3) maximum impact peak load, (4) residual strength, (5) maximum displacement, and (6) failure mechanisms of the composite structure.

Study on C-S and P-R EOS in pseudo-potential lattice Boltzmann model for two-phase flows

NASA Astrophysics Data System (ADS)

Peng, Yong; Mao, Yun Fei; Wang, Bo; Xie, Bo

Equations of State (EOS) is crucial in simulating multiphase flows by the pseudo-potential lattice Boltzmann method (LBM). In the present study, the Peng and Robinson (P-R) and Carnahan and Starling (C-S) EOS in the pseudo-potential LBM with Exact Difference Method (EDM) scheme for two-phase flows have been compared. Both of P-R and C-S EOS have been used to study the two-phase separation, surface tension, the maximum two-phase density ratio and spurious currents. The study shows that both of P-R and C-S EOS agree with the analytical solutions although P-R EOS may perform better. The prediction of liquid phase by P-R EOS is more accurate than that of air phase and the contrary is true for C-S EOS. Predictions by both of EOS conform with the Laplace’s law. Besides, adjustment of surface tension is achieved by adjusting T. The P-R EOS can achieve larger maximum density ratio than C-S EOS under the same τ. Besides, no matter the C-S EOS or the P-R EOS, if τ tends to 0.5, the computation is prone to numerical instability. The maximum spurious current for P-R is larger than that of C-S. The multiple-relaxation-time LBM still can improve obviously the numerical stability and can achieve larger maximum density ratio.

Metabolic networks evolve towards states of maximum entropy production.

PubMed

Unrean, Pornkamol; Srienc, Friedrich

2011-11-01

A metabolic network can be described by a set of elementary modes or pathways representing discrete metabolic states that support cell function. We have recently shown that in the most likely metabolic state the usage probability of individual elementary modes is distributed according to the Boltzmann distribution law while complying with the principle of maximum entropy production. To demonstrate that a metabolic network evolves towards such state we have carried out adaptive evolution experiments with Thermoanaerobacterium saccharolyticum operating with a reduced metabolic functionality based on a reduced set of elementary modes. In such reduced metabolic network metabolic fluxes can be conveniently computed from the measured metabolite secretion pattern. Over a time span of 300 generations the specific growth rate of the strain continuously increased together with a continuous increase in the rate of entropy production. We show that the rate of entropy production asymptotically approaches the maximum entropy production rate predicted from the state when the usage probability of individual elementary modes is distributed according to the Boltzmann distribution. Therefore, the outcome of evolution of a complex biological system can be predicted in highly quantitative terms using basic statistical mechanical principles. Copyright © 2011 Elsevier Inc. All rights reserved.

Optimization of microwave-assisted extraction of total extract, stevioside and rebaudioside-A from Stevia rebaudiana (Bertoni) leaves, using response surface methodology (RSM) and artificial neural network (ANN) modelling.

PubMed

Ameer, Kashif; Bae, Seong-Woo; Jo, Yunhee; Lee, Hyun-Gyu; Ameer, Asif; Kwon, Joong-Ho

2017-08-15

Stevia rebaudiana (Bertoni) consists of stevioside and rebaudioside-A (Reb-A). We compared response surface methodology (RSM) and artificial neural network (ANN) modelling for their estimation and predictive capabilities in building effective models with maximum responses. A 5-level 3-factor central composite design was used to optimize microwave-assisted extraction (MAE) to obtain maximum yield of target responses as a function of extraction time (X 1 : 1-5min), ethanol concentration, (X 2 : 0-100%) and microwave power (X 3 : 40-200W). Maximum values of the three output parameters: 7.67% total extract yield, 19.58mg/g stevioside yield, and 15.3mg/g Reb-A yield, were obtained under optimum extraction conditions of 4min X 1 , 75% X 2 , and 160W X 3 . The ANN model demonstrated higher efficiency than did the RSM model. Hence, RSM can demonstrate interaction effects of inherent MAE parameters on target responses, whereas ANN can reliably model the MAE process with better predictive and estimation capabilities. Copyright © 2017. Published by Elsevier Ltd.

Predictive Model of Supercooled Water Droplet Pinning/Repulsion Impacting a Superhydrophobic Surface: The Role of the Gas-Liquid Interface Temperature.

PubMed

Mohammadi, Morteza; Tembely, Moussa; Dolatabadi, Ali

2017-02-28

Dynamical analysis of an impacting liquid drop on superhydrophobic surfaces is mostly carried out by evaluating the droplet contact time and maximum spreading diameter. In this study, we present a general transient model of the droplet spreading diameter developed from the previously defined mass-spring model for bouncing drops. The effect of viscosity was also considered in the model by definition of a dash-pot term extracted from experiments on various viscous liquid droplets on a superhydrophobic surface. Furthermore, the resultant shear force of the stagnation air flow was also considered with the help of the classical Homann flow approach. It was clearly shown that the proposed model predicts the maximum spreading diameter and droplet contact time very well. On the other hand, where stagnation air flow is present in contradiction to the theoretical model, the droplet contact time was reduced as a function of both droplet Weber numbers and incoming air velocities. Indeed, the reduction in the droplet contact time (e.g., 35% at a droplet Weber number of up to 140) was justified by the presence of a formed thin air layer underneath the impacting drop on the superhydrophobic surface (i.e., full slip condition). Finally, the droplet wetting model was also further developed to account for low temperature through the incorporation of classical nucleation theory. Homogeneous ice nucleation was integrated into the model through the concept of the reduction of the supercooled water drop surface tension as a function of the gas-liquid interface temperature, which was directly correlated with the Nusselt number of incoming air flow. It was shown that the experimental results was qualitatively predicted by the proposed model under all supercooling conditions (i.e., from -10 to -30 °C).

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

Kaplan, C.R.; Shaddix, C.R.; Smyth, K.C.

This paper presents time-dependent numerical simulations of both steady and time-varying CH{sub 4}/air diffusion flames to examine the differences in combustion conditions which lead to the observed enhancement in soot production in the flickering flames. The numerical model solves the two-dimensional, time-dependent, reactive-flow Navier-Stokes equations coupled with submodels for soot formation and radiation transport. Qualitative comparisons between the experimental and computed steady flame show good agreement for the soot burnout height and overall flame shape except near the burner lip. Quantitative comparisons between experimental and computed radial profiles of temperature and soot volume fraction for the steady flame show goodmore » to excellent agreement at mid-flame heights, but some discrepancies near the burner lip and at high flame heights. For the time-varying CH{sub 4}/air flame, the simulations successfully predict that the maximum soot concentration increases by over four times compared to the steady flame with the same mean fuel and air velocities. By numerically tracking fluid parcels in the flowfield, the temperature and stoichiometry history were followed along their convective pathlines. Results for the pathline which passes through the maximum sooting region show that flickering flames exhibit much longer residence times during which the local temperatures and stoichiometries are favorable for soot production. The simulations also suggest that soot inception occurs later in flickering flames, and at slightly higher temperatures and under somewhat leaner conditions compared to the steady flame. The integrated soot model of Syed et al., which was developed from a steady CH{sub 4}/air flame, successfully predicts soot production in the time-varying CH{sub 4}/air flames.« less

Biofilm development in fixed bed biofilm reactors: experiments and simple models for engineering design purposes.

PubMed

Szilágyi, N; Kovács, R; Kenyeres, I; Csikor, Zs

2013-01-01

Biofilm development in a fixed bed biofilm reactor system performing municipal wastewater treatment was monitored aiming at accumulating colonization and maximum biofilm mass data usable in engineering practice for process design purposes. Initially a 6 month experimental period was selected for investigations where the biofilm formation and the performance of the reactors were monitored. The results were analyzed by two methods: for simple, steady-state process design purposes the maximum biofilm mass on carriers versus influent load and a time constant of the biofilm growth were determined, whereas for design approaches using dynamic models a simple biofilm mass prediction model including attachment and detachment mechanisms was selected and fitted to the experimental data. According to a detailed statistical analysis, the collected data have not allowed us to determine both the time constant of biofilm growth and the maximum biofilm mass on carriers at the same time. The observed maximum biofilm mass could be determined with a reasonable error and ranged between 438 gTS/m(2) carrier surface and 843 gTS/m(2), depending on influent load, and hydrodynamic conditions. The parallel analysis of the attachment-detachment model showed that the experimental data set allowed us to determine the attachment rate coefficient which was in the range of 0.05-0.4 m d(-1) depending on influent load and hydrodynamic conditions.

Seasonal prediction of Indian summer monsoon rainfall in NCEP CFSv2: forecast and predictability error

NASA Astrophysics Data System (ADS)

Pokhrel, Samir; Saha, Subodh Kumar; Dhakate, Ashish; Rahman, Hasibur; Chaudhari, Hemantkumar S.; Salunke, Kiran; Hazra, Anupam; Sujith, K.; Sikka, D. R.

2016-04-01

A detailed analysis of sensitivity to the initial condition for the simulation of the Indian summer monsoon using retrospective forecast by the latest version of the Climate Forecast System version-2 (CFSv2) is carried out. This study primarily focuses on the tropical region of Indian and Pacific Ocean basin, with special emphasis on the Indian land region. The simulated seasonal mean and the inter-annual standard deviations of rainfall, upper and lower level atmospheric circulations and Sea Surface Temperature (SST) tend to be more skillful as the lead forecast time decreases (5 month lead to 0 month lead time i.e. L5-L0). In general spatial correlation (bias) increases (decreases) as forecast lead time decreases. This is further substantiated by their averaged value over the selected study regions over the Indian and Pacific Ocean basins. The tendency of increase (decrease) of model bias with increasing (decreasing) forecast lead time also indicates the dynamical drift of the model. Large scale lower level circulation (850 hPa) shows enhancement of anomalous westerlies (easterlies) over the tropical region of the Indian Ocean (Western Pacific Ocean), which indicates the enhancement of model error with the decrease in lead time. At the upper level circulation (200 hPa) biases in both tropical easterly jet and subtropical westerlies jet tend to decrease as the lead time decreases. Despite enhancement of the prediction skill, mean SST bias seems to be insensitive to the initialization. All these biases are significant and together they make CFSv2 vulnerable to seasonal uncertainties in all the lead times. Overall the zeroth lead (L0) seems to have the best skill, however, in case of Indian summer monsoon rainfall (ISMR), the 3 month lead forecast time (L3) has the maximum ISMR prediction skill. This is valid using different independent datasets, wherein these maximum skill scores are 0.64, 0.42 and 0.57 with respect to the Global Precipitation Climatology Project, CPC Merged Analysis of Precipitation and the India Meteorological Department precipitation dataset respectively for L3. Despite significant El-Niño Southern Oscillation (ENSO) spring predictability barrier at L3, the ISMR skill score is highest at L3. Further, large scale zonal wind shear (Webster-Yang index) and SST over Niño3.4 region is best at L1 and L0. This implies that predictability aspect of ISMR is controlled by factors other than ENSO and Indian Ocean Dipole. Also, the model error (forecast error) outruns the error acquired by the inadequacies in the initial conditions (predictability error). Thus model deficiency is having more serious consequences as compared to the initial condition error for the seasonal forecast. All the model parameters show the increase in the predictability error as the lead decreases over the equatorial eastern Pacific basin and peaks at L2, then it further decreases. The dynamical consistency of both the forecast and the predictability error among all the variables indicates that these biases are purely systematic in nature and improvement of the physical processes in the CFSv2 may enhance the overall predictability.

Should fluid dynamics be included in computer models of RF cardiac ablation by irrigated-tip electrodes?

PubMed

González-Suárez, Ana; Pérez, Juan J; Berjano, Enrique

2018-04-20

Although accurate modeling of the thermal performance of irrigated-tip electrodes in radiofrequency cardiac ablation requires the solution of a triple coupled problem involving simultaneous electrical conduction, heat transfer, and fluid dynamics, in certain cases it is difficult to combine the software with the expertise necessary to solve these coupled problems, so that reduced models have to be considered. We here focus on a reduced model which avoids the fluid dynamics problem by setting a constant temperature at the electrode tip. Our aim was to compare the reduced and full models in terms of predicting lesion dimensions and the temperatures reached in tissue and blood. The results showed that the reduced model overestimates the lesion surface width by up to 5 mm (i.e. 70%) for any electrode insertion depth and blood flow rate. Likewise, it drastically overestimates the maximum blood temperature by more than 15 °C in all cases. However, the reduced model is able to predict lesion depth reasonably well (within 0.1 mm of the full model), and also the maximum tissue temperature (difference always less than 3 °C). These results were valid throughout the entire ablation time (60 s) and regardless of blood flow rate and electrode insertion depth (ranging from 0.5 to 1.5 mm). The findings suggest that the reduced model is not able to predict either the lesion surface width or the maximum temperature reached in the blood, and so would not be suitable for the study of issues related to blood temperature, such as the incidence of thrombus formation during ablation. However, it could be used to study issues related to maximum tissue temperature, such as the steam pop phenomenon.

Postoperative Tachycardia: Clinically Meaningful or Benign Consequence of Orthopedic Surgery?

PubMed

Sigmund, Alana E; Fang, Yixin; Chin, Matthew; Reynolds, Harmony R; Horwitz, Leora I; Dweck, Ezra; Iturrate, Eduardo

2017-01-01

To determine the clinical significance of tachycardia in the postoperative period. Individuals 18 years or older undergoing hip and knee arthroplasty were included in the study. Two data sets were collected from different time periods: development data set from January 1, 2011, through December 31, 2011, and validation data set from December 1, 2012, through September 1, 2014. We used the development data set to identify the optimal definition of tachycardia with the strongest association with the vascular composite outcome (pulmonary embolism and myocardial necrosis and infarction). The predictive value of this definition was assessed in the validation data set for each outcome of interest, pulmonary embolism, myocardial necrosis and infarction, and infection using multiple logistic regression to control for known risk factors. In 1755 patients in the development data set, a maximum heart rate (HR) greater than 110 beats/min was found to be the best cutoff as a correlate of the composite vascular outcome. Of the 4621 patients who underwent arthroplasty in the validation data set, 40 (0.9%) had pulmonary embolism. The maximum HR greater than 110 beats/min had an odds ratio (OR) of 9.39 (95% CI, 4.67-18.87; sensitivity, 72.5%; specificity, 78.0%; positive predictive value, 2.8%; negative predictive value, 99.7%) for pulmonary embolism. Ninety-seven patients (2.1%) had myocardial necrosis (elevated troponin). The maximum HR greater than 110 beats/min had an OR of 4.71 (95% CI, 3.06-7.24; sensitivity, 47.4%; specificity, 78.1%; positive predictive value, 4.4%; negative predictive value, 98.6%) for this outcome. Thirteen (.3%) patients had myocardial infarction according to our predetermined definition, and the maximum HR greater than 110 beats/min had an OR of 1.72 (95% CI, 0.47-6.27). Postoperative tachycardia within the first 4 days of surgery should not be dismissed as a postoperative variation in HR, but may precede clinically significant adverse outcomes. Copyright © 2016 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

A predictive software tool for optimal timing in contrast enhanced carotid MR angiography

NASA Astrophysics Data System (ADS)

Moghaddam, Abbas N.; Balawi, Tariq; Habibi, Reza; Panknin, Christoph; Laub, Gerhard; Ruehm, Stefan; Finn, J. Paul

2008-03-01

A clear understanding of the first pass dynamics of contrast agents in the vascular system is crucial in synchronizing data acquisition of 3D MR angiography (MRA) with arrival of the contrast bolus in the vessels of interest. We implemented a computational model to simulate contrast dynamics in the vessels using the theory of linear time-invariant systems. The algorithm calculates a patient-specific impulse response for the contrast concentration from time-resolved images following a small test bolus injection. This is performed for a specific region of interest and through deconvolution of the intensity curve using the long division method. Since high spatial resolution 3D MRA is not time-resolved, the method was validated on time-resolved arterial contrast enhancement in Multi Slice CT angiography. For 20 patients, the timing of the contrast enhancement of the main bolus was predicted by our algorithm from the response to the test bolus, and then for each case the predicted time of maximum intensity was compared to the corresponding time in the actual scan which resulted in an acceptable agreement. Furthermore, as a qualitative validation, the algorithm's predictions of the timing of the carotid MRA in 20 patients with high quality MRA were correlated with the actual timing of those studies. We conclude that the above algorithm can be used as a practical clinical tool to eliminate guesswork and to replace empiric formulae by a priori computation of patient-specific timing of data acquisition for MR angiography.

Estimates of the low-level wind shear and turbulence in the vicinity of Kennedy International Airport on 24 June 1975

NASA Technical Reports Server (NTRS)

Lewellen, W. S.; Williamson, G. G.

1976-01-01

A study was conducted to estimate the type of wind and turbulence distributions which may have existed at the time of the crash of Eastern Airlines Flight 66 while attempting to land. A number of different wind and turbulence profiles are predicted for the site and date of the crash. The morning and mid-afternoon predictions are in reasonably good agreement with magnitude and direction as reported by the weather observer. Although precise predictions cannot be made during the passage of the thunderstorm which coincides with the time of the accident, a number of different profiles which might exist under or in the vicinity of a thunderstorm are presented. The profile that is most probable predicts the mean headwind shear over 100 m (300 feet) altitude change and the average fluctuations about the mean headwind distribution. This combination of means and fluctuations leads to a reasonable probability that the instantaneous headwind shear would equal the maximum value reported in the flight recorder data.

Statistical modelling coupled with LC-MS analysis to predict human upper intestinal absorption of phytochemical mixtures.

PubMed

Selby-Pham, Sophie N B; Howell, Kate S; Dunshea, Frank R; Ludbey, Joel; Lutz, Adrian; Bennett, Louise

2018-04-15

A diet rich in phytochemicals confers benefits for health by reducing the risk of chronic diseases via regulation of oxidative stress and inflammation (OSI). For optimal protective bio-efficacy, the time required for phytochemicals and their metabolites to reach maximal plasma concentrations (T max ) should be synchronised with the time of increased OSI. A statistical model has been reported to predict T max of individual phytochemicals based on molecular mass and lipophilicity. We report the application of the model for predicting the absorption profile of an uncharacterised phytochemical mixture, herein referred to as the 'functional fingerprint'. First, chemical profiles of phytochemical extracts were acquired using liquid chromatography mass spectrometry (LC-MS), then the molecular features for respective components were used to predict their plasma absorption maximum, based on molecular mass and lipophilicity. This method of 'functional fingerprinting' of plant extracts represents a novel tool for understanding and optimising the health efficacy of plant extracts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Potential for thermal tolerance to mediate climate change effects on three members of a cool temperate lizard genus, Niveoscincus.

PubMed

Caldwell, Amanda J; While, Geoffrey M; Beeton, Nicholas J; Wapstra, Erik

2015-08-01

Climatic changes are predicted to be greater in higher latitude and mountainous regions but species specific impacts are difficult to predict. This is partly due to inter-specific variance in the physiological traits which mediate environmental temperature effects at the organismal level. We examined variation in the critical thermal minimum (CTmin), critical thermal maximum (CTmax) and evaporative water loss rates (EWL) of a widespread lowland (Niveoscincus ocellatus) and two range restricted highland (N. microlepidotus and N. greeni) members of a cool temperate Tasmanian lizard genus. The widespread lowland species had significantly higher CTmin and CTmax and significantly lower EWL than both highland species. Implications of inter-specific variation in thermal tolerance for activity were examined under contemporary and future climate change scenarios. Instances of air temperatures below CTmin were predicted to decline in frequency for the widespread lowland and both highland species. Air temperatures of high altitude sites were not predicted to exceed the CTmax of either highland species throughout the 21st century. In contrast, the widespread lowland species is predicted to experience air temperatures in excess of CTmax on 1 or 2 days by three of six global circulation models from 2068-2096. To estimate climate change effects on activity we reran the thermal tolerance models using minimum and maximum temperatures selected for activity. A net gain in available activity time was predicted under climate change for all three species; while air temperatures were predicted to exceed maximum temperatures selected for activity with increasing frequency, the change was not as great as the predicted decline in air temperatures below minimum temperatures selected for activity. We hypothesise that the major effect of rising air temperatures under climate change is an increase in available activity period for both the widespread lowland and highland species. The consequences of a greater available activity period will depend on the extent to which changes in climate alters other related factors, such as the nature and level of competition between the respective species. Copyright © 2015 Elsevier Ltd. All rights reserved.

MEM spectral analysis for predicting influenza epidemics in Japan.

PubMed

Sumi, Ayako; Kamo, Ken-ichi

2012-03-01

The prediction of influenza epidemics has long been the focus of attention in epidemiology and mathematical biology. In this study, we tested whether time series analysis was useful for predicting the incidence of influenza in Japan. The method of time series analysis we used consists of spectral analysis based on the maximum entropy method (MEM) in the frequency domain and the nonlinear least squares method in the time domain. Using this time series analysis, we analyzed the incidence data of influenza in Japan from January 1948 to December 1998; these data are unique in that they covered the periods of pandemics in Japan in 1957, 1968, and 1977. On the basis of the MEM spectral analysis, we identified the periodic modes explaining the underlying variations of the incidence data. The optimum least squares fitting (LSF) curve calculated with the periodic modes reproduced the underlying variation of the incidence data. An extension of the LSF curve could be used to predict the incidence of influenza quantitatively. Our study suggested that MEM spectral analysis would allow us to model temporal variations of influenza epidemics with multiple periodic modes much more effectively than by using the method of conventional time series analysis, which has been used previously to investigate the behavior of temporal variations in influenza data.

Real-time Interplanetary Shock Prediction System

NASA Astrophysics Data System (ADS)

Vandegriff, J. D.; Ho, G. C.; Plauger, J. M.

2002-05-01

We are creating a system to predict the arrival times and maximum intensities of energetic storm particle (ESP) events at the earth using particle fluxes measured by the EPAM instrument aboard NASA's ACE spacecraft. Real-time flux measurements, consisting of 5 minute averages made available 24 hours per day by the NOAA Space Environment Center, are fed into algorithms looking for characteristic changes in flux, velocity dispersion, and anisotropy. These quantities typically show changes up to 3 hours before shock passage, and thus we expect our system to deliver enhanced probabilities for shock arrival with approximately the same lead time. Forecasting information will be made publicly available through http://sd-www.jhuapl.edu/ACE/EPAM/, the Johns Hopkins University Applied Physics Lab web site for the ACE/EPAM instrument. Early results on the training of our algorithms and comparisons with past shock data will be presented.

The Stellar IMF from Isothermal MHD Turbulence

NASA Astrophysics Data System (ADS)

Haugbølle, Troels; Padoan, Paolo; Nordlund, Åke

2018-02-01

We address the turbulent fragmentation scenario for the origin of the stellar initial mass function (IMF), using a large set of numerical simulations of randomly driven supersonic MHD turbulence. The turbulent fragmentation model successfully predicts the main features of the observed stellar IMF assuming an isothermal equation of state without any stellar feedback. As a test of the model, we focus on the case of a magnetized isothermal gas, neglecting stellar feedback, while pursuing a large dynamic range in both space and timescales covering the full spectrum of stellar masses from brown dwarfs to massive stars. Our simulations represent a generic 4 pc region within a typical Galactic molecular cloud, with a mass of 3000 M ⊙ and an rms velocity 10 times the isothermal sound speed and 5 times the average Alfvén velocity, in agreement with observations. We achieve a maximum resolution of 50 au and a maximum duration of star formation of 4.0 Myr, forming up to a thousand sink particles whose mass distribution closely matches the observed stellar IMF. A large set of medium-size simulations is used to test the sink particle algorithm, while larger simulations are used to test the numerical convergence of the IMF and the dependence of the IMF turnover on physical parameters predicted by the turbulent fragmentation model. We find a clear trend toward numerical convergence and strong support for the model predictions, including the initial time evolution of the IMF. We conclude that the physics of isothermal MHD turbulence is sufficient to explain the origin of the IMF.

Predicting coral bleaching hotspots: the role of regional variability in thermal stress and potential adaptation rates

NASA Astrophysics Data System (ADS)

Teneva, Lida; Karnauskas, Mandy; Logan, Cheryl A.; Bianucci, Laura; Currie, Jock C.; Kleypas, Joan A.

2012-03-01

Sea surface temperature fields (1870-2100) forced by CO2-induced climate change under the IPCC SRES A1B CO2 scenario, from three World Climate Research Programme Coupled Model Intercomparison Project Phase 3 (WCRP CMIP3) models (CCSM3, CSIRO MK 3.5, and GFDL CM 2.1), were used to examine how coral sensitivity to thermal stress and rates of adaption affect global projections of coral-reef bleaching. The focus of this study was two-fold, to: (1) assess how the impact of Degree-Heating-Month (DHM) thermal stress threshold choice affects potential bleaching predictions and (2) examine the effect of hypothetical adaptation rates of corals to rising temperature. DHM values were estimated using a conventional threshold of 1°C and a variability-based threshold of 2σ above the climatological maximum Coral adaptation rates were simulated as a function of historical 100-year exposure to maximum annual SSTs with a dynamic rather than static climatological maximum based on the previous 100 years, for a given reef cell. Within CCSM3 simulations, the 1°C threshold predicted later onset of mild bleaching every 5 years for the fraction of reef grid cells where 1°C > 2σ of the climatology time series of annual SST maxima (1961-1990). Alternatively, DHM values using both thresholds, with CSIRO MK 3.5 and GFDL CM 2.1 SSTs, did not produce drastically different onset timing for bleaching every 5 years. Across models, DHMs based on 1°C thermal stress threshold show the most threatened reefs by 2100 could be in the Central and Western Equatorial Pacific, whereas use of the variability-based threshold for DHMs yields the Coral Triangle and parts of Micronesia and Melanesia as bleaching hotspots. Simulations that allow corals to adapt to increases in maximum SST drastically reduce the rates of bleaching. These findings highlight the importance of considering the thermal stress threshold in DHM estimates as well as potential adaptation models in future coral bleaching projections.

Experimental design and response surface modelling for optimization of vat dye from water by nano zero valent iron (NZVI).

PubMed

Arabi, Simin; Sohrabi, Mahmoud Reza

2013-01-01

In this study, NZVI particles was prepared and studied for the removal of vat green 1 dye from aqueous solution. A four-factor central composite design (CCD) combined with response surface modeling (RSM) to evaluate the combined effects of variables as well as optimization was employed for maximizing the dye removal by prepared NZVI based on 30 different experimental data obtained in a batch study. Four independent variables, viz. NZVI dose (0.1-0.9 g/L), pH (1.5-9.5), contact time (20-100 s), and initial dye concentration (10-50 mg/L) were transform to coded values and quadratic model was built to predict the responses. The significant of independent variables and their interactions were tested by the analysis of variance (ANOVA). Adequacy of the model was tested by the correlation between experimental and predicted values of the response and enumeration of prediction errors. The ANOVA results indicated that the proposed model can be used to navigate the design space. Optimization of the variables for maximum adsorption of dye by NZVI particles was performed using quadratic model. The predicted maximum adsorption efficiency (96.97%) under the optimum conditions of the process variables (NZVI dose 0.5 g/L, pH 4, contact time 60 s, and initial dye concentration 30 mg/L) was very close to the experimental value (96.16%) determined in batch experiment. In the optimization, R2 and R2adj correlation coefficients for the model were evaluated as 0.95 and 0.90, respectively.

Predicting a 10 repetition maximum for the free weight parallel squat using the 45 degrees angled leg press.

PubMed

Willardson, Jeffrey M; Bressel, Eadric

2004-08-01

The purpose of this research was to devise prediction equations whereby a 10 repetition maximum (10RM) for the free weight parallel squat could be predicted using the following predictor variables: 10RM for the 45 degrees angled leg press, body mass, and limb length. Sixty men were tested over a 3-week period, with 1 testing session each week. During each testing session, subjects performed a 10RM for the free weight parallel squat and 45 degrees angled leg press. Stepwise multiple regression analysis showed leg press mass lifted to be a significant predictor of squat mass lifted for both the advanced and the novice groups (p < 0.05). Leg press mass lifted accounted for approximately 25% of the variance in squat mass lifted for the novice group and 55% of the variance in squat mass lifted for the advanced group. Limb length and body mass were not significant predictors of squat mass lifted for either group. The following prediction equations were devised: (a) novice group squat mass = leg press mass (0.210) + 36.244 kg, (b) advanced group squat mass = leg press mass (0.310) + 19.438 kg, and (c) subject pool squat mass = leg press mass (0.354) + 2.235 kg. These prediction equations may save time and reduce the risk of injury when switching from the leg press to the squat exercise.

Model-driven development of covariances for spatiotemporal environmental health assessment.

PubMed

Kolovos, Alexander; Angulo, José Miguel; Modis, Konstantinos; Papantonopoulos, George; Wang, Jin-Feng; Christakos, George

2013-01-01

Known conceptual and technical limitations of mainstream environmental health data analysis have directed research to new avenues. The goal is to deal more efficiently with the inherent uncertainty and composite space-time heterogeneity of key attributes, account for multi-sourced knowledge bases (health models, survey data, empirical relationships etc.), and generate more accurate predictions across space-time. Based on a versatile, knowledge synthesis methodological framework, we introduce new space-time covariance functions built by integrating epidemic propagation models and we apply them in the analysis of existing flu datasets. Within the knowledge synthesis framework, the Bayesian maximum entropy theory is our method of choice for the spatiotemporal prediction of the ratio of new infectives (RNI) for a case study of flu in France. The space-time analysis is based on observations during a period of 15 weeks in 1998-1999. We present general features of the proposed covariance functions, and use these functions to explore the composite space-time RNI dependency. We then implement the findings to generate sufficiently detailed and informative maps of the RNI patterns across space and time. The predicted distributions of RNI suggest substantive relationships in accordance with the typical physiographic and climatologic features of the country.

Characterization and Prediction of the SPI Background

NASA Technical Reports Server (NTRS)

Teegarden, B. J.; Jean, P.; Knodlseder, J.; Skinner, G. K.; Weidenspointer, G.

2003-01-01

The INTEGRAL Spectrometer, like most gamma-ray instruments, is background dominated. Signal-to-background ratios of a few percent are typical. The background is primarily due to interactions of cosmic rays in the instrument and spacecraft. It characteristically varies by +/- 5% on time scales of days. This variation is caused mainly by fluctuations in the interplanetary magnetic field that modulates the cosmic ray intensity. To achieve the maximum performance from SPI it is essential to have a high quality model of this background that can predict its value to a fraction of a percent. In this poster we characterize the background and its variability, explore various models, and evaluate the accuracy of their predictions.

Leonid predictions for the period 2001-2100

NASA Astrophysics Data System (ADS)

Maslov, Mikhail

2007-02-01

This article provides a set of summaries of what to expect from the Leonid meteor shower for each year of the period 2001-2100. Each summary contains the moments of maximum/maxima, their expected intensity and some comments about average meteor brightness during them. Special attention was paid to background (traditional) maxima, which are characterized with their expected times and intensities.

Non-Gaussian effects, space-time decoupling, and mobility bifurcation in glassy hard-sphere fluids and suspensions.

PubMed

Saltzman, Erica J; Schweizer, Kenneth S

2006-12-01

Brownian trajectory simulation methods are employed to fully establish the non-Gaussian fluctuation effects predicted by our nonlinear Langevin equation theory of single particle activated dynamics in glassy hard-sphere fluids. The consequences of stochastic mobility fluctuations associated with the space-time complexities of the transient localization and barrier hopping processes have been determined. The incoherent dynamic structure factor was computed for a range of wave vectors and becomes of an increasingly non-Gaussian form for volume fractions beyond the (naive) ideal mode coupling theory (MCT) transition. The non-Gaussian parameter (NGP) amplitude increases markedly with volume fraction and is well described by a power law in the maximum restoring force of the nonequilibrium free energy profile. The time scale associated with the NGP peak becomes much smaller than the alpha relaxation time for systems characterized by significant entropic barriers. An alternate non-Gaussian parameter that probes the long time alpha relaxation process displays a different shape, peak intensity, and time scale of its maximum. However, a strong correspondence between the classic and alternate NGP amplitudes is predicted which suggests a deep connection between the early and final stages of cage escape. Strong space-time decoupling emerges at high volume fractions as indicated by a nondiffusive wave vector dependence of the relaxation time and growth of the translation-relaxation decoupling parameter. Displacement distributions exhibit non-Gaussian behavior at intermediate times, evolving into a strongly bimodal form with slow and fast subpopulations at high volume fractions. Qualitative and semiquantitative comparisons of the theoretical results with colloid experiments, ideal MCT, and multiple simulation studies are presented.

Climate predictability and prediction skill on seasonal time scales over South America from CHFP models

NASA Astrophysics Data System (ADS)

Osman, Marisol; Vera, C. S.

2017-10-01

This work presents an assessment of the predictability and skill of climate anomalies over South America. The study was made considering a multi-model ensemble of seasonal forecasts for surface air temperature, precipitation and regional circulation, from coupled global circulation models included in the Climate Historical Forecast Project. Predictability was evaluated through the estimation of the signal-to-total variance ratio while prediction skill was assessed computing anomaly correlation coefficients. Both indicators present over the continent higher values at the tropics than at the extratropics for both, surface air temperature and precipitation. Moreover, predictability and prediction skill for temperature are slightly higher in DJF than in JJA while for precipitation they exhibit similar levels in both seasons. The largest values of predictability and skill for both variables and seasons are found over northwestern South America while modest but still significant values for extratropical precipitation at southeastern South America and the extratropical Andes. The predictability levels in ENSO years of both variables are slightly higher, although with the same spatial distribution, than that obtained considering all years. Nevertheless, predictability at the tropics for both variables and seasons diminishes in both warm and cold ENSO years respect to that in all years. The latter can be attributed to changes in signal rather than in the noise. Predictability and prediction skill for low-level winds and upper-level zonal winds over South America was also assessed. Maximum levels of predictability for low-level winds were found were maximum mean values are observed, i.e. the regions associated with the equatorial trade winds, the midlatitudes westerlies and the South American Low-Level Jet. Predictability maxima for upper-level zonal winds locate where the subtropical jet peaks. Seasonal changes in wind predictability are observed that seem to be related to those associated with the signal, especially at the extratropics.

Predictive modeling of mosquito abundance and dengue transmission in Kenya

NASA Astrophysics Data System (ADS)

Caldwell, J.; Krystosik, A.; Mutuku, F.; Ndenga, B.; LaBeaud, D.; Mordecai, E.

2017-12-01

Approximately 390 million people are exposed to dengue virus every year, and with no widely available treatments or vaccines, predictive models of disease risk are valuable tools for vector control and disease prevention. The aim of this study was to modify and improve climate-driven predictive models of dengue vector abundance (Aedes spp. mosquitoes) and viral transmission to people in Kenya. We simulated disease transmission using a temperature-driven mechanistic model and compared model predictions with vector trap data for larvae, pupae, and adult mosquitoes collected between 2014 and 2017 at four sites across urban and rural villages in Kenya. We tested predictive capacity of our models using four temperature measurements (minimum, maximum, range, and anomalies) across daily, weekly, and monthly time scales. Our results indicate seasonal temperature variation is a key driving factor of Aedes mosquito abundance and disease transmission. These models can help vector control programs target specific locations and times when vectors are likely to be present, and can be modified for other Aedes-transmitted diseases and arboviral endemic regions around the world.

On the Maximum and Characteristic Curvature of Current Density of High tc Superconductor Ybco in Flux Relaxation

NASA Astrophysics Data System (ADS)

Ye, Jiping; Sun, Lei; Dai, Xianxi; Dai, Jixin

The flux relaxation is one of important topics in the studies of high Tc superconductivity, because it is related to the energy loss in practical applications. There are many mechanisms, theories and relaxation laws suggested in the literatures. It is very interesting to test them according to the characters and compare them with the experiments. Some people think that the characters of the famous theories are their negative curvature. According our inversion solution, the relaxation ArcG law and experimental data analysis, the relaxation law has both positive and negative signs. This prediction is hopeful to be checked by experiments in future. The current densities of many high Tc superconductors decrease very rapidly in the early time in the relaxation. People do not know what their maximums are. In this work, a theory to determine these maximums of the current densities is presented. The theory is concretely realized by inversion for some real data of the YBCO and their maximum current densities are obtained.

Sensitivity analysis of tall buildings in Semarang, Indonesia due to fault earthquakes with maximum 7 Mw

NASA Astrophysics Data System (ADS)

Partono, Windu; Pardoyo, Bambang; Atmanto, Indrastono Dwi; Azizah, Lisa; Chintami, Rouli Dian

2017-11-01

Fault is one of the dangerous earthquake sources that can cause building failure. A lot of buildings were collapsed caused by Yogyakarta (2006) and Pidie (2016) fault source earthquakes with maximum magnitude 6.4 Mw. Following the research conducted by Team for Revision of Seismic Hazard Maps of Indonesia 2010 and 2016, Lasem, Demak and Semarang faults are three closest earthquake sources surrounding Semarang. The ground motion from those three earthquake sources should be taken into account for structural design and evaluation. Most of tall buildings, with minimum 40 meter high, in Semarang were designed and constructed following the 2002 and 2012 Indonesian Seismic Code. This paper presents the result of sensitivity analysis research with emphasis on the prediction of deformation and inter-story drift of existing tall building within the city against fault earthquakes. The analysis was performed by conducting dynamic structural analysis of 8 (eight) tall buildings using modified acceleration time histories. The modified acceleration time histories were calculated for three fault earthquakes with magnitude from 6 Mw to 7 Mw. The modified acceleration time histories were implemented due to inadequate time histories data caused by those three fault earthquakes. Sensitivity analysis of building against earthquake can be predicted by evaluating surface response spectra calculated using seismic code and surface response spectra calculated from acceleration time histories from a specific earthquake event. If surface response spectra calculated using seismic code is greater than surface response spectra calculated from acceleration time histories the structure will stable enough to resist the earthquake force.

Methods for utilizing maximum power from a solar array

NASA Technical Reports Server (NTRS)

Decker, D. K.

1972-01-01

A preliminary study of maximum power utilization methods was performed for an outer planet spacecraft using an ion thruster propulsion system and a solar array as the primary energy source. The problems which arise from operating the array at or near the maximum power point of its 1-V characteristic are discussed. Two closed loop system configurations which use extremum regulators to track the array's maximum power point are presented. Three open loop systems are presented that either: (1) measure the maximum power of each array section and compute the total array power, (2) utilize a reference array to predict the characteristics of the solar array, or (3) utilize impedance measurements to predict the maximum power utilization. The advantages and disadvantages of each system are discussed and recommendations for further development are made.

Serial evaluation of the MODS, SOFA and LOD scores to predict ICU mortality in mixed critically ill patients.

PubMed

Khwannimit, Bodin

2008-09-01

To perform a serial assessment and compare ability in predicting the intensive care unit (ICU) mortality of the multiple organ dysfunction score (MODS), sequential organ failure assessment (SOFA) and logistic organ dysfunction (LOD) score. The data were collected prospectively on consecutive ICU admissions over a 24-month period at a tertiary referral university hospital. The MODS, SOFA, and LOD scores were calculated on initial and repeated every 24 hrs. Two thousand fifty four patients were enrolled in the present study. The maximum and delta-scores of all the organ dysfunction scores correlated with ICU mortality. The maximum score of all models had better ability for predicting ICU mortality than initial or delta score. The areas under the receiver operating characteristic curve (AUC) for maximum scores was 0.892 for the MODS, 0.907 for the SOFA, and 0.92for the LOD. No statistical difference existed between all maximum scores and Acute Physiology and Chronic Health Evaluation II (APACHE II) score. Serial assessment of organ dysfunction during the ICU stay is reliable with ICU mortality. The maximum scores is the best discrimination comparable with APACHE II score in predicting ICU mortality.

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. Copyright © 2016 Elsevier Inc. All rights reserved.

Rock Cutting Depth Model Based on Kinetic Energy of Abrasive Waterjet

NASA Astrophysics Data System (ADS)

Oh, Tae-Min; Cho, Gye-Chun

2016-03-01

Abrasive waterjets are widely used in the fields of civil and mechanical engineering for cutting a great variety of hard materials including rocks, metals, and other materials. Cutting depth is an important index to estimate operating time and cost, but it is very difficult to predict because there are a number of influential variables (e.g., energy, geometry, material, and nozzle system parameters). In this study, the cutting depth is correlated to the maximum kinetic energy expressed in terms of energy (i.e., water pressure, water flow rate, abrasive feed rate, and traverse speed), geometry (i.e., standoff distance), material (i.e., α and β), and nozzle system parameters (i.e., nozzle size, shape, and jet diffusion level). The maximum kinetic energy cutting depth model is verified with experimental test data that are obtained using one type of hard granite specimen for various parameters. The results show a unique curve for a specific rock type in a power function between cutting depth and maximum kinetic energy. The cutting depth model developed here can be very useful for estimating the process time when cutting rock using an abrasive waterjet.

Effect of operating conditions on yield and quality of biocrude during hydrothermal liquefaction of halophytic microalga Tetraselmis sp.

PubMed

Eboibi, B E; Lewis, D M; Ashman, P J; Chinnasamy, S

2014-10-01

The biomass of halophytic microalga Tetraselmis sp. with 16%w/w solids was converted into biocrude by a hydrothermal liquefaction (HTL) process in a batch reactor at different temperatures (310, 330, 350 and 370°C) and reaction times (5, 15, 30, 45 and 60min). The biocrude yield, elemental composition, energy density and severity parameter obtained at various reaction conditions were used to predict the optimum condition for maximum recovery of biocrude with improved quality. This study clearly indicated that the operating condition for obtaining maximum biocrude yield and ideal quality biocrude for refining were different. A maximum biocrude yield of ∼65wt% ash free dry weight (AFDW) was obtained at 350°C and 5min, with a severity parameter and energy density of 5.21 and ∼35MJ/kg, respectively. The treatment with 45min reaction time recorded ∼62wt% (AFDW) yield of biocrude with and energy density of ∼39MJ/kg and higher severity parameter of 7.53. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prediction of work metabolism from heart rate measurements in forest work: some practical methodological issues.

PubMed

Dubé, Philippe-Antoine; Imbeau, Daniel; Dubeau, Denise; Auger, Isabelle; Leone, Mario

2015-01-01

Individual heart rate (HR) to workload relationships were determined using 93 submaximal step-tests administered to 26 healthy participants attending physical activities in a university training centre (laboratory study) and 41 experienced forest workers (field study). Predicted maximum aerobic capacity (MAC) was compared to measured MAC from a maximal treadmill test (laboratory study) to test the effect of two age-predicted maximum HR Equations (220-age and 207-0.7 × age) and two clothing insulation levels (0.4 and 0.91 clo) during the step-test. Work metabolism (WM) estimated from forest work HR was compared against concurrent work V̇O2 measurements while taking into account the HR thermal component. Results show that MAC and WM can be accurately predicted from work HR measurements and simple regression models developed in this study (1% group mean prediction bias and up to 25% expected prediction bias for a single individual). Clothing insulation had no impact on predicted MAC nor age-predicted maximum HR equations. Practitioner summary: This study sheds light on four practical methodological issues faced by practitioners regarding the use of HR methodology to assess WM in actual work environments. More specifically, the effect of wearing work clothes and the use of two different maximum HR prediction equations on the ability of a submaximal step-test to assess MAC are examined, as well as the accuracy of using an individual's step-test HR to workload relationship to predict WM from HR data collected during actual work in the presence of thermal stress.

Cycling Power Outputs Predict Functional Threshold Power And Maximum Oxygen Uptake.

PubMed

Denham, Joshua; Scott-Hamilton, John; Hagstrom, Amanda D; Gray, Adrian J

2017-09-11

Functional threshold power (FTP) has emerged as a correlate of lactate threshold and is commonly assessed by recreational and professional cyclists for tailored exercise programing. To identify whether results from traditional aerobic and anaerobic cycling tests could predict FTP and V˙ O2max, we analysed the association between estimated FTP, maximum oxygen uptake (V˙ O2max [mlkgmin]) and power outputs obtained from a maximal cycle ergometry cardiopulmonary exercise test (CPET) and a 30-s Wingate test in a heterogeneous cohort of cycle-trained and untrained individuals (N=40, mean±SD; age: 32.6±10.6 y; relative V˙ O2max: 46.8±9.1 mlkgmin). The accuracy and sensitivity of the prediction equations was also assessed in young men (N=11) before and after a 6-wk sprint interval training intervention.Moderate to strong positive correlations were observed between FTP, relative V˙ O2max and power outputs achieved during incremental and 30-s Wingate cycling tests (r=.39-.965, all P<.05). While maximum power achieved during incremental cycle testing (Pmax) and relative V˙ O2max were predictors of FTP (r =.93), age and FTP (Wkg) estimated relative V˙ O2max (r=.80). Our findings confirm that FTP predominantly relies on aerobic metabolism and indicate both prediction models are sensitive enough to detect meaningful exercise-induced changes in FTP and V˙ O2max. Thus, coaches should consider limiting the time and load demands placed on athletes by conducting a maximal cycle ergometry CPET to estimate FTP. Additionally, a 20-min FTP test is a convenient method to assess V˙ O2max and is particularly relevant for exercise professionals without access to expensive CPET equipment.

Proposal for a New Prognostic Score for Linac-Based Radiosurgery in Cerebral Arteriovenous Malformations

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

Milker-Zabel, Stefanie, E-mail: Stefanie_Milker-Zabel@med.uni-heidelberg.de; Kopp-Schneider, Annette; Wiesbauer, Hannah

2012-06-01

Purpose: We evaluate patient-, angioma-, and treatment-specific factors for successful obliteration of cerebral arteriovenous malformations (AVM) to develop a new appropriate score to predict patient outcome after linac-based radiosurgery (RS). Methods and Materials: This analysis in based on 293 patients with cerebral AVM. Mean age at treatment was 38.8 years (4-73 years). AVM classification according Spetzler-Martin was 55 patients Grade I (20.5%), 114 Grade II (42.5%), 79 Grade III (29.5%), 19 Grade IV (7.1%), and 1 Grade V (0.4%). Median maximum AVM diameter was 3.0 cm (range, 0.3-10 cm). Median dose prescribed to the 80% isodose was 18 Gy (range,more » 12-22 Gy). Eighty-five patients (29.1%) had prior partial embolization; 141 patients (51.9%) experienced intracranial hemorrhage before RS. Median follow-up was 4.2 years. Results: Age at treatment, maximum diameter, nidus volume, and applied dose were significant factors for successful obliteration. Under presumption of proportional hazard in the dose range between 12 and 22 Gy/80% isodose, an increase of obliteration rate of approximately 25% per Gy was seen. On the basis of multivariate analysis, a prediction score was calculated including AVM maximum diameter and age at treatment. The prediction error up to the time point 8 years was 0.173 for the Heidelberg score compared with the Kaplan-Meier value of 0.192. An increase of the score of 1 point results in a decrease of obliteration chance by a factor of 0.447. Conclusion: The proposed score is linac-based radiosurgery-specific and easy to handle to predict patient outcome. Further validation on an independent patient cohort is necessary.« less

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

NASA Astrophysics Data System (ADS)

Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William

2017-10-01

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.

Prediction modeling of physiological responses and human performance in the heat with application to space operations

NASA Technical Reports Server (NTRS)

Pandolf, Kent B.; Stroschein, Leander A.; Gonzalez, Richard R.; Sawka, Michael N.

1994-01-01

This institute has developed a comprehensive USARIEM heat strain model for predicting physiological responses and soldier performance in the heat which has been programmed for use by hand-held calculators, personal computers, and incorporated into the development of a heat strain decision aid. This model deals directly with five major inputs: the clothing worn, the physical work intensity, the state of heat acclimation, the ambient environment (air temperature, relative humidity, wind speed, and solar load), and the accepted heat casualty level. In addition to predicting rectal temperature, heart rate, and sweat loss given the above inputs, our model predicts the expected physical work/rest cycle, the maximum safe physical work time, the estimated recovery time from maximal physical work, and the drinking water requirements associated with each of these situations. This model provides heat injury risk management guidance based on thermal strain predictions from the user specified environmental conditions, soldier characteristics, clothing worn, and the physical work intensity. If heat transfer values for space operations' clothing are known, NASA can use this prediction model to help avoid undue heat strain in astronauts during space flight.

Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

PubMed

Azevedo Peixoto, Leonardo de; Laviola, Bruno Galvêas; Alves, Alexandre Alonso; Rosado, Tatiana Barbosa; Bhering, Leonardo Lopes

2017-01-01

Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

Seizure prediction in hippocampal and neocortical epilepsy using a model-based approach

PubMed Central

Aarabi, Ardalan; He, Bin

2014-01-01

Objectives The aim of this study is to develop a model based seizure prediction method. Methods A neural mass model was used to simulate the macro-scale dynamics of intracranial EEG data. The model was composed of pyramidal cells, excitatory and inhibitory interneurons described through state equations. Twelve model’s parameters were estimated by fitting the model to the power spectral density of intracranial EEG signals and then integrated based on information obtained by investigating changes in the parameters prior to seizures. Twenty-one patients with medically intractable hippocampal and neocortical focal epilepsy were studied. Results Tuned to obtain maximum sensitivity, an average sensitivity of 87.07% and 92.6% with an average false prediction rate of 0.2 and 0.15/h were achieved using maximum seizure occurrence periods of 30 and 50 min and a minimum seizure prediction horizon of 10 s, respectively. Under maximum specificity conditions, the system sensitivity decreased to 82.9% and 90.05% and the false prediction rates were reduced to 0.16 and 0.12/h using maximum seizure occurrence periods of 30 and 50 min, respectively. Conclusions The spatio-temporal changes in the parameters demonstrated patient-specific preictal signatures that could be used for seizure prediction. Significance The present findings suggest that the model-based approach may aid prediction of seizures. PMID:24374087

Maximum caliber inference of nonequilibrium processes

NASA Astrophysics Data System (ADS)

Otten, Moritz; Stock, Gerhard

2010-07-01

Thirty years ago, Jaynes suggested a general theoretical approach to nonequilibrium statistical mechanics, called maximum caliber (MaxCal) [Annu. Rev. Phys. Chem. 31, 579 (1980)]. MaxCal is a variational principle for dynamics in the same spirit that maximum entropy is a variational principle for equilibrium statistical mechanics. Motivated by the success of maximum entropy inference methods for equilibrium problems, in this work the MaxCal formulation is applied to the inference of nonequilibrium processes. That is, given some time-dependent observables of a dynamical process, one constructs a model that reproduces these input data and moreover, predicts the underlying dynamics of the system. For example, the observables could be some time-resolved measurements of the folding of a protein, which are described by a few-state model of the free energy landscape of the system. MaxCal then calculates the probabilities of an ensemble of trajectories such that on average the data are reproduced. From this probability distribution, any dynamical quantity of the system can be calculated, including population probabilities, fluxes, or waiting time distributions. After briefly reviewing the formalism, the practical numerical implementation of MaxCal in the case of an inference problem is discussed. Adopting various few-state models of increasing complexity, it is demonstrated that the MaxCal principle indeed works as a practical method of inference: The scheme is fairly robust and yields correct results as long as the input data are sufficient. As the method is unbiased and general, it can deal with any kind of time dependency such as oscillatory transients and multitime decays.

Pretest parametric calculations for the heated pillar experiment in the WIPP In-Situ Experimental Area

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

Branstetter, L.J.

Results are presented for a pretest parametric study of several configurations and heat loads for the heated pillar experiment (Room H) in the Waste Isolation Pilot Plant (WIPP) In Situ Experimental Area. The purpose of this study is to serve as a basis for selection of a final experiment geometry and heat load. The experiment consists of a pillar of undisturbed rock salt surrounded by an excavated annular room. The pillar surface is covered by a blanket heat source which is externally insulated. A total of five thermal and ten structural calculations are described in a four to five yearmore » experimental time frame. Results are presented which include relevant temperature-time histories, deformations, rock salt stress component and effective stress profiles, and maximum stresses in anhydrite layers which are in close proximity to the room. Also included are predicted contours of a conservative post-processed measure of potential salt failure. Observed displacement histories are seen to be highly dependent on pillar and room height, but insensitive to other geometrical variations. The use of a tensile cutoff across slidelines is seen to produce more accurate predictions of anhydrite maximum stress, but to have little effect on rock salt stresses. The potential for salt failure is seen to be small in each case for the time frame of interest, and is only seen at longer times in the center of the room floor.« less

Message survival and decision dynamics in a class of reactive complex systems subject to external fields

NASA Astrophysics Data System (ADS)

Rodriguez Lucatero, C.; Schaum, A.; Alarcon Ramos, L.; Bernal-Jaquez, R.

2014-07-01

In this study, the dynamics of decisions in complex networks subject to external fields are studied within a Markov process framework using nonlinear dynamical systems theory. A mathematical discrete-time model is derived using a set of basic assumptions regarding the convincement mechanisms associated with two competing opinions. The model is analyzed with respect to the multiplicity of critical points and the stability of extinction states. Sufficient conditions for extinction are derived in terms of the convincement probabilities and the maximum eigenvalues of the associated connectivity matrices. The influences of exogenous (e.g., mass media-based) effects on decision behavior are analyzed qualitatively. The current analysis predicts: (i) the presence of fixed-point multiplicity (with a maximum number of four different fixed points), multi-stability, and sensitivity with respect to the process parameters; and (ii) the bounded but significant impact of exogenous perturbations on the decision behavior. These predictions were verified using a set of numerical simulations based on a scale-free network topology.

Spatiotemporal modeling of PM2.5 concentrations at the national scale combining land use regression and Bayesian maximum entropy in China.

PubMed

Chen, Li; Gao, Shuang; Zhang, Hui; Sun, Yanling; Ma, Zhenxing; Vedal, Sverre; Mao, Jian; Bai, Zhipeng

2018-05-03

Concentrations of particulate matter with aerodynamic diameter <2.5 μm (PM 2.5 ) are relatively high in China. Estimation of PM 2.5 exposure is complex because PM 2.5 exhibits complex spatiotemporal patterns. To improve the validity of exposure predictions, several methods have been developed and applied worldwide. A hybrid approach combining a land use regression (LUR) model and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals were developed to estimate the PM 2.5 concentrations on a national scale in China. This hybrid model could potentially provide more valid predictions than a commonly-used LUR model. The LUR/BME model had good performance characteristics, with R 2  = 0.82 and root mean square error (RMSE) of 4.6 μg/m 3 . Prediction errors of the LUR/BME model were reduced by incorporating soft data accounting for data uncertainty, with the R 2 increasing by 6%. The performance of LUR/BME is better than OK/BME. The LUR/BME model is the most accurate fine spatial scale PM 2.5 model developed to date for China. Copyright © 2018. Published by Elsevier Ltd.

Daily sea level prediction at Chiayi coast, Taiwan using extreme learning machine and relevance vector machine

NASA Astrophysics Data System (ADS)

Imani, Moslem; Kao, Huan-Chin; Lan, Wen-Hau; Kuo, Chung-Yen

2018-02-01

The analysis and the prediction of sea level fluctuations are core requirements of marine meteorology and operational oceanography. Estimates of sea level with hours-to-days warning times are especially important for low-lying regions and coastal zone management. The primary purpose of this study is to examine the applicability and capability of extreme learning machine (ELM) and relevance vector machine (RVM) models for predicting sea level variations and compare their performances with powerful machine learning methods, namely, support vector machine (SVM) and radial basis function (RBF) models. The input dataset from the period of January 2004 to May 2011 used in the study was obtained from the Dongshi tide gauge station in Chiayi, Taiwan. Results showed that the ELM and RVM models outperformed the other methods. The performance of the RVM approach was superior in predicting the daily sea level time series given the minimum root mean square error of 34.73 mm and the maximum determination coefficient of 0.93 (R2) during the testing periods. Furthermore, the obtained results were in close agreement with the original tide-gauge data, which indicates that RVM approach is a promising alternative method for time series prediction and could be successfully used for daily sea level forecasts.

Creep fatigue life prediction for engine hot section materials (isotropic)

NASA Technical Reports Server (NTRS)

Moreno, Vito; Nissley, David; Lin, Li-Sen Jim

1985-01-01

The first two years of a two-phase program aimed at improving the high temperature crack initiation life prediction technology for gas turbine hot section components are discussed. In Phase 1 (baseline) effort, low cycle fatigue (LCF) models, using a data base generated for a cast nickel base gas turbine hot section alloy (B1900+Hf), were evaluated for their ability to predict the crack initiation life for relevant creep-fatigue loading conditions and to define data required for determination of model constants. The variables included strain range and rate, mean strain, strain hold times and temperature. None of the models predicted all of the life trends within reasonable data requirements. A Cycle Damage Accumulation (CDA) was therefore developed which follows an exhaustion of material ductility approach. Material ductility is estimated based on observed similarities of deformation structure between fatigue, tensile and creep tests. The cycle damage function is based on total strain range, maximum stress and stress amplitude and includes both time independent and time dependent components. The CDA model accurately predicts all of the trends in creep-fatigue life with loading conditions. In addition, all of the CDA model constants are determinable from rapid cycle, fully reversed fatigue tests and monotonic tensile and/or creep data.

Effects of environmental conditions on growth and survival of Salmonella in pasteurized whole egg.

PubMed

Jakočiūnė, Džiuginta; Bisgaard, Magne; Hervé, Gaëlle; Protais, Jocelyne; Olsen, John Elmerdahl; Chemaly, Marianne

2014-08-01

This study investigated the influence of three parameters (time, temperature and NaCl concentration) on survival and four parameters (temperature, NaCl and lysozyme concentrations and pH) on growth of Salmonella enterica serovar Enteritidis (S. Enteritidis) in pasteurized whole egg (PWE). Doehlert uniform shell design was employed to choose conditions for trials and data was fitted to polynomial models and were presented as estimated response surfaces. A model for prediction of reduction of S. Enteritidis in PWE within temperatures between 50 and 58°C, NaCl concentrations of 0-12%, and heating times between 30 and 210s and a model for prediction of growth rate of S. Enteritidis in PWE in the temperature range of 1-25°C, NaCl concentration of 0-12%, pH between 5 and 9, and lysozyme concentrations of 107-1007 U/mg proteins were developed. The maximum reduction condition was 58°C, 0% of NaCl at a fixed heating time of 120s, while maximum growth rate was estimated at 25°C and 0% of NaCl. pH and lysozyme concentration were shown not to influence growth performance significantly in the range of values studied. Results inform industry of the optimal pasteurization and storage parameters for liquid whole egg. Copyright © 2014 Elsevier B.V. All rights reserved.

Predicting liver metastasis of gastrointestinal tract cancer by diffusion-weighted imaging of apparent diffusion coefficient values

PubMed Central

Zheng, De-Xian; Meng, Shu-Chun; Liu, Qing-Jun; Li, Chuan-Ting; Shang, Xi-Dan; Zhu, Yu-Seng; Bai, Tian-Jun; Xu, Shi-Ming

2016-01-01

AIM: To determine if efficacy of chemotherapy on liver metastasis of gastrointestinal tract cancer can be predicted by apparent diffusion coefficient (ADC) values of diffusion-weighted imaging (DWI). METHODS: In total, 86 patients with liver metastasis of gastrointestinal tract cancer (156 metastatic lesions) diagnosed in our hospital were included in this study. The maximum diameters of these tumors were compared with each other before treatment, 2 wk after treatment, and 12 wk after treatment. Selected patients were classified as the effective group and the ineffective group, depending on the maximum diameter of the tumor after 12 wk of treatment; and the ADC values at different treatment times between the two groups were compared. Spearman rank correlation was used to analyze the relationship between ADC value and tumor diameter. Receiver operating characteristic curve (ROC curve) was used to analyze the ADC values before treatment to predict the patient’s sensitivity and specificity degree of efficacy to the chemotherapy. RESULTS: There was no difference in age between the two groups and in maximum tumor diameter before treatment and 2 wk after treatment. However, after 12 wk of treatment, maximum tumor diameter in the effective group was significantly lower than that in the ineffective group (P < 0.05). Before treatment, ADC values in the ineffective group were significantly higher than those in the effective group (P < 0.05). There was no difference in ADC values between the effective and ineffective groups after 2 and 12 wk of treatment. However, ADC values were significantly higher after 2 and 12 wk of treatment compared to before treatment in the effective group (P < 0.05). Spearman rank correlation analysis showed that ADC value before treatment and the reduced percentage of the maximum tumor diameter after 12 wk of treatment were negatively correlated, while the increase in the percentage of the ADC value 12 wk after treatment and the decrease in the percentage of the maximum tumor diameter were significantly positively correlated. The results of the ROC curve showed that ADC value with a chemotherapy ineffective threshold value of 1.14 × 10-3 mm2/s before treatment had a sensitivity and specificity of 94.3% and 76.7%, respectively. CONCLUSION: DWI ADC values can be used to predict the response of patients with liver metastasis of gastrointestinal tract cancer to chemotherapy with high sensitivity and relatively high specificity. PMID:26973399

Technical Note: Using experimentally determined proton spot scanning timing parameters to accurately model beam delivery time.

PubMed

Shen, Jiajian; Tryggestad, Erik; Younkin, James E; Keole, Sameer R; Furutani, Keith M; Kang, Yixiu; Herman, Michael G; Bues, Martin

2017-10-01

To accurately model the beam delivery time (BDT) for a synchrotron-based proton spot scanning system using experimentally determined beam parameters. A model to simulate the proton spot delivery sequences was constructed, and BDT was calculated by summing times for layer switch, spot switch, and spot delivery. Test plans were designed to isolate and quantify the relevant beam parameters in the operation cycle of the proton beam therapy delivery system. These parameters included the layer switch time, magnet preparation and verification time, average beam scanning speeds in x- and y-directions, proton spill rate, and maximum charge and maximum extraction time for each spill. The experimentally determined parameters, as well as the nominal values initially provided by the vendor, served as inputs to the model to predict BDTs for 602 clinical proton beam deliveries. The calculated BDTs (T BDT ) were compared with the BDTs recorded in the treatment delivery log files (T Log ): ∆t = T Log -T BDT . The experimentally determined average layer switch time for all 97 energies was 1.91 s (ranging from 1.9 to 2.0 s for beam energies from 71.3 to 228.8 MeV), average magnet preparation and verification time was 1.93 ms, the average scanning speeds were 5.9 m/s in x-direction and 19.3 m/s in y-direction, the proton spill rate was 8.7 MU/s, and the maximum proton charge available for one acceleration is 2.0 ± 0.4 nC. Some of the measured parameters differed from the nominal values provided by the vendor. The calculated BDTs using experimentally determined parameters matched the recorded BDTs of 602 beam deliveries (∆t = -0.49 ± 1.44 s), which were significantly more accurate than BDTs calculated using nominal timing parameters (∆t = -7.48 ± 6.97 s). An accurate model for BDT prediction was achieved by using the experimentally determined proton beam therapy delivery parameters, which may be useful in modeling the interplay effect and patient throughput. The model may provide guidance on how to effectively reduce BDT and may be used to identifying deteriorating machine performance. © 2017 American Association of Physicists in Medicine.

Seasonal prediction and predictability of Eurasian spring snow water equivalent in NCEP Climate Forecast System version 2 reforecasts

NASA Astrophysics Data System (ADS)

He, Qiong; Zuo, Zhiyan; Zhang, Renhe; Zhang, Ruonan

2018-01-01

The spring snow water equivalent (SWE) over Eurasia plays an important role in East Asian and Indian monsoon rainfall. This study evaluates the seasonal prediction capability of NCEP Climate Forecast System version 2 (CFSv2) retrospective forecasts (1983-2010) for the Eurasian spring SWE. The results demonstrate that CFSv2 is able to represent the climatological distribution of the observed Eurasian spring SWE with a lead time of 1-3 months, with the maximum SWE occurring over western Siberia and Northeastern Europe. For a longer lead time, the SWE is exaggerated in CFSv2 because the start of snow ablation in CFSv2 lags behind that of the observation, and the simulated snowmelt rate is less than that in the observation. Generally, CFSv2 can simulate the interannual variations of the Eurasian spring SWE 1-5 months ahead of time but with an exaggerated magnitude. Additionally, the downtrend in CFSv2 is also overestimated. Because the initial conditions (ICs) are related to the corresponding simulation results significantly, the robust interannual variability and the downtrend in the ICs are most likely the causes for these biases. Moreover, CFSv2 exhibits a high potential predictability for the Eurasian spring SWE, especially the spring SWE over Siberia, with a lead time of 1-5 months. For forecasts with lead times longer than 5 months, the model predictability gradually decreases mainly due to the rapid decrease in the model signal.

WRF model forecasts and their use for hydroclimate monitoring over southern South America

NASA Astrophysics Data System (ADS)

Muller, Omar; Lovino, Miguel; Berbery, E. Hugo

2017-04-01

Weather forecasting and monitoring systems based on regional models are becoming increasingly relevant for decision support in agriculture and water management. This work evaluates the predictive and monitoring capabilities of a system based on WRF model simulations at 15 km grid spacing over a domain that encompasses La Plata Basin (LPB) in southern South America, where agriculture and water resources are essential. The model's skill up to a lead-time of 7 days is evaluated with daily precipitation and 2m temperature in-situ observations. Results show high prediction performance with 7 days lead-time throughout the domain and particularly over LPB, where about 70% of rain and no-rain days are correctly predicted. The scores tend to be better over humid climates than over arid-to-semiarid climates. Compared to the arid-semiarid climate, the humid climate has a higher probability of detection and less false alarms. The ranges of the skill scores are similar to those found over the United States, suggesting that proper choice of parameterizations lead to no loss of performance of the model. Daily mean, minimum and maximum forecast temperatures are highly correlated with observations up to 7 day lead time. The best performance is for daily mean temperature, followed by minimum temperature and a slightly weaker performance for maximum temperature over arid regions. The usefulness of WRF products for hydroclimate monitoring was tested for an unprecedented drought in southern Brazil and for a slightly above normal precipitation season in northeastern Argentina. In both cases the model products reproduce the observed precipitation conditions with consistent impacts on soil moisture, evapotranspiration and runoff. This evaluation validates the model's usefulness to fore-cast weather up to one week and to monitor climate conditions in real time. The scores suggest that the forecast lead-time can be extended into week two, while bias correction methods can reduce part of the systematic errors.

Two-Dimensional High-Lift Aerodynamic Optimization Using Neural Networks

NASA Technical Reports Server (NTRS)

Greenman, Roxana M.

1998-01-01

The high-lift performance of a multi-element airfoil was optimized by using neural-net predictions that were trained using a computational data set. The numerical data was generated using a two-dimensional, incompressible, Navier-Stokes algorithm with the Spalart-Allmaras turbulence model. Because it is difficult to predict maximum lift for high-lift systems, an empirically-based maximum lift criteria was used in this study to determine both the maximum lift and the angle at which it occurs. The 'pressure difference rule,' which states that the maximum lift condition corresponds to a certain pressure difference between the peak suction pressure and the pressure at the trailing edge of the element, was applied and verified with experimental observations for this configuration. Multiple input, single output networks were trained using the NASA Ames variation of the Levenberg-Marquardt algorithm for each of the aerodynamic coefficients (lift, drag and moment). The artificial neural networks were integrated with a gradient-based optimizer. Using independent numerical simulations and experimental data for this high-lift configuration, it was shown that this design process successfully optimized flap deflection, gap, overlap, and angle of attack to maximize lift. Once the neural nets were trained and integrated with the optimizer, minimal additional computer resources were required to perform optimization runs with different initial conditions and parameters. Applying the neural networks within the high-lift rigging optimization process reduced the amount of computational time and resources by 44% compared with traditional gradient-based optimization procedures for multiple optimization runs.

Capturing Pressure Oscillations in Numerical Simulations of Internal Combustion Engines

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

Gubba, Sreenivasa Rao; Jupudi, Ravichandra S.; Pasunurthi, Shyam Sundar

In an earlier publication, the authors compared numerical predictions of the mean cylinder pressure of diesel and dual-fuel combustion, to that of measured pressure data from a medium-speed, large-bore engine. In these earlier comparisons, measured data from a flush-mounted in-cylinder pressure transducer showed notable and repeatable pressure oscillations which were not evident in the mean cylinder pressure predictions from computational fluid dynamics (CFD). In this paper, the authors present a methodology for predicting and reporting the local cylinder pressure consistent with that of a measurement location. Such predictions for large-bore, medium-speed engine operation demonstrate pressure oscillations in accordance with thosemore » measured. The temporal occurrences of notable pressure oscillations were during the start of combustion and around the time of maximum cylinder pressure. With appropriate resolutions in time steps and mesh sizes, the local cell static pressure predicted for the transducer location showed oscillations in both diesel and dual-fuel combustion modes which agreed with those observed in the experimental data. Fast Fourier transform (FFT) analysis on both experimental and calculated pressure traces revealed that the CFD predictions successfully captured both the amplitude and frequency range of the oscillations. Furthermore, resolving propagating pressure waves with the smaller time steps and grid sizes necessary to achieve these results required a significant increase in computer resources.« less

Capturing Pressure Oscillations in Numerical Simulations of Internal Combustion Engines

DOE PAGES

Gubba, Sreenivasa Rao; Jupudi, Ravichandra S.; Pasunurthi, Shyam Sundar; ...

2018-04-09

In an earlier publication, the authors compared numerical predictions of the mean cylinder pressure of diesel and dual-fuel combustion, to that of measured pressure data from a medium-speed, large-bore engine. In these earlier comparisons, measured data from a flush-mounted in-cylinder pressure transducer showed notable and repeatable pressure oscillations which were not evident in the mean cylinder pressure predictions from computational fluid dynamics (CFD). In this paper, the authors present a methodology for predicting and reporting the local cylinder pressure consistent with that of a measurement location. Such predictions for large-bore, medium-speed engine operation demonstrate pressure oscillations in accordance with thosemore » measured. The temporal occurrences of notable pressure oscillations were during the start of combustion and around the time of maximum cylinder pressure. With appropriate resolutions in time steps and mesh sizes, the local cell static pressure predicted for the transducer location showed oscillations in both diesel and dual-fuel combustion modes which agreed with those observed in the experimental data. Fast Fourier transform (FFT) analysis on both experimental and calculated pressure traces revealed that the CFD predictions successfully captured both the amplitude and frequency range of the oscillations. Furthermore, resolving propagating pressure waves with the smaller time steps and grid sizes necessary to achieve these results required a significant increase in computer resources.« less

Comparison of CME/Shock Propagation Models with Heliospheric Imaging and In Situ Observations

NASA Astrophysics Data System (ADS)

Zhao, Xinhua; Liu, Ying D.; Inhester, Bernd; Feng, Xueshang; Wiegelmann, Thomas; Lu, Lei

2016-10-01

The prediction of the arrival time for fast coronal mass ejections (CMEs) and their associated shocks is highly desirable in space weather studies. In this paper, we use two shock propagation models, I.e., Data Guided Shock Time Of Arrival (DGSTOA) and Data Guided Shock Propagation Model (DGSPM), to predict the kinematical evolution of interplanetary shocks associated with fast CMEs. DGSTOA is based on the similarity theory of shock waves in the solar wind reference frame, and DGSPM is based on the non-similarity theory in the stationary reference frame. The inputs are the kinematics of the CME front at the maximum speed moment obtained from the geometric triangulation method applied to STEREO imaging observations together with the Harmonic Mean approximation. The outputs provide the subsequent propagation of the associated shock. We apply these models to the CMEs on 2012 January 19, January 23, and March 7. We find that the shock models predict reasonably well the shock’s propagation after the impulsive acceleration. The shock’s arrival time and local propagation speed at Earth predicted by these models are consistent with in situ measurements of WIND. We also employ the Drag-Based Model (DBM) as a comparison, and find that it predicts a steeper deceleration than the shock models after the rapid deceleration phase. The predictions of DBM at 1 au agree with the following ICME or sheath structure, not the preceding shock. These results demonstrate the applicability of the shock models used here for future arrival time prediction of interplanetary shocks associated with fast CMEs.

Time-dependent seismic hazard analysis for the Greater Tehran and surrounding areas

NASA Astrophysics Data System (ADS)

Jalalalhosseini, Seyed Mostafa; Zafarani, Hamid; Zare, Mehdi

2018-01-01

This study presents a time-dependent approach for seismic hazard in Tehran and surrounding areas. Hazard is evaluated by combining background seismic activity, and larger earthquakes may emanate from fault segments. Using available historical and paleoseismological data or empirical relation, the recurrence time and maximum magnitude of characteristic earthquakes for the major faults have been explored. The Brownian passage time (BPT) distribution has been used to calculate equivalent fictitious seismicity rate for major faults in the region. To include ground motion uncertainty, a logic tree and five ground motion prediction equations have been selected based on their applicability in the region. Finally, hazard maps have been presented.

High-resolution spatiotemporal mapping of PM2.5 concentrations at Mainland China using a combined BME-GWR technique

NASA Astrophysics Data System (ADS)

Xiao, Lu; Lang, Yichao; Christakos, George

2018-01-01

With rapid economic development, industrialization and urbanization, the ambient air PM2.5 has become a major pollutant linked to respiratory, heart and lung diseases. In China, PM2.5 pollution constitutes an extreme environmental and social problem of widespread public concern. In this work we estimate ground-level PM2.5 from satellite-derived aerosol optical depth (AOD), topography data, meteorological data, and pollutant emission using an integrative technique. In particular, Geographically Weighted Regression (GWR) analysis was combined with Bayesian Maximum Entropy (BME) theory to assess the spatiotemporal characteristics of PM2.5 exposure in a large region of China and generate informative PM2.5 space-time predictions (estimates). It was found that, due to its integrative character, the combined BME-GWR method offers certain improvements in the space-time prediction of PM2.5 concentrations over China compared to previous techniques. The combined BME-GWR technique generated realistic maps of space-time PM2.5 distribution, and its performance was superior to that of seven previous studies of satellite-derived PM2.5 concentrations in China in terms of prediction accuracy. The purely spatial GWR model can only be used at a fixed time, whereas the integrative BME-GWR approach accounts for cross space-time dependencies and can predict PM2.5 concentrations in the composite space-time domain. The 10-fold results of BME-GWR modeling (R2 = 0.883, RMSE = 11.39 μg /m3) demonstrated a high level of space-time PM2.5 prediction (estimation) accuracy over China, revealing a definite trend of severe PM2.5 levels from the northern coast toward inland China (Nov 2015-Feb 2016). Future work should focus on the addition of higher resolution AOD data, developing better satellite-based prediction models, and related air pollutants for space-time PM2.5 prediction purposes.

Seasonal prediction of typhoon genesis frequency and track patterns in the North West Pacific area

NASA Astrophysics Data System (ADS)

Hyoun, Yoosun; Kang, Kiryong; Shin, Do-Shick

2014-05-01

This study is to investigate the performance of the typhoon seasonal predictability using a dynamical model. The check items are the monthly statistics for total number of typhoon genesis in Western North Pacific (WNP) area and possible threat to Korean peninsula among them, and the probability of each categorized track pattern. As the dynamical model the Florida State University/Center for Ocean-Atmospheric Prediction Studies (FSU/COAPS) was used, and it uses five ensemble members including control run are generated using time-lagged methods and the resolution of T126L27 (a Gaussian grid spacing of 0.94º). The model initial conditions are obtained from the National Center for Enviromental Prediction Global Forecast System (NCEP GFS) and the SST from Climate Forecast System with bias correction was used for ocean surface boundary condition. The summer (Jun-Jul-Aug) season prediction is made one month prior to target season. The detection of tropical cyclone used in this system is based on six criteria. First, the isolated vortex type minimum sea level pressure should be below 1008hPa. Second, the maximum wind speed is larger than 17m s-1. Third, the magnitude of the maximum relative vorticity at 850hPa exceeds 3.5x10-5s-1. Fourth, the average temperature difference from the area mean of surrounding region at 300hPa, 500hPa, 700hPa exceeds 2.5K. Fifth, the maximum wind speed at 850hPa is larger than that at 300hPa. Sixth, this identified vortex should last more than two days. These criteria were chosen after close examination from model-observation comparison. In this study, we will focus on performance of the system typhoon frequency and track pattern in the WNP area during 2004-2013.

Inferences on mass composition and tests of hadronic interactions from 0.3 to 100 EeV using the water-Cherenkov detectors of the Pierre Auger Observatory

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

Aab, A.; Abreu, P.; Aglietta, M.

We present a new method for probing the hadronic interaction models at ultra-high energy and extracting details about mass composition. This is done using the time profiles of the signals recorded with the water-Cherenkov detectors of the Pierre Auger Observatory. The profiles arise from a mix of the muon and electromagnetic components of air-showers. Using the risetimes of the recorded signals we define a new parameter, which we use to compare our observations with predictions from simulations. We find, firstly, inconsistencies between our data and predictions over a greater energy range and with substantially more events than in previous studies.more » Secondly, by calibrating the new parameter with fluorescence measurements from observations made at the Auger Observatory, we can infer the depth of shower maximum for a sample of over 81,000 events extending from 0.3 EeV to over 100 EeV. Above 30 EeV, the sample is nearly fourteen times larger than currently available from fluorescence measurements and extending the covered energy range by half a decade. The energy dependence of the average depth of shower maximum is compared to simulations and interpreted in terms of the mean of the logarithmic mass. Here, we find good agreement with previous work and extend the measurement of the mean depth of shower maximum to greater energies than before, reducing significantly the statistical uncertainty associated with the inferences about mass composition.« less

Inferences on mass composition and tests of hadronic interactions from 0.3 to 100 EeV using the water-Cherenkov detectors of the Pierre Auger Observatory

DOE PAGES

Aab, A.; Abreu, P.; Aglietta, M.; ...

2017-12-08

We present a new method for probing the hadronic interaction models at ultra-high energy and extracting details about mass composition. This is done using the time profiles of the signals recorded with the water-Cherenkov detectors of the Pierre Auger Observatory. The profiles arise from a mix of the muon and electromagnetic components of air-showers. Using the risetimes of the recorded signals we define a new parameter, which we use to compare our observations with predictions from simulations. We find, firstly, inconsistencies between our data and predictions over a greater energy range and with substantially more events than in previous studies.more » Secondly, by calibrating the new parameter with fluorescence measurements from observations made at the Auger Observatory, we can infer the depth of shower maximum for a sample of over 81,000 events extending from 0.3 EeV to over 100 EeV. Above 30 EeV, the sample is nearly fourteen times larger than currently available from fluorescence measurements and extending the covered energy range by half a decade. The energy dependence of the average depth of shower maximum is compared to simulations and interpreted in terms of the mean of the logarithmic mass. Here, we find good agreement with previous work and extend the measurement of the mean depth of shower maximum to greater energies than before, reducing significantly the statistical uncertainty associated with the inferences about mass composition.« less

Canonical Statistical Model for Maximum Expected Immission of Wire Conductor in an Aperture Enclosure

NASA Technical Reports Server (NTRS)

Bremner, Paul G.; Vazquez, Gabriel; Christiano, Daniel J.; Trout, Dawn H.

2016-01-01

Prediction of the maximum expected electromagnetic pick-up of conductors inside a realistic shielding enclosure is an important canonical problem for system-level EMC design of space craft, launch vehicles, aircraft and automobiles. This paper introduces a simple statistical power balance model for prediction of the maximum expected current in a wire conductor inside an aperture enclosure. It calculates both the statistical mean and variance of the immission from the physical design parameters of the problem. Familiar probability density functions can then be used to predict the maximum expected immission for deign purposes. The statistical power balance model requires minimal EMC design information and solves orders of magnitude faster than existing numerical models, making it ultimately viable for scaled-up, full system-level modeling. Both experimental test results and full wave simulation results are used to validate the foundational model.

Integrating paleoecology and genetics of bird populations in two sky island archipelagos.

PubMed

McCormack, John E; Bowen, Bonnie S; Smith, Thomas B

2008-06-27

Genetic tests of paleoecological hypotheses have been rare, partly because recent genetic divergence is difficult to detect and time. According to fossil plant data, continuous woodland in the southwestern USA and northern Mexico became fragmented during the last 10,000 years, as warming caused cool-adapted species to retreat to high elevations. Most genetic studies of resulting 'sky islands' have either failed to detect recent divergence or have found discordant evidence for ancient divergence. We test this paleoecological hypothesis for the region with intraspecific mitochondrial DNA and microsatellite data from sky-island populations of a sedentary bird, the Mexican jay (Aphelocoma ultramarina). We predicted that populations on different sky islands would share common, ancestral alleles that existed during the last glaciation, but that populations on each sky island, owing to their isolation, would contain unique variants of postglacial origin. We also predicted that divergence times estimated from corrected genetic distance and a coalescence model would post-date the last glacial maximum. Our results provide multiple independent lines of support for postglacial divergence, with the predicted pattern of shared and unique mitochondrial DNA haplotypes appearing in two independent sky-island archipelagos, and most estimates of divergence time based on corrected genetic distance post-dating the last glacial maximum. Likewise, an isolation model based on multilocus gene coalescence indicated postglacial divergence of five pairs of sky islands. In contrast to their similar recent histories, the two archipelagos had dissimilar historical patterns in that sky islands in Arizona showed evidence for older divergence, suggesting different responses to the last glaciation. This study is one of the first to provide explicit support from genetic data for a postglacial divergence scenario predicted by one of the best paleoecological records in the world. Our results demonstrate that sky islands act as generators of genetic diversity at both recent and historical timescales and underscore the importance of thorough sampling and the use of loci with fast mutation rates to studies that test hypotheses concerning recent genetic divergence.

Experimental study of gravitation effects in the flow of a particle-laden thin film on an inclined plane

NASA Astrophysics Data System (ADS)

Ward, Thomas; Wey, Chi; Glidden, Robert; Hosoi, A. E.; Bertozzi, A. L.

2009-08-01

The flow of viscous, particle-laden wetting thin films on an inclined plane is studied experimentally as the particle concentration is increased to the maximum packing limit. The slurry is a non-neutrally buoyant mixture of silicone oil and either solid glass beads or glass bubbles. At low concentrations (ϕ <0.45), the elapsed time versus average front position scales with the exponent predicted by Huppert [Nature (London) 300, 427 (1982)]. At higher concentrations, the average front position still scales with the exponent predicted by Huppert on some time interval, but there are observable deviations due to internal motion of the particles. At the larger concentration values and at later times, the departure from Huppert is seen to strongly depend on total slurry volume VT, inclination angle α, density difference, and particle size range.

Correlation of in vitro time-kill curves and kinetics of bacterial killing in cerebrospinal fluid during ceftriaxone therapy of experimental Escherichia coli meningitis.

PubMed Central

Decazes, J M; Ernst, J D; Sande, M A

1983-01-01

Ceftriaxone was highly active in eliminating Escherichia coli from the cerebrospinal fluid of rabbits infected with experimental meningitis. However, concentrations equal to or greater than 10 times the minimal bactericidal concentration had to be achieved to ensure optimal efficacy (rate of kill, 1.5 log10 CFU/ml per h). In contrast to other beta-lactams studied in this model, ceftriaxone concentrations in cerebrospinal fluid progressively increased, whereas serum steady state was obtained by constant infusion. The percent penetration was 2.1% after 1 h of therapy, in contrast to 8.9% after 7 h (P less than 0.001). In vitro time-kill curves done in cerebrospinal fluid or broth more closely predicted the drug concentrations required for a maximum cidal effect in vivo than that predicted by determinations of minimal inhibitory or bactericidal concentrations. PMID:6316841

Tailoff thrust and impulse imbalance between pairs of Space Shuttle solid rocket motors

NASA Technical Reports Server (NTRS)

Jacobs, E. P.; Yeager, J. M.

1975-01-01

The tailoff thrust and impulse imbalance between pairs of solid rocket motors is of particular interest for the Space Shuttle Vehicle because of the potential control problems that exist with this asymmetric configuration. Although a similar arrangement of solid rocket motors was utilized for the Titan Program, they produced less than one-half the thrust level of the Space Shuttle at web action time, and the overall vehicle was symmetric. Since the Titan Program does provide the most applicable actual test data, 23 flight pairs were analyzed to determine the actual tailoff thrust and impulse imbalance experienced. The results were scaled up using the predicted web action time thrust and tailoff time to arrive at values for the Space Shuttle. These values were then statistically treated to obtain a prediction of the maximum imbalance one could expect to experience during the Shuttle Program.

High temperature low cycle fatigue mechanisms for nickel base and a copper base alloy. M.S. Thesis Final Report

NASA Technical Reports Server (NTRS)

Shih, C. I.

1982-01-01

Damage mechanisms were studied in Rene' 95 and NARloy Z, using optical, scanning and transmission in microscopy. In necklace Rene' 95, crack initiation was mainly associated with cracking of surface MC carbides, except for hold time tests at higher strain ranges where initiation was associated more with a grain boundary mechanism. A mixed mode of propagation with a faceted fracture morphology was typical for all cycle characters. The dependence of life on maximum tensile stress can be demonstrated by the data falling onto three lines corresponding to the three tensile hold times, in the life against maximum tensile stress plot. In NARloy Z, crack initiation was always at the grain boundaries. The mode of crack propagation depended on the cycle character. The life decreased with decreasing strain rate and with tensile holds. In terms of damage mode, different life prediction laws may be applicable to different cycle characters.

Photometric studies of δ Scuti stars. I. IP Virginis

USGS Publications Warehouse

Joner, Michael D.; Hintz, Eric G.; Collier, Matthew W.

1998-01-01

We report 15 new times of maximum light for the δ Scuti star IP Virginis (formerly known as SA 106‐1024). An analysis of all times of maximum light indicates that IP Vir has been decreasing in period at a constant rate of − days day−1. Evidence is also presented that IP Vir is a double‐mode variable with a period ratio of . This period ratio predicts a [Fe/H] value of −0.3. From photometric (uvbyβ) observations, we find a foreground reddening of .008 mag and a metallicity of [Fe/H] = +0.05. It is shown that [Fe/H] = −0.3 is most likely the correct value. Intrinsic ‐ and c1‐values, plotted in a model atmosphere grid, indicate a mean effective temperature, K, and a mean surface gravity, . All of these physical parameters support Landolt's initial conclusion that IP Vir is an ordinary δ Sct star.

A comparison of observed and forecast energetics over North America

NASA Technical Reports Server (NTRS)

Baker, W. E.; Brin, Y.

1985-01-01

The observed kinetic energy balance is calculated over North America and compared with that computed from forecast fields for the 13-15 January 1979 cyclone. The FGGE upper-air rawinsonde network serves as the observational database while the forecast energetics are derived from a numerical integration with the GLAS fourth-order general circulation model initialized at 00 GMT 13 January. Maps of the observed and predicted kinetic energy and eddy conversion are in good qualitative agreement, although the model eddy conversion tends to be 2 to 3 times stronger than the observed values. Both the forecast and observations exhibit the lower and upper tropospheric maxima in vertical profiles of kinetic energy generation and dissipation typically found in cyclonic disturbances. An interesting time lag is noted in the observational analysis with the maximum observed kinetic energy occurring 12 h later than the maximum eddy conversion over the same region.

Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model

PubMed Central

Chen, Chieh-Fan; Ho, Wen-Hsien; Chou, Huei-Yin; Yang, Shu-Mei; Chen, I-Te; Shi, Hon-Yi

2011-01-01

This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume. The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error. Sensitivity of prediction errors to model training time was also evaluated. The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue. Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume. Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume. Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume. The model also performed well in forecasting revenue and visitor volume. PMID:22203886

Long-term prediction of emergency department revenue and visitor volume using autoregressive integrated moving average model.

PubMed

Chen, Chieh-Fan; Ho, Wen-Hsien; Chou, Huei-Yin; Yang, Shu-Mei; Chen, I-Te; Shi, Hon-Yi

2011-01-01

This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume. The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error. Sensitivity of prediction errors to model training time was also evaluated. The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue. Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume. Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume. Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume. The model also performed well in forecasting revenue and visitor volume.

High-Lift Optimization Design Using Neural Networks on a Multi-Element Airfoil

NASA Technical Reports Server (NTRS)

Greenman, Roxana M.; Roth, Karlin R.; Smith, Charles A. (Technical Monitor)

1998-01-01

The high-lift performance of a multi-element airfoil was optimized by using neural-net predictions that were trained using a computational data set. The numerical data was generated using a two-dimensional, incompressible, Navier-Stokes algorithm with the Spalart-Allmaras turbulence model. Because it is difficult to predict maximum lift for high-lift systems, an empirically-based maximum lift criteria was used in this study to determine both the maximum lift and the angle at which it occurs. Multiple input, single output networks were trained using the NASA Ames variation of the Levenberg-Marquardt algorithm for each of the aerodynamic coefficients (lift, drag, and moment). The artificial neural networks were integrated with a gradient-based optimizer. Using independent numerical simulations and experimental data for this high-lift configuration, it was shown that this design process successfully optimized flap deflection, gap, overlap, and angle of attack to maximize lift. Once the neural networks were trained and integrated with the optimizer, minimal additional computer resources were required to perform optimization runs with different initial conditions and parameters. Applying the neural networks within the high-lift rigging optimization process reduced the amount of computational time and resources by 83% compared with traditional gradient-based optimization procedures for multiple optimization runs.

Radiative Forcing of the Pinatubo Aerosol as a Function of Latitude and Time

NASA Technical Reports Server (NTRS)

Bergstrom, R. W.; Kinne, S.; Russell, P. B.; Bauman, J. J.; Minnis, P.

1996-01-01

We present calculations of the radiative forcing of the Mt. Pinatubo aerosols as a function of latitude and time after the eruption and compare the results with GOES satellite data. The results from the model indicate that the net effect of the aerosol was to cool the earth-atmosphere system with the most significant radiative effect in the tropics (corresponding to the location of the tropical stratospheric reservoir) and at latitudes greater than 60 deg. The high-latitude maximum is a combined effect of the high-latitude peak in optical depth (Trepte et al 1994) and the large solar zenith angles. The comparison of the predicted and measured net flux shows relatively good agreement, with the model consistently under predicting the cooling effect of the aerosol.

Optimal firing rate estimation

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

2001-01-01

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

Robust distributed model predictive control of linear systems with structured time-varying uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Langwen; Xie, Wei; Wang, Jingcheng

2017-11-01

In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min-max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.

Radiative Forcing of the Pinatubo Aerosol as a Function of Latitude and Time

NASA Technical Reports Server (NTRS)

Bergstrom, Robert W.; Kinne, S.; Russell, P. B.; Bauman, J. J.; Minnis, P.

2000-01-01

We present calculations of the radiative forcing of the Mt. Pinatubo aerosols as a function of latitude and time after the eruption and compare the results with GOES satellite data. The results from the model indicate that the net effect of the aerosol was to cool the earth-atmosphere system with the most significant radiative effect in the tropics (corresponding to the location of the tropical stratospheric reservoir) and at latitudes greater than 60 degrees. The high-latitude maximum is a combined effect of the high-latitude peak in optical depth (Trepte et al 1994) and the large solar zenith angles. The comparison of the predicted and measured net flux shows relatively good agreement, with the model consistently under predicting the cooling effect of the aerosol.

Inhibitory effect of chlorine and ultraviolet radiation on growth of Listeria monocytogenes in chicken breast and development of predictive growth models.

PubMed

Oh, S R; Kang, I; Oh, M H; Ha, S D

2014-01-01

The inhibitory effect of chlorine (50, 100, and 200 mg/kg) was investigated with and without UV radiation (300 mW·s/cm(2)) for the growth of Listeria monocytogenes in chicken breast meat. Using a polynomial model, predictive growth models were also developed as a function of chlorine concentration, UV exposure, and storage temperature (4, 10, and 15°C). A maximum L. monocytogenes reduction (0.8 log cfu, cfu/g) was obtained when combining chlorine at 200 mg/kg and UV at 300 mW·s/cm(2), and a maximum synergistic effect (0.4 log cfu/g) was observed when using chlorine at 100 mg/kg and UV at 300 mW·s/cm(2). Primary models developed for specific growth rate and lag time showed a good fitness (R(2) > 0.91), as determined by the reparameterized Gompertz equation. Secondary polynomial models were obtained using nonlinear regression analysis. The developed models were validated with mean square error, bias factor, and accuracy factor, which were 0.0003, 0.96, and 1.11, respectively, for specific growth rate and 7.69, 0.99, and 1.04, respectively, for lag time. The treatment of chlorine and UV did not change the color and texture of chicken breast after 7 d of storage at 4°C. As a result, the combination of chlorine at 100 mg/kg and UV at 300 mW·s/cm(2) appears to an effective method into inhibit L. monocytogenes growth in broiler carcasses with no negative effects on color and textural quality. Based on the validation results, the predictive models can be used to accurately predict L. monocytogenes growth in chicken breast.

Shuttle radiation dose measurements in the International Space Station orbits

NASA Technical Reports Server (NTRS)

Badhwar, Gautam D.

2002-01-01

The International Space Station (ISS) is now a reality with the start of a permanent human presence on board. Radiation presents a serious risk to the health and safety of the astronauts, and there is a clear requirement for estimating their exposures prior to and after flights. Predictions of the dose rate at times other than solar minimum or solar maximum have not been possible, because there has been no method to calculate the trapped-particle spectrum at intermediate times. Over the last few years, a tissue-equivalent proportional counter (TEPC) has been flown at a fixed mid-deck location on board the Space Shuttle in 51.65 degrees inclination flights. These flights have provided data that cover the expected changes in the dose rates due to changes in altitude and changes in solar activity from the solar minimum to the solar maximum of the current 23rd solar cycle. Based on these data, a simple function of the solar deceleration potential has been derived that can be used to predict the galactic cosmic radiation (GCR) dose rates to within +/-10%. For altitudes to be covered by the ISS, the dose rate due to the trapped particles is found to be a power-law function, rho(-2/3), of the atmospheric density, rho. This relationship can be used to predict trapped dose rates inside these spacecraft to +/-10% throughout the solar cycle. Thus, given the shielding distribution for a location inside the Space Shuttle or inside an ISS module, this approach can be used to predict the combined GCR + trapped dose rate to better than +/-15% for quiet solar conditions.

Integrated CFD modeling of gas turbine combustors

NASA Technical Reports Server (NTRS)

Fuller, E. J.; Smith, C. E.

1993-01-01

3D, curvilinear, multi-domain CFD analysis is becoming a valuable tool in gas turbine combustor design. Used as a supplement to experimental testing. CFD analysis can provide improved understanding of combustor aerodynamics and used to qualitatively assess new combustor designs. This paper discusses recent advancements in CFD combustor methodology, including the timely integration of the design (i.e. CAD) and analysis (i.e. CFD) processes. Allied Signal's F124 combustor was analyzed at maximum power conditions. The assumption of turbulence levels at the nozzle/swirler inlet was shown to be very important in the prediction of combustor exit temperatures. Predicted exit temperatures were compared to experimental rake data, and good overall agreement was seen. Exit radial temperature profiles were well predicted, while the predicted pattern factor was 25 percent higher than the harmonic-averaged experimental pattern factor.

Beyond SaGMRotI: Conversion to SaArb, SaSN, and SaMaxRot

USGS Publications Warehouse

Watson-Lamprey, J. A.; Boore, D.M.

2007-01-01

In the seismic design of structures, estimates of design forces are usually provided to the engineer in the form of elastic response spectra. Predictive equations for elastic response spectra are derived from empirical recordings of ground motion. The geometric mean of the two orthogonal horizontal components of motion is often used as the response value in these predictive equations, although it is not necessarily the most relevant estimate of forces within the structure. For some applications it is desirable to estimate the response value on a randomly chosen single component of ground motion, and in other applications the maximum response in a single direction is required. We give adjustment factors that allow converting the predictions of geometric-mean ground-motion predictions into either of these other two measures of seismic ground-motion intensity. In addition, we investigate the relation of the strike-normal component of ground motion to the maximum response values. We show that the strike-normal component of ground motion seldom corresponds to the maximum horizontal-component response value (in particular, at distances greater than about 3 km from faults), and that focusing on this case in exclusion of others can result in the underestimation of the maximum component. This research provides estimates of the maximum response value of a single component for all cases, not just near-fault strike-normal components. We provide modification factors that can be used to convert predictions of ground motions in terms of the geometric mean to the maximum spectral acceleration (SaMaxRot) and the random component of spectral acceleration (SaArb). Included are modification factors for both the mean and the aleatory standard deviation of the logarithm of the motions.

A predictive model for diagnosing bipolar disorder based on the clinical characteristics of major depressive episodes in Chinese population.

PubMed

Gan, Zhaoyu; Diao, Feici; Wei, Qinling; Wu, Xiaoli; Cheng, Minfeng; Guan, Nianhong; Zhang, Ming; Zhang, Jinbei

2011-11-01

A correct timely diagnosis of bipolar depression remains a big challenge for clinicians. This study aimed to develop a clinical characteristic based model to predict the diagnosis of bipolar disorder among patients with current major depressive episodes. A prospective study was carried out on 344 patients with current major depressive episodes, with 268 completing 1-year follow-up. Data were collected through structured interviews. Univariate binary logistic regression was conducted to select potential predictive variables among 19 initial variables, and then multivariate binary logistic regression was performed to analyze the combination of risk factors and build a predictive model. Receiver operating characteristic (ROC) curve was plotted. Of 19 initial variables, 13 variables were preliminarily selected, and then forward stepwise exercise produced a final model consisting of 6 variables: age at first onset, maximum duration of depressive episodes, somatalgia, hypersomnia, diurnal variation of mood, irritability. The correct prediction rate of this model was 78% (95%CI: 75%-86%) and the area under the ROC curve was 0.85 (95%CI: 0.80-0.90). The cut-off point for age at first onset was 28.5 years old, while the cut-off point for maximum duration of depressive episode was 7.5 months. The limitations of this study include small sample size, relatively short follow-up period and lack of treatment information. Our predictive models based on six clinical characteristics of major depressive episodes prove to be robust and can help differentiate bipolar depression from unipolar depression. Copyright © 2011 Elsevier B.V. All rights reserved.

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

Lafontaine Rivera, Jimmy G.; Theisen, Matthew K.; Chen, Po-Wei

The product formation yield (product formed per unit substrate consumed) is often the most important performance indicator in metabolic engineering. Until now, the actual yield cannot be predicted, but it can be bounded by its maximum theoretical value. The maximum theoretical yield is calculated by considering the stoichiometry of the pathways and cofactor regeneration involved. Here in this paper we found that in many cases, dynamic stability becomes an issue when excessive pathway flux is drawn to a product. This constraint reduces the yield and renders the maximal theoretical yield too loose to be predictive. We propose a more realisticmore » quantity, defined as the kinetically accessible yield (KAY) to predict the maximum accessible yield for a given flux alteration. KAY is either determined by the point of instability, beyond which steady states become unstable and disappear, or a local maximum before becoming unstable. Thus, KAY is the maximum flux that can be redirected for a given metabolic engineering strategy without losing stability. Strictly speaking, calculation of KAY requires complete kinetic information. With limited or no kinetic information, an Ensemble Modeling strategy can be used to determine a range of likely values for KAY, including an average prediction. We first apply the KAY concept with a toy model to demonstrate the principle of kinetic limitations on yield. We then used a full-scale E. coli model (193 reactions, 153 metabolites) and this approach was successful in E. coli for predicting production of isobutanol: the calculated KAY values are consistent with experimental data for three genotypes previously published.« less

An improved method for predicting the evolution of the characteristic parameters of an information system

NASA Astrophysics Data System (ADS)

Dushkin, A. V.; Kasatkina, T. I.; Novoseltsev, V. I.; Ivanov, S. V.

2018-03-01

The article proposes a forecasting method that allows, based on the given values of entropy and error level of the first and second kind, to determine the allowable time for forecasting the development of the characteristic parameters of a complex information system. The main feature of the method under consideration is the determination of changes in the characteristic parameters of the development of the information system in the form of the magnitude of the increment in the ratios of its entropy. When a predetermined value of the prediction error ratio is reached, that is, the entropy of the system, the characteristic parameters of the system and the depth of the prediction in time are estimated. The resulting values of the characteristics and will be optimal, since at that moment the system possessed the best ratio of entropy as a measure of the degree of organization and orderliness of the structure of the system. To construct a method for estimating the depth of prediction, it is expedient to use the maximum principle of the value of entropy.

Afterbody Heating Predictions for a Mars Science Laboratory Entry Vehicle

NASA Technical Reports Server (NTRS)

Edquist, Karl T.

2005-01-01

The Mars Science Laboratory mission intends to deliver a large rover to the Martian surface within 10 km of its target site. One candidate entry vehicle aeroshell consists of a 3.75-m diameter, 70-deg sphere-cone forebody and a biconic afterbody similar to that of Viking. This paper presents computational fluid dynamics predictions of laminar afterbody heating rates for this configuration and a 2010 arrival at Mars. Computational solutions at flight conditions used an 8-species Mars gas model in chemical and thermal non-equilibrium. A grid resolution study examined the effects of mesh spacing on afterbody heating rates and resulted in grids used for heating predictions on a reference entry trajectory. Afterbody heating rate reaches its maximum value near 0.6 W/sq cm on the first windward afterbody cone at the time of peak freestream dynamic pressure. Predicted afterbody heating rates generally are below 3% of the forebody laminar nose cap heating rate throughout the design trajectory. The heating rates integrated over time provide total heat load during entry, which drives thermal protection material thickness.

Trait Acclimation Mitigates Mortality Risks of Tropical Canopy Trees under Global Warming.

PubMed

Sterck, Frank; Anten, Niels P R; Schieving, Feike; Zuidema, Pieter A

2016-01-01

There is a heated debate about the effect of global change on tropical forests. Many scientists predict large-scale tree mortality while others point to mitigating roles of CO2 fertilization and - the notoriously unknown - physiological trait acclimation of trees. In this opinion article we provided a first quantification of the potential of trait acclimation to mitigate the negative effects of warming on tropical canopy tree growth and survival. We applied a physiological tree growth model that incorporates trait acclimation through an optimization approach. Our model estimated the maximum effect of acclimation when trees optimize traits that are strongly plastic on a week to annual time scale (leaf photosynthetic capacity, total leaf area, stem sapwood area) to maximize carbon gain. We simulated tree carbon gain for temperatures (25-35°C) and ambient CO2 concentrations (390-800 ppm) predicted for the 21st century. Full trait acclimation increased simulated carbon gain by up to 10-20% and the maximum tolerated temperature by up to 2°C, thus reducing risks of tree death under predicted warming. Functional trait acclimation may thus increase the resilience of tropical trees to warming, but cannot prevent tree death during extremely hot and dry years at current CO2 levels. We call for incorporating trait acclimation in field and experimental studies of plant functional traits, and in models that predict responses of tropical forests to climate change.

Mapping the birch and grass pollen seasons in the UK using satellite sensor time-series.

PubMed

Khwarahm, Nabaz R; Dash, Jadunandan; Skjøth, C A; Newnham, R M; Adams-Groom, B; Head, K; Caulton, Eric; Atkinson, Peter M

2017-02-01

Grass and birch pollen are two major causes of seasonal allergic rhinitis (hay fever) in the UK and parts of Europe affecting around 15-20% of the population. Current prediction of these allergens in the UK is based on (i) measurements of pollen concentrations at a limited number of monitoring stations across the country and (ii) general information about the phenological status of the vegetation. Thus, the current prediction methodology provides information at a coarse spatial resolution only. Most station-based approaches take into account only local observations of flowering, while only a small number of approaches take into account remote observations of land surface phenology. The systematic gathering of detailed information about vegetation status nationwide would therefore be of great potential utility. In particular, there exists an opportunity to use remote sensing to estimate phenological variables that are related to the flowering phenophase and, thus, pollen release. In turn, these estimates can be used to predict pollen release at a fine spatial resolution. In this study, time-series of MERIS Terrestrial Chlorophyll Index (MTCI) data were used to predict two key phenological variables: the start of season and peak of season. A technique was then developed to estimate the flowering phenophase of birch and grass from the MTCI time-series. For birch, the timing of flowering was defined as the time after the start of the growing season when the MTCI value reached 25% of the maximum. Similarly, for grass this was defined as the time when the MTCI value reached 75% of the maximum. The predicted pollen release dates were validated with data from nine pollen monitoring stations in the UK. For both birch and grass, we obtained large positive correlations between the MTCI-derived start of pollen season and the start of the pollen season defined using station data, with a slightly larger correlation observed for birch than for grass. The technique was applied to produce detailed maps for the flowering of birch and grass across the UK for each of the years from 2003 to 2010. The results demonstrate that the remote sensing-based maps of onset flowering of birch and grass for the UK together with the pollen forecast from the Meteorology Office and National Pollen and Aerobiology Research Unit (NPARU) can potentially provide more accurate information to pollen allergy sufferers in the UK. Copyright © 2016 Elsevier B.V. All rights reserved.

Prediction of whole-genome risk for selection and management of hyperketonemia in Holstein dairy cattle.

PubMed

Weigel, K A; Pralle, R S; Adams, H; Cho, K; Do, C; White, H M

2017-06-01

Hyperketonemia (HYK), a common early postpartum health disorder characterized by elevated blood concentrations of β-hydroxybutyrate (BHB), affects millions of dairy cows worldwide and leads to significant economic losses and animal welfare concerns. In this study, blood concentrations of BHB were assessed for 1,453 Holstein cows using electronic handheld meters at four time points between 5 and 18 days postpartum. Incidence rates of subclinical (1.2 ≤ maximum BHB ≤ 2.9 mmol/L) and clinical ketosis (maximum BHB ≥ 3.0 mmol/L) were 24.0 and 2.4%, respectively. Variance components, estimated breeding values, and predicted HYK phenotypes were computed on the original, square-root, and binary scales. Heritability estimates for HYK ranged from 0.058 to 0.072 in pedigree-based analyses, as compared to estimates that ranged from 0.071 to 0.093 when pedigrees were augmented with 60,671 single nucleotide polymorphism genotypes of 959 cows and 801 male ancestors. On average, predicted HYK phenotypes from the genome-enhanced analysis ranged from 0.55 mmol/L for first-parity cows in the best contemporary group to 1.40 mmol/L for fourth-parity cows in the worst contemporary group. Genome-enhanced predictions of HYK phenotypes were more closely associated with actual phenotypes than pedigree-based predictions in five-fold cross-validation, and transforming phenotypes to reduce skewness and kurtosis also improved predictive ability. This study demonstrates the feasibility of using repeated cowside measurement of blood BHB concentration in early lactation to construct a reference population that can be used to estimate HYK breeding values for genomic selection programmes and predict HYK phenotypes for genome-guided management decisions. © 2017 Blackwell Verlag GmbH.

Maximum likelihood Bayesian model averaging and its predictive analysis for groundwater reactive transport models

USGS Publications Warehouse

Curtis, Gary P.; Lu, Dan; Ye, Ming

2015-01-01

While Bayesian model averaging (BMA) has been widely used in groundwater modeling, it is infrequently applied to groundwater reactive transport modeling because of multiple sources of uncertainty in the coupled hydrogeochemical processes and because of the long execution time of each model run. To resolve these problems, this study analyzed different levels of uncertainty in a hierarchical way, and used the maximum likelihood version of BMA, i.e., MLBMA, to improve the computational efficiency. This study demonstrates the applicability of MLBMA to groundwater reactive transport modeling in a synthetic case in which twenty-seven reactive transport models were designed to predict the reactive transport of hexavalent uranium (U(VI)) based on observations at a former uranium mill site near Naturita, CO. These reactive transport models contain three uncertain model components, i.e., parameterization of hydraulic conductivity, configuration of model boundary, and surface complexation reactions that simulate U(VI) adsorption. These uncertain model components were aggregated into the alternative models by integrating a hierarchical structure into MLBMA. The modeling results of the individual models and MLBMA were analyzed to investigate their predictive performance. The predictive logscore results show that MLBMA generally outperforms the best model, suggesting that using MLBMA is a sound strategy to achieve more robust model predictions relative to a single model. MLBMA works best when the alternative models are structurally distinct and have diverse model predictions. When correlation in model structure exists, two strategies were used to improve predictive performance by retaining structurally distinct models or assigning smaller prior model probabilities to correlated models. Since the synthetic models were designed using data from the Naturita site, the results of this study are expected to provide guidance for real-world modeling. Limitations of applying MLBMA to the synthetic study and future real-world modeling are discussed.

Maximum spreading of liquid drop on various substrates with different wettabilities

NASA Astrophysics Data System (ADS)

Choudhury, Raihan; Choi, Junho; Yang, Sangsun; Kim, Yong-Jin; Lee, Donggeun

2017-09-01

This paper describes a novel model developed for a priori prediction of the maximal spread of a liquid drop on a surface. As a first step, a series of experiments were conducted under precise control of the initial drop diameter, its falling height, roughness, and wettability of dry surfaces. The transient liquid spreading was recorded by a high-speed camera to obtain its maximum spreading under various conditions. Eight preexisting models were tested for accurate prediction of the maximum spread; however, most of the model predictions were not satisfactory except one, in comparison with our experimental data. A comparative scaling analysis of the literature models was conducted to elucidate the condition-dependent prediction characteristics of the models. The conditioned bias in the predictions was mainly attributed to the inappropriate formulations of viscous dissipation or interfacial energy of liquid on the surface. Hence, a novel model based on energy balance during liquid impact was developed to overcome the limitations of the previous models. As a result, the present model was quite successful in predicting the liquid spread in all the conditions.

Using a Convection Model to Predict Altitudes of White Stork Migration Over Central Israel

NASA Astrophysics Data System (ADS)

Shamoun-Baranes, Judy; Liechti, Olivier; Yom-Tov, Yoram; Leshem, Yossi

Soaring migrants such as storks, pelicans and large birds of prey rely on thermal convection during migration. The convection model ALPTHERM was designed to predict the onset, strength, duration and depth of thermal convection for varying topographies for glider pilots, based on atmospheric conditions at midnight. We tested ALPTHERM predictions as configured for two topographies of central Israel, the Coastal Plains and the Judean and Samarian Mountains in order to predict altitudes of migrating white storks (Ciconia ciconia). Migrating flocks of white storks were tracked with a motorized glider, to measure maximum altitudes of migration during spring 2000. A significant positive correlation was found between the maximum daily altitudes of migration measured and the predicted upper boundary of thermal convection for the Coastal Plains and Samarian Mountains. Thirty-minute predictions for the Coastal Plains and Samarian Mountains correlated positively with measured maximum migration altitudes per thermal. ALPTHERM forecasts can be used to alter flight altitudes in both civil and especially military aviation and reduce the hazard of serious aircraft collisions with soaring migrants.

Calcaneal loading during walking and running

NASA Technical Reports Server (NTRS)

Giddings, V. L.; Beaupre, G. S.; Whalen, R. T.; Carter, D. R.

2000-01-01

PURPOSE: This study of the foot uses experimentally measured kinematic and kinetic data with a numerical model to evaluate in vivo calcaneal stresses during walking and running. METHODS: External ground reaction forces (GRF) and kinematic data were measured during walking and running using cineradiography and force plate measurements. A contact-coupled finite element model of the foot was developed to assess the forces acting on the calcaneus during gait. RESULTS: We found that the calculated force-time profiles of the joint contact, ligament, and Achilles tendon forces varied with the time-history curve of the moment about the ankle joint. The model predicted peak talocalcaneal and calcaneocuboid joint loads of 5.4 and 4.2 body weights (BW) during walking and 11.1 and 7.9 BW during running. The maximum predicted Achilles tendon forces were 3.9 and 7.7 BW for walking and running. CONCLUSIONS: Large magnitude forces and calcaneal stresses are generated late in the stance phase, with maximum loads occurring at approximately 70% of the stance phase during walking and at approximately 60% of the stance phase during running, for the gait velocities analyzed. The trajectories of the principal stresses, during both walking and running, corresponded to each other and qualitatively to the calcaneal trabecular architecture.

Athletes at altitude

PubMed Central

Pugh, L. G. C. E.

1967-01-01

1. Six international middle-distance runners were investigated during 4 weeks in England and during a similar period in Mexico City (2270 m (7450 ft.)) 2. In 3-mile (4828 m) time trials at 2270 m the increase in time taken by four subjects compared with sea level was 8·5% on the 4th day and 5·7% on the 29th day. There was thus a gain of 2·8% or 20 sec in time associated with acclimatization. 3. In 1-mile (1609 m) time trials the times were increased by 3·6% in the first week at altitude and by 1·5% in the 4th week. The improvement amounted to 2·1%, or 4·9 sec. 4. In 5 min maximum exercise on the ergometer maximum O2 intake for six subjects at altitude was reduced by 14·6% on the 2nd day and 9·5% on the 27th. Only one subject showed no change in maximum oxygen intake (V̇O2, max) with time spent at altitude. 5. Although V̇O2, max was persistently reduced at altitude work rates finally exceeded sea-level values, owing to increased over-all efficiency. 6. Forty-minute recovery O2 intakes after 5 min maximum exercise averaged 17·35 l. at sea level and 17·53 l. at altitude. Mean values from 40th to 50th min were within ± 7% of pre-exercise values. 7. Serial tests at increasing loads yielded a straight-line relation between O2 intake and work rate over a wide range of work rates at sea level and at altitude. Heart rate and ventilation for given work intensity were maximal in the first 2-10 days at altitude and thereafter declined. 8. Capillary HbO2 saturation fell from 93% at rest to 87% in maximum exercise. The corresponding alveolar gas tensions were PA, O2 89 mm Hg, PA, CO2 24 mm Hg. About half the total unsaturation in maximum exercise was explained by the Bohr effect. 9. In six of eight pairs of determinations V̇O2, max measured on the ergometer was within ± 0·15 l./min of V̇O2, max measured on the running track. Nevertheless, it was not possible to predict running performance from ergometer measurements. PMID:6058997

Numerical simulation of mushrooms during freezing using the FEM and an enthalpy: Kirchhoff formulation

NASA Astrophysics Data System (ADS)

Santos, M. V.; Lespinard, A. R.

2011-12-01

The shelf life of mushrooms is very limited since they are susceptible to physical and microbial attack; therefore they are usually blanched and immediately frozen for commercial purposes. The aim of this work was to develop a numerical model using the finite element technique to predict freezing times of mushrooms considering the actual shape of the product. The original heat transfer equation was reformulated using a combined enthalpy-Kirchhoff formulation, therefore an own computational program using Matlab 6.5 (MathWorks, Natick, Massachusetts) was developed, considering the difficulties encountered when simulating this non-linear problem in commercial softwares. Digital images were used to generate the irregular contour and the domain discretization. The numerical predictions agreed with the experimental time-temperature curves during freezing of mushrooms (maximum absolute error <3.2°C) obtaining accurate results and minimum computer processing times. The codes were then applied to determine required processing times for different operating conditions (external fluid temperatures and surface heat transfer coefficients).

Prediction of Compressional Wave Velocity Using Regression and Neural Network Modeling and Estimation of Stress Orientation in Bokaro Coalfield, India

NASA Astrophysics Data System (ADS)

Paul, Suman; Ali, Muhammad; Chatterjee, Rima

2018-01-01

Velocity of compressional wave ( V P) of coal and non-coal lithology is predicted from five wells from the Bokaro coalfield (CF), India. Shear sonic travel time logs are not recorded for all wells under the study area. Shear wave velocity ( Vs) is available only for two wells: one from east and other from west Bokaro CF. The major lithologies of this CF are dominated by coal, shaly coal of Barakar formation. This paper focuses on the (a) relationship between Vp and Vs, (b) prediction of Vp using regression and neural network modeling and (c) estimation of maximum horizontal stress from image log. Coal characterizes with low acoustic impedance (AI) as compared to the overlying and underlying strata. The cross-plot between AI and Vp/ Vs is able to identify coal, shaly coal, shale and sandstone from wells in Bokaro CF. The relationship between Vp and Vs is obtained with excellent goodness of fit ( R 2) ranging from 0.90 to 0.93. Linear multiple regression and multi-layered feed-forward neural network (MLFN) models are developed for prediction Vp from two wells using four input log parameters: gamma ray, resistivity, bulk density and neutron porosity. Regression model predicted Vp shows poor fit (from R 2 = 0.28) to good fit ( R 2 = 0.79) with the observed velocity. MLFN model predicted Vp indicates satisfactory to good R2 values varying from 0.62 to 0.92 with the observed velocity. Maximum horizontal stress orientation from a well at west Bokaro CF is studied from Formation Micro-Imager (FMI) log. Breakouts and drilling-induced fractures (DIFs) are identified from the FMI log. Breakout length of 4.5 m is oriented towards N60°W whereas the orientation of DIFs for a cumulative length of 26.5 m is varying from N15°E to N35°E. The mean maximum horizontal stress in this CF is towards N28°E.

Prediction of pathogen growth on iceberg lettuce under real temperature history during distribution from farm to table.

PubMed

Koseki, Shigenobu; Isobe, Seiichiro

2005-10-25

The growth of pathogenic bacteria Escherichia coli O157:H7, Salmonella spp., and Listeria monocytogenes on iceberg lettuce under constant and fluctuating temperatures was modelled in order to estimate the microbial safety of this vegetable during distribution from the farm to the table. Firstly, we examined pathogen growth on lettuce at constant temperatures, ranging from 5 to 25 degrees C, and then we obtained the growth kinetic parameters (lag time, maximum growth rate (micro(max)), and maximum population density (MPD)) using the Baranyi primary growth model. The parameters were similar to those predicted by the pathogen modelling program (PMP), with the exception of MPD. The MPD of each pathogen on lettuce was 2-4 log(10) CFU/g lower than that predicted by PMP. Furthermore, the MPD of pathogens decreased with decreasing temperature. The relationship between mu(max) and temperature was linear in accordance with Ratkowsky secondary model as was the relationship between the MPD and temperature. Predictions of pathogen growth under fluctuating temperature used the Baranyi primary microbial growth model along with the Ratkowsky secondary model and MPD equation. The fluctuating temperature profile used in this study was the real temperature history measured during distribution from the field at harvesting to the retail store. Overall predictions for each pathogen agreed well with observed viable counts in most cases. The bias and root mean square error (RMSE) of the prediction were small. The prediction in which mu(max) was based on PMP showed a trend of overestimation relative to prediction based on lettuce. However, the prediction concerning E. coli O157:H7 and Salmonella spp. on lettuce greatly overestimated growth in the case of a temperature history starting relatively high, such as 25 degrees C for 5 h. In contrast, the overall prediction of L. monocytogenes under the same circumstances agreed with the observed data.

In Vivo Knee Contact Force Prediction Using Patient-Specific Musculoskeletal Geometry in a Segment-Based Computational Model.

PubMed

Ding, Ziyun; Nolte, Daniel; Kit Tsang, Chui; Cleather, Daniel J; Kedgley, Angela E; Bull, Anthony M J

2016-02-01

Segment-based musculoskeletal models allow the prediction of muscle, ligament, and joint forces without making assumptions regarding joint degrees-of-freedom (DOF). The dataset published for the "Grand Challenge Competition to Predict in vivo Knee Loads" provides directly measured tibiofemoral contact forces for activities of daily living (ADL). For the Sixth Grand Challenge Competition to Predict in vivo Knee Loads, blinded results for "smooth" and "bouncy" gait trials were predicted using a customized patient-specific musculoskeletal model. For an unblinded comparison, the following modifications were made to improve the predictions: further customizations, including modifications to the knee center of rotation; reductions to the maximum allowable muscle forces to represent known loss of strength in knee arthroplasty patients; and a kinematic constraint to the hip joint to address the sensitivity of the segment-based approach to motion tracking artifact. For validation, the improved model was applied to normal gait, squat, and sit-to-stand for three subjects. Comparisons of the predictions with measured contact forces showed that segment-based musculoskeletal models using patient-specific input data can estimate tibiofemoral contact forces with root mean square errors (RMSEs) of 0.48-0.65 times body weight (BW) for normal gait trials. Comparisons between measured and predicted tibiofemoral contact forces yielded an average coefficient of determination of 0.81 and RMSEs of 0.46-1.01 times BW for squatting and 0.70-0.99 times BW for sit-to-stand tasks. This is comparable to the best validations in the literature using alternative models.

Predicting outgrowth and inactivation of Clostridium perfringens in meat products during low temperature long time heat treatment.

PubMed

Duan, Zhi; Hansen, Terese Holst; Hansen, Tina Beck; Dalgaard, Paw; Knøchel, Susanne

2016-08-02

With low temperature long time (LTLT) cooking it can take hours for meat to reach a final core temperature above 53°C and germination followed by growth of Clostridium perfringens is a concern. Available and new growth data in meats including 154 lag times (tlag), 224 maximum specific growth rates (μmax) and 25 maximum population densities (Nmax) were used to developed a model to predict growth of C. perfringens during the coming-up time of LTLT cooking. New data were generate in 26 challenge tests with chicken (pH6.8) and pork (pH5.6) at two different slowly increasing temperature (SIT) profiles (10°C to 53°C) followed by 53°C in up to 30h in total. Three inoculum types were studied including vegetative cells, non-heated spores and heat activated (75°C, 20min) spores of C. perfringens strain 790-94. Concentrations of vegetative cells in chicken increased 2 to 3logCFU/g during the SIT profiles. Similar results were found for non-heated and heated spores in chicken, whereas in pork C. perfringens 790-94 increased less than 1logCFU/g. At 53°C C. perfringens 790-94 was log-linearly inactivated. Observed and predicted concentrations of C. perfringens, at the time when 53°C (log(N53)) was reached, were used to evaluate the new growth model and three available predictive models previously published for C. perfringens growth during cooling rather than during SIT profiles. Model performance was evaluated by using mean deviation (MD), mean absolute deviation (MAD) and the acceptable simulation zone (ASZ) approach with a zone of ±0.5logCFU/g. The new model showed best performance with MD=0.27logCFU/g, MAD=0.66logCFU/g and ASZ=67%. The two growth models that performed best, were used together with a log-linear inactivation model and D53-values from the present study to simulate the behaviour of C. perfringens under the fast and slow SIT profiles investigated in the present study. Observed and predicted concentrations were compared using a new fail-safe acceptable zone (FSAZ) method. FSAZ was defined as the predicted concentration of C. perfringens plus 0.5logCFU/g. If at least 85% of the observed log-counts were below the FSAZ, the model was considered fail-safe. The two models showed similar performance but none of them performed satisfactorily for all conditions. It is recommended to use the models without a lag phase until more precise lag time models become available. Copyright © 2016 Elsevier B.V. All rights reserved.

Novel self-organization mechanism in ultrathin liquid films: theory and experiment.

PubMed

Trice, Justin; Favazza, Christopher; Thomas, Dennis; Garcia, Hernando; Kalyanaraman, Ramki; Sureshkumar, Radhakrishna

2008-07-04

When an ultrathin metal film of thickness h (<20 nm) is melted by a nanosecond pulsed laser, the film temperature is a nonmonotonic function of h and achieves its maximum at a certain thickness h*. This is a consequence of the h and time dependence of energy absorption and heat flow. Linear stability analysis and nonlinear dynamical simulations that incorporate such intrinsic interfacial thermal gradients predict a characteristic pattern length scale Lambda that decreases for h>h*, in contrast to the classical spinodal dewetting behavior where Lambda increases monotonically as h2. These predictions agree well with experimental observations for Co and Fe films on SiO2.

Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

PubMed Central

Niwas, Ram; Osama, Khwaja; Khan, Saif; Haque, Shafiul; Tripathi, C. K. M.; Mishra, B. N.

2015-01-01

Cholesterol oxidase (COD) is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD) and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO4, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL) obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500. PMID:26368924

Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

PubMed

Pathak, Lakshmi; Singh, Vineeta; Niwas, Ram; Osama, Khwaja; Khan, Saif; Haque, Shafiul; Tripathi, C K M; Mishra, B N

2015-01-01

Cholesterol oxidase (COD) is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD) and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO4, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL) obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500.

Development of a Threshold Model to Predict Germination of Populus tomentosa Seeds after Harvest and Storage under Ambient Condition

PubMed Central

Wang, Wei-Qing; Cheng, Hong-Yan; Song, Song-Quan

2013-01-01

Effects of temperature, storage time and their combination on germination of aspen (Populus tomentosa) seeds were investigated. Aspen seeds were germinated at 5 to 30°C at 5°C intervals after storage for a period of time under 28°C and 75% relative humidity. The effect of temperature on aspen seed germination could not be effectively described by the thermal time (TT) model, which underestimated the germination rate at 5°C and poorly predicted the time courses of germination at 10, 20, 25 and 30°C. A modified TT model (MTT) which assumed a two-phased linear relationship between germination rate and temperature was more accurate in predicting the germination rate and percentage and had a higher likelihood of being correct than the TT model. The maximum lifetime threshold (MLT) model accurately described the effect of storage time on seed germination across all the germination temperatures. An aging thermal time (ATT) model combining both the TT and MLT models was developed to describe the effect of both temperature and storage time on seed germination. When the ATT model was applied to germination data across all the temperatures and storage times, it produced a relatively poor fit. Adjusting the ATT model to separately fit germination data at low and high temperatures in the suboptimal range increased the models accuracy for predicting seed germination. Both the MLT and ATT models indicate that germination of aspen seeds have distinct physiological responses to temperature within a suboptimal range. PMID:23658654

US EPA 2012 Air Quality Fused Surface for the Conterminous U.S. Map Service

EPA Pesticide Factsheets

This web service contains a polygon layer that depicts fused air quality predictions for 2012 for census tracts in the conterminous United States. Fused air quality predictions (for ozone and PM2.5) are modeled using a Bayesian space-time downscaling fusion model approach described in a series of three published journal papers: 1) (Berrocal, V., Gelfand, A. E. and Holland, D. M. (2012). Space-time fusion under error in computer model output: an application to modeling air quality. Biometrics 68, 837-848; 2) Berrocal, V., Gelfand, A. E. and Holland, D. M. (2010). A bivariate space-time downscaler under space and time misalignment. The Annals of Applied Statistics 4, 1942-1975; and 3) Berrocal, V., Gelfand, A. E., and Holland, D. M. (2010). A spatio-temporal downscaler for output from numerical models. J. of Agricultural, Biological,and Environmental Statistics 15, 176-197) is used to provide daily, predictive PM2.5 (daily average) and O3 (daily 8-hr maximum) surfaces for 2012. Summer (O3) and annual (PM2.5) means calculated and published. The downscaling fusion model uses both air quality monitoring data from the National Air Monitoring Stations/State and Local Air Monitoring Stations (NAMS/SLAMS) and numerical output from the Models-3/Community Multiscale Air Quality (CMAQ). Currently, predictions at the US census tract centroid locations within the 12 km CMAQ domain are archived. Predictions at the CMAQ grid cell centroids, or any desired set of locations co

Early visual responses predict conscious face perception within and between subjects during binocular rivalry

PubMed Central

Sandberg, Kristian; Bahrami, Bahador; Kanai, Ryota; Barnes, Gareth Robert; Overgaard, Morten; Rees, Geraint

2014-01-01

Previous studies indicate that conscious face perception may be related to neural activity in a large time window around 170-800ms after stimulus presentation, yet in the majority of these studies changes in conscious experience are confounded with changes in physical stimulation. Using multivariate classification on MEG data recorded when participants reported changes in conscious perception evoked by binocular rivalry between a face and a grating, we showed that only MEG signals in the 120-320ms time range, peaking at the M170 around 180ms and the P2m at around 260ms, reliably predicted conscious experience. Conscious perception could not only be decoded significantly better than chance from the sensors that showed the largest average difference, as previous studies suggest, but also from patterns of activity across groups of occipital sensors that individually were unable to predict perception better than chance. Additionally, source space analyses showed that sources in the early and late visual system predicted conscious perception more accurately than frontal and parietal sites, although conscious perception could also be decoded there. Finally, the patterns of neural activity associated with conscious face perception generalized from one participant to another around the times of maximum prediction accuracy. Our work thus demonstrates that the neural correlates of particular conscious contents (here, faces) are highly consistent in time and space within individuals and that these correlates are shared to some extent between individuals. PMID:23281780

Earthquake-triggered liquefaction in Southern Siberia and surroundings: a base for predictive models and seismic hazard estimation

NASA Astrophysics Data System (ADS)

Lunina, Oksana

2016-04-01

The forms and location patterns of soil liquefaction induced by earthquakes in southern Siberia, Mongolia, and northern Kazakhstan in 1950 through 2014 have been investigated, using field methods and a database of coseismic effects created as a GIS MapInfo application, with a handy input box for large data arrays. Statistical analysis of the data has revealed regional relationships between the magnitude (Ms) of an earthquake and the maximum distance of its environmental effect to the epicenter and to the causative fault (Lunina et al., 2014). Estimated limit distances to the fault for the Ms = 8.1 largest event are 130 km that is 3.5 times as short as those to the epicenter, which is 450 km. Along with this the wider of the fault the less liquefaction cases happen. 93% of them are within 40 km from the causative fault. Analysis of liquefaction locations relative to nearest faults in southern East Siberia shows the distances to be within 8 km but 69% of all cases are within 1 km. As a result, predictive models have been created for locations of seismic liquefaction, assuming a fault pattern for some parts of the Baikal rift zone. Base on our field and world data, equations have been suggested to relate the maximum sizes of liquefaction-induced clastic dikes (maximum width, visible maximum height and intensity index of clastic dikes) with Ms and local shaking intensity corresponding to the MSK-64 macroseismic intensity scale (Lunina and Gladkov, 2015). The obtained results make basis for modeling the distribution of the geohazard for the purposes of prediction and for estimating the earthquake parameters from liquefaction-induced clastic dikes. The author would like to express their gratitude to the Institute of the Earth's Crust, Siberian Branch of the Russian Academy of Sciences for providing laboratory to carry out this research and Russian Scientific Foundation for their financial support (Grant 14-17-00007).

Evolution of supersaturation of amorphous pharmaceuticals: the effect of rate of supersaturation generation.

PubMed

Sun, Dajun D; Lee, Ping I

2013-11-04

The combination of a rapidly dissolving and supersaturating "spring" with a precipitation retarding "parachute" has often been pursued as an effective formulation strategy for amorphous solid dispersions (ASDs) to enhance the rate and extent of oral absorption. However, the interplay between these two rate processes in achieving and maintaining supersaturation remains inadequately understood, and the effect of rate of supersaturation buildup on the overall time evolution of supersaturation during the dissolution of amorphous solids has not been explored. The objective of this study is to investigate the effect of supersaturation generation rate on the resulting kinetic solubility profiles of amorphous pharmaceuticals and to delineate the evolution of supersaturation from a mechanistic viewpoint. Experimental concentration-time curves under varying rates of supersaturation generation and recrystallization for model drugs, indomethacin (IND), naproxen (NAP) and piroxicam (PIR), were generated from infusing dissolved drug (e.g., in ethanol) into the dissolution medium and compared with that predicted from a comprehensive mechanistic model based on the classical nucleation theory taking into account both the particle growth and ripening processes. In the absence of any dissolved polymer to inhibit drug precipitation, both our experimental and predicted results show that the maximum achievable supersaturation (i.e., kinetic solubility) of the amorphous solids increases, the time to reach maximum decreases, and the rate of concentration decline in the de-supersaturation phase increases, with increasing rate of supersaturation generation (i.e., dissolution rate). Our mechanistic model also predicts the existence of an optimal supersaturation rate which maximizes the area under the curve (AUC) of the kinetic solubility concentration-time profile, which agrees well with experimental data. In the presence of a dissolved polymer from ASD dissolution, these observed trends also hold true except the de-supersaturation phase is more extended due to the crystallization inhibition effect. Since the observed kinetic solubility of nonequilibrium amorphous solids depends on the rate of supersaturation generation, our results also highlight the underlying difficulty in determining a reproducible solubility advantage for amorphous solids.

Evaluation of a Revised Interplanetary Shock Prediction Model: 1D CESE-HD-2 Solar-Wind Model

NASA Astrophysics Data System (ADS)

Zhang, Y.; Du, A. M.; Du, D.; Sun, W.

2014-08-01

We modified the one-dimensional conservation element and solution element (CESE) hydrodynamic (HD) model into a new version [ 1D CESE-HD-2], by considering the direction of the shock propagation. The real-time performance of the 1D CESE-HD-2 model during Solar Cycle 23 (February 1997 - December 2006) is investigated and compared with those of the Shock Time of Arrival Model ( STOA), the Interplanetary-Shock-Propagation Model ( ISPM), and the Hakamada-Akasofu-Fry version 2 ( HAFv.2). Of the total of 584 flare events, 173 occurred during the rising phase, 166 events during the maximum phase, and 245 events during the declining phase. The statistical results show that the success rates of the predictions by the 1D CESE-HD-2 model for the rising, maximum, declining, and composite periods are 64 %, 62 %, 57 %, and 61 %, respectively, with a hit window of ± 24 hours. The results demonstrate that the 1D CESE-HD-2 model shows the highest success rates when the background solar-wind speed is relatively fast. Thus, when the background solar-wind speed at the time of shock initiation is enhanced, the forecasts will provide potential values to the customers. A high value (27.08) of χ 2 and low p-value (< 0.0001) for the 1D CESE-HD-2 model give considerable confidence for real-time forecasts by using this new model. Furthermore, the effects of various shock characteristics (initial speed, shock duration, background solar wind, longitude, etc.) and background solar wind on the forecast are also investigated statistically.

Evaluation of a fast single-photon avalanche photodiode for measurement of early transmitted photons through diffusive media.

PubMed

Mu, Ying; Valim, Niksa; Niedre, Mark

2013-06-15

We tested the performance of a fast single-photon avalanche photodiode (SPAD) in measurement of early transmitted photons through diffusive media. In combination with a femtosecond titanium:sapphire laser, the overall instrument temporal response time was 59 ps. Using two experimental models, we showed that the SPAD allowed measurement of photon-density sensitivity functions that were approximately 65% narrower than the ungated continuous wave case at very early times. This exceeds the performance that we have previously achieved with photomultiplier-tube-based systems and approaches the theoretical maximum predicted by time-resolved Monte Carlo simulations.

Hinge Moment Coefficient Prediction Tool and Control Force Analysis of Extra-300 Aerobatic Aircraft

NASA Astrophysics Data System (ADS)

Nurohman, Chandra; Arifianto, Ony; Barecasco, Agra

2018-04-01

This paper presents the development of tool that is applicable to predict hinge moment coefficients of subsonic aircraft based on Roskam’s method, including the validation and its application to predict hinge moment coefficient of an Extra-300. The hinge moment coefficients are used to predict the stick forces of the aircraft during several aerobatic maneuver i.e. inside loop, half cuban 8, split-s, and aileron roll. The maximum longitudinal stick force is 566.97 N occurs in inside loop while the maximum lateral stick force is 340.82 N occurs in aileron roll. Furthermore, validation hinge moment prediction method is performed using Cessna 172 data.

A comparison of solar irradiances measured by SBUV, SME, and rockets

NASA Technical Reports Server (NTRS)

Schlesinger, Barry M.; Heath, Donald F.

1988-01-01

In this paper, Solar Backscatter Ultraviolet (SBUV) measurements of solar irradiance and predictions from the Mg 280-nm index are compared with each other and with coincident Solar Mesosphere Explorer (SME) and rocket measurements. The SBUV irradiances show a systematic decrease with time not seen in the rocket measurements; a correction for this decrease is introduced. The scatter and overall structure in the SME spectra is 3-5 percent, of the order of or larger than most of the changes predicted by the Mg index. The corrected SBUV ratio and the Mg index prediction for it agree to within 1 percent. Such agreement supports a common origin for variations between solar maximum and minimum and those for individual rotations: the degree to which active regions cover the visible hemisphere of the sun.

Kinetically accessible yield (KAY) for redirection of metabolism to produce exo-metabolites

DOE PAGES

Lafontaine Rivera, Jimmy G.; Theisen, Matthew K.; Chen, Po-Wei; ...

2017-04-05

The product formation yield (product formed per unit substrate consumed) is often the most important performance indicator in metabolic engineering. Until now, the actual yield cannot be predicted, but it can be bounded by its maximum theoretical value. The maximum theoretical yield is calculated by considering the stoichiometry of the pathways and cofactor regeneration involved. Here in this paper we found that in many cases, dynamic stability becomes an issue when excessive pathway flux is drawn to a product. This constraint reduces the yield and renders the maximal theoretical yield too loose to be predictive. We propose a more realisticmore » quantity, defined as the kinetically accessible yield (KAY) to predict the maximum accessible yield for a given flux alteration. KAY is either determined by the point of instability, beyond which steady states become unstable and disappear, or a local maximum before becoming unstable. Thus, KAY is the maximum flux that can be redirected for a given metabolic engineering strategy without losing stability. Strictly speaking, calculation of KAY requires complete kinetic information. With limited or no kinetic information, an Ensemble Modeling strategy can be used to determine a range of likely values for KAY, including an average prediction. We first apply the KAY concept with a toy model to demonstrate the principle of kinetic limitations on yield. We then used a full-scale E. coli model (193 reactions, 153 metabolites) and this approach was successful in E. coli for predicting production of isobutanol: the calculated KAY values are consistent with experimental data for three genotypes previously published.« less

A. Palmgren Revisited: A Basis for Bearing Life Prediction

NASA Technical Reports Server (NTRS)

Zaretsky, Erwin V.

1997-01-01

Bearing technology, as well as the bearing industry, began to develop with the invention of the bicycle in the 1850's. At the same time, high-quality steel was made possible by the Bessemer process. In 1881, H. Hertz published his contact stress analysis. By 1902, R. Stribeck had published his work based on Hertz theory to calculate the maximum load of a radially loaded ball bearing. By 1920, all of the rolling bearing types used today were being manufactured. AISI 52100 bearing steel became the material of choice for these bearings. Beginning in 1918, engineers directed their attention to predicting the lives of these bearings. In 1924, A. Palmgren published a paper outlining his approach to bearing life prediction. This paper was the basis for the Lundberg-Palmgren life theory published in 1947. A critical review of the 1924 Palmgren paper is presented here together with a discussion of its effect on bearing life prediction.

Accounting of fundamental components of the rotation parameters of the Earth in the formation of a high-accuracy orbit of navigation satellites

NASA Astrophysics Data System (ADS)

Markov, Yu. G.; Mikhailov, M. V.; Pochukaev, V. N.

2012-07-01

An analysis of perturbing factors influencing the motion of a navigation satellite (NS) is carried out, and the degree of influence of each factor on the GLONASS orbit is estimated. It is found that fundamental components of the Earth's rotation parameters (ERP) are one substantial factor commensurable with maximum perturbations. Algorithms for the calculation of orbital perturbations caused by these parameters are given; these algorithms can be implemented in a consumer's equipment. The daily prediction of NS coordinates is performed on the basis of real GLONASS satellite ephemerides transmitted to a consumer, using the developed prediction algorithms taking the ERP into account. The obtained accuracy of the daily prediction of GLONASS ephemerides exceeds by tens of times the accuracy of the daily prediction performed using algorithms recommended in interface control documents.

Improving the Accuracy of Predicting Maximal Oxygen Consumption (VO2pk)

NASA Technical Reports Server (NTRS)

Downs, Meghan E.; Lee, Stuart M. C.; Ploutz-Snyder, Lori; Feiveson, Alan

2016-01-01

Maximal oxygen (VO2pk) is the maximum amount of oxygen that the body can use during intense exercise and is used for benchmarking endurance exercise capacity. The most accurate method to determineVO2pk requires continuous measurements of ventilation and gas exchange during an exercise test to maximal effort, which necessitates expensive equipment, a trained staff, and time to set-up the equipment. For astronauts, accurate VO2pk measures are important to assess mission critical task performance capabilities and to prescribe exercise intensities to optimize performance. Currently, astronauts perform submaximal exercise tests during flight to predict VO2pk; however, while submaximal VO2pk prediction equations provide reliable estimates of mean VO2pk for populations, they can be unacceptably inaccurate for a given individual. The error in current predictions and logistical limitations of measuring VO2pk, particularly during spaceflight, highlights the need for improved estimation methods.

Short-Term Forecasting of Taiwanese Earthquakes Using a Universal Model of Fusion-Fission Processes

PubMed Central

Cheong, Siew Ann; Tan, Teck Liang; Chen, Chien-Chih; Chang, Wu-Lung; Liu, Zheng; Chew, Lock Yue; Sloot, Peter M. A.; Johnson, Neil F.

2014-01-01

Predicting how large an earthquake can be, where and when it will strike remains an elusive goal in spite of the ever-increasing volume of data collected by earth scientists. In this paper, we introduce a universal model of fusion-fission processes that can be used to predict earthquakes starting from catalog data. We show how the equilibrium dynamics of this model very naturally explains the Gutenberg-Richter law. Using the high-resolution earthquake catalog of Taiwan between Jan 1994 and Feb 2009, we illustrate how out-of-equilibrium spatio-temporal signatures in the time interval between earthquakes and the integrated energy released by earthquakes can be used to reliably determine the times, magnitudes, and locations of large earthquakes, as well as the maximum numbers of large aftershocks that would follow. PMID:24406467

Conditional nonlinear optimal perturbations based on the particle swarm optimization and their applications to the predictability problems

NASA Astrophysics Data System (ADS)

Zheng, Qin; Yang, Zubin; Sha, Jianxin; Yan, Jun

2017-02-01

In predictability problem research, the conditional nonlinear optimal perturbation (CNOP) describes the initial perturbation that satisfies a certain constraint condition and causes the largest prediction error at the prediction time. The CNOP has been successfully applied in estimation of the lower bound of maximum predictable time (LBMPT). Generally, CNOPs are calculated by a gradient descent algorithm based on the adjoint model, which is called ADJ-CNOP. This study, through the two-dimensional Ikeda model, investigates the impacts of the nonlinearity on ADJ-CNOP and the corresponding precision problems when using ADJ-CNOP to estimate the LBMPT. Our conclusions are that (1) when the initial perturbation is large or the prediction time is long, the strong nonlinearity of the dynamical model in the prediction variable will lead to failure of the ADJ-CNOP method, and (2) when the objective function has multiple extreme values, ADJ-CNOP has a large probability of producing local CNOPs, hence making a false estimation of the LBMPT. Furthermore, the particle swarm optimization (PSO) algorithm, one kind of intelligent algorithm, is introduced to solve this problem. The method using PSO to compute CNOP is called PSO-CNOP. The results of numerical experiments show that even with a large initial perturbation and long prediction time, or when the objective function has multiple extreme values, PSO-CNOP can always obtain the global CNOP. Since the PSO algorithm is a heuristic search algorithm based on the population, it can overcome the impact of nonlinearity and the disturbance from multiple extremes of the objective function. In addition, to check the estimation accuracy of the LBMPT presented by PSO-CNOP and ADJ-CNOP, we partition the constraint domain of initial perturbations into sufficiently fine grid meshes and take the LBMPT obtained by the filtering method as a benchmark. The result shows that the estimation presented by PSO-CNOP is closer to the true value than the one by ADJ-CNOP with the forecast time increasing.

Assessment of precursory information in seismo-electromagnetic phenomena

NASA Astrophysics Data System (ADS)

Han, P.; Hattori, K.; Zhuang, J.

2017-12-01

Previous statistical studies showed that there were correlations between seismo-electromagnetic phenomena and sizeable earthquakes in Japan. In this study, utilizing Molchan's error diagram, we evaluate whether these phenomena contain precursory information and discuss how they can be used in short-term forecasting of large earthquake events. In practice, for given series of precursory signals and related earthquake events, each prediction strategy is characterized by the leading time of alarms, the length of alarm window, the alarm radius (area) and magnitude. The leading time is the time length between a detected anomaly and its following alarm, and the alarm window is the duration that an alarm lasts. The alarm radius and magnitude are maximum predictable distance and minimum predictable magnitude of earthquake events, respectively. We introduce the modified probability gain (PG') and the probability difference (D') to quantify the forecasting performance and to explore the optimal prediction parameters for a given electromagnetic observation. The above methodology is firstly applied to ULF magnetic data and GPS-TEC data. The results show that the earthquake predictions based on electromagnetic anomalies are significantly better than random guesses, indicating the data contain potential useful precursory information. Meanwhile, we reveal the optimal prediction parameters for both observations. The methodology proposed in this study could be also applied to other pre-earthquake phenomena to find out whether there is precursory information, and then on this base explore the optimal alarm parameters in practical short-term forecast.

European shags optimize their flight behavior according to wind conditions.

PubMed

Kogure, Yukihisa; Sato, Katsufumi; Watanuki, Yutaka; Wanless, Sarah; Daunt, Francis

2016-02-01

Aerodynamics results in two characteristic speeds of flying birds: the minimum power speed and the maximum range speed. The minimum power speed requires the lowest rate of energy expenditure per unit time to stay airborne and the maximum range speed maximizes air distance traveled per unit of energy consumed. Therefore, if birds aim to minimize the cost of transport under a range of wind conditions, they are predicted to fly at the maximum range speed. Furthermore, take-off is predicted to be strongly affected by wind speed and direction. To investigate the effect of wind conditions on take-off and cruising flight behavior, we equipped 14 European shags Phalacrocorax aristotelis with a back-mounted GPS logger to measure position and hence ground speed, and a neck-mounted accelerometer to record wing beat frequency and strength. Local wind conditions were recorded during the deployment period. Shags always took off into the wind regardless of their intended destination and take-off duration was correlated negatively with wind speed. We combined ground speed and direction during the cruising phase with wind speed and direction to estimate air speed and direction. Whilst ground speed was highly variable, air speed was comparatively stable, although it increased significantly during strong head winds, because of stronger wing beats. The increased air speeds in head winds suggest that birds fly at the maximum range speed, not at the minimum power speed. Our study demonstrates that European shags actively adjust their flight behavior to utilize wind power to minimize the costs of take-off and cruising flight. © 2016. Published by The Company of Biologists Ltd.

Prediction of effects of wing contour modifications on low-speed maximum lift and transonic performance for the EA-6B aircraft

NASA Technical Reports Server (NTRS)

Allison, Dennis O.; Waggoner, E. G.

1990-01-01

Computational predictions of the effects of wing contour modifications on maximum lift and transonic performance were made and verified against low speed and transonic wind tunnel data. This effort was part of a program to improve the maneuvering capability of the EA-6B electronics countermeasures aircraft, which evolved from the A-6 attack aircraft. The predictions were based on results from three computer codes which all include viscous effects: MCARF, a 2-D subsonic panel code; TAWFIVE, a transonic full potential code; and WBPPW, a transonic small disturbance potential flow code. The modifications were previously designed with the aid of these and other codes. The wing modifications consists of contour changes to the leading edge slats and trailing edge flaps and were designed for increased maximum lift with minimum effect on transonic performance. The prediction of the effects of the modifications are presented, with emphasis on verification through comparisons with wind tunnel data from the National Transonic Facility. Attention is focused on increments in low speed maximum lift and increments in transonic lift, pitching moment, and drag resulting from the contour modifications.

Coupled Modes over Indian Ocean at Sub-seasonal time Scales and its Prediction

NASA Astrophysics Data System (ADS)

Jung, E.; Kirtman, B. P.

2014-12-01

Sub-seasonal variability over the Indian Ocean, such as Madden-Julian Oscillation impacts weather and climate globally. However, the prediction of tropical sub-seasonal variability (TSV) remains a challenge, and understanding air-sea interactions on TSV time-scales is likely to be an important part of the prediction problem. The purpose of this paper is to examine the predictability of sub-seasonal variability in the tropical Indo-Pacific region. The analysis emphasizes on variability associated with coupled air-sea interactions in observational estimates, and how well these coupled modes are simulated and predicted within the context of a 30-year retrospective forecast experiment with a state-of-the-art atmosphere-ocean coupled model. The analysis shows that Sea Surface Temperature anomalies (SSTA) over the Indian Ocean tend to precede precipitation anomalies by 7-11 days with maximum amplitude over the Arabian Sea and the Bay of Bengal for summer and along the Seychelles-Chagos Thermocline Ridge (SCTR) region for winter. Though these coupled modes are captured by the models, the forecasts fail to predict its evolution. Based on the diagnosis of these coupled modes, we introduce a SCTR-SST index and an index that measures the modulation of the low-frequency amplitude (LFAM) of sub-seasonal SSTA variability over SCTR as a way to predict the coupled modes. Based on correlation with the observed variability, SCTR-SST has forecast skill of about 45 days over the Indian Ocean. However the sub-seasonal SSTAs in the predictions and the observational estimates do not have any direct ENSO tele-connection. In contrast, the LFAM of the sub-seasonal SSTA variance over SCTR is strongly correlated with ENSO, suggesting enhanced sub-seasonal variance on seasonal time-scales is potentially predictable.

Assessing the stability of human locomotion: a review of current measures

PubMed Central

Bruijn, S. M.; Meijer, O. G.; Beek, P. J.; van Dieën, J. H.

2013-01-01

Falling poses a major threat to the steadily growing population of the elderly in modern-day society. A major challenge in the prevention of falls is the identification of individuals who are at risk of falling owing to an unstable gait. At present, several methods are available for estimating gait stability, each with its own advantages and disadvantages. In this paper, we review the currently available measures: the maximum Lyapunov exponent (λS and λL), the maximum Floquet multiplier, variability measures, long-range correlations, extrapolated centre of mass, stabilizing and destabilizing forces, foot placement estimator, gait sensitivity norm and maximum allowable perturbation. We explain what these measures represent and how they are calculated, and we assess their validity, divided up into construct validity, predictive validity in simple models, convergent validity in experimental studies, and predictive validity in observational studies. We conclude that (i) the validity of variability measures and λS is best supported across all levels, (ii) the maximum Floquet multiplier and λL have good construct validity, but negative predictive validity in models, negative convergent validity and (for λL) negative predictive validity in observational studies, (iii) long-range correlations lack construct validity and predictive validity in models and have negative convergent validity, and (iv) measures derived from perturbation experiments have good construct validity, but data are lacking on convergent validity in experimental studies and predictive validity in observational studies. In closing, directions for future research on dynamic gait stability are discussed. PMID:23516062

Model for forecasting Olea europaea L. airborne pollen in South-West Andalusia, Spain

NASA Astrophysics Data System (ADS)

Galán, C.; Cariñanos, Paloma; García-Mozo, Herminia; Alcázar, Purificación; Domínguez-Vilches, Eugenio

Data on predicted average and maximum airborne pollen concentrations and the dates on which these maximum values are expected are of undoubted value to allergists and allergy sufferers, as well as to agronomists. This paper reports on the development of predictive models for calculating total annual pollen output, on the basis of pollen and weather data compiled over the last 19 years (1982-2000) for Córdoba (Spain). Models were tested in order to predict the 2000 pollen season; in addition, and in view of the heavy rainfall recorded in spring 2000, the 1982-1998 data set was used to test the model for 1999. The results of the multiple regression analysis show that the variables exerting the greatest influence on the pollen index were rainfall in March and temperatures over the months prior to the flowering period. For prediction of maximum values and dates on which these values might be expected, the start of the pollen season was used as an additional independent variable. Temperature proved the best variable for this prediction. Results improved when the 5-day moving average was taken into account. Testing of the predictive model for 1999 and 2000 yielded fairly similar results. In both cases, the difference between expected and observed pollen data was no greater than 10%. However, significant differences were recorded between forecast and expected maximum and minimum values, owing to the influence of rainfall during the flowering period.

Energetic constraints, size gradients, and size limits in benthic marine invertebrates.

PubMed

Sebens, Kenneth P

2002-08-01

Populations of marine benthic organisms occupy habitats with a range of physical and biological characteristics. In the intertidal zone, energetic costs increase with temperature and aerial exposure, and prey intake increases with immersion time, generating size gradients with small individuals often found at upper limits of distribution. Wave action can have similar effects, limiting feeding time or success, although certain species benefit from wave dislodgment of their prey; this also results in gradients of size and morphology. The difference between energy intake and metabolic (and/or behavioral) costs can be used to determine an energetic optimal size for individuals in such populations. Comparisons of the energetic optimal size to the maximum predicted size based on mechanical constraints, and the ensuing mortality schedule, provides a mechanism to study and explain organism size gradients in intertidal and subtidal habitats. For species where the energetic optimal size is well below the maximum size that could persist under a certain set of wave/flow conditions, it is probable that energetic constraints dominate. When the opposite is true, populations of small individuals can dominate habitats with strong dislodgment or damage probability. When the maximum size of individuals is far below either energetic optima or mechanical limits, other sources of mortality (e.g., predation) may favor energy allocation to early reproduction rather than to continued growth. Predictions based on optimal size models have been tested for a variety of intertidal and subtidal invertebrates including sea anemones, corals, and octocorals. This paper provides a review of the optimal size concept, and employs a combination of the optimal energetic size model and life history modeling approach to explore energy allocation to growth or reproduction as the optimal size is approached.

Flow-covariate prediction of stream pesticide concentrations.

PubMed

Mosquin, Paul L; Aldworth, Jeremy; Chen, Wenlin

2018-01-01

Potential peak functions (e.g., maximum rolling averages over a given duration) of annual pesticide concentrations in the aquatic environment are important exposure parameters (or target quantities) for ecological risk assessments. These target quantities require accurate concentration estimates on nonsampled days in a monitoring program. We examined stream flow as a covariate via universal kriging to improve predictions of maximum m-day (m = 1, 7, 14, 30, 60) rolling averages and the 95th percentiles of atrazine concentration in streams where data were collected every 7 or 14 d. The universal kriging predictions were evaluated against the target quantities calculated directly from the daily (or near daily) measured atrazine concentration at 32 sites (89 site-yr) as part of the Atrazine Ecological Monitoring Program in the US corn belt region (2008-2013) and 4 sites (62 site-yr) in Ohio by the National Center for Water Quality Research (1993-2008). Because stream flow data are strongly skewed to the right, 3 transformations of the flow covariate were considered: log transformation, short-term flow anomaly, and normalized Box-Cox transformation. The normalized Box-Cox transformation resulted in predictions of the target quantities that were comparable to those obtained from log-linear interpolation (i.e., linear interpolation on the log scale) for 7-d sampling. However, the predictions appeared to be negatively affected by variability in regression coefficient estimates across different sample realizations of the concentration time series. Therefore, revised models incorporating seasonal covariates and partially or fully constrained regression parameters were investigated, and they were found to provide much improved predictions in comparison with those from log-linear interpolation for all rolling average measures. Environ Toxicol Chem 2018;37:260-273. © 2017 SETAC. © 2017 SETAC.

Optimal Ge/SiGe nanofin geometries for hole mobility enhancement: Technology limit from atomic simulations

NASA Astrophysics Data System (ADS)

Vedula, Ravi Pramod; Mehrotra, Saumitra; Kubis, Tillmann; Povolotskyi, Michael; Klimeck, Gerhard; Strachan, Alejandro

2015-05-01

We use first principles simulations to engineer Ge nanofins for maximum hole mobility by controlling strain tri-axially through nano-patterning. Large-scale molecular dynamics predict fully relaxed, atomic structures for experimentally achievable nanofins, and orthogonal tight binding is used to obtain the corresponding electronic structure. Hole transport properties are then obtained via a linearized Boltzmann formalism. This approach explicitly accounts for free surfaces and associated strain relaxation as well as strain gradients which are critical for quantitative predictions in nanoscale structures. We show that the transverse strain relaxation resulting from the reduction in the aspect ratio of the fins leads to a significant enhancement in phonon limited hole mobility (7× over unstrained, bulk Ge, and 3.5× over biaxially strained Ge). Maximum enhancement is achieved by reducing the width to be approximately 1.5 times the height and further reduction in width does not result in additional gains. These results indicate significant room for improvement over current-generation Ge nanofins, provide geometrical guidelines to design optimized geometries and insight into the physics behind the significant mobility enhancement.

Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data

NASA Astrophysics Data System (ADS)

Pohjoranta, Antti; Halinen, Matias; Pennanen, Jari; Kiviaho, Jari

2015-03-01

Generalized predictive control (GPC) is applied to control the maximum temperature in a solid oxide fuel cell (SOFC) stack and the temperature difference over the stack. GPC is a model predictive control method and the models utilized in this work are ARX-type (autoregressive with extra input), multiple input-multiple output, polynomial models that were identified from experimental data obtained from experiments with a complete SOFC system. The proposed control is evaluated by simulation with various input-output combinations, with and without constraints. A comparison with conventional proportional-integral-derivative (PID) control is also made. It is shown that if only the stack maximum temperature is controlled, a standard PID controller can be used to obtain output performance comparable to that obtained with the significantly more complex model predictive controller. However, in order to control the temperature difference over the stack, both the stack minimum and the maximum temperature need to be controlled and this cannot be done with a single PID controller. In such a case the model predictive controller provides a feasible and effective solution.

Two methods for estimating limits to large-scale wind power generation

PubMed Central

Miller, Lee M.; Brunsell, Nathaniel A.; Mechem, David B.; Gans, Fabian; Monaghan, Andrew J.; Vautard, Robert; Keith, David W.; Kleidon, Axel

2015-01-01

Wind turbines remove kinetic energy from the atmospheric flow, which reduces wind speeds and limits generation rates of large wind farms. These interactions can be approximated using a vertical kinetic energy (VKE) flux method, which predicts that the maximum power generation potential is 26% of the instantaneous downward transport of kinetic energy using the preturbine climatology. We compare the energy flux method to the Weather Research and Forecasting (WRF) regional atmospheric model equipped with a wind turbine parameterization over a 105 km2 region in the central United States. The WRF simulations yield a maximum generation of 1.1 We⋅m−2, whereas the VKE method predicts the time series while underestimating the maximum generation rate by about 50%. Because VKE derives the generation limit from the preturbine climatology, potential changes in the vertical kinetic energy flux from the free atmosphere are not considered. Such changes are important at night when WRF estimates are about twice the VKE value because wind turbines interact with the decoupled nocturnal low-level jet in this region. Daytime estimates agree better to 20% because the wind turbines induce comparatively small changes to the downward kinetic energy flux. This combination of downward transport limits and wind speed reductions explains why large-scale wind power generation in windy regions is limited to about 1 We⋅m−2, with VKE capturing this combination in a comparatively simple way. PMID:26305925

Impact of Threat Level, Task Instruction, and Individual Characteristics on Cold Pressor Pain and Fear among Children and Their Parents.

PubMed

Boerner, Katelynn E; Noel, Melanie; Birnie, Kathryn A; Caes, Line; Petter, Mark; Chambers, Christine T

2016-07-01

The cold pressor task (CPT) is increasingly used to induce experimental pain in children, but the specific methodology of the CPT is quite variable across pediatric studies. This study examined how subtle variations in CPT methodology (eg. provision of low- or high-threat information regarding the task; provision or omission of maximum immersion time) may influence children's and parents' perceptions of the pain experience. Forty-eight children (8 to 14 years) and their parents were randomly assigned to receive information about the CPT that varied on 2 dimensions, prior to completing the task: (i) threat level: high-threat (task described as very painful, high pain expressions depicted) or low-threat (standard CPT instructions provided, low pain expressions depicted); (ii) ceiling: informed (provided maximum immersion time) or uninformed (information about maximum immersion time omitted). Parents and children in the high-threat condition expected greater child pain, and these children reported higher perceived threat of pain and state pain catastrophizing. For children in the low-threat condition, an informed ceiling was associated with less state pain catastrophizing during the CPT. Pain intensity, tolerance, and fear during the CPT did not differ by experimental group, but were predicted by child characteristics. Findings suggest that provision of threatening information may impact anticipatory outcomes, but experienced pain was better explained by individual child variables. © 2015 World Institute of Pain.

Fourier transform spectrometer observations of solar carbon monoxide. III - Time-resolved spectroscopy of the Delta V = 1 bands

NASA Astrophysics Data System (ADS)

Ayres, Thomas R.; Brault, James W.

1990-11-01

Time series of the 2100/cm Delta v = 1 absorption bands of CO at the center of the solar disk and at the extreme limb have been recorded by Fourier transform spectrometer. The photospheric 5-min oscillation appears prominently at sun center. The peak-to-peak brightness temperature amplitude is roughly 300 K, and the peak-to-peak Doppler shift is roughly 1100 m/s. The 70 deg phase lag of maximum core intensity with respect to maximum redshift for the strongest Delta v = 1 absorptions is less than the 90 deg expected in the adiabatic limit. No dominant four-minute signal in the line intensity like that reported by Deming et al. (1984, 1986, and 1987) is found, nor is evidence for extreme fluctuations on short time scales like those proposed by Kalkofen et al. (1984). The strong Delta v = 1 lines exhibit systematic Doppler shifts of less than about 1 km/s, contrary to the predictions of transonic redshifts if the CO 'clouds' are associated with a dynamic cooling phase of the Ca II 'cell flashes.'

A maximum likelihood convolutional decoder model vs experimental data comparison

NASA Technical Reports Server (NTRS)

Chen, R. Y.

1979-01-01

This article describes the comparison of a maximum likelihood convolutional decoder (MCD) prediction model and the actual performance of the MCD at the Madrid Deep Space Station. The MCD prediction model is used to develop a subroutine that has been utilized by the Telemetry Analysis Program (TAP) to compute the MCD bit error rate for a given signal-to-noise ratio. The results indicate that that the TAP can predict quite well compared to the experimental measurements. An optimal modulation index also can be found through TAP.

Expiratory and phonation times as measures of disease severity in patients with Multiple Sclerosis. A case-control study.

PubMed

Nordio, Sara; Bernitsas, Evanthia; Meneghello, Francesca; Palmer, Katie; Stabile, Maria Rosaria; Dipietro, Laura; Di Stadio, Arianna

2018-04-21

Speech disorders are common in patients with Multiple Sclerosis (MS). They can be assessed with several methods, which are however expensive, complex, and not easily accessible to physicians during routine clinic visits. This study aimed at measuring maximum phonation times, maximum expiratory times, and articulation abilities scores in patients with MS compared to healthy subjects and at investigating if any of these parameters could be used as a measure of MS progression. 50 MS patients and 50 gender- and age-matched healthy controls were enrolled in the study. Maximum expiratory times and maximum phonation times were collected from both groups. Articulation abilities were evaluated using the articulation subtest from the Fussi assessment (dysarthria scores). MS patients were evaluated with the Expanded Disability Status Scale (EDSS). Correlations between EDSS scores and maximum expiratory times, maximum phonation times, and dysarthria scores were calculated. EDSS scores of MS patients ranged from 4.5 to 7.5. In MS patients, maximum expiratory times, maximum phonation times, and dysarthria scores were significantly altered compared to healthy controls. Moreover, the EDSS scores were correlated with the maximum expiratory times; the maximum expiratory times were correlated with the maximum phonation times, and the maximum phonation times were correlated with the dysarthria scores. As the expiratory times were significantly correlated with the EDSS scores, they could be used to measure the severity of MS and to monitor its progression. Copyright © 2018 Elsevier B.V. All rights reserved.

Probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty from maximum temperature metric selection.

PubMed

DeWeber, Jefferson T; Wagner, Tyler

2018-06-01

Predictions of the projected changes in species distributions and potential adaptation action benefits can help guide conservation actions. There is substantial uncertainty in projecting species distributions into an unknown future, however, which can undermine confidence in predictions or misdirect conservation actions if not properly considered. Recent studies have shown that the selection of alternative climate metrics describing very different climatic aspects (e.g., mean air temperature vs. mean precipitation) can be a substantial source of projection uncertainty. It is unclear, however, how much projection uncertainty might stem from selecting among highly correlated, ecologically similar climate metrics (e.g., maximum temperature in July, maximum 30-day temperature) describing the same climatic aspect (e.g., maximum temperatures) known to limit a species' distribution. It is also unclear how projection uncertainty might propagate into predictions of the potential benefits of adaptation actions that might lessen climate change effects. We provide probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty stemming from the selection of four maximum temperature metrics for brook trout (Salvelinus fontinalis), a cold-water salmonid of conservation concern in the eastern United States. Projected losses in suitable stream length varied by as much as 20% among alternative maximum temperature metrics for mid-century climate projections, which was similar to variation among three climate models. Similarly, the regional average predicted increase in brook trout occurrence probability under an adaptation action scenario of full riparian forest restoration varied by as much as .2 among metrics. Our use of Bayesian inference provides probabilistic measures of vulnerability and adaptation action benefits for individual stream reaches that properly address statistical uncertainty and can help guide conservation actions. Our study demonstrates that even relatively small differences in the definitions of climate metrics can result in very different projections and reveal high uncertainty in predicted climate change effects. © 2018 John Wiley & Sons Ltd.

Probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty from maximum temperature metric selection

USGS Publications Warehouse

DeWeber, Jefferson T.; Wagner, Tyler

2018-01-01

Predictions of the projected changes in species distributions and potential adaptation action benefits can help guide conservation actions. There is substantial uncertainty in projecting species distributions into an unknown future, however, which can undermine confidence in predictions or misdirect conservation actions if not properly considered. Recent studies have shown that the selection of alternative climate metrics describing very different climatic aspects (e.g., mean air temperature vs. mean precipitation) can be a substantial source of projection uncertainty. It is unclear, however, how much projection uncertainty might stem from selecting among highly correlated, ecologically similar climate metrics (e.g., maximum temperature in July, maximum 30‐day temperature) describing the same climatic aspect (e.g., maximum temperatures) known to limit a species’ distribution. It is also unclear how projection uncertainty might propagate into predictions of the potential benefits of adaptation actions that might lessen climate change effects. We provide probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty stemming from the selection of four maximum temperature metrics for brook trout (Salvelinus fontinalis), a cold‐water salmonid of conservation concern in the eastern United States. Projected losses in suitable stream length varied by as much as 20% among alternative maximum temperature metrics for mid‐century climate projections, which was similar to variation among three climate models. Similarly, the regional average predicted increase in brook trout occurrence probability under an adaptation action scenario of full riparian forest restoration varied by as much as .2 among metrics. Our use of Bayesian inference provides probabilistic measures of vulnerability and adaptation action benefits for individual stream reaches that properly address statistical uncertainty and can help guide conservation actions. Our study demonstrates that even relatively small differences in the definitions of climate metrics can result in very different projections and reveal high uncertainty in predicted climate change effects.

Fusing human and machine skills for remote robotic operations

NASA Technical Reports Server (NTRS)

Schenker, Paul S.; Kim, Won S.; Venema, Steven C.; Bejczy, Antal K.

1991-01-01

The question of how computer assists can improve teleoperator trajectory tracking during both free and force-constrained motions is addressed. Computer graphics techniques which enable the human operator to both visualize and predict detailed 3D trajectories in real-time are reported. Man-machine interactive control procedures for better management of manipulator contact forces and positioning are also described. It is found that collectively, these novel advanced teleoperations techniques both enhance system performance and significantly reduce control problems long associated with teleoperations under time delay. Ongoing robotic simulations of the 1984 space shuttle Solar Maximum EVA Repair Mission are briefly described.

Modulating Effects of Mesoscale Oceanic Eddies on Sea Surface Temperature Response to Tropical Cyclones Over the Western North Pacific

NASA Astrophysics Data System (ADS)

Ma, Zhanhong; Fei, Jianfang; Huang, Xiaogang; Cheng, Xiaoping

2018-01-01

The impact of mesoscale oceanic eddies on the temporal and spatial characteristics of sea surface temperature (SST) response to tropical cyclones is investigated in this study based on composite analysis of cyclone-eddy interactions over the western North Pacific. The occurrence times of maximum cooling, recovery time, and spatial patterns of SST response are specially evaluated. The influence of cold-core eddies (CCEs) renders the mean occurrence time of maximum SST cooling to become about half a day longer than that in eddy-free condition, while warm-core eddies (WCEs) have little effect on this facet. The recovery time of SST cooling also takes longer in presence of CCEs, being overall more pronounced for stronger or slower tropical cyclones. The effect of WCEs on the recovery time is again not significant. The modulation of maximum SST decrease by WCEs for category 2-5 storms is found to be remarkable in the subtropical region but not evident in the tropical region, while the role of CCEs is remarkable in both regions. The CCEs are observed to change the spatial characteristics of SST response, with enhanced SST decrease initially at the right side of storm track. During the recovery period the strengthened SST cooling by CCEs propagates leftward gradually, with a feature similar as both the westward-propagating eddies and the recovery of cold wake. These results underscore the importance of resolving mesoscale oceanic eddies in coupled numerical models to improve the prediction of storm-induced SST response.

Using novel acoustic and visual mapping tools to predict the small-scale spatial distribution of live biogenic reef framework in cold-water coral habitats

NASA Astrophysics Data System (ADS)

De Clippele, L. H.; Gafeira, J.; Robert, K.; Hennige, S.; Lavaleye, M. S.; Duineveld, G. C. A.; Huvenne, V. A. I.; Roberts, J. M.

2017-03-01

Cold-water corals form substantial biogenic habitats on continental shelves and in deep-sea areas with topographic highs, such as banks and seamounts. In the Atlantic, many reef and mound complexes are engineered by Lophelia pertusa, the dominant framework-forming coral. In this study, a variety of mapping approaches were used at a range of scales to map the distribution of both cold-water coral habitats and individual coral colonies at the Mingulay Reef Complex (west Scotland). The new ArcGIS-based British Geological Survey (BGS) seabed mapping toolbox semi-automatically delineated over 500 Lophelia reef `mini-mounds' from bathymetry data with 2-m resolution. The morphometric and acoustic characteristics of the mini-mounds were also automatically quantified and captured using this toolbox. Coral presence data were derived from high-definition remotely operated vehicle (ROV) records and high-resolution microbathymetry collected by a ROV-mounted multibeam echosounder. With a resolution of 0.35 × 0.35 m, the microbathymetry covers 0.6 km2 in the centre of the study area and allowed identification of individual live coral colonies in acoustic data for the first time. Maximum water depth, maximum rugosity, mean rugosity, bathymetric positioning index and maximum current speed were identified as the environmental variables that contributed most to the prediction of live coral presence. These variables were used to create a predictive map of the likelihood of presence of live cold-water coral colonies in the area of the Mingulay Reef Complex covered by the 2-m resolution data set. Predictive maps of live corals across the reef will be especially valuable for future long-term monitoring surveys, including those needed to understand the impacts of global climate change. This is the first study using the newly developed BGS seabed mapping toolbox and an ROV-based microbathymetric grid to explore the environmental variables that control coral growth on cold-water coral reefs.

TH-E-BRF-05: Comparison of Survival-Time Prediction Models After Radiotherapy for High-Grade Glioma Patients Based On Clinical and DVH Features

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

Magome, T; Haga, A; Igaki, H

Purpose: Although many outcome prediction models based on dose-volume information have been proposed, it is well known that the prognosis may be affected also by multiple clinical factors. The purpose of this study is to predict the survival time after radiotherapy for high-grade glioma patients based on features including clinical and dose-volume histogram (DVH) information. Methods: A total of 35 patients with high-grade glioma (oligodendroglioma: 2, anaplastic astrocytoma: 3, glioblastoma: 30) were selected in this study. All patients were treated with prescribed dose of 30–80 Gy after surgical resection or biopsy from 2006 to 2013 at The University of Tokyomore » Hospital. All cases were randomly separated into training dataset (30 cases) and test dataset (5 cases). The survival time after radiotherapy was predicted based on a multiple linear regression analysis and artificial neural network (ANN) by using 204 candidate features. The candidate features included the 12 clinical features (tumor location, extent of surgical resection, treatment duration of radiotherapy, etc.), and the 192 DVH features (maximum dose, minimum dose, D95, V60, etc.). The effective features for the prediction were selected according to a step-wise method by using 30 training cases. The prediction accuracy was evaluated by a coefficient of determination (R{sup 2}) between the predicted and actual survival time for the training and test dataset. Results: In the multiple regression analysis, the value of R{sup 2} between the predicted and actual survival time was 0.460 for the training dataset and 0.375 for the test dataset. On the other hand, in the ANN analysis, the value of R{sup 2} was 0.806 for the training dataset and 0.811 for the test dataset. Conclusion: Although a large number of patients would be needed for more accurate and robust prediction, our preliminary Result showed the potential to predict the outcome in the patients with high-grade glioma. This work was partly supported by the JSPS Core-to-Core Program(No. 23003) and Grant-in-aid from the JSPS Fellows.« less

A Time-Variant Reliability Model for Copper Bending Pipe under Seawater-Active Corrosion Based on the Stochastic Degradation Process

PubMed Central

Li, Mengmeng; Feng, Qiang; Yang, Dezhen

2018-01-01

In the degradation process, the randomness and multiplicity of variables are difficult to describe by mathematical models. However, they are common in engineering and cannot be neglected, so it is necessary to study this issue in depth. In this paper, the copper bending pipe in seawater piping systems is taken as the analysis object, and the time-variant reliability is calculated by solving the interference of limit strength and maximum stress. We did degradation experiments and tensile experiments on copper material, and obtained the limit strength at each time. In addition, degradation experiments on copper bending pipe were done and the thickness at each time has been obtained, then the response of maximum stress was calculated by simulation. Further, with the help of one kind of Monte Carlo method we propose, the time-variant reliability of copper bending pipe was calculated based on the stochastic degradation process and interference theory. Compared with traditional methods and verified by maintenance records, the results show that the time-variant reliability model based on the stochastic degradation process proposed in this paper has better applicability in the reliability analysis, and it can be more convenient and accurate to predict the replacement cycle of copper bending pipe under seawater-active corrosion. PMID:29584695

Hierarchical Star Formation in Turbulent Media: Evidence from Young Star Clusters

NASA Astrophysics Data System (ADS)

Grasha, K.; Elmegreen, B. G.; Calzetti, D.; Adamo, A.; Aloisi, A.; Bright, S. N.; Cook, D. O.; Dale, D. A.; Fumagalli, M.; Gallagher, J. S., III; Gouliermis, D. A.; Grebel, E. K.; Kahre, L.; Kim, H.; Krumholz, M. R.; Lee, J. C.; Messa, M.; Ryon, J. E.; Ubeda, L.

2017-06-01

We present an analysis of the positions and ages of young star clusters in eight local galaxies to investigate the connection between the age difference and separation of cluster pairs. We find that star clusters do not form uniformly but instead are distributed so that the age difference increases with the cluster pair separation to the 0.25-0.6 power, and that the maximum size over which star formation is physically correlated ranges from ˜200 pc to ˜1 kpc. The observed trends between age difference and separation suggest that cluster formation is hierarchical both in space and time: clusters that are close to each other are more similar in age than clusters born further apart. The temporal correlations between stellar aggregates have slopes that are consistent with predictions of turbulence acting as the primary driver of star formation. The velocity associated with the maximum size is proportional to the galaxy’s shear, suggesting that the galactic environment influences the maximum size of the star-forming structures.

Trait Acclimation Mitigates Mortality Risks of Tropical Canopy Trees under Global Warming

PubMed Central

Sterck, Frank; Anten, Niels P. R.; Schieving, Feike; Zuidema, Pieter A.

2016-01-01

There is a heated debate about the effect of global change on tropical forests. Many scientists predict large-scale tree mortality while others point to mitigating roles of CO2 fertilization and – the notoriously unknown – physiological trait acclimation of trees. In this opinion article we provided a first quantification of the potential of trait acclimation to mitigate the negative effects of warming on tropical canopy tree growth and survival. We applied a physiological tree growth model that incorporates trait acclimation through an optimization approach. Our model estimated the maximum effect of acclimation when trees optimize traits that are strongly plastic on a week to annual time scale (leaf photosynthetic capacity, total leaf area, stem sapwood area) to maximize carbon gain. We simulated tree carbon gain for temperatures (25–35°C) and ambient CO2 concentrations (390–800 ppm) predicted for the 21st century. Full trait acclimation increased simulated carbon gain by up to 10–20% and the maximum tolerated temperature by up to 2°C, thus reducing risks of tree death under predicted warming. Functional trait acclimation may thus increase the resilience of tropical trees to warming, but cannot prevent tree death during extremely hot and dry years at current CO2 levels. We call for incorporating trait acclimation in field and experimental studies of plant functional traits, and in models that predict responses of tropical forests to climate change. PMID:27242814

A mobile-mobile transport model for simulating reactive transport in connected heterogeneous fields

NASA Astrophysics Data System (ADS)

Lu, Chunhui; Wang, Zhiyuan; Zhao, Yue; Rathore, Saubhagya Singh; Huo, Jinge; Tang, Yuening; Liu, Ming; Gong, Rulan; Cirpka, Olaf A.; Luo, Jian

2018-05-01

Mobile-immobile transport models can be effective in reproducing heavily tailed breakthrough curves of concentration. However, such models may not adequately describe transport along multiple flow paths with intermediate velocity contrasts in connected fields. We propose using the mobile-mobile model for simulating subsurface flow and associated mixing-controlled reactive transport in connected fields. This model includes two local concentrations, one in the fast- and the other in the slow-flow domain, which predict both the concentration mean and variance. The normalized total concentration variance within the flux is found to be a non-monotonic function of the discharge ratio with a maximum concentration variance at intermediate values of the discharge ratio. We test the mobile-mobile model for mixing-controlled reactive transport with an instantaneous, irreversible bimolecular reaction in structured and connected random heterogeneous domains, and compare the performance of the mobile-mobile to the mobile-immobile model. The results indicate that the mobile-mobile model generally predicts the concentration breakthrough curves (BTCs) of the reactive compound better. Particularly, for cases of an elliptical inclusion with intermediate hydraulic-conductivity contrasts, where the travel-time distribution shows bimodal behavior, the prediction of both the BTCs and maximum product concentration is significantly improved. Our results exemplify that the conceptual model of two mobile domains with diffusive mass transfer in between is in general good for predicting mixing-controlled reactive transport, and particularly so in cases where the transfer in the low-conductivity zones is by slow advection rather than diffusion.

A catchment-scale model to predict spatial and temporal burden of E. coli on pasture from grazing livestock.

PubMed

Oliver, David M; Bartie, Phil J; Louise Heathwaite, A; Reaney, Sim M; Parnell, Jared A Q; Quilliam, Richard S

2018-03-01

Effective management of diffuse microbial water pollution from agriculture requires a fundamental understanding of how spatial patterns of microbial pollutants, e.g. E. coli, vary over time at the landscape scale. The aim of this study was to apply the Visualising Pathogen &Environmental Risk (ViPER) model, developed to predict E. coli burden on agricultural land, in a spatially distributed manner to two contrasting catchments in order to map and understand changes in E. coli burden contributed to land from grazing livestock. The model was applied to the River Ayr and Lunan Water catchments, with significant correlations observed between area of improved grassland and the maximum total E. coli per 1km 2 grid cell (Ayr: r=0.57; p<0.001, Lunan: r=0.32; p<0.001). There was a significant difference in the predicted maximum E. coli burden between seasons in both catchments, with summer and autumn predicted to accrue higher E. coli contributions relative to spring and winter (P<0.001), driven largely by livestock presence. The ViPER model thus describes, at the landscape scale, spatial nuances in the vulnerability of E. coli loading to land as driven by stocking density and livestock grazing regimes. Resulting risk maps therefore provide the underpinning evidence to inform spatially-targeted decision-making with respect to managing sources of E. coli in agricultural environments. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

On the level of skill in predicting maximum sunspot number - A comparative study of single variate and bivariate precursor techniques

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

1990-01-01

The level of skill in predicting the size of the sunspot cycle is investigated for the two types of precursor techniques, single variate and bivariate fits, both applied to cycle 22. The present level of growth in solar activity is compared to the mean level of growth (cycles 10-21) and to the predictions based on the precursor techniques. It is shown that, for cycle 22, both single variate methods (based on geomagnetic data) and bivariate methods suggest a maximum amplitude smaller than that observed for cycle 19, and possibly for cycle 21. Compared to the mean cycle, cycle 22 is presently behaving as if it were a +2.6 sigma cycle (maximum amplitude of about 225), which means that either it will be the first cycle not to be reliably predicted by the combined precursor techniques or its deviation relative to the mean cycle will substantially decrease over the next 18 months.

An Estimate of the Size and Shape of Sunspot Cycle 24 Based on its Early Cycle Behavior using the Hathaway-Wilson-Reichmann Shape-Fitting Function

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

2011-01-01

On the basis of 12-month moving averages (12-mma) of monthly mean sunspot number (R), sunspot cycle 24 had its minimum amplitude (Rm = 1.7) in December 2008. At 12 mo past minimum, R measured 8.3, and at 18 mo past minimum, it measured 16.4. Thus far, the maximum month-to-month rate of rise in 12-mma values of monthly mean sunspot number (AR(t) max) has been 1.7, having occurred at elapsed times past minimum amplitude (t) of 14 and 15 mo. Compared to other sunspot cycles of the modern era, cycle 24?s Rm and AR(t) max (as observed so far) are the smallest on record, suggesting that it likely will be a slow-rising, long-period sunspot cycle of below average maximum amplitude (RM). Supporting this view is the now observed relative strength of cycle 24?s geomagnetic minimum amplitude as measured using the 12-mma value of the aa-geomagnetic index (aam = 8.4), which also is the smallest on record, having occurred at t equals 8 and 9 mo. From the method of Ohl (the inferred preferential association between RM and aam), one predicts RM = 55 +/- 17 (the ?1 se prediction interval) for cycle 24. Furthermore, from the Waldmeier effect (the inferred preferential association between the ascent duration (ASC) and RM) one predicts an ASC longer than 48 mo for cycle 24; hence, maximum amplitude occurrence should be after December 2012. Application of the Hathaway-Wilson-Reichmann shape-fitting function, using an RM = 70 and ASC = 56 mo, is found to adequately fit the early sunspot number growth of cycle 24.

Anatomical and neuromuscular variables strongly predict maximum knee extension torque in healthy men.

PubMed

Trezise, J; Collier, N; Blazevich, A J

2016-06-01

This study examined the relative influence of anatomical and neuromuscular variables on maximal isometric and concentric knee extensor torque and provided a comparative dataset for healthy young males. Quadriceps cross-sectional area (CSA) and fascicle length (l f) and angle (θ f) from the four quadriceps components; agonist (EMG:M) and antagonist muscle activity, and percent voluntary activation (%VA); patellar tendon moment arm distance (MA) and maximal voluntary isometric and concentric (60° s(-1)) torques, were measured in 56 men. Linear regression models predicting maximum torque were ranked using Akaike's Information Criterion (AICc), and Pearson's correlation coefficients assessed relationships between variables. The best-fit models explained up to 72 % of the variance in maximal voluntary knee extension torque. The combination of 'CSA + θ f + EMG:M + %VA' best predicted maximum isometric torque (R (2) = 72 %, AICc weight = 0.38) and 'CSA + θ f + MA' (R (2) = 65 %, AICc weight = 0.21) best predicted maximum concentric torque. Proximal quadriceps CSA was included in all models rather than the traditionally used mid-muscle CSA. Fascicle angle appeared consistently in all models despite its weak correlation with maximum torque in isolation, emphasising the importance of examining interactions among variables. While muscle activity was important for torque prediction in both contraction modes, MA only strongly influenced maximal concentric torque. These models identify the main sources of inter-individual differences strongly influencing maximal knee extension torque production in healthy men. The comparative dataset allows the identification of potential variables to target (i.e. weaknesses) in individuals.

Regression modeling and prediction of road sweeping brush load characteristics from finite element analysis and experimental results.

PubMed

Wang, Chong; Sun, Qun; Wahab, Magd Abdel; Zhang, Xingyu; Xu, Limin

2015-09-01

Rotary cup brushes mounted on each side of a road sweeper undertake heavy debris removal tasks but the characteristics have not been well known until recently. A Finite Element (FE) model that can analyze brush deformation and predict brush characteristics have been developed to investigate the sweeping efficiency and to assist the controller design. However, the FE model requires large amount of CPU time to simulate each brush design and operating scenario, which may affect its applications in a real-time system. This study develops a mathematical regression model to summarize the FE modeled results. The complex brush load characteristic curves were statistically analyzed to quantify the effects of cross-section, length, mounting angle, displacement and rotational speed etc. The data were then fitted by a multiple variable regression model using the maximum likelihood method. The fitted results showed good agreement with the FE analysis results and experimental results, suggesting that the mathematical regression model may be directly used in a real-time system to predict characteristics of different brushes under varying operating conditions. The methodology may also be used in the design and optimization of rotary brush tools. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Guo, Yi; Keller, Jonathan; Zhang, Zhiwei

The planetary load sharing characteristics of wind turbine gearboxes supported by cylindrical roller bearings (CRBs) and preloaded tapered roller bearings (TRBs) when subjected to rotor moments are compared in this work. Planetary bearing loads were measured in field-representative dynamometer tests and compared to loads predicted by finite-element models. Load sharing was significantly improved with preloaded TRBs. In pure torque conditions, the upwind planet bearing loads in the gearbox with preloaded TRBs were a maximum of 1.14 compared to 1.47 in the gearbox with CRBs. Consequently, the predicted fatigue life of the complete set of planetary bearings for the gearbox withmore » preloaded TRBs is 3.5 times greater than that of the gearbox with CRBs.« less

Cumulative slant path rain attenuation associated with COMSTAR beacon at 28.56 GHz for Wallops Island, Virginia

NASA Technical Reports Server (NTRS)

Goldhirsh, J.

1978-01-01

Yearly, monthly, and time of day fade statistics are presented and characterized. A 19.04 GHz yearly fade distribution, corresponding to a second COMSTAR beacon frequency, is predicted using the concept of effective path length, disdrometer, and rain rate results. The yearly attenuation and rain rate distributions follow with good approximation log normal variations for most fade and rain rate levels. Attenuations were exceeded for the longest and shortest periods of times for all fades in August and February, respectively. The eight hour time period showing the maximum and minimum number of minutes over the year for which fades exceeded 12 db were approximately between 1600 to 2400, and 0400 to 1200 hours, respectively. In employing the predictive method for obtaining the 19.04 GHz fade distribution, it is demonstrated theoretically that the ratio of attenuations at two frequencies is minimally dependent of raindrop size distribution providing these frequencies are not widely separated.

QuickVina: accelerating AutoDock Vina using gradient-based heuristics for global optimization.

PubMed

Handoko, Stephanus Daniel; Ouyang, Xuchang; Su, Chinh Tran To; Kwoh, Chee Keong; Ong, Yew Soon

2012-01-01

Predicting binding between macromolecule and small molecule is a crucial phase in the field of rational drug design. AutoDock Vina, one of the most widely used docking software released in 2009, uses an empirical scoring function to evaluate the binding affinity between the molecules and employs the iterated local search global optimizer for global optimization, achieving a significantly improved speed and better accuracy of the binding mode prediction compared its predecessor, AutoDock 4. In this paper, we propose further improvement in the local search algorithm of Vina by heuristically preventing some intermediate points from undergoing local search. Our improved version of Vina-dubbed QVina-achieved a maximum acceleration of about 25 times with the average speed-up of 8.34 times compared to the original Vina when tested on a set of 231 protein-ligand complexes while maintaining the optimal scores mostly identical. Using our heuristics, larger number of different ligands can be quickly screened against a given receptor within the same time frame.

Ups and Downs in the Ocean: Effects of Biofouling on Vertical Transport of Microplastics.

PubMed

Kooi, Merel; Nes, Egbert H van; Scheffer, Marten; Koelmans, Albert A

2017-07-18

Recent studies suggest size-selective removal of small plastic particles from the ocean surface, an observation that remains unexplained. We studied one of the hypotheses regarding this size-selective removal: the formation of a biofilm on the microplastics (biofouling). We developed the first theoretical model that is capable of simulating the effect of biofouling on the fate of microplastic. The model is based on settling, biofilm growth, and ocean depth profiles for light, water density, temperature, salinity, and viscosity. Using realistic parameters, the model simulates the vertical transport of small microplastic particles over time, and predicts that the particles either float, sink to the ocean floor, or oscillate vertically, depending on the size and density of the particle. The predicted size-dependent vertical movement of microplastic particles results in a maximum concentration at intermediate depths. Consequently, relatively low abundances of small particles are predicted at the ocean surface, while at the same time these small particles may never reach the ocean floor. Our results hint at the fate of "lost" plastic in the ocean, and provide a start for predicting risks of exposure to microplastics for potentially vulnerable species living at these depths.

CFD-RANS prediction of individual exposure from continuous release of hazardous airborne materials in complex urban environments

NASA Astrophysics Data System (ADS)

Efthimiou, G. C.; Andronopoulos, S.; Bartzis, J. G.; Berbekar, E.; Harms, F.; Leitl, B.

2017-02-01

One of the key issues of recent research on the dispersion inside complex urban environments is the ability to predict individual exposure (maximum dosages) of an airborne material which is released continuously from a point source. The present work addresses the question whether the computational fluid dynamics (CFD)-Reynolds-averaged Navier-Stokes (RANS) methodology can be used to predict individual exposure for various exposure times. This is feasible by providing the two RANS concentration moments (mean and variance) and a turbulent time scale to a deterministic model. The whole effort is focused on the prediction of individual exposure inside a complex real urban area. The capabilities of the proposed methodology are validated against wind-tunnel data (CUTE experiment). The present simulations were performed 'blindly', i.e. the modeller had limited information for the inlet boundary conditions and the results were kept unknown until the end of the COST Action ES1006. Thus, a high uncertainty of the results was expected. The general performance of the methodology due to this 'blind' strategy is good. The validation metrics fulfil the acceptance criteria. The effect of the grid and the turbulence model on the model performance is examined.

Prediction of reinforcement corrosion using corrosion induced cracks width in corroded reinforced concrete beams

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

Khan, Inamullah; François, Raoul; Castel, Arnaud

2014-02-15

This paper studies the evolution of reinforcement corrosion in comparison to corrosion crack width in a highly corroded reinforced concrete beam. Cracking and corrosion maps of the beam were drawn and steel reinforcement was recovered from the beam to observe the corrosion pattern and to measure the loss of mass of steel reinforcement. Maximum steel cross-section loss of the main reinforcement and average steel cross-section loss between stirrups were plotted against the crack width. The experimental results were compared with existing models proposed by Rodriguez et al., Vidal et al. and Zhang et al. Time prediction models for a givenmore » opening threshold are also compared to experimental results. Steel cross-section loss for stirrups was also measured and was plotted against the crack width. It was observed that steel cross-section loss in the stirrups had no relationship with the crack width of longitudinal corrosion cracks. -- Highlights: •Relationship between crack and corrosion of reinforcement was investigated. •Corrosion results of natural process and then corresponds to in-situ conditions. •Comparison with time predicting model is provided. •Prediction of load-bearing capacity from crack pattern was studied.« less

Predicting Drug-Target Interaction Networks Based on Functional Groups and Biological Features

PubMed Central

Shi, Xiao-He; Hu, Le-Le; Kong, Xiangyin; Cai, Yu-Dong; Chou, Kuo-Chen

2010-01-01

Background Study of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner. Methods/Principal Findings To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively. Conclusion/Significance Our results indicate that the network prediction system thus established is quite promising and encouraging. PMID:20300175

Risk-Seeking Versus Risk-Avoiding Investments in Noisy Periodic Environments

NASA Astrophysics Data System (ADS)

Navarro-Barrientos, J. Emeterio; Walter, Frank E.; Schweitzer, Frank

We study the performance of various agent strategies in an artificial investment scenario. Agents are equipped with a budget, x(t), and at each time step invest a particular fraction, q(t), of their budget. The return on investment (RoI), r(t), is characterized by a periodic function with different types and levels of noise. Risk-avoiding agents choose their fraction q(t) proportional to the expected positive RoI, while risk-seeking agents always choose a maximum value qmax if they predict the RoI to be positive ("everything on red"). In addition to these different strategies, agents have different capabilities to predict the future r(t), dependent on their internal complexity. Here, we compare "zero-intelligent" agents using technical analysis (such as moving least squares) with agents using reinforcement learning or genetic algorithms to predict r(t). The performance of agents is measured by their average budget growth after a certain number of time steps. We present results of extensive computer simulations, which show that, for our given artificial environment, (i) the risk-seeking strategy outperforms the risk-avoiding one, and (ii) the genetic algorithm was able to find this optimal strategy itself, and thus outperforms other prediction approaches considered.

Prediction of transmission distortion for wireless video communication: analysis.

PubMed

Chen, Zhifeng; Wu, Dapeng

2012-03-01

Transmitting video over wireless is a challenging problem since video may be seriously distorted due to packet errors caused by wireless channels. The capability of predicting transmission distortion (i.e., video distortion caused by packet errors) can assist in designing video encoding and transmission schemes that achieve maximum video quality or minimum end-to-end video distortion. This paper is aimed at deriving formulas for predicting transmission distortion. The contribution of this paper is twofold. First, we identify the governing law that describes how the transmission distortion process evolves over time and analytically derive the transmission distortion formula as a closed-form function of video frame statistics, channel error statistics, and system parameters. Second, we identify, for the first time, two important properties of transmission distortion. The first property is that the clipping noise, which is produced by nonlinear clipping, causes decay of propagated error. The second property is that the correlation between motion-vector concealment error and propagated error is negative and has dominant impact on transmission distortion, compared with other correlations. Due to these two properties and elegant error/distortion decomposition, our formula provides not only more accurate prediction but also lower complexity than the existing methods.

Acidic processing of hemicellulosic saccharides from pine wood: product distribution and kinetic modeling.

PubMed

Rivas, Sandra; González-Muñoz, María Jesús; Santos, Valentín; Parajó, Juan Carlos

2014-06-01

Water soluble compounds were removed from Pinus pinaster wood by a mild aqueous extraction, and the treated wood was subjected to hydrothermal processing to convert most hemicelluloses into soluble saccharides (including low molecular weight polymers, oligomers and monosaccharides). The liquid phase containing hemicellulose-derived saccharides was acidified with sulfuric acid and heated up to 130-250°C to obtain furans and levulinic acid as major products. The concentration profiles of the major compounds participating in the reactions were interpreted by a kinetic model. A maximum conversion of pentoses into furfural near 80% was predicted at high temperature and short time, conditions leading to 24% conversion of hexoses into HMF. Production of levulinic acid was favored at low temperatures. Maximum molar conversion of hexoses into levulinic acid (66.7% at 130°C) needed a long reaction time (235 h). A value of 53.0% can be achieved at 170°C after 5 h. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

Maze, Grace M.

STREAM II is the aqueous transport model of the Weather Information Display (WIND) emergency response system at Savannah River Site. It is used to calculate transport in the event of a chemical or radiological spill into the waterways on the Savannah River Site. Improvements were made to the code (STREAM II V7) to include flow from all site tributaries to the Savannah River total flow and utilize a 4 digit year input. The predicted downstream concentrations using V7 were generally on the same order of magnitude as V6 with slightly lower concentrations and quicker arrival times when all onsite streammore » flows are contributing to the Savannah River flow. The downstream arrival time at the Savannah River Water Plant ranges from no change to an increase of 8.77%, with minimum changes typically in March/April and maximum changes typically in October/November. The downstream concentrations are generally no more than 15% lower using V7 with the maximum percent change in January through April and minimum changes in June/July.« less

An Improved Model Predictive Current Controller of Switched Reluctance Machines Using Time-Multiplexed Current Sensor

PubMed Central

Li, Bingchu; Ling, Xiao; Huang, Yixiang; Gong, Liang; Liu, Chengliang

2017-01-01

This paper presents a fixed-switching-frequency model predictive current controller using multiplexed current sensor for switched reluctance machine (SRM) drives. The converter was modified to distinguish currents from simultaneously excited phases during the sampling period. The only current sensor installed in the converter was time division multiplexing for phase current sampling. During the commutation stage, the control steps of adjacent phases were shifted so that sampling time was staggered. The maximum and minimum duty ratio of pulse width modulation (PWM) was limited to keep enough sampling time for analog-to-digital (A/D) conversion. Current sensor multiplexing was realized without complex adjustment of either driver circuit nor control algorithms, while it helps to reduce the cost and errors introduced in current sampling due to inconsistency between sensors. The proposed controller is validated by both simulation and experimental results with a 1.5 kW three-phase 12/8 SRM. Satisfied current sampling is received with little difference compared with independent phase current sensors for each phase. The proposed controller tracks the reference current profile as accurately as the model predictive current controller with independent phase current sensors, while having minor tracking errors compared with a hysteresis current controller. PMID:28513554

Evaluation of Model Performance over the Maritime Continent

NASA Astrophysics Data System (ADS)

Reynolds, C. A.; Barton, N. P.; Chen, S.; Flatau, M. K.; Ridout, J. A.; Janiga, M.; Jensen, T.; Richman, J. G.; Metzger, E. J.; Baranowski, D.

2017-12-01

The introduction of high-resolution global coupled models holds promise for extended-range (subseasonal to seasonal) prediction of high-impact weather. While forecast models have shown considerable improvement in the prediction of tropical phenomena on these timescales, specifically in the simulation and prediction of the Madden-Julian Oscillation (MJO), obstacles remain. In particular, many models still have difficulty accurately simulating the propagation of the MJO over the maritime continent. This has been hypothesized, at least in part, to be related to deficiencies in simulating the diurnal cycle over this region, which in turn is dependent on accurate representation of fine-scale atmosphere-ocean-land interactions, orography, and atmospheric convection. These issues have motivated the international Year of Maritime Continent (YMC) effort and the Office of Naval Research Propagation of Intra-Seasonal Tropical Oscillations (PISTON) initiative. In preparation for YMC and PISTON, we closely evaluate the performance of the Navy Earth System Model (NESM), a coupled global forecast model, in representing the diurnal cycle and other prominent phenomena in the maritime continent region. NESM performance is compared with stand-alone atmospheric simulations with prescribed fixed and analyzed sea surface temperatures (SSTs). Initial results from the Dynamics of the Madden-Julian Oscillation field phase (Fall 2011) period indicate that NESM is able to capture the precipitation day-time maximum over land and night-time maximum over ocean, but day-time precipitation over Borneo, Sumatra and the Malay Peninsula is too strong as compared to TRMM observations. The simulation of low-level winds qualitatively captures sea and land breeze patterns as compared with ERA-Interim analysis, with quantitative biases varying by island. The fully-coupled system and the stand-alone atmospheric model simulations are more similar to each other than to the observations, indicating that active ocean coupling is not the most prominent issue contributing to biases in these simulations. The performance of NESM will be more thoroughly evaluated and compared to other forecast systems using the 45-day forecasts currently being produced four times per week for the 1999-2015 time period under the NOAA SubX project.

Predicting protein β-sheet contacts using a maximum entropy-based correlated mutation measure.

PubMed

Burkoff, Nikolas S; Várnai, Csilla; Wild, David L

2013-03-01

The problem of ab initio protein folding is one of the most difficult in modern computational biology. The prediction of residue contacts within a protein provides a more tractable immediate step. Recently introduced maximum entropy-based correlated mutation measures (CMMs), such as direct information, have been successful in predicting residue contacts. However, most correlated mutation studies focus on proteins that have large good-quality multiple sequence alignments (MSA) because the power of correlated mutation analysis falls as the size of the MSA decreases. However, even with small autogenerated MSAs, maximum entropy-based CMMs contain information. To make use of this information, in this article, we focus not on general residue contacts but contacts between residues in β-sheets. The strong constraints and prior knowledge associated with β-contacts are ideally suited for prediction using a method that incorporates an often noisy CMM. Using contrastive divergence, a statistical machine learning technique, we have calculated a maximum entropy-based CMM. We have integrated this measure with a new probabilistic model for β-contact prediction, which is used to predict both residue- and strand-level contacts. Using our model on a standard non-redundant dataset, we significantly outperform a 2D recurrent neural network architecture, achieving a 5% improvement in true positives at the 5% false-positive rate at the residue level. At the strand level, our approach is competitive with the state-of-the-art single methods achieving precision of 61.0% and recall of 55.4%, while not requiring residue solvent accessibility as an input. http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/

Hydrogen production econometric studies. [hydrogen and fossil fuels

NASA Technical Reports Server (NTRS)

Howell, J. R.; Bannerot, R. B.

1975-01-01

The current assessments of fossil fuel resources in the United States were examined, and predictions of the maximum and minimum lifetimes of recoverable resources according to these assessments are presented. In addition, current rates of production in quads/year for the fossil fuels were determined from the literature. Where possible, costs of energy, location of reserves, and remaining time before these reserves are exhausted are given. Limitations that appear to hinder complete development of each energy source are outlined.

Prediction of Response to Neoadjuvant Chemotherapy and Radiation Therapy with Baseline and Restaging 18F-FDG PET Imaging Biomarkers in Patients with Esophageal Cancer.

PubMed

Beukinga, Roelof J; Hulshoff, Jan Binne; Mul, Véronique E M; Noordzij, Walter; Kats-Ugurlu, Gursah; Slart, Riemer H J A; Plukker, John T M

2018-06-01

Purpose To assess the value of baseline and restaging fluorine 18 ( 18 F) fluorodeoxyglucose (FDG) positron emission tomography (PET) radiomics in predicting pathologic complete response to neoadjuvant chemotherapy and radiation therapy (NCRT) in patients with locally advanced esophageal cancer. Materials and Methods In this retrospective study, 73 patients with histologic analysis-confirmed T1/N1-3/M0 or T2-4a/N0-3/M0 esophageal cancer were treated with NCRT followed by surgery (Chemoradiotherapy for Esophageal Cancer followed by Surgery Study regimen) between October 2014 and August 2017. Clinical variables and radiomic features from baseline and restaging 18 F-FDG PET were selected by univariable logistic regression and least absolute shrinkage and selection operator. The selected variables were used to fit a multivariable logistic regression model, which was internally validated by using bootstrap resampling with 20 000 replicates. The performance of this model was compared with reference prediction models composed of maximum standardized uptake value metrics, clinical variables, and maximum standardized uptake value at baseline NCRT radiomic features. Outcome was defined as complete versus incomplete pathologic response (tumor regression grade 1 vs 2-5 according to the Mandard classification). Results Pathologic response was complete in 16 patients (21.9%) and incomplete in 57 patients (78.1%). A prediction model combining clinical T-stage and restaging NCRT (post-NCRT) joint maximum (quantifying image orderliness) yielded an optimism-corrected area under the receiver operating characteristics curve of 0.81. Post-NCRT joint maximum was replaceable with five other redundant post-NCRT radiomic features that provided equal model performance. All reference prediction models exhibited substantially lower discriminatory accuracy. Conclusion The combination of clinical T-staging and quantitative assessment of post-NCRT 18 F-FDG PET orderliness (joint maximum) provided high discriminatory accuracy in predicting pathologic complete response in patients with esophageal cancer. © RSNA, 2018 Online supplemental material is available for this article.

Stereoselective Inhibition of CYP2C19 and CYP3A4 by Fluoxetine and Its Metabolite: Implications for Risk Assessment of Multiple Time-Dependent Inhibitor Systems

PubMed Central

Lutz, Justin D.; VandenBrink, Brooke M.; Babu, Katipudi N.; Nelson, Wendel L.; Kunze, Kent L.

2013-01-01

Recent guidance on drug-drug interaction (DDI) testing recommends evaluation of circulating metabolites. However, there is little consensus on how to quantitatively predict and/or assess the risk of in vivo DDIs by multiple time-dependent inhibitors (TDIs) including metabolites from in vitro data. Fluoxetine was chosen as the model drug to evaluate the role of TDI metabolites in DDI prediction because it is a TDI of both CYP3A4 and CYP2C19 with a circulating N-dealkylated inhibitory metabolite, norfluoxetine. In pooled human liver microsomes, both enantiomers of fluoxetine and norfluoxetine were TDIs of CYP2C19, (S)-norfluoxetine was the most potent inhibitor with time-dependent inhibition affinity constant (KI) of 7 μM, and apparent maximum time-dependent inhibition rate (kinact,app) of 0.059 min−1. Only (S)-fluoxetine and (R)-norfluoxetine were TDIs of CYP3A4, with (R)-norfluoxetine being the most potent (KI = 8 μM, and kinact,app = 0.011 min−1). Based on in-vitro-to-in-vivo predictions, (S)-norfluoxetine plays the most important role in in vivo CYP2C19 DDIs, whereas (R)-norfluoxetine is most important in CYP3A4 DDIs. Comparison of two multiple TDI prediction models demonstrated significant differences between them in in-vitro-to-in-vitro predictions but not in in-vitro-to-in-vivo predictions. Inclusion of all four inhibitors predicted an in vivo decrease in CYP2C19 (95%) and CYP3A4 (60–62%) activity. The results of this study suggest that adequate worst-case risk assessment for in vivo DDIs by multiple TDI systems can be achieved by incorporating time-dependent inhibition by both parent and metabolite via simple addition of the in vivo time-dependent inhibition rate/cytochrome P450 degradation rate constant (λ/kdeg) values, but quantitative DDI predictions will require a more thorough understanding of TDI mechanisms. PMID:23785064

Statistical validation of a solar wind propagation model from 1 to 10 AU

NASA Astrophysics Data System (ADS)

Zieger, Bertalan; Hansen, Kenneth C.

2008-08-01

A one-dimensional (1-D) numerical magnetohydrodynamic (MHD) code is applied to propagate the solar wind from 1 AU through 10 AU, i.e., beyond the heliocentric distance of Saturn's orbit, in a non-rotating frame of reference. The time-varying boundary conditions at 1 AU are obtained from hourly solar wind data observed near the Earth. Although similar MHD simulations have been carried out and used by several authors, very little work has been done to validate the statistical accuracy of such solar wind predictions. In this paper, we present an extensive analysis of the prediction efficiency, using 12 selected years of solar wind data from the major heliospheric missions Pioneer, Voyager, and Ulysses. We map the numerical solution to each spacecraft in space and time, and validate the simulation, comparing the propagated solar wind parameters with in-situ observations. We do not restrict our statistical analysis to the times of spacecraft alignment, as most of the earlier case studies do. Our superposed epoch analysis suggests that the prediction efficiency is significantly higher during periods with high recurrence index of solar wind speed, typically in the late declining phase of the solar cycle. Among the solar wind variables, the solar wind speed can be predicted to the highest accuracy, with a linear correlation of 0.75 on average close to the time of opposition. We estimate the accuracy of shock arrival times to be as high as 10-15 hours within ±75 d from apparent opposition during years with high recurrence index. During solar activity maximum, there is a clear bias for the model to predicted shocks arriving later than observed in the data, suggesting that during these periods, there is an additional acceleration mechanism in the solar wind that is not included in the model.

Approximate method for predicting the permanent set in a beam in vacuo and in water subject to a shock wave

NASA Technical Reports Server (NTRS)

Stiehl, A. L.; Haberman, R. C.; Cowles, J. H.

1988-01-01

An approximate method to compute the maximum deformation and permanent set of a beam subjected to shock wave laoding in vacuo and in water was investigated. The method equates the maximum kinetic energy of the beam (and water) to the elastic plastic work done by a static uniform load applied to a beam. Results for the water case indicate that the plastic deformation is controlled by the kinetic energy of the water. The simplified approach can result in significant savings in computer time or it can expediently be used as a check of results from a more rigorous approach. The accuracy of the method is demonstrated by various examples of beams with simple support and clamped support boundary conditions.

Prediction of solar energetic particle event histories using real-time particle and solar wind measurements

NASA Technical Reports Server (NTRS)

Roelof, E. C.; Gold, R. E.

1978-01-01

The comparatively well-ordered magnetic structure in the solar corona during the decline of Solar Cycle 20 revealed a characteristic dependence of solar energetic particle injection upon heliographic longitude. When analyzed using solar wind mapping of the large scale interplanetary magnetic field line connection from the corona to the Earth, particle fluxes display an approximately exponential dependence on heliographic longitude. Since variations in the solar wind velocity (and hence the coronal connection longitude) can severely distort the simple coronal injection profile, the use of real-time solar wind velocity measurements can be of great aid in predicting the decay of solar particle events. Although such exponential injection profiles are commonplace during 1973-1975, they have also been identified earlier in Solar Cycle 20, and hence this structure may be present during the rise and maximum of the cycle, but somewhat obscured by greater temporal variations in particle injection.

Excel-Based Tool for Pharmacokinetically Guided Dose Adjustment of Paclitaxel.

PubMed

Kraff, Stefanie; Lindauer, Andreas; Joerger, Markus; Salamone, Salvatore J; Jaehde, Ulrich

2015-12-01

Neutropenia is a frequent and severe adverse event in patients receiving paclitaxel chemotherapy. The time above a paclitaxel threshold concentration of 0.05 μmol/L (Tc > 0.05 μmol/L) is a strong predictor for paclitaxel-associated neutropenia and has been proposed as a target pharmacokinetic (PK) parameter for paclitaxel therapeutic drug monitoring and dose adaptation. Up to now, individual Tc > 0.05 μmol/L values are estimated based on a published PK model of paclitaxel by using the software NONMEM. Because many clinicians are not familiar with the use of NONMEM, an Excel-based dosing tool was developed to allow calculation of paclitaxel Tc > 0.05 μmol/L and give clinicians an easy-to-use tool. Population PK parameters of paclitaxel were taken from a published PK model. An Alglib VBA code was implemented in Excel 2007 to compute differential equations for the paclitaxel PK model. Maximum a posteriori Bayesian estimates of the PK parameters were determined with the Excel Solver using individual drug concentrations. Concentrations from 250 patients were simulated receiving 1 cycle of paclitaxel chemotherapy. Predictions of paclitaxel Tc > 0.05 μmol/L as calculated by the Excel tool were compared with NONMEM, whereby maximum a posteriori Bayesian estimates were obtained using the POSTHOC function. There was a good concordance and comparable predictive performance between Excel and NONMEM regarding predicted paclitaxel plasma concentrations and Tc > 0.05 μmol/L values. Tc > 0.05 μmol/L had a maximum bias of 3% and an error on precision of <12%. The median relative deviation of the estimated Tc > 0.05 μmol/L values between both programs was 1%. The Excel-based tool can estimate the time above a paclitaxel threshold concentration of 0.05 μmol/L with acceptable accuracy and precision. The presented Excel tool allows reliable calculation of paclitaxel Tc > 0.05 μmol/L and thus allows target concentration intervention to improve the benefit-risk ratio of the drug. The easy use facilitates therapeutic drug monitoring in clinical routine.

Domain wall formation in late-time phase transitions

NASA Technical Reports Server (NTRS)

Kolb, Edward W.; Wang, Yun

1992-01-01

We examine domain wall formulation in late time phase transitions. We find that in the invisible axion domain wall phenomenon, thermal effects alone are insufficient to drive different parts of the disconnected vacuum manifold. This suggests that domain walls do not form unless either there is some supplemental (but perhaps not unreasonable) dynamics to localize the scalar field responsible for the phase transition to the low temperature maximum (to an extraordinary precision) before the onset of the phase transition, or there is some non-thermal mechanism to produce large fluctuations in the scalar field. The fact that domain wall production is not a robust prediction of late time transitions may suggest future directions in model building.

Integrating paleoecology and genetics of bird populations in two sky island archipelagos

PubMed Central

McCormack, John E; Bowen, Bonnie S; Smith, Thomas B

2008-01-01

Background Genetic tests of paleoecological hypotheses have been rare, partly because recent genetic divergence is difficult to detect and time. According to fossil plant data, continuous woodland in the southwestern USA and northern Mexico became fragmented during the last 10,000 years, as warming caused cool-adapted species to retreat to high elevations. Most genetic studies of resulting 'sky islands' have either failed to detect recent divergence or have found discordant evidence for ancient divergence. We test this paleoecological hypothesis for the region with intraspecific mitochondrial DNA and microsatellite data from sky-island populations of a sedentary bird, the Mexican jay (Aphelocoma ultramarina). We predicted that populations on different sky islands would share common, ancestral alleles that existed during the last glaciation, but that populations on each sky island, owing to their isolation, would contain unique variants of postglacial origin. We also predicted that divergence times estimated from corrected genetic distance and a coalescence model would post-date the last glacial maximum. Results Our results provide multiple independent lines of support for postglacial divergence, with the predicted pattern of shared and unique mitochondrial DNA haplotypes appearing in two independent sky-island archipelagos, and most estimates of divergence time based on corrected genetic distance post-dating the last glacial maximum. Likewise, an isolation model based on multilocus gene coalescence indicated postglacial divergence of five pairs of sky islands. In contrast to their similar recent histories, the two archipelagos had dissimilar historical patterns in that sky islands in Arizona showed evidence for older divergence, suggesting different responses to the last glaciation. Conclusion This study is one of the first to provide explicit support from genetic data for a postglacial divergence scenario predicted by one of the best paleoecological records in the world. Our results demonstrate that sky islands act as generators of genetic diversity at both recent and historical timescales and underscore the importance of thorough sampling and the use of loci with fast mutation rates to studies that test hypotheses concerning recent genetic divergence. PMID:18588695

Effect of Caffeine on near Maximal Blood Pressure and Blood Pressure Recovery in Physically-Active, College-Aged Females

PubMed Central

CONNAHAN, LAURA E.; OTT, CHRISTOPHER A.; BARRY, VAUGHN W.

2017-01-01

The purpose of this study is to determine how caffeine affects exercise blood pressure (BP) and active and passive recovery BP after vigorous intensity exercise in physically active college-aged females. Fifteen physically active, ACSM stratified low-risk females (age (y): 23.53 ± 4.07, weight (kg): 60.34 ± 3.67, height (cm): 165.14 ± 7.20, BMI (kg/m2): 22.18 ± 1.55) participated in two Bruce protocol exercise tests. Before each test participants consumed 1) a placebo or 2) 3.3 mg·kg−1 of caffeine at least one hour before exercise in a counterbalanced double-blinded fashion. After reaching 85% of their age-predicted maximum heart rate, BP was taken and participants began an active (i.e. walking) recovery phase for 6 minutes followed by a passive (i.e. sitting) recovery phase. BP was assessed every two minutes in each phase. Recovery times were assessed until active and passive BP equaled 20 mmHg and 10 mmHg above resting, respectively. Participants completed each test 1–2 weeks a part. Maximal systolic and diastolic blood pressures were not significantly different between the two trials. Active recovery, passive recovery, and total recovery times were all significantly longer during the caffeine trial than the placebo trial. Furthermore, the time to reach age-predicted maximum heart rate was significantly shorter in the placebo trial than the caffeine trial. While caffeine consumption did not significantly affect maximal blood pressure, it did affect active and passive recovery time following vigorous intensity exercise in physically active females. Exercise endurance also improved after consuming caffeine in this population. PMID:28344739

Effect of Caffeine on near Maximal Blood Pressure and Blood Pressure Recovery in Physically-Active, College-Aged Females.

PubMed

Connahan, Laura E; Ott, Christopher A; Barry, Vaughn W

2017-01-01

The purpose of this study is to determine how caffeine affects exercise blood pressure (BP) and active and passive recovery BP after vigorous intensity exercise in physically active college-aged females. Fifteen physically active, ACSM stratified low-risk females (age (y): 23.53 ± 4.07, weight (kg): 60.34 ± 3.67, height (cm): 165.14 ± 7.20, BMI (kg/m 2 ): 22.18 ± 1.55) participated in two Bruce protocol exercise tests. Before each test participants consumed 1) a placebo or 2) 3.3 mg·kg -1 of caffeine at least one hour before exercise in a counterbalanced double-blinded fashion. After reaching 85% of their age-predicted maximum heart rate, BP was taken and participants began an active (i.e. walking) recovery phase for 6 minutes followed by a passive (i.e. sitting) recovery phase. BP was assessed every two minutes in each phase. Recovery times were assessed until active and passive BP equaled 20 mmHg and 10 mmHg above resting, respectively. Participants completed each test 1-2 weeks a part. Maximal systolic and diastolic blood pressures were not significantly different between the two trials. Active recovery, passive recovery, and total recovery times were all significantly longer during the caffeine trial than the placebo trial. Furthermore, the time to reach age-predicted maximum heart rate was significantly shorter in the placebo trial than the caffeine trial. While caffeine consumption did not significantly affect maximal blood pressure, it did affect active and passive recovery time following vigorous intensity exercise in physically active females. Exercise endurance also improved after consuming caffeine in this population.

A simple phenomenological model for grain clustering in turbulence

NASA Astrophysics Data System (ADS)

Hopkins, Philip F.

2016-01-01

We propose a simple model for density fluctuations of aerodynamic grains, embedded in a turbulent, gravitating gas disc. The model combines a calculation for the behaviour of a group of grains encountering a single turbulent eddy, with a hierarchical approximation of the eddy statistics. This makes analytic predictions for a range of quantities including: distributions of grain densities, power spectra and correlation functions of fluctuations, and maximum grain densities reached. We predict how these scale as a function of grain drag time ts, spatial scale, grain-to-gas mass ratio tilde{ρ }, strength of turbulence α, and detailed disc properties. We test these against numerical simulations with various turbulence-driving mechanisms. The simulations agree well with the predictions, spanning ts Ω ˜ 10-4-10, tilde{ρ }˜ 0{-}3, α ˜ 10-10-10-2. Results from `turbulent concentration' simulations and laboratory experiments are also predicted as a special case. Vortices on a wide range of scales disperse and concentrate grains hierarchically. For small grains this is most efficient in eddies with turnover time comparable to the stopping time, but fluctuations are also damped by local gas-grain drift. For large grains, shear and gravity lead to a much broader range of eddy scales driving fluctuations, with most power on the largest scales. The grain density distribution has a log-Poisson shape, with fluctuations for large grains up to factors ≳1000. We provide simple analytic expressions for the predictions, and discuss implications for planetesimal formation, grain growth, and the structure of turbulence.

Predicting clicks of PubMed articles.

PubMed

Mao, Yuqing; Lu, Zhiyong

2013-01-01

Predicting the popularity or access usage of an article has the potential to improve the quality of PubMed searches. We can model the click trend of each article as its access changes over time by mining the PubMed query logs, which contain the previous access history for all articles. In this article, we examine the access patterns produced by PubMed users in two years (July 2009 to July 2011). We explore the time series of accesses for each article in the query logs, model the trends with regression approaches, and subsequently use the models for prediction. We show that the click trends of PubMed articles are best fitted with a log-normal regression model. This model allows the number of accesses an article receives and the time since it first becomes available in PubMed to be related via quadratic and logistic functions, with the model parameters to be estimated via maximum likelihood. Our experiments predicting the number of accesses for an article based on its past usage demonstrate that the mean absolute error and mean absolute percentage error of our model are 4.0% and 8.1% lower than the power-law regression model, respectively. The log-normal distribution is also shown to perform significantly better than a previous prediction method based on a human memory theory in cognitive science. This work warrants further investigation on the utility of such a log-normal regression approach towards improving information access in PubMed.

Predicting clicks of PubMed articles

PubMed Central

Mao, Yuqing; Lu, Zhiyong

2013-01-01

Predicting the popularity or access usage of an article has the potential to improve the quality of PubMed searches. We can model the click trend of each article as its access changes over time by mining the PubMed query logs, which contain the previous access history for all articles. In this article, we examine the access patterns produced by PubMed users in two years (July 2009 to July 2011). We explore the time series of accesses for each article in the query logs, model the trends with regression approaches, and subsequently use the models for prediction. We show that the click trends of PubMed articles are best fitted with a log-normal regression model. This model allows the number of accesses an article receives and the time since it first becomes available in PubMed to be related via quadratic and logistic functions, with the model parameters to be estimated via maximum likelihood. Our experiments predicting the number of accesses for an article based on its past usage demonstrate that the mean absolute error and mean absolute percentage error of our model are 4.0% and 8.1% lower than the power-law regression model, respectively. The log-normal distribution is also shown to perform significantly better than a previous prediction method based on a human memory theory in cognitive science. This work warrants further investigation on the utility of such a log-normal regression approach towards improving information access in PubMed. PMID:24551386

Time-resolved contrast-enhanced MR angiography of the thorax in adults with congenital heart disease.

PubMed

Mohrs, Oliver K; Petersen, Steffen E; Voigtlaender, Thomas; Peters, Jutta; Nowak, Bernd; Heinemann, Markus K; Kauczor, Hans-Ulrich

2006-10-01

The aim of this study was to evaluate the diagnostic value of time-resolved contrast-enhanced MR angiography in adults with congenital heart disease. Twenty patients with congenital heart disease (mean age, 38 +/- 14 years; range, 16-73 years) underwent contrast-enhanced turbo fast low-angle shot MR angiography. Thirty consecutive coronal 3D slabs with a frame rate of 1-second duration were acquired. The mask defined as the first data set was subtracted from subsequent images. Image quality was evaluated using a 5-point scale (from 1, not assessable, to 5, excellent image quality). Twelve diagnostic parameters yielded 1 point each in case of correct diagnosis (binary analysis into normal or abnormal) and were summarized into three categories: anatomy of the main thoracic vessels (maximum, 5 points), sequential cardiac anatomy (maximum, 5 points), and shunt detection (maximum, 2 points). The results were compared with a combined clinical reference comprising medical or surgical reports and other imaging studies. Diagnostic accuracies were calculated for each of the parameters as well as for the three categories. The mean image quality was 3.7 +/- 1.0. Using a binary approach, 220 (92%) of the 240 single diagnostic parameters could be analyzed. The percentage of maximum diagnostic points, the sensitivity, the specificity, and the positive and the negative predictive values were all 100% for the anatomy of the main thoracic vessels; 97%, 87%, 100%, 100%, and 96% for sequential cardiac anatomy; and 93%, 93%, 92%, 88%, and 96% for shunt detection. Time-resolved contrast-enhanced MR angiography provides, in one breath-hold, anatomic and qualitative functional information in adult patients with congenital heart disease. The high diagnostic accuracy allows the investigator to tailor subsequent specific MR sequences within the same session.

Scaling for turbulent viscosity of buoyant plumes in stratified fluids: PIV measurement with implications for submarine hydrothermal plume turbulence

NASA Astrophysics Data System (ADS)

Zhang, Wei; He, Zhiguo; Jiang, Houshuo

2017-11-01

Time-resolved particle image velocimetry (PIV) has been used to measure instantaneous two-dimensional velocity vector fields of laboratory-generated turbulent buoyant plumes in linearly stratified saltwater over extended periods of time. From PIV-measured time-series flow data, characteristics of plume mean flow and turbulence have been quantified. To be specific, maximum plume penetration scaling and entrainment coefficient determined from the mean flow agree well with the theory based on the entrainment hypothesis for buoyant plumes in stratified fluids. Besides the well-known persistent entrainment along the plume stem (i.e., the 'plume-stem' entrainment), the mean plume velocity field shows persistent entrainment along the outer edge of the plume cap (i.e., the 'plume-cap' entrainment), thereby confirming predictions from previous numerical simulation studies. To our knowledge, the present PIV investigation provides the first measured flow field data in the plume cap region. As to measured plume turbulence, both the turbulent kinetic energy field and the turbulence dissipation rate field attain their maximum close to the source, while the turbulent viscosity field reaches its maximum within the plume cap region; the results also show that maximum turbulent viscosity scales as νt,max = 0.030(B/N)1/2, where B is source buoyancy flux and N is ambient buoyancy frequency. These PIV data combined with previously published numerical simulation results have implications for understanding the roles of hydrothermal plume turbulence, i.e. plume turbulence within the cap region causes the 'plume-cap' entrainment that plays an equally important role as the 'plume-stem' entrainment in supplying the final volume flux at the plume spreading level.

Wind directions predicted from global circulation models and wind directions determined from eolian sandstones of the western United States-A comparison

USGS Publications Warehouse

Parrish, Judith T.; Peterson, F.

1988-01-01

Wind directions for Middle Pennsylvanian through Jurassic time are predicted from global circulation models for the western United States. These predictions are compared with paleowind directions interpreted from eolian sandstones of Middle Pennsylvanian through Jurassic age. Predicted regional wind directions correspond with at least three-quarters of the paleowind data from the sandstones; the rest of the data may indicate problems with correlation, local effects of paleogeography on winds, and lack of resolution of the circulation models. The data and predictions suggest the following paleoclimatic developments through the time interval studied: predominance of winter subtropical high-pressure circulation in the Late Pennsylvanian; predominance of summer subtropical high-pressure circulation in the Permian; predominance of summer monsoonal circulation in the Triassic and earliest Jurassic; and, during the remainder of the Jurassic, influence of both summer subtropical and summer monsoonal circulation, with the boundary between the two systems over the western United States. This sequence of climatic changes is largely owing to paleogeographic changes, which influenced the buildup and breakdown of the monsoonal circulation, and possibly owing partly to a decrease in the global temperature gradient, which might have lessened the influence of the subtropical high-pressure circulation. The atypical humidity of Triassic time probably resulted from the monsoonal circulation created by the geography of Pangaea. This circulation is predicted to have been at a maximum in the Triassic and was likely to have been powerful enough to draw moisture along the equator from the ocean to the west. ?? 1988.

A Maximum Muscle Strength Prediction Formula Using Theoretical Grade 3 Muscle Strength Value in Daniels et al.'s Manual Muscle Test, in Consideration of Age: An Investigation of Hip and Knee Joint Flexion and Extension.

PubMed

Usa, Hideyuki; Matsumura, Masashi; Ichikawa, Kazuna; Takei, Hitoshi

2017-01-01

This study attempted to develop a formula for predicting maximum muscle strength value for young, middle-aged, and elderly adults using theoretical Grade 3 muscle strength value (moment fair: M f )-the static muscular moment to support a limb segment against gravity-from the manual muscle test by Daniels et al. A total of 130 healthy Japanese individuals divided by age group performed isometric muscle contractions at maximum effort for various movements of hip joint flexion and extension and knee joint flexion and extension, and the accompanying resisting force was measured and maximum muscle strength value (moment max, M m ) was calculated. Body weight and limb segment length (thigh and lower leg length) were measured, and M f was calculated using anthropometric measures and theoretical calculation. There was a linear correlation between M f and M m in each of the four movement types in all groups, excepting knee flexion in elderly. However, the formula for predicting maximum muscle strength was not sufficiently compatible in middle-aged and elderly adults, suggesting that the formula obtained in this study is applicable in young adults only.

Observed and Predicted Pier Scour in Maine

USGS Publications Warehouse

Hodgkins, Glenn A.; Lombard, Pamela J.

2002-01-01

Pier-scour and related data were collected and analyzed for nine high river flows at eight bridges across Maine from 1997 through 2001. Six bridges had multiple piers. Fifteen of 23 piers where data were measured during a high flow had observed maximum scour depths ranging from 0.5 feet (ft) to 12.0 ft. No pier scour was observed at the remaining eight piers. The maximum predicted pier-scour depths associated with the 23 piers were computed using the equations in the Federal Highway Administration's Hydraulic Engineering Circular number 18 (HEC-18), with data collected for this study. The predicted HEC-18 maximum pier-scour depths were compared to the observed maximum pier-scour depths. The HEC-18 pier-scour equations are intended to be envelope equations, ideally never underpredicting scour depths and not appreciably overpredicting them. The HEC-18 pier-scour equations performed well for rivers in Maine. Twenty-two out of 23 pier-scour depths were overpredicted by 0.7 ft to 18.3 ft. One pier-scour depth was underpredicted by 4.5 ft. For one pier at each of two bridges, large amounts of debris lodged on the piers after high-flow measurements were made at those sites. The scour associated with the debris increased the maximum pier-scour depths by about 5 ft in each case.

A Maximum Muscle Strength Prediction Formula Using Theoretical Grade 3 Muscle Strength Value in Daniels et al.'s Manual Muscle Test, in Consideration of Age: An Investigation of Hip and Knee Joint Flexion and Extension

PubMed Central

Matsumura, Masashi; Ichikawa, Kazuna; Takei, Hitoshi

2017-01-01

This study attempted to develop a formula for predicting maximum muscle strength value for young, middle-aged, and elderly adults using theoretical Grade 3 muscle strength value (moment fair: Mf)—the static muscular moment to support a limb segment against gravity—from the manual muscle test by Daniels et al. A total of 130 healthy Japanese individuals divided by age group performed isometric muscle contractions at maximum effort for various movements of hip joint flexion and extension and knee joint flexion and extension, and the accompanying resisting force was measured and maximum muscle strength value (moment max, Mm) was calculated. Body weight and limb segment length (thigh and lower leg length) were measured, and Mf was calculated using anthropometric measures and theoretical calculation. There was a linear correlation between Mf and Mm in each of the four movement types in all groups, excepting knee flexion in elderly. However, the formula for predicting maximum muscle strength was not sufficiently compatible in middle-aged and elderly adults, suggesting that the formula obtained in this study is applicable in young adults only. PMID:28133549

Comparative analysis of the numerical methods for estimation of predictability time of NEAs motion. (Russian Title: Сравнительный анализ численных методов оценивания времени предсказуемости движения АСЗ)

NASA Astrophysics Data System (ADS)

Bykova, L. E.; Galushina, T. Yu.; Razdymakhina, O. N.

2011-07-01

The paper presents the results of comparative analysis of different algorithms for determination of predictability time of Near-Earth asteroids (NEAs) motion. Three algorithms have been considered: shadow path method, variation method, MEGNO-analysis, where the characteristic of dynamic chaos is the time-weighted integral quantity of maximum characteristic Lyapunov exponent. The developed algorithms and software complex has been applied to identify the chaotic motion of some NEAs. It is shown that MEGNO-analysis allows enough accurately separate regular and chaotic motion of asteroids in a relatively short time intervals.

A root-mean-square approach for predicting fatigue crack growth under random loading

NASA Technical Reports Server (NTRS)

Hudson, C. M.

1981-01-01

A method for predicting fatigue crack growth under random loading which employs the concept of Barsom (1976) is presented. In accordance with this method, the loading history for each specimen is analyzed to determine the root-mean-square maximum and minimum stresses, and the predictions are made by assuming the tests have been conducted under constant-amplitude loading at the root-mean-square maximum and minimum levels. The procedure requires a simple computer program and a desk-top computer. For the eleven predictions made, the ratios of the predicted lives to the test lives ranged from 2.13 to 0.82, which is a good result, considering that the normal scatter in the fatigue-crack-growth rates may range from a factor of two to four under identical loading conditions.

Cold formability prediction by the modified maximum force criterion with a non-associated Hill48 model accounting for anisotropic hardening

NASA Astrophysics Data System (ADS)

Lian, J.; Ahn, D. C.; Chae, D. C.; Münstermann, S.; Bleck, W.

2016-08-01

Experimental and numerical investigations on the characterisation and prediction of cold formability of a ferritic steel sheet are performed in this study. Tensile tests and Nakajima tests were performed for the plasticity characterisation and the forming limit diagram determination. In the numerical prediction, the modified maximum force criterion is selected as the localisation criterion. For the plasticity model, a non-associated formulation of the Hill48 model is employed. With the non-associated flow rule, the model can result in a similar predictive capability of stress and r-value directionality to the advanced non-quadratic associated models. To accurately characterise the anisotropy evolution during hardening, the anisotropic hardening is also calibrated and implemented into the model for the prediction of the formability.

Estimating the time for dissolution of spent fuel exposed to unlimited water

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

Leider, H.R.; Nguyen, S.N.; Stout, R.B.

1991-12-01

The release of radionuclides from spent fuel cannot be precisely predicted at this point because a satisfactory dissolution model based on specific chemical processes is not yet available. However, preliminary results on the dissolution rate of UO{sub 2} and spent fuel as a function of temperature and water composition have recently been reported. This information, together with data on fragment size distribution of spent fuel, are used to estimate the dissolution response of spent fuel in excess flowing water within the framework of a simple model. In this model, the reaction/dissolution front advances linearly with time and geometry is preserved.more » This also estimates the dissolution rate of the bulk of the fission products and higher actinides, which are uniformly distributed in the UO{sub 2} matrix and are presumed to dissolve congruently. We have used a fuel fragment distribution actually observed to calculate the time for total dissolution of spent fuel. A worst-case estimate was also made using the initial (maximum) rate of dissolution to predict the total dissolution time. The time for total dissolution of centimeter size particles is estimated to be 5.5 {times} 10{sup 4} years at 25{degrees}C.« less

Late-Time Evolution of Broad-Bandwidth, Laser-Imposed Nonuniformities in Accelerated Foils

NASA Astrophysics Data System (ADS)

Smalyuk, V. A.; Boehly, T. R.; Bradley, D. K.; Knauer, J. P.; Meyerhofer, D. D.; Oron, D.; Srebro, Y.; Shvarts, D.

1998-11-01

The late-time evolution of broad-bandwidth nonuniformities is studied in planar-foil experiments on the OMEGA laser system. Five beams with ~600-μm-diam uniform region accelerate 20-μm-thick CH foils at an average intensity of 2×10^14\\:W/cm^2 in a 3-ns square pulse. Growth of perturbations seeded by irradiation nonuniformities was observed using time-gated, pinhole photographs of ~1.2-keV x rays from a backlighter. At late times collective saturation is observed at levels similar to Haan's prediction.(S. W. Haan, Phys. Rev. A 39), 5812 (1989). The maximum of the nonuniformity spectrum moves toward longer wavelength in time as expected. Target images taken at different times show the formation of bubbles and spikes from initial elongated ``wormy'' structures. This work was supported by the U.S. Department of Energy Office of Inertial Confinement Fusion under Cooperative Agreement No. DE-FC03-92SF19460, the University of Rochester, and the New York State Energy Research and Development Authority. The support of DOE does not constitute an endorsement by DOE of the views expressed in this article.

Experimental investigation of the Peregrine Breather of gravity waves on finite water depth

NASA Astrophysics Data System (ADS)

Dong, G.; Liao, B.; Ma, Y.; Perlin, M.

2018-06-01

A series of laboratory experiments were performed to study the Peregrine Breather (PB) evolution in a wave flume of finite depth and deep water. Experimental cases were selected with water depths k0h (k0 is the wave number and h is the water depth) varying from 3.11 to 8.17 and initial steepness k0a0 (a0 is the background wave amplitude) in the range 0.06 to 0.12, and the corresponding initial Ursell number in the range 0.03 to 0.061. Experimental results indicate that the water depth plays an important role in the formation of the extreme waves in finite depth; the maximum wave amplification of the PB packets is also strongly dependent on the initial Ursell number. For experimental cases with the initial Ursell number larger than 0.05, the maximum crest amplification can exceed three. If the initial Ursell number is nearly 0.05, a shorter propagation distance is needed for maximum amplification of the height in deeper water. A time-frequency analysis using the wavelet transform reveals that the energy of the higher harmonics is almost in-phase with the carrier wave. The contribution of the higher harmonics to the extreme wave is significant for the cases with initial Ursell number larger than 0.05 in water depth k0h < 5.0. Additionally, the experimental results are compared with computations based on both the nonlinear Schrödinger (NLS) equation and the Dysthe equation, both with a dissipation term. It is found that both models with a dissipation term can predict the maximum amplitude amplification of the primary waves. However, the Dysthe equation also can predict the group horizontal asymmetry.

An evaluation of the effect of recent temperature variability on the prediction of coral bleaching events.

PubMed

Donner, Simon D

2011-07-01

Over the past 30 years, warm thermal disturbances have become commonplace on coral reefs worldwide. These periods of anomalous sea surface temperature (SST) can lead to coral bleaching, a breakdown of the symbiosis between the host coral and symbiotic dinoflagellates which reside in coral tissue. The onset of bleaching is typically predicted to occur when the SST exceeds a local climatological maximum by 1 degrees C for a month or more. However, recent evidence suggests that the threshold at which bleaching occurs may depend on thermal history. This study uses global SST data sets (HadISST and NOAA AVHRR) and mass coral bleaching reports (from Reefbase) to examine the effect of historical SST variability on the accuracy of bleaching prediction. Two variability-based bleaching prediction methods are developed from global analysis of seasonal and interannual SST variability. The first method employs a local bleaching threshold derived from the historical variability in maximum annual SST to account for spatial variability in past thermal disturbance frequency. The second method uses a different formula to estimate the local climatological maximum to account for the low seasonality of SST in the tropics. The new prediction methods are tested against the common globally fixed threshold method using the observed bleaching reports. The results find that estimating the bleaching threshold from local historical SST variability delivers the highest predictive power, but also a higher rate of Type I errors. The second method has the lowest predictive power globally, though regional analysis suggests that it may be applicable in equatorial regions. The historical data analysis suggests that the bleaching threshold may have appeared to be constant globally because the magnitude of interannual variability in maximum SST is similar for many of the world's coral reef ecosystems. For example, the results show that a SST anomaly of 1 degrees C is equivalent to 1.73-2.94 standard deviations of the maximum monthly SST for two-thirds of the world's coral reefs. Coral reefs in the few regions that experience anomalously high interannual SST variability like the equatorial Pacific could prove critical to understanding how coral communities acclimate or adapt to frequent and/or severe thermal disturbances.

Extracting Maximum Total Water Levels from Video "Brightest" Images

NASA Astrophysics Data System (ADS)

Brown, J. A.; Holman, R. A.; Stockdon, H. F.; Plant, N. G.; Long, J.; Brodie, K.

2016-02-01

An important parameter for predicting storm-induced coastal change is the maximum total water level (TWL). Most studies estimate the TWL as the sum of slowly varying water levels, including tides and storm surge, and the extreme runup parameter R2%, which includes wave setup and swash motions over minutes to seconds. Typically, R2% is measured using video remote sensing data, where cross-shore timestacks of pixel intensity are digitized to extract the horizontal runup timeseries. However, this technique must be repeated at multiple alongshore locations to resolve alongshore variability, and can be tedious and time consuming. We seek an efficient, video-based approach that yields a synoptic estimate of TWL that accounts for alongshore variability and can be applied during storms. In this work, the use of a video product termed the "brightest" image is tested; this represents the highest intensity of each pixel captured during a 10-minute collection period. Image filtering and edge detection techniques are applied to automatically determine the shoreward edge of the brightest region (i.e., the swash zone) at each alongshore pixel. The edge represents the horizontal position of the maximum TWL along the beach during the collection period, and is converted to vertical elevations using measured beach topography. This technique is evaluated using video and topographic data collected every half-hour at Duck, NC, during differing hydrodynamic conditions. Relationships between the maximum TWL estimates from the brightest images and various runup statistics computed using concurrent runup timestacks are examined, and errors associated with mapping the horizontal results to elevations are discussed. This technique is invaluable, as it can be used to routinely estimate maximum TWLs along a coastline from a single brightest image product, and provides a means for examining alongshore variability of TWLs at high alongshore resolution. These advantages will be useful in validating numerical hydrodynamic models and improving coastal change predictions.

Participant-Predicted, Observed, and Calculated Peak Blood Alcohol Levels: A Gender-Specific Analysis

PubMed Central

Van Tassel, W.E.; Manser, M.P.

2000-01-01

In recent years there has been a push by federal and state governments to lower the maximum blood alcohol level at which drivers are considered intoxicated. Many states have lowered the maximum blood alcohol level to .08%. This paper offers insight into drinkers’ ability to predict their level of impairment prior to consuming a given amount of alcohol. It addresses the problem of drinkers not knowing how many drinks they can consume before becoming legally impaired. Results indicate males and females differ in their ability to predict impairment levels. PMID:11558094

Development and application of an empirical probability distribution for the prediction error of re-entry body maximum dynamic pressure

NASA Technical Reports Server (NTRS)

Lanzi, R. James; Vincent, Brett T.

1993-01-01

The relationship between actual and predicted re-entry maximum dynamic pressure is characterized using a probability density function and a cumulative distribution function derived from sounding rocket flight data. This paper explores the properties of this distribution and demonstrates applications of this data with observed sounding rocket re-entry body damage characteristics to assess probabilities of sustaining various levels of heating damage. The results from this paper effectively bridge the gap existing in sounding rocket reentry analysis between the known damage level/flight environment relationships and the predicted flight environment.

Cosmic Ray Hysteresis as Evidence for Time-dependent Diffusive Processes in the Long Term Solar Modulation

NASA Technical Reports Server (NTRS)

Ogallagher, J. J.

1973-01-01

A simple one-dimensional time-dependent diffusion-convection model for the modulation of cosmic rays is presented. This model predicts that the observed intensity at a given time is approximately equal to the intensity given by the time independent diffusion convection solution under interplanetary conditions which existed a time iota in the past, (U(t sub o) = U sub s(t sub o - tau)) where iota is the average time spent by a particle inside the modulating cavity. Delay times in excess of several hundred days are possible with reasonable modulation parameters. Interpretation of phase lags observed during the 1969 to 1970 solar maximum in terms of this model suggests that the modulating region is probably not less than 10 a.u. and maybe as much as 35 a.u. in extent.

A toy model that predicts the qualitative role of bar bend in a push jerk.

PubMed

Santos, Aaron; Meltzer, Norman E

2009-11-01

In this work, we describe a simple coarse-grained model of a barbell that can be used to determine the qualitative role of bar bend during a jerk. In simulations of this model, we observed a narrow time window during which the lifter can leverage the elasticity of the bar in order to lift the weight to a maximal height. This time window shifted to later times as the weight was increased. In addition, we found that the optimal time to initiate the drive was strongly correlated with the time at which the bar had reached a maximum upward velocity after recoiling. By isolating the effect of the bar, we obtained a generalized strategy for lifting heavy weight in the jerk.

SN~2012cg: Evidence for Interaction Between a Normal Type Ia Supernova and a Non-degenerate Binary Companion

NASA Astrophysics Data System (ADS)

Marion, G. H.; Brown, Peter J.; Vinkó, Jozsef; Silverman, Jeffrey M.; Sand, David J.; Challis, Peter; Kirshner, Robert P.; Wheeler, J. Craig; Berlind, Perry; Brown, Warren R.; Calkins, Michael L.; Camacho, Yssavo; Dhungana, Govinda; Foley, Ryan J.; Friedman, Andrew S.; Graham, Melissa L.; Howell, D. Andrew; Hsiao, Eric Y.; Irwin, Jonathan M.; Jha, Saurabh W.; Kehoe, Robert; Macri, Lucas M.; Maeda, Keiichi; Mandel, Kaisey; McCully, Curtis; Pandya, Viraj; Rines, Kenneth J.; Wilhelmy, Steven; Zheng, Weikang

2016-04-01

We report evidence for excess blue light from the Type Ia supernova (Sn Ia) SN 2012cg at 15 and 16 days before maximum B-band brightness. The emission is consistent with predictions for the impact of the supernova on a non-degenerate binary companion. This is the first evidence for emission from a companion to a normal SN Ia. Sixteen days before maximum light, the B-V color of SN 2012cg is 0.2 mag bluer than for other normal SN Ia. At later times, this supernova has a typical SN Ia light curve, with extinction-corrected {M}B=-19.62+/- 0.02 mag and {{Δ }}{m}15(B)=0.86+/- 0.02. Our data set is extensive, with photometry in seven filters from five independent sources. Early spectra also show the effects of blue light, and high-velocity features are observed at early times. Near maximum, the spectra are normal with a silicon velocity vSi = -10,500 km s-1. Comparing the early data with models by Kasen favors a main-sequence companion of about six solar masses. It is possible that many other SN Ia have main-sequence companions that have eluded detection because the emission from the impact is fleeting and faint.

Continuous protein concentration via free-flow moving reaction boundary electrophoresis.

PubMed

Kong, Fanzhi; Zhang, Min; Chen, Jingjing; Fan, Liuyin; Xiao, Hua; Liu, Shaorong; Cao, Chengxi

2017-07-28

In this work, we developed the model and theory of free-flow moving reaction boundary electrophoresis (FFMRB) for continuous protein concentration for the first time. The theoretical results indicated that (i) the moving reaction boundary (MRB) can be quantitatively designed in free-flow electrophoresis (FFE) system; (ii) charge-to-mass ratio (Z/M) analysis could provide guidance for protein concentration optimization; and (iii) the maximum processing capacity could be predicted. To demonstrate the model and theory, three model proteins of hemoglobin (Hb), cytochrome C (Cyt C) and C-phycocyanin (C-PC) were chosen for the experiments. The experimental results verified that (i) stable MRBs with different velocities could be established in FFE apparatus with weak acid/weak base neutralization reaction system; (ii) proteins of Hb, Cyt C and C-PC were well concentrated with FFMRB; and (iii) a maximum processing capacity and recovery ratio of Cyt C enrichment were 126mL/h and 95.5% respectively, and a maximum enrichment factor was achieved 12.6 times for Hb. All of the experiments demonstrated the protein concentration model and theory. In contrast to other methods, the continuous processing ability enables FFMRB to efficiently enrich diluted protein or peptide in large volume solution. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact of landfill liner time-temperature history on the service life of HDPE geomembranes.

PubMed

Rowe, R Kerry; Islam, M Z

2009-10-01

The observed temperatures in different landfills are used to establish a number of idealized time-temperature histories for geomembrane liners in municipal solid waste (MSW) landfills. These are then used for estimating the service life of different HDPE geomembranes. The predicted antioxidant depletion times (Stage I) are between 7 and 750 years with the large variation depending on the specific HDPE geomembrane product, exposure conditions, and most importantly, the magnitude and duration of the peak liner temperature. The higher end of the range corresponds to data from geomembranes aged in simulated landfill liner tests and a maximum liner temperature of 37 degrees C. The lower end of the range corresponds to a testing condition where geomembranes were immersed in a synthetic leachate and a maximum liner temperature of 60 degrees C. The total service life of the geomembranes was estimated to be between 20 and 3300 years depending on the time-temperature history examined. The range illustrates the important role that time-temperature history could play in terms of geomembrane service life. The need for long-term monitoring of landfill liner temperature and for geomembrane ageing studies that will provide improved data for assessing the likely long-term performance of geomembranes in MSW landfills are highlighted.

Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Felice, Matteo De; Catalano, Franco; Lee, June-Yi; Wang, Bin; Lee, Doo Young; Yoo, Jin-Ho; Weisheimer, Antije

2018-04-01

Multi-model ensembles (MMEs) are powerful tools in dynamical climate prediction as they account for the overconfidence and the uncertainties related to single-model ensembles. Previous works suggested that the potential benefit that can be expected by using a MME amplifies with the increase of the independence of the contributing Seasonal Prediction Systems. In this work we combine the two MME Seasonal Prediction Systems (SPSs) independently developed by the European (ENSEMBLES) and by the Asian-Pacific (APCC/CliPAS) communities. To this aim, all the possible multi-model combinations obtained by putting together the 5 models from ENSEMBLES and the 11 models from APCC/CliPAS have been evaluated. The grand ENSEMBLES-APCC/CliPAS MME enhances significantly the skill in predicting 2m temperature and precipitation compared to previous estimates from the contributing MMEs. Our results show that, in general, the better combinations of SPSs are obtained by mixing ENSEMBLES and APCC/CliPAS models and that only a limited number of SPSs is required to obtain the maximum performance. The number and selection of models that perform better is usually different depending on the region/phenomenon under consideration so that all models are useful in some cases. It is shown that the incremental performance contribution tends to be higher when adding one model from ENSEMBLES to APCC/CliPAS MMEs and vice versa, confirming that the benefit of using MMEs amplifies with the increase of the independence the contributing models. To verify the above results for a real world application, the Grand ENSEMBLES-APCC/CliPAS MME is used to predict retrospective energy demand over Italy as provided by TERNA (Italian Transmission System Operator) for the period 1990-2007. The results demonstrate the useful application of MME seasonal predictions for energy demand forecasting over Italy. It is shown a significant enhancement of the potential economic value of forecasting energy demand when using the better combinations from the Grand MME by comparison to the maximum value obtained from the better combinations of each of the two contributing MMEs. The above results demonstrate for the first time the potential of the Grand MME to significantly contribute in obtaining useful predictions at the seasonal time-scale.

Predicting Solar Cycle 24 Using a Geomagnetic Precursor Pair

NASA Technical Reports Server (NTRS)

Pesnell, W. Dean

2014-01-01

We describe using Ap and F(10.7) as a geomagnetic-precursor pair to predict the amplitude of Solar Cycle 24. The precursor is created by using F(10.7) to remove the direct solar-activity component of Ap. Four peaks are seen in the precursor function during the decline of Solar Cycle 23. A recurrence index that is generated by a local correlation of Ap is then used to determine which peak is the correct precursor. The earliest peak is the most prominent but coincides with high levels of non-recurrent solar activity associated with the intense solar activity of October and November 2003. The second and third peaks coincide with some recurrent activity on the Sun and show that a weak cycle precursor closely following a period of strong solar activity may be difficult to resolve. A fourth peak, which appears in early 2008 and has recurrent activity similar to precursors of earlier solar cycles, appears to be the "true" precursor peak for Solar Cycle 24 and predicts the smallest amplitude for Solar Cycle 24. To determine the timing of peak activity it is noted that the average time between the precursor peak and the following maximum is approximately equal to 6.4 years. Hence, Solar Cycle 24 would peak during 2014. Several effects contribute to the smaller prediction when compared with other geomagnetic-precursor predictions. During Solar Cycle 23 the correlation between sunspot number and F(10.7) shows that F(10.7) is higher than the equivalent sunspot number over most of the cycle, implying that the sunspot number underestimates the solar-activity component described by F(10.7). During 2003 the correlation between aa and Ap shows that aa is 10 % higher than the value predicted from Ap, leading to an overestimate of the aa precursor for that year. However, the most important difference is the lack of recurrent activity in the first three peaks and the presence of significant recurrent activity in the fourth. While the prediction is for an amplitude of Solar Cycle 24 of 65 +/- 20 in smoothed sunspot number, a below-average amplitude for Solar Cycle 24, with maximum at 2014.5+/-0.5, we conclude that Solar Cycle 24 will be no stronger than average and could be much weaker than average.

Performance of a New Model for Predicting End of Flowering Date (bbch 69) of Grapevine (Vitis Vinifera L.)

NASA Astrophysics Data System (ADS)

Gentilucci, Matteo

2017-04-01

The end of flowering date (BBCH 69) is an important phenological stage for grapevine (Vitis Vinifera L.), in fact up to this date the growth is focused on the plant and gradually passes on the berries through fruit set. The aim of this study is to perform a model to predict the date of the end of flowering (BBCH69) for some grapevine varieties. This research carried out using three cultivars of grapevine (Maceratino, Montepulciano, Sangiovese) in three different locations (Macerata, Morrovalle and Potenza Picena), places of an equal number of wine farms for the time interval between 2006 and 2013. In order to have reliable temperatures for each location, the data of 6 weather stations near these farms have been interpolated using cokriging methods with elevation as independent variable. The procedure to predict the end of flowering date starts with an investigation of cardinal temperatures typical of each grapevine cultivar. In fact the analysis is characterized by four temperature thresholds (cardinals): minimum activity temperature (TCmin = below this temperature there is no growth for the plant), lower optimal temperature (TLopt = above this temperature there is maximum growth), upper optimal temperature (TUopt = below this temperature there is maximum growth) and maximum activity temperature (TC max = above this temperature there is no growth). Thus this model take into consideration maximum, mean and minimum daily temperatures of each location, relating them with the four above mentioned cultivar temperature thresholds. In this way it has been obtained some possible cases (32) corresponding to as many equations, depending on the position of temperatures compared with the thresholds, in order to calculate the amount of growing degree units (GDU) for each day. Several iterative tests (about 1000 for each cultivar) have been performed, changing the values of temperature thresholds and GDU in order to find the best possible combination which minimizes error between observed and predicted days from budburst to end of flowering. It has been assessed the minimization of error for the predicted dates compared with real ones, calculating some statistical indexes as root mean square error, mean absolute error and coefficient of variation. The procedure led to the identification of four cardinal temperatures and the amount of GDU for each cultivar between BBCH01 (budburst) and BBCH69 (end of flowering). In conclusion, this research has achieved some goals such as the plant response to temperature (same cardinal temperatures for Maceratino and Sangiovese but higher ones for Montepulciano), the interval ranging of growing degree units (from 35 to 38) and the differences between observed and predicted days (ranged from 2 to 3.5), for each grape varieties.

Linear prediction and single-channel recording.

PubMed

Carter, A A; Oswald, R E

1995-08-01

The measurement of individual single-channel events arising from the gating of ion channels provides a detailed data set from which the kinetic mechanism of a channel can be deduced. In many cases, the pattern of dwells in the open and closed states is very complex, and the kinetic mechanism and parameters are not easily determined. Assuming a Markov model for channel kinetics, the probability density function for open and closed time dwells should consist of a sum of decaying exponentials. One method of approaching the kinetic analysis of such a system is to determine the number of exponentials and the corresponding parameters which comprise the open and closed dwell time distributions. These can then be compared to the relaxations predicted from the kinetic model to determine, where possible, the kinetic constants. We report here the use of a linear technique, linear prediction/singular value decomposition, to determine the number of exponentials and the exponential parameters. Using simulated distributions and comparing with standard maximum-likelihood analysis, the singular value decomposition techniques provide advantages in some situations and are a useful adjunct to other single-channel analysis techniques.

Acoustic energy relations in Mudejar-Gothic churches.

PubMed

Zamarreño, Teófilo; Girón, Sara; Galindo, Miguel

2007-01-01

Extensive objective energy-based parameters have been measured in 12 Mudejar-Gothic churches in the south of Spain. Measurements took place in unoccupied churches according to the ISO-3382 standard. Monoaural objective measures in the 125-4000 Hz frequency range and in their spatial distributions were obtained. Acoustic parameters: clarity C80, definition D50, sound strength G and center time Ts have been deduced using impulse response analysis through a maximum length sequence measurement system in each church. These parameters spectrally averaged according to the most extended criteria in auditoria in order to consider acoustic quality were studied as a function of source-receiver distance. The experimental results were compared with predictions given by classical and other existing theoretical models proposed for concert halls and churches. An analytical semi-empirical model based on the measured values of the C80 parameter is proposed in this work for these spaces. The good agreement between predicted values and experimental data for definition, sound strength, and center time in the churches analyzed shows that the model can be used for design predictions and other purposes with reasonable accuracy.

Yo-Yo IR1 vs. incremental continuous running test for prediction of 3000-m performance.

PubMed

Schmitz, Boris; Klose, Andreas; Schelleckes, Katrin; Jekat, Charlotte M; Krüger, Michael; Brand, Stefan-Martin

2017-11-01

This study aimed to compare physiological responses during the Yo-Yo intermittent recovery level 1 (Yo-Yo IR1) Test and an incremental continuous running field Test (ICRT) and to analyze their predictive value on 3000-m running performance. Forty moderately trained individuals (18 females) performed the ICRT and Yo-Yo IR1 Test to exhaustion. The ICRT was performed as graded running test with an increase of 2.0 km·h-1 after each 3 min interval for lactate diagnostic. In both tests, blood lactate levels were determined after the test and at 2 and 5 min of recovery. Heart rate (HR) was recorded to monitor differences in HR slopes and HR recovery. Comparison revealed a correlation between ICRT and Yo-Yo IR1 Test performance (R2=0.83, P<0.001), while significant differences in HRmax existed (Yo-Yo IR1, 189±10 bpm; ICRT, 195±16 bpm; P<0.005; ES=0.5). Maximum lactate levels were also different between test (Yo-Yo IR1, 10.1±2.1 mmol∙L-1; ICRT, 11.7±2.4 mmol∙L-1; P<0.01; ES=0.7). Significant inverse correlations were found between the Yo-Yo IR1 Test performance and 3000 m running time (R2=0.77, P<0.0001) as well as the ICRT and 3000 m time (R2=0.90, P<0.0001). Our data suggest that ICRT and Yo-Yo IR1 test are useful field test methods for the prediction of competitive running performances such as 3000-m runs but maximum HR and blood lactate values differ significantly. The ICRT may have higher predictive power for middle- to long- distance running performance such as 3000-m runs offering a reliable test for coaches in the recruitment of athletes or supervision of training concepts.

Ultra scale-down device to predict dewatering levels of solids recovered in a continuous scroll decanter centrifuge.

PubMed

Lopes, A G; Keshavarz-Moore, E

2013-01-01

During centrifugation operation, the major challenge in the recovery of extracellular proteins is the removal of the maximum liquid entrapped within the spaces between the settled solids-dewatering level. The ability of the scroll decanter centrifuge (SDC) to process continuously large amounts of feed material with high concentration of solids without the need for resuspension of feeds, and also to achieve relatively high dewatering, could be of great benefit for future use in the biopharmaceutical industry. However, for reliable prediction of dewatering in such a centrifuge, tests using the same kind of equipment at pilot-scale are required, which are time consuming and costly. To alleviate the need of pilot-scale trials, a novel USD device, with reduced amounts of feed (2 mL) and to be used in the laboratory, was developed to predict the dewatering levels of a SDC. To verify USD device, dewatering levels achieved were plotted against equivalent compression (Gtcomp ) and decanting (Gtdec ) times, obtained from scroll rates and feed flow rates operated at pilot-scale, respectively. The USD device was able to successfully match dewatering trends of the pilot-scale as a function of both Gtcomp and Gtdec , particularly for high cell density feeds, hence accounting for all key variables that influenced dewatering in a SDC. In addition, it accurately mimicked the maximum dewatering performance of the pilot-scale equipment. Therefore the USD device has the potential to be a useful tool at early stages of process development to gather performance data in the laboratory thus minimizing lengthy and costly runs with pilot-scale SDC. © 2013 American Institute of Chemical Engineers.

The Effect of Single-Level Disc Degeneration on Dynamic Response of the Whole Lumbar Spine to Vertical Vibration.

PubMed

Guo, Li-Xin; Fan, Wei

2017-09-01

The objective of this study was to investigate the effect of single-level disc degeneration on dynamic response of the whole lumbar spine to vertical whole body vibration that is typically present when driving vehicles. Ligamentous finite element models of the lumbar L1-S1 motion segment in different grades of degeneration (healthy, mild, and moderate) at the L4-L5 level were developed with consideration of changing disc height and material properties of the nucleus pulpous. All models were loaded with a compressive follower preload of 400 N and a sinusoidal vertical vibration load of ±40 N. After transient dynamic analyses, computational results for the 3 models in terms of disc bulge, von-Mises stress in annulus ground substance, and nucleus pressure were plotted as a function of time and compared. All the predicted results showed a cyclic response with time. At the degenerated L4-L5 disc level, as degeneration progressed, maximum value of the predicted response showed a decrease in disc bulge and von-Mises stress in annulus ground substance but a slight increase in nucleus pressure, and their vibration amplitudes were all decreased. At the adjacent levels of the degenerated disc, there was a slight decrease in maximum value and vibration amplitude of these predicted responses with the degeneration. The results indicated that single-level disc degeneration can alter vibration characteristics of the whole lumbar spine especially for the degenerated disc level, and increasing the degeneration did not deteriorate the effect of vertical vibration on the spine. Copyright © 2017 Elsevier Inc. All rights reserved.

Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models

PubMed Central

Grün, Sonja; Helias, Moritz

2017-01-01

Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distribution for the population-averaged activity, and for some population sizes the second mode would peak at high activities, that experimentally would be equivalent to 90% of the neuron population active within time-windows of few milliseconds. Several problems are connected with this bimodality: 1. The presence of the high-activity mode is unrealistic in view of observed neuronal activity and on neurobiological grounds. 2. Boltzmann learning becomes non-ergodic, hence the pairwise maximum-entropy distribution cannot be found: in fact, Boltzmann learning would produce an incorrect distribution; similarly, common variants of mean-field approximations also produce an incorrect distribution. 3. The Glauber dynamics associated with the model is unrealistically bistable and cannot be used to generate realistic surrogate data. This bimodality problem is first demonstrated for an experimental dataset from 159 neurons in the motor cortex of macaque monkey. Evidence is then provided that this problem affects typical neural recordings of population sizes of a couple of hundreds or more neurons. The cause of the bimodality problem is identified as the inability of standard maximum-entropy distributions with a uniform reference measure to model neuronal inhibition. To eliminate this problem a modified maximum-entropy model is presented, which reflects a basic effect of inhibition in the form of a simple but non-uniform reference measure. This model does not lead to unrealistic bimodalities, can be found with Boltzmann learning, and has an associated Glauber dynamics which incorporates a minimal asymmetric inhibition. PMID:28968396

Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models.

PubMed

Rostami, Vahid; Porta Mana, PierGianLuca; Grün, Sonja; Helias, Moritz

2017-10-01

Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distribution for the population-averaged activity, and for some population sizes the second mode would peak at high activities, that experimentally would be equivalent to 90% of the neuron population active within time-windows of few milliseconds. Several problems are connected with this bimodality: 1. The presence of the high-activity mode is unrealistic in view of observed neuronal activity and on neurobiological grounds. 2. Boltzmann learning becomes non-ergodic, hence the pairwise maximum-entropy distribution cannot be found: in fact, Boltzmann learning would produce an incorrect distribution; similarly, common variants of mean-field approximations also produce an incorrect distribution. 3. The Glauber dynamics associated with the model is unrealistically bistable and cannot be used to generate realistic surrogate data. This bimodality problem is first demonstrated for an experimental dataset from 159 neurons in the motor cortex of macaque monkey. Evidence is then provided that this problem affects typical neural recordings of population sizes of a couple of hundreds or more neurons. The cause of the bimodality problem is identified as the inability of standard maximum-entropy distributions with a uniform reference measure to model neuronal inhibition. To eliminate this problem a modified maximum-entropy model is presented, which reflects a basic effect of inhibition in the form of a simple but non-uniform reference measure. This model does not lead to unrealistic bimodalities, can be found with Boltzmann learning, and has an associated Glauber dynamics which incorporates a minimal asymmetric inhibition.

A rapid estimation of tsunami run-up based on finite fault models

NASA Astrophysics Data System (ADS)

Campos, J.; Fuentes, M. A.; Hayes, G. P.; Barrientos, S. E.; Riquelme, S.

2014-12-01

Many efforts have been made to estimate the maximum run-up height of tsunamis associated with large earthquakes. This is a difficult task, because of the time it takes to construct a tsunami model using real time data from the source. It is possible to construct a database of potential seismic sources and their corresponding tsunami a priori. However, such models are generally based on uniform slip distributions and thus oversimplify our knowledge of the earthquake source. Instead, we can use finite fault models of earthquakes to give a more accurate prediction of the tsunami run-up. Here we show how to accurately predict tsunami run-up from any seismic source model using an analytic solution found by Fuentes et al, 2013 that was especially calculated for zones with a very well defined strike, i.e, Chile, Japan, Alaska, etc. The main idea of this work is to produce a tool for emergency response, trading off accuracy for quickness. Our solutions for three large earthquakes are promising. Here we compute models of the run-up for the 2010 Mw 8.8 Maule Earthquake, the 2011 Mw 9.0 Tohoku Earthquake, and the recent 2014 Mw 8.2 Iquique Earthquake. Our maximum rup-up predictions are consistent with measurements made inland after each event, with a peak of 15 to 20 m for Maule, 40 m for Tohoku, and 2,1 m for the Iquique earthquake. Considering recent advances made in the analysis of real time GPS data and the ability to rapidly resolve the finiteness of a large earthquake close to existing GPS networks, it will be possible in the near future to perform these calculations within the first five minutes after the occurrence of any such event. Such calculations will thus provide more accurate run-up information than is otherwise available from existing uniform-slip seismic source databases.

Using Chitosan/CHPATC as coagulant to remove color and turbidity of industrial wastewater: Optimization through RSM design.

PubMed

Momeni, Meysam Mohammad; Kahforoushan, Davood; Abbasi, Farhang; Ghanbarian, Saeid

2018-04-01

One of the most important solid-liquid separation processes is coagulation and flocculation that is extensively used in the primary treatment of industrial wastewater. The biopolymers, because of biodegradable properties and low cost have been used as coagulants. In this study, chitosan as a natural coagulant of choice, was modified by (3-chloro 2-hydroxypropyl)trimethylammonium chloride and was used to remove the color and turbidity of industrial wastewater. To evaluate the effect of pH, settling time, the initial turbidity of wastewater, the amount of coagulant, and the concentration of dye (Melanoidin) were chosen to study their effects on removal of wastewater color and turbidity. The experiments were done in a batch system by using a jar test. To achieve the optimum conditions for the removal of color and turbidity, the response surface methodology (RSM) experimental design method was used. The results obtained from experiments showed that the optimum conditions for the removal of color were as: pH = 3, concentration of dye = 1000 mg/L, settling time = 78.93 min, and dose of coagulant = 3 g/L. The maximum color removal in these conditions was predicted 82.78% by the RSM model. The optimal conditions for the removal of turbidity of the waste water were as: pH = 5.66, initial turbidity = 60 NTU, settling time = 105 min, and amount of coagulant = 3 g/L. The maximum turbidity removal in these circumstances was predicted 94.19% by the model. The experimental results obtained in optimum conditions for removal of color and turbidity were 76.20% and 90.14%, respectively, indicating the high accuracy of the prediction model. Copyright © 2018 Elsevier Ltd. All rights reserved.

Rapid modeling of complex multi-fault ruptures with simplistic models from real-time GPS: Perspectives from the 2016 Mw 7.8 Kaikoura earthquake

NASA Astrophysics Data System (ADS)

Crowell, B.; Melgar, D.

2017-12-01

The 2016 Mw 7.8 Kaikoura earthquake is one of the most complex earthquakes in recent history, rupturing across at least 10 disparate faults with varying faulting styles, and exhibiting intricate surface deformation patterns. The complexity of this event has motivated the need for multidisciplinary geophysical studies to get at the underlying source physics to better inform earthquake hazards models in the future. However, events like Kaikoura beg the question of how well (or how poorly) such earthquakes can be modeled automatically in real-time and still satisfy the general public and emergency managers. To investigate this question, we perform a retrospective real-time GPS analysis of the Kaikoura earthquake with the G-FAST early warning module. We first perform simple point source models of the earthquake using peak ground displacement scaling and a coseismic offset based centroid moment tensor (CMT) inversion. We predict ground motions based on these point sources as well as simple finite faults determined from source scaling studies, and validate against true recordings of peak ground acceleration and velocity. Secondly, we perform a slip inversion based upon the CMT fault orientations and forward model near-field tsunami maximum expected wave heights to compare against available tide gauge records. We find remarkably good agreement between recorded and predicted ground motions when using a simple fault plane, with the majority of disagreement in ground motions being attributable to local site effects, not earthquake source complexity. Similarly, the near-field tsunami maximum amplitude predictions match tide gauge records well. We conclude that even though our models for the Kaikoura earthquake are devoid of rich source complexities, the CMT driven finite fault is a good enough "average" source and provides useful constraints for rapid forecasting of ground motion and near-field tsunami amplitudes.

Wake Flow About the Mars Pathfinder Entry Vehicle

NASA Technical Reports Server (NTRS)

Mitcheltree, R. A.; Gnoffo, P. A.

1995-01-01

A computational approach is used to describe the aerothermodynamics of the Mars Pathfinder vehicle entering the Mars atmosphere at the maximum heating and maximum deceleration points in its trajectory. Ablating and nonablating boundary conditions are developed which produce maximum recombination of CO2 on the surface. For the maximum heating trajectory point, an axisymmetric, nonablating calculation predicts a stagnation-point value for the convective heating of 115 W/cm(exp 2). Radiative heating estimates predict an additional 5-12 W/cm(exp 2) at the stagnation point. Peak convective heating on the afterbody occurs on the vehicle's flat stern with a value of 5.9% of the stagnation value. The forebody flow exhibits chemical nonequilibrium behavior, and the flow is frozen in the near wake. Including ablation injection on the forebody lowers the stagnation-point convective heating 18%.

Robustness of neuroprosthetic decoding algorithms.

PubMed

Serruya, Mijail; Hatsopoulos, Nicholas; Fellows, Matthew; Paninski, Liam; Donoghue, John

2003-03-01

We assessed the ability of two algorithms to predict hand kinematics from neural activity as a function of the amount of data used to determine the algorithm parameters. Using chronically implanted intracortical arrays, single- and multineuron discharge was recorded during trained step tracking and slow continuous tracking tasks in macaque monkeys. The effect of increasing the amount of data used to build a neural decoding model on the ability of that model to predict hand kinematics accurately was examined. We evaluated how well a maximum-likelihood model classified discrete reaching directions and how well a linear filter model reconstructed continuous hand positions over time within and across days. For each of these two models we asked two questions: (1) How does classification performance change as the amount of data the model is built upon increases? (2) How does varying the time interval between the data used to build the model and the data used to test the model affect reconstruction? Less than 1 min of data for the discrete task (8 to 13 neurons) and less than 3 min (8 to 18 neurons) for the continuous task were required to build optimal models. Optimal performance was defined by a cost function we derived that reflects both the ability of the model to predict kinematics accurately and the cost of taking more time to build such models. For both the maximum-likelihood classifier and the linear filter model, increasing the duration between the time of building and testing the model within a day did not cause any significant trend of degradation or improvement in performance. Linear filters built on one day and tested on neural data on a subsequent day generated error-measure distributions that were not significantly different from those generated when the linear filters were tested on neural data from the initial day (p<0.05, Kolmogorov-Smirnov test). These data show that only a small amount of data from a limited number of cortical neurons appears to be necessary to construct robust models to predict kinematic parameters for the subsequent hours. Motor-control signals derived from neurons in motor cortex can be reliably acquired for use in neural prosthetic devices. Adequate decoding models can be built rapidly from small numbers of cells and maintained with daily calibration sessions.

Local magnitude determinations for intermountain seismic belt earthquakes from broadband digital data

USGS Publications Warehouse

Pechmann, J.C.; Nava, S.J.; Terra, F.M.; Bernier, J.C.

2007-01-01

The University of Utah Seismograph Stations (UUSS) earthquake catalogs for the Utah and Yellowstone National Park regions contain two types of size measurements: local magnitude (ML) and coda magnitude (MC), which is calibrated against ML. From 1962 through 1993, UUSS calculated ML values for southern and central Intermountain Seismic Belt earthquakes using maximum peak-to-peak (p-p) amplitudes on paper records from one to five Wood-Anderson (W-A) seismographs in Utah. For ML determinations of earthquakes since 1994, UUSS has utilized synthetic W-A seismograms from U.S. National Seismic Network and UUSS broadband digital telemetry stations in the region, which numbered 23 by the end of our study period on 30 June 2002. This change has greatly increased the percentage of earthquakes for which ML can be determined. It is now possible to determine ML for all M ???3 earthquakes in the Utah and Yellowstone regions and earthquakes as small as M <1 in some areas. To maintain continuity in the magnitudes in the UUSS earthquake catalogs, we determined empirical ML station corrections that minimize differences between MLs calculated from paper and synthetic W-A records. Application of these station corrections, in combination with distance corrections from Richter (1958) which have been in use at UUSS since 1962, produces ML values that do not show any significant distance dependence. ML determinations for the Utah and Yellowstone regions for 1981-2002 using our station corrections and Richter's distance corrections have provided a reliable data set for recalibrating the MC scales for these regions. Our revised ML values are consistent with available moment magnitude determinations for Intermountain Seismic Belt earthquakes. To facilitate automatic ML measurements, we analyzed the distribution of the times of maximum p-p amplitudes in synthetic W-A records. A 30-sec time window for maximum amplitudes, beginning 5 sec before the predicted Sg time, encompasses 95% of the maximum p-p amplitudes. In our judgment, this time window represents a good compromise between maximizing the chances of capturing the maximum amplitude and minimizing the risk of including other seismic events.

Maximum likelihood Bayesian model averaging and its predictive analysis for groundwater reactive transport models

DOE PAGES

Lu, Dan; Ye, Ming; Curtis, Gary P.

2015-08-01

While Bayesian model averaging (BMA) has been widely used in groundwater modeling, it is infrequently applied to groundwater reactive transport modeling because of multiple sources of uncertainty in the coupled hydrogeochemical processes and because of the long execution time of each model run. To resolve these problems, this study analyzed different levels of uncertainty in a hierarchical way, and used the maximum likelihood version of BMA, i.e., MLBMA, to improve the computational efficiency. Our study demonstrates the applicability of MLBMA to groundwater reactive transport modeling in a synthetic case in which twenty-seven reactive transport models were designed to predict themore » reactive transport of hexavalent uranium (U(VI)) based on observations at a former uranium mill site near Naturita, CO. Moreover, these reactive transport models contain three uncertain model components, i.e., parameterization of hydraulic conductivity, configuration of model boundary, and surface complexation reactions that simulate U(VI) adsorption. These uncertain model components were aggregated into the alternative models by integrating a hierarchical structure into MLBMA. The modeling results of the individual models and MLBMA were analyzed to investigate their predictive performance. The predictive logscore results show that MLBMA generally outperforms the best model, suggesting that using MLBMA is a sound strategy to achieve more robust model predictions relative to a single model. MLBMA works best when the alternative models are structurally distinct and have diverse model predictions. When correlation in model structure exists, two strategies were used to improve predictive performance by retaining structurally distinct models or assigning smaller prior model probabilities to correlated models. Since the synthetic models were designed using data from the Naturita site, the results of this study are expected to provide guidance for real-world modeling. Finally, limitations of applying MLBMA to the synthetic study and future real-world modeling are discussed.« less

Fine Sediment Residency in Streambeds in Southeastern Australia.

NASA Astrophysics Data System (ADS)

Croke, J. C.; Thompson, C. J.; Rhodes, E.

2007-12-01

A detailed understanding of channel forming and maintenance processes in streams requires some measurement and/or prediction of bed load transport and sediment mobility. Traditional field based measurements of such processes are often problematic due to the high discharge characteristics of upland streams. In part to compensate for such difficulties, empirical flow competence equations have also been developed to predict armour or bedform stabilising grain mobility. These equations have been applied to individual reaches to predict the entrainment of a threshold grain size and the vertical extent of flushing. In cobble- and boulder-bed channels the threshold grain size relates to the size of the bedform stabilising grains (eg. D84, D90). This then allows some prediction of when transport of the matrix material occurs. The application of Optically Stimulated Luminescence (OSL) dating is considered here as an alternative and innovative way to determine fine sediment residency times in stream beds. Age estimates derived from the technique are used to assist in calibrating sediment entrainment models to specific channel types and hydrological regimes. The results from a one-dimensional HEC-RAS model indicate that recurrence interval floods exceeding bankfull up to 13 years are competent to mobilise the maximum overlying surface grain sizes at the sites. OSL minimum age model results of well bleached quartz in the fine matrix particles are in general agreement with selected competence equation predictions. The apparent long (100-1400y) burial age of most of the mineral quartz suggests that competent flows are not able to flush all subsurface fine-bed material. Maximum bed load exchange (flushing) depth was limited to twice the depth of the overlying D90 grain size. Application of OSL in this study provides important insight into the nature of matrix material storage and flushing in mountain streams.

Stimulus uncertainty enhances long-term potentiation-like plasticity in human motor cortex.

PubMed

Sale, Martin V; Nydam, Abbey S; Mattingley, Jason B

2017-03-01

Plasticity can be induced in human cortex using paired associative stimulation (PAS), which repeatedly and predictably pairs a peripheral electrical stimulus with transcranial magnetic stimulation (TMS) to the contralateral motor region. Many studies have reported small or inconsistent effects of PAS. Given that uncertain stimuli can promote learning, the predictable nature of the stimulation in conventional PAS paradigms might serve to attenuate plasticity induction. Here, we introduced stimulus uncertainty into the PAS paradigm to investigate if it can boost plasticity induction. Across two experimental sessions, participants (n = 28) received a modified PAS paradigm consisting of a random combination of 90 paired stimuli and 90 unpaired (TMS-only) stimuli. Prior to each of these stimuli, participants also received an auditory cue which either reliably predicted whether the upcoming stimulus was paired or unpaired (no uncertainty condition) or did not predict the upcoming stimulus (maximum uncertainty condition). Motor evoked potentials (MEPs) evoked from abductor pollicis brevis (APB) muscle quantified cortical excitability before and after PAS. MEP amplitude increased significantly 15 min following PAS in the maximum uncertainty condition. There was no reliable change in MEP amplitude in the no uncertainty condition, nor between post-PAS MEP amplitudes across the two conditions. These results suggest that stimulus uncertainty may provide a novel means to enhance plasticity induction with the PAS paradigm in human motor cortex. To provide further support to the notion that stimulus uncertainty and prediction error promote plasticity, future studies should further explore the time course of these changes, and investigate what aspects of stimulus uncertainty are critical in boosting plasticity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Climate change and health: Indoor heat exposure in vulnerable populations☆

PubMed Central

White-Newsome, Jalonne L.; Sánchez, Brisa N.; Jolliet, Olivier; Zhang, Zhenzhen; Parker, Edith A.; Dvonch, J. Timothy; O'Neill, Marie S.

2015-01-01

Introduction Climate change is increasing the frequency of heat waves and hot weather in many urban environments. Older people are more vulnerable to heat exposure but spend most of their time indoors. Few published studies have addressed indoor heat exposure in residences occupied by an elderly population. The purpose of this study is to explore the relationship between outdoor and indoor temperatures in homes occupied by the elderly and determine other predictors of indoor temperature. Materials and methods We collected hourly indoor temperature measurements of 30 different homes; outdoor temperature, dewpoint temperature, and solar radiation data during summer 2009 in Detroit, MI. We used mixed linear regression to model indoor temperatures’ responsiveness to weather, housing and environmental characteristics, and evaluated our ability to predict indoor heat exposures based on outdoor conditions. Results Average maximum indoor temperature for all locations was 34.85 °C, 13.8 °C higher than average maximum outdoor temperature. Indoor temperatures of single family homes constructed of vinyl paneling or wood siding were more sensitive than brick homes to outdoor temperature changes and internal heat gains. Outdoor temperature, solar radiation, and dewpoint temperature predicted 38% of the variability of indoor temperatures. Conclusions Indoor exposures to heat in Detroit exceed the comfort range among elderly occupants, and can be predicted using outdoor temperatures, characteristics of the housing stock and surroundings PMID:22071034

Energies of backstreaming protons in the foreshock

NASA Technical Reports Server (NTRS)

Greenstadt, E. W.

1976-01-01

A predicted pattern of energy vs detector location in the cislunar region is displayed for protons of zero pitch angle traveling upstream away from the quasi-parallel bow shock. The pattern is implied by upstream wave boundary properties. In the solar ecliptic, protons are estimated to have a minimum of 1.1 times the solar wind bulk energy E sub SW when the wave boundary is in the early morning sector and a maximum of 8.2 E sub SW when the boundary is near the predawn flank.

Importance of Antecedent Beach and Surf-Zone Morphology to Wave Runup Predictions

DTIC Science & Technology

2016-10-01

position on the dune, the laser reflects well off of the water surface when foam is present (blue dots, Figure 1B). Maximum range of measurement...depends upon the amount of breaking and foam present in the surf-zone at any given time, but rarely exceeds 150 m for this laser scanner. Drawbacks to...determined by reverse-shoaling data from the FRF’s 11 m Acoustic Wave and Current (AWAC) profiler to deep water values. Local water levels (tide and surge

Correlating cookoff violence with pre-ignition damage.

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

Wente, William Baker; Hobbs, Michael L.; Kaneshige, Michael Jiro

Predicting the response of energetic materials during accidents, such as fire, is important for high consequence safety analysis. We hypothesize that responses of ener-getic materials before and after ignition depend on factors that cause thermal and chemi-cal damage. We have previously correlated violence from PETN to the extent of decom-position at ignition, determined as the time when the maximum Damkoehler number ex-ceeds a threshold value. We seek to understand if our method of violence correlation ap-plies universally to other explosive starting with RDX.

How long will the traffic flow time series keep efficacious to forecast the future?

NASA Astrophysics Data System (ADS)

Yuan, PengCheng; Lin, XuXun

2017-02-01

This paper investigate how long will the historical traffic flow time series keep efficacious to forecast the future. In this frame, we collect the traffic flow time series data with different granularity at first. Then, using the modified rescaled range analysis method, we analyze the long memory property of the traffic flow time series by computing the Hurst exponent. We calculate the long-term memory cycle and test its significance. We also compare it with the maximum Lyapunov exponent method result. Our results show that both of the freeway traffic flow time series and the ground way traffic flow time series demonstrate positively correlated trend (have long-term memory property), both of their memory cycle are about 30 h. We think this study is useful for the short-term or long-term traffic flow prediction and management.

Are EMS call volume predictions based on demand pattern analysis accurate?

PubMed

Brown, Lawrence H; Lerner, E Brooke; Larmon, Baxter; LeGassick, Todd; Taigman, Michael

2007-01-01

Most EMS systems determine the number of crews they will deploy in their communities and when those crews will be scheduled based on anticipated call volumes. Many systems use historical data to calculate their anticipated call volumes, a method of prediction known as demand pattern analysis. To evaluate the accuracy of call volume predictions calculated using demand pattern analysis. Seven EMS systems provided 73 consecutive weeks of hourly call volume data. The first 20 weeks of data were used to calculate three common demand pattern analysis constructs for call volume prediction: average peak demand (AP), smoothed average peak demand (SAP), and 90th percentile rank (90%R). The 21st week served as a buffer. Actual call volumes in the last 52 weeks were then compared to the predicted call volumes by using descriptive statistics. There were 61,152 hourly observations in the test period. All three constructs accurately predicted peaks and troughs in call volume but not exact call volume. Predictions were accurate (+/-1 call) 13% of the time using AP, 10% using SAP, and 19% using 90%R. Call volumes were overestimated 83% of the time using AP, 86% using SAP, and 74% using 90%R. When call volumes were overestimated, predictions exceeded actual call volume by a median (Interquartile range) of 4 (2-6) calls for AP, 4 (2-6) for SAP, and 3 (2-5) for 90%R. Call volumes were underestimated 4% of time using AP, 4% using SAP, and 7% using 90%R predictions. When call volumes were underestimated, call volumes exceeded predictions by a median (Interquartile range; maximum under estimation) of 1 (1-2; 18) call for AP, 1 (1-2; 18) for SAP, and 2 (1-3; 20) for 90%R. Results did not vary between systems. Generally, demand pattern analysis estimated or overestimated call volume, making it a reasonable predictor for ambulance staffing patterns. However, it did underestimate call volume between 4% and 7% of the time. Communities need to determine if these rates of over-and underestimation are acceptable given their resources and local priorities.

Predictive model for disinfection by-product in Alexandria drinking water, northern west of Egypt.

PubMed

Abdullah, Ali M; Hussona, Salah El-dien

2013-10-01

Chlorine has been utilized in the early stages of water treatment processes as disinfectant. Disinfection for drinking water reduces the risk of pathogenic infection but may pose a chemical threat to human health due to disinfection residues and their by-products (DBP) when the organic and inorganic precursors are present in water. In the last two decades, many modeling attempts have been made to predict the occurrence of DBP in drinking water. Models have been developed based on data generated in laboratory-scale and field-scale investigations. The objective of this paper is to develop a predictive model for DBP formation in the Alexandria governorate located at the northern west of Egypt based on field-scale investigations as well as laboratory-controlled experimentations. The present study showed that the correlation coefficient between trihalomethanes (THM) predicted and THM measured was R (2)=0.88 and the minimum deviation percentage between THM predicted and THM measured was 0.8 %, the maximum deviation percentage was 89.3 %, and the average deviation was 17.8 %, while the correlation coefficient between dichloroacetic acid (DCAA) predicted and DCAA measured was R (2)=0.98 and the minimum deviation percentage between DCAA predicted and DCAA measured was 1.3 %, the maximum deviation percentage was 47.2 %, and the average deviation was 16.6 %. In addition, the correlation coefficient between trichloroacetic acid (TCAA) predicted and TCAA measured was R (2)=0.98 and the minimum deviation percentage between TCAA predicted and TCAA measured was 4.9 %, the maximum deviation percentage was 43.0 %, and the average deviation was 16.0 %.

QRS analysis using wavelet transformation for the prediction of response to cardiac resynchronization therapy: a prospective pilot study.

PubMed

Vassilikos, Vassilios P; Mantziari, Lilian; Dakos, Georgios; Kamperidis, Vasileios; Chouvarda, Ioanna; Chatzizisis, Yiannis S; Kalpidis, Panagiotis; Theofilogiannakos, Efstratios; Paraskevaidis, Stelios; Karvounis, Haralambos; Mochlas, Sotirios; Maglaveras, Nikolaos; Styliadis, Ioannis H

2014-01-01

Wider QRS and left bundle branch block morphology are related to response to cardiac resynchronization therapy (CRT). A novel time-frequency analysis of the QRS complex may provide additional information in predicting response to CRT. Signal-averaged electrocardiograms were prospectively recorded, before CRT, in orthogonal leads and QRS decomposition in three frequency bands was performed using the Morlet wavelet transformation. Thirty eight patients (age 65±10years, 31 males) were studied. CRT responders (n=28) had wider baseline QRS compared to non-responders and lower QRS energies in all frequency bands. The combination of QRS duration and mean energy in the high frequency band had the best predicting ability (AUC 0.833, 95%CI 0.705-0.962, p=0.002) followed by the maximum energy in the high frequency band (AUC 0.811, 95%CI 0.663-0.960, p=0.004). Wavelet transformation of the QRS complex is useful in predicting response to CRT. © 2013.

Application of the predicted heat strain model in development of localized, threshold-based heat stress management guidelines for the construction industry.

PubMed

Rowlinson, Steve; Jia, Yunyan Andrea

2014-04-01

Existing heat stress risk management guidelines recommended by international standards are not practical for the construction industry which needs site supervision staff to make instant managerial decisions to mitigate heat risks. The ability of the predicted heat strain (PHS) model [ISO 7933 (2004). Ergonomics of the thermal environment analytical determination and interpretation of heat stress using calculation of the predicted heat strain. Geneva: International Standard Organisation] to predict maximum allowable exposure time (D lim) has now enabled development of localized, action-triggering and threshold-based guidelines for implementation by lay frontline staff on construction sites. This article presents a protocol for development of two heat stress management tools by applying the PHS model to its full potential. One of the tools is developed to facilitate managerial decisions on an optimized work-rest regimen for paced work. The other tool is developed to enable workers' self-regulation during self-paced work.

Prediction possibilities of Arosa total ozone

NASA Astrophysics Data System (ADS)

Kane, R. P.

1987-01-01

Using the periodicities obtained by a Maximum Entropy Spectral Analysis (MESA) of the Arosa total ozone data ( CC') series for 1932 1971, the values predicted for 1972 onwards were compared with the observed values of the ( AD) series. A change of level was noticed, with the observed ( AD) values lower by about 7 D.U. Also, the matching was poor in 1980, 1981, 1982. In the monthly values, the most prominent periodicity was the annual wave, comprising some 80% variance. In the 12 month running averages, the annual wave was eliminated and the most prominent periodicity was T=3.7 years, encompassing roundly 20% variance. This and other periodicities at T=4.7, 5.4, 6.2, 10 and 16 years were all statistically significant at a 3.5δ a priori i.e., 2δ a posteriori level. However, the predictions from these were unsatisfactory, probably because some of these periodicities may be transient i.e., changing amplitudes and/or phases with time. Thus, no meaningful prediction seem possible for Arosa total ozone.

The constructal law of design and evolution in nature

PubMed Central

Bejan, Adrian; Lorente, Sylvie

2010-01-01

Constructal theory is the view that (i) the generation of images of design (pattern, rhythm) in nature is a phenomenon of physics and (ii) this phenomenon is covered by a principle (the constructal law): ‘for a finite-size flow system to persist in time (to live) it must evolve such that it provides greater and greater access to the currents that flow through it’. This law is about the necessity of design to occur, and about the time direction of the phenomenon: the tape of the design evolution ‘movie’ runs such that existing configurations are replaced by globally easier flowing configurations. The constructal law has two useful sides: the prediction of natural phenomena and the strategic engineering of novel architectures, based on the constructal law, i.e. not by mimicking nature. We show that the emergence of scaling laws in inanimate (geophysical) flow systems is the same phenomenon as the emergence of allometric laws in animate (biological) flow systems. Examples are lung design, animal locomotion, vegetation, river basins, turbulent flow structure, self-lubrication and natural multi-scale porous media. This article outlines the place of the constructal law as a self-standing law in physics, which covers all the ad hoc (and contradictory) statements of optimality such as minimum entropy generation, maximum entropy generation, minimum flow resistance, maximum flow resistance, minimum time, minimum weight, uniform maximum stresses and characteristic organ sizes. Nature is configured to flow and move as a conglomerate of ‘engine and brake’ designs. PMID:20368252

The constructal law of design and evolution in nature.

PubMed

Bejan, Adrian; Lorente, Sylvie

2010-05-12

Constructal theory is the view that (i) the generation of images of design (pattern, rhythm) in nature is a phenomenon of physics and (ii) this phenomenon is covered by a principle (the constructal law): 'for a finite-size flow system to persist in time (to live) it must evolve such that it provides greater and greater access to the currents that flow through it'. This law is about the necessity of design to occur, and about the time direction of the phenomenon: the tape of the design evolution 'movie' runs such that existing configurations are replaced by globally easier flowing configurations. The constructal law has two useful sides: the prediction of natural phenomena and the strategic engineering of novel architectures, based on the constructal law, i.e. not by mimicking nature. We show that the emergence of scaling laws in inanimate (geophysical) flow systems is the same phenomenon as the emergence of allometric laws in animate (biological) flow systems. Examples are lung design, animal locomotion, vegetation, river basins, turbulent flow structure, self-lubrication and natural multi-scale porous media. This article outlines the place of the constructal law as a self-standing law in physics, which covers all the ad hoc (and contradictory) statements of optimality such as minimum entropy generation, maximum entropy generation, minimum flow resistance, maximum flow resistance, minimum time, minimum weight, uniform maximum stresses and characteristic organ sizes. Nature is configured to flow and move as a conglomerate of 'engine and brake' designs.

Development of In Vitro-In Vivo Correlation for Potassium Chloride Extended Release Tablet Formulation Using Urinary Pharmacokinetic Data.

PubMed

Mittapalli, Rajendar K; Marroum, Patrick; Qiu, Yihong; Apfelbaum, Kathleen; Xiong, Hao

2017-07-01

To develop and validate a Level A in vitro-in vivo correlation (IVIVC) for potassium chloride extended-release (ER) formulations. Three prototype ER formulations of potassium chloride with different in vitro release rates were developed and their urinary pharmacokinetic profiles were evaluated in healthy subjects. A mathematical model between in vitro dissolution and in vivo urinary excretion, a surrogate for measuring in vivo absorption, was developed using time-scale and time-shift parameters. The IVIVC model was then validated based on internal and external predictability. With the established IVIVC model, there was a good correlation between the observed fraction of dose excreted in urine and the time-scaled and time-shifted fraction of the drug dissolved, and between the in vitro dissolution time and the in vivo urinary excretion time for the ER formulations. The percent prediction error (%PE) on cumulative urinary excretion over the 24 h interval (A e0-24h ) and maximum urinary excretion rate (R max ) was less than 15% for the individual formulations and less than 10% for the average of the two formulations used to develop the model. Further, the %PE values using external predictability were below 10%. A novel Level A IVIVC was successfully developed and validated for the new potassium chloride ER formulations using urinary pharmacokinetic data. This successful IVIVC may facilitate future development or manufacturing changes to the potassium chloride ER formulation.

An analysis of collegiate band directors' exposure to sound pressure levels

NASA Astrophysics Data System (ADS)

Roebuck, Nikole Moore

Noise-induced hearing loss (NIHL) is a significant but unfortunate common occupational hazard. The purpose of the current study was to measure the magnitude of sound pressure levels generated within a collegiate band room and determine if those sound pressure levels are of a magnitude that exceeds the policy standards and recommendations of the Occupational Safety and Health Administration (OSHA), and the National Institute of Occupational Safety and Health (NIOSH). In addition, reverberation times were measured and analyzed in order to determine the appropriateness of acoustical conditions for the band rehearsal environment. Sound pressure measurements were taken from the rehearsal of seven collegiate marching bands. Single sample t test were conducted to compare the sound pressure levels of all bands to the noise exposure standards of OSHA and NIOSH. Multiple regression analysis were conducted and analyzed in order to determine the effect of the band room's conditions on the sound pressure levels and reverberation times. Time weighted averages (TWA), noise percentage doses, and peak levels were also collected. The mean Leq for all band directors was 90.5 dBA. The total accumulated noise percentage dose for all band directors was 77.6% of the maximum allowable daily noise dose under the OSHA standard. The total calculated TWA for all band directors was 88.2% of the maximum allowable daily noise dose under the OSHA standard. The total accumulated noise percentage dose for all band directors was 152.1% of the maximum allowable daily noise dose under the NIOSH standards, and the total calculated TWA for all band directors was 93dBA of the maximum allowable daily noise dose under the NIOSH standard. Multiple regression analysis revealed that the room volume, the level of acoustical treatment and the mean room reverberation time predicted 80% of the variance in sound pressure levels in this study.

Analysis and Testing of Plates with Piezoelectric Sensors and Actuators

NASA Technical Reports Server (NTRS)

Bevan, Jeffrey S.

1998-01-01

Piezoelectric material inherently possesses coupling between electrostatics and structural dynamics. Utilizing linear piezoelectric theory results in an intrinsically coupled pair of piezoelectric constitutive equations. One equation describes the direct piezoelectric effect where strains produce an electric field and the other describes the converse effect where an applied electrical field produces strain. The purpose of this study is to compare finite element analysis and experiments of a thin plate with bonded piezoelectric material. Since an isotropic plate in combination with a thin piezoelectric layer constitutes a special case of a laminated composite, the classical laminated plate theory is used in the formulation to accommodated generic laminated composite panels with multiple bonded and embedded piezoelectric layers. Additionally, the von Karman large deflection plate theory is incorporated. The formulation results in laminate constitutive equations that are amiable to the inclusion of the piezoelectric constitutive equations yielding in a fully electro-mechanically coupled composite laminate. Using the finite element formulation, the governing differential equations of motion of a composite laminate with embedded piezoelectric layers are derived. The finite element model not only considers structural degrees of freedom (d.o.f.) but an additional electrical d.o.f. for each piezoelectric layer. Comparison between experiment and numerical prediction is performed by first treating the piezoelectric as a sensor and then again treating it as an actuator. To assess the piezoelectric layer as a sensor, various uniformly distributed pressure loads were simulated in the analysis and the corresponding generated voltages were calculated using both linear and nonlinear finite element analyses. Experiments were carried out by applying the same uniformly distributed loads and measuring the resulting generated voltages and corresponding maximum plate deflections. It is found that a highly nonlinear relationship exists between maximum deflection and voltage versus pressure loading. In order to assess comparisons of predicted and measured piezoelectric actuation, sinusoidal excitation voltages are simulated/applied and maximum deflections are calculated/measured. The maximum deflection as a function of time was determined using the linear finite elements analysis. Good correlation between prediction and measurement was achieved in all cases.

Ratcheting in a nonlinear viscoelastic adhesive

NASA Astrophysics Data System (ADS)

Lemme, David; Smith, Lloyd

2017-11-01

Uniaxial time-dependent creep and cycled stress behavior of a standard and toughened film adhesive were studied experimentally. Both adhesives exhibited progressive accumulation of strain from an applied cycled stress. Creep tests were fit to a viscoelastic power law model at three different applied stresses which showed nonlinear response in both adhesives. A third order nonlinear power law model with a permanent strain component was used to describe the creep behavior of both adhesives and to predict creep recovery and the accumulation of strain due to cycled stress. Permanent strain was observed at high stress but only up to 3% of the maximum strain. Creep recovery was under predicted by the nonlinear model, while cycled stress showed less than 3% difference for the first cycle but then over predicted the response above 1000 cycles by 4-14% at high stress. The results demonstrate the complex response observed with structural adhesives, and the need for further analytical advancements to describe their behavior.

Nonequilibrium Tricritical Point in a System with Long-Range Interactions

NASA Astrophysics Data System (ADS)

Antoniazzi, Andrea; Fanelli, Duccio; Ruffo, Stefano; Yamaguchi, Yoshiyuki Y.

2007-07-01

Systems with long-range interactions display a short-time relaxation towards quasistationary states whose lifetime increases with system size. With reference to the Hamiltonian mean field model, we here show that a maximum entropy principle, based on Lynden-Bell’s pioneering idea of “violent relaxation,” predicts the presence of out-of-equilibrium phase transitions separating the relaxation towards homogeneous (zero magnetization) or inhomogeneous (nonzero magnetization) quasistationary states. When varying the initial condition within a family of “water bags” with different initial magnetization and energy, first- and second-order phase transition lines are found that merge at an out-of-equilibrium tricritical point. Metastability is theoretically predicted and numerically checked around the first-order phase transition line.

Fast depth decision for HEVC inter prediction based on spatial and temporal correlation

NASA Astrophysics Data System (ADS)

Chen, Gaoxing; Liu, Zhenyu; Ikenaga, Takeshi

2016-07-01

High efficiency video coding (HEVC) is a video compression standard that outperforms the predecessor H.264/AVC by doubling the compression efficiency. To enhance the compression accuracy, the partition sizes ranging is from 4x4 to 64x64 in HEVC. However, the manifold partition sizes dramatically increase the encoding complexity. This paper proposes a fast depth decision based on spatial and temporal correlation. Spatial correlation utilize the code tree unit (CTU) Splitting information and temporal correlation utilize the motion vector predictor represented CTU in inter prediction to determine the maximum depth in each CTU. Experimental results show that the proposed method saves about 29.1% of the original processing time with 0.9% of BD-bitrate increase on average.

41 CFR 301-31.10 - How will my agency pay my subsistence expenses?

Code of Federal Regulations, 2011 CFR

2011-07-01

... maximum lodging amount applicable to the locality .75 times the maximum lodging amount applicable to the locality .5 times the maximum lodging amount applicable to the locality. Payment for lodging, meals, and other per diem expenses The maximum per diem rate applicable to the locality .75 times the maximum per...

Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

PubMed

Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

2016-05-01

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

Using leg muscles as shock absorbers: theoretical predictions and experimental results of drop landing performance.

PubMed

Minetti, A E; Ardigò, L P; Susta, D; Cotelli, F

1998-12-01

The use of muscles as power dissipators is investigated in this study, both from the modellistic and the experimental points of view. Theoretical predictions of the drop landing manoeuvre for a range of initial conditions have been obtained by accounting for the mechanical characteristics of knee extensor muscles, the limb geometry and assuming maximum neural activation. Resulting dynamics have been represented in the phase plane (vertical displacement versus speed) to better classify the damping performance. Predictions of safe landing in sedentary subjects were associated to dropping from a maximum (feet) height of 1.6-2.0 m (about 11 m on the moon). Athletes can extend up to 2.6-3.0 m, while for obese males (m = 100 kg, standard stature) the limit should reduce to 0.9-1.3 m. These results have been calculated by including in the model the estimated stiffness of the 'global elastic elements' acting below the squat position. Experimental landings from a height of 0.4, 0.7, 1.1 m (sedentary males (SM) and male (AM) and female (AF) athletes from the alpine ski national team) showed dynamics similar to the model predictions. While the peak power (for a drop height of about 0.7 m) was similar in SM and AF (AM shows a +40% increase, about 33 W/kg), AF stopped the downward movement after a time interval (0.219 +/- 0.030 s) from touch-down 20% significantly shorter than SM. Landing strategy and the effect of anatomical constraints are discussed in the paper.

A Hubble Space Telescope survey for Novae in M87. II. Snuffing out the maximum magnitude–rate of decline relation for novae as a non-standard candle, and a prediction of the existence of ultrafast novae

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

Shara, Michael M.; Doyle, Trisha; Lauer, Tod R.

The extensive grid of numerical simulations of nova eruptions first predicted that some classical novae might significantly deviate from the Maximum Magnitude–Rate of Decline (MMRD) relation, which purports to characterize novae as standard candles. Kasliwal et al. have announced the observational detection of a new class of faint, fast classical novae in the Andromeda galaxy. These objects deviate strongly from the MMRD relationship, as predicted by Yaron et al. Recently, Shara et al. reported the first detections of faint, fast novae in M87. These previously overlooked objects are as common in the giant elliptical galaxy M87 as they are inmore » the giant spiral M31; they comprise about 40% of all classical nova eruptions and greatly increase the observational scatter in the MMRD relation. We use the extensive grid of the nova simulations of Yaron et al. to identify the underlying causes of the existence of faint, fast novae. These are systems that have accreted, and can thus eject, only very low-mass envelopes, of the order of 10 –7–10 –8 M ⊙, on massive white dwarfs. Such binaries include, but are not limited to, the recurrent novae. As a result, these same models predict the existence of ultrafast novae that display decline times, t 2, to be as short as five hours. We outline a strategy for their future detection.« less

A Hubble Space Telescope Survey for Novae in M87. II. Snuffing out the Maximum Magnitude–Rate of Decline Relation for Novae as a Non-standard Candle, and a Prediction of the Existence of Ultrafast Novae

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

Shara, Michael M.; Doyle, Trisha; Zurek, David

The extensive grid of numerical simulations of nova eruptions from the work of Yaron et al. first predicted that some classical novae might significantly deviate from the Maximum Magnitude–Rate of Decline (MMRD) relation, which purports to characterize novae as standard candles. Kasliwal et al. have announced the observational detection of a new class of faint, fast classical novae in the Andromeda galaxy. These objects deviate strongly from the MMRD relationship, as predicted by Yaron et al. Recently, Shara et al. reported the first detections of faint, fast novae in M87. These previously overlooked objects are as common in the giantmore » elliptical galaxy M87 as they are in the giant spiral M31; they comprise about 40% of all classical nova eruptions and greatly increase the observational scatter in the MMRD relation. We use the extensive grid of the nova simulations of Yaron et al. to identify the underlying causes of the existence of faint, fast novae. These are systems that have accreted, and can thus eject, only very low-mass envelopes, of the order of 10{sup −7}–10{sup −8} M {sub ⊙}, on massive white dwarfs. Such binaries include, but are not limited to, the recurrent novae. These same models predict the existence of ultrafast novae that display decline times, t {sub 2,} to be as short as five hours. We outline a strategy for their future detection.« less

A Hubble Space Telescope survey for Novae in M87. II. Snuffing out the maximum magnitude–rate of decline relation for novae as a non-standard candle, and a prediction of the existence of ultrafast novae

DOE PAGES

Shara, Michael M.; Doyle, Trisha; Lauer, Tod R.; ...

2017-04-20

The extensive grid of numerical simulations of nova eruptions first predicted that some classical novae might significantly deviate from the Maximum Magnitude–Rate of Decline (MMRD) relation, which purports to characterize novae as standard candles. Kasliwal et al. have announced the observational detection of a new class of faint, fast classical novae in the Andromeda galaxy. These objects deviate strongly from the MMRD relationship, as predicted by Yaron et al. Recently, Shara et al. reported the first detections of faint, fast novae in M87. These previously overlooked objects are as common in the giant elliptical galaxy M87 as they are inmore » the giant spiral M31; they comprise about 40% of all classical nova eruptions and greatly increase the observational scatter in the MMRD relation. We use the extensive grid of the nova simulations of Yaron et al. to identify the underlying causes of the existence of faint, fast novae. These are systems that have accreted, and can thus eject, only very low-mass envelopes, of the order of 10 –7–10 –8 M ⊙, on massive white dwarfs. Such binaries include, but are not limited to, the recurrent novae. As a result, these same models predict the existence of ultrafast novae that display decline times, t 2, to be as short as five hours. We outline a strategy for their future detection.« less

Spatial variation in water loss predicts terrestrial salamander distribution and population dynamics.

PubMed

Peterman, W E; Semlitsch, R D

2014-10-01

Many patterns observed in ecology, such as species richness, life history variation, habitat use, and distribution, have physiological underpinnings. For many ectothermic organisms, temperature relationships shape these patterns, but for terrestrial amphibians, water balance may supersede temperature as the most critical physiologically limiting factor. Many amphibian species have little resistance to water loss, which restricts them to moist microhabitats, and may significantly affect foraging, dispersal, and courtship. Using plaster models as surrogates for terrestrial plethodontid salamanders (Plethodon albagula), we measured water loss under ecologically relevant field conditions to estimate the duration of surface activity time across the landscape. Surface activity time was significantly affected by topography, solar exposure, canopy cover, maximum air temperature, and time since rain. Spatially, surface activity times were highest in ravine habitats and lowest on ridges. Surface activity time was a significant predictor of salamander abundance, as well as a predictor of successful recruitment; the probability of a juvenile salamander occupying an area with high surface activity time was two times greater than an area with limited predicted surface activity. Our results suggest that survival, recruitment, or both are demographic processes that are affected by water loss and the ability of salamanders to be surface-active. Results from our study extend our understanding of plethodontid salamander ecology, emphasize the limitations imposed by their unique physiology, and highlight the importance of water loss to spatial population dynamics. These findings are timely for understanding the effects that fluctuating temperature and moisture conditions predicted for future climates will have on plethodontid salamanders.

Mechanical-Electrochemical-Thermal Simulation of Lithium-Ion Cells

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

Santhanagopalan, Shriram; Zhang, Chao; Sprague, Michael A.

2016-06-01

Models capture the force response for single-cell and cell-string levels to within 15%-20% accuracy and predict the location for the origin of failure based on the deformation data from the experiments. At the module level, there is some discrepancy due to poor mechanical characterization of the packaging material between the cells. The thermal response (location and value of maximum temperature) agrees qualitatively with experimental data. In general, the X-plane results agree with model predictions to within 20% (pending faulty thermocouples, etc.); the Z-plane results show a bigger variability both between the models and test-results, as well as among multiple repeatsmore » of the tests. The models are able to capture the timing and sequence in voltage drop observed in the multi-cell experiments; the shapes of the current and temperature profiles need more work to better characterize propagation. The cells within packaging experience about 60% less force under identical impact test conditions, so the packaging on the test articles is robust. However, under slow-crush simulations, the maximum deformation of the cell strings with packaging is about twice that of cell strings without packaging.« less

Long-wavelength Instability of Trailing Vortices Behind a Delta Wing

NASA Astrophysics Data System (ADS)

Miller, G. D.; Williamson, C. H. K.

1996-11-01

The long-wavelength instability of a vortex pair is studied in the wake of a delta wing. While many previous studies of the instability exist, almost none are accompanied by accurate measurements of the vortex core parameters upon which the theoretical predictions depend. The present measurements of wavelength and maximum growth rate from visualization images are accompanied by extensive DPIV measurements of the distributions of vorticity and axial velocity. Axial velocity was found to be wake-like, with a velocity deficit. The vorticity distribution in the cores is well modeled by an Oseen vortex, as is the downstream growth of the core. The naturally occuring wavelength was measured to be 4.5 times the inter-vortex spacing, which compares very well with the wavelength of maximum growth rate predicted by theory using measured core parameters. Also, the measured value of the growth rate and the lower stability limit correspond well with theory. The response of the wake to forcing is also examined, and reveals that the wake is receptive to forcing at wavelengths near the natural wavelength. We demonstrate control over the rate at which the wake decays by hastening the action of the instabilty with initial forcing. Supported by NDSEG Fellowship for first author.

An analysis of the surface-normal coupling efficiency of a metal grating coupler embedded in a Scotch tape optical waveguide

NASA Astrophysics Data System (ADS)

Barrios, Carlos Angulo; Canalejas-Tejero, Víctor

2017-01-01

The coupling efficiency at normal incidence of recently demonstrated aluminum grating couplers integrated in flexible Scotch tape waveguides has been analyzed theoretically and experimentally. Finite difference time domain (FDTD) and rigorously coupled wave analysis (RCWA) methods have been used to optimize the dimensions (duty cycle and metal thickness) of Scotch tape-embedded 1D Al gratings for maximum coupling at 635 nm wavelength. Good dimension and tape refractive index tolerances are predicted. FDTD simulations reveal the incident beam width and impinging position (alignment) values that avoid rediffraction and thus maximize the coupling efficiency. A 1D Al diffraction grating integrated into a Scotch tape optical waveguide has been fabricated and characterized. The fabrication process, based on pattern transfer, has been optimized to allow complete Al grating transfer onto the Scotch tape waveguide. A maximum coupling efficiency of 20% for TM-polarized normal incidence has been measured, which is in good agreement with the theoretical predictions. The measured coupling efficiency is further increased up to 28% for TM polarization under oblique incidence. Temperature dependence measurements have been also achieved and related to the simulations results and fabrication procedure.

Validity of one-repetition maximum predictive equations in men with spinal cord injury.

PubMed

Ribeiro Neto, F; Guanais, P; Dornelas, E; Coutinho, A C B; Costa, R R G

2017-10-01

Cross-sectional study. The study aimed (a) to test the cross-validation of current one-repetition maximum (1RM) predictive equations in men with spinal cord injury (SCI); (b) to compare the current 1RM predictive equations to a newly developed equation based on the 4- to 12-repetition maximum test (4-12RM). SARAH Rehabilitation Hospital Network, Brasilia, Brazil. Forty-five men aged 28.0 years with SCI between C6 and L2 causing complete motor impairment were enrolled in the study. Volunteers were tested, in a random order, in 1RM test or 4-12RM with 2-3 interval days. Multiple regression analysis was used to generate an equation for predicting 1RM. There were no significant differences between 1RM test and the current predictive equations. ICC values were significant and were classified as excellent for all current predictive equations. The predictive equation of Lombardi presented the best Bland-Altman results (0.5 kg and 12.8 kg for mean difference and interval range around the differences, respectively). The two created equation models for 1RM demonstrated the same and a high adjusted R 2 (0.971, P<0.01), but different SEE of measured 1RM (2.88 kg or 5.4% and 2.90 kg or 5.5%). All 1RM predictive equations are accurate to assess individuals with SCI at the bench press exercise. However, the predictive equation of Lombardi presented the best associated cross-validity results. A specific 1RM prediction equation was also elaborated for individuals with SCI. The created equation should be tested in order to verify whether it presents better accuracy than the current ones.

GASP: Gapped Ancestral Sequence Prediction for proteins

PubMed Central

Edwards, Richard J; Shields, Denis C

2004-01-01

Background The prediction of ancestral protein sequences from multiple sequence alignments is useful for many bioinformatics analyses. Predicting ancestral sequences is not a simple procedure and relies on accurate alignments and phylogenies. Several algorithms exist based on Maximum Parsimony or Maximum Likelihood methods but many current implementations are unable to process residues with gaps, which may represent insertion/deletion (indel) events or sequence fragments. Results Here we present a new algorithm, GASP (Gapped Ancestral Sequence Prediction), for predicting ancestral sequences from phylogenetic trees and the corresponding multiple sequence alignments. Alignments may be of any size and contain gaps. GASP first assigns the positions of gaps in the phylogeny before using a likelihood-based approach centred on amino acid substitution matrices to assign ancestral amino acids. Important outgroup information is used by first working down from the tips of the tree to the root, using descendant data only to assign probabilities, and then working back up from the root to the tips using descendant and outgroup data to make predictions. GASP was tested on a number of simulated datasets based on real phylogenies. Prediction accuracy for ungapped data was similar to three alternative algorithms tested, with GASP performing better in some cases and worse in others. Adding simple insertions and deletions to the simulated data did not have a detrimental effect on GASP accuracy. Conclusions GASP (Gapped Ancestral Sequence Prediction) will predict ancestral sequences from multiple protein alignments of any size. Although not as accurate in all cases as some of the more sophisticated maximum likelihood approaches, it can process a wide range of input phylogenies and will predict ancestral sequences for gapped and ungapped residues alike. PMID:15350199

Predictive model accuracy in estimating last Δ9-tetrahydrocannabinol (THC) intake from plasma and whole blood cannabinoid concentrations in chronic, daily cannabis smokers administered subchronic oral THC.

PubMed

Karschner, Erin L; Schwope, David M; Schwilke, Eugene W; Goodwin, Robert S; Kelly, Deanna L; Gorelick, David A; Huestis, Marilyn A

2012-10-01

Determining time since last cannabis/Δ9-tetrahydrocannabinol (THC) exposure is important in clinical, workplace, and forensic settings. Mathematical models calculating time of last exposure from whole blood concentrations typically employ a theoretical 0.5 whole blood-to-plasma (WB/P) ratio. No studies previously evaluated predictive models utilizing empirically-derived WB/P ratios, or whole blood cannabinoid pharmacokinetics after subchronic THC dosing. Ten male chronic, daily cannabis smokers received escalating around-the-clock oral THC (40-120 mg daily) for 8 days. Cannabinoids were quantified in whole blood and plasma by two-dimensional gas chromatography-mass spectrometry. Maximum whole blood THC occurred 3.0 h after the first oral THC dose and 103.5h (4.3 days) during multiple THC dosing. Median WB/P ratios were THC 0.63 (n=196), 11-hydroxy-THC 0.60 (n=189), and 11-nor-9-carboxy-THC (THCCOOH) 0.55 (n=200). Predictive models utilizing these WB/P ratios accurately estimated last cannabis exposure in 96% and 100% of specimens collected within 1-5h after a single oral THC dose and throughout multiple dosing, respectively. Models were only 60% and 12.5% accurate 12.5 and 22.5h after the last THC dose, respectively. Predictive models estimating time since last cannabis intake from whole blood and plasma cannabinoid concentrations were inaccurate during abstinence, but highly accurate during active THC dosing. THC redistribution from large cannabinoid body stores and high circulating THCCOOH concentrations create different pharmacokinetic profiles than those in less than daily cannabis smokers that were used to derive the models. Thus, the models do not accurately predict time of last THC intake in individuals consuming THC daily. Published by Elsevier Ireland Ltd.

Hydraulic droplet coarsening in open-channel capillaries

NASA Astrophysics Data System (ADS)

Warren, Patrick B.

2016-11-01

Over a range of liquid-solid contact angles, an open-channel capillary with curved or angled sides can show a maximum in the Laplace pressure as a function of the filling state. Examples include double-angle wedges, grooves scored into flat surfaces, steps on surfaces, and the groove between touching parallel cylinders. The liquid in such a channel exhibits a beading instability if the channel is filled beyond the Laplace pressure maximum. The subsequent droplet coarsening takes place by hydraulic transport through the connecting liquid columns that remain in the groove. A mean-field scaling argument predicts the characteristic droplet radius R ˜t1 /7 , as a function of time t . This is confirmed by one-dimensional simulations of the coarsening kinetics. Some remarks are also made on the spreading kinetics of an isolated drop deposited in such a channel.

Hydroelectric power plant on a paper strip.

PubMed

Das, Sankha Shuvra; Kar, Shantimoy; Anwar, Tarique; Saha, Partha; Chakraborty, Suman

2018-05-03

We exploit the combinatorial advantage of electrokinetics and tortuosity of a cellulose-based paper network on laboratory grade filter paper for the development of a simple, inexpensive, yet extremely robust (shows constant performance for 12 days) 'paper-and-pencil'-based device for energy harvesting applications. We successfully achieve harvesting of a maximum output power of ∼640 pW in a single channel, while the same is significantly improved (by ∼100 times) with the use of a multichannel microfluidic array (maximum of up to 20 channels). Furthermore, we also provide theoretical insights into the observed phenomenon and show that the experimentally predicted trends agree well with our theoretical calculations. Thus, we envisage that such ultra-low cost devices may turn out to be extremely useful in energizing analytical microdevices in resource limited settings, for instance, in extreme point of care diagnostic applications.

A general scaling law reveals why the largest animals are not the fastest.

PubMed

Hirt, Myriam R; Jetz, Walter; Rall, Björn C; Brose, Ulrich

2017-08-01

Speed is the fundamental constraint on animal movement, yet there is no general consensus on the determinants of maximum speed itself. Here, we provide a general scaling model of maximum speed with body mass, which holds across locomotion modes, ecosystem types and taxonomic groups. In contrast to traditional power-law scaling, we predict a hump-shaped relationship resulting from a finite acceleration time for animals, which explains why the largest animals are not the fastest. This model is strongly supported by extensive empirical data (474 species, with body masses ranging from 30 μg to 100 tonnes) from terrestrial as well as aquatic ecosystems. Our approach unravels a fundamental constraint on the upper limit of animal movement, thus enabling a better understanding of realized movement patterns in nature and their multifold ecological consequences.

Comparison of Forecast and Observed Energetics

NASA Technical Reports Server (NTRS)

Baker, W. E.; Brin, Y.

1985-01-01

An energetics analysis scheme was developed to compare the observed kinetic energy balance over North America with that derived from forecast cyclone case. It is found that: (1) the observed and predicted kinetic energy and eddy conversion are in good qualitative agreement, although the model eddy conversion tends to be 2 to 3 times stronger than the observed values. The eddy conversion which is stronger in the 12 h forecast than in observations and may be due to several factors is studied; (2) vertical profiles of kinetic energy generation and dissipation exhibit lower and upper tropospheric maxima in both the forecast and observations; and (3) a lag in the observational analysis with the maximum in the observed kinetic energy occurring at 0000 GMT 14 January over the same region as the maximum Eddy conversion 12 h earlier is noted.

Modeling of a resonant heat engine

NASA Astrophysics Data System (ADS)

Preetham, B. S.; Anderson, M.; Richards, C.

2012-12-01

A resonant heat engine in which the piston assembly is replaced by a sealed elastic cavity is modeled and analyzed. A nondimensional lumped-parameter model is derived and used to investigate the factors that control the performance of the engine. The thermal efficiency predicted by the model agrees with that predicted from the relation for the Otto cycle based on compression ratio. The predictions show that for a fixed mechanical load, increasing the heat input results in increased efficiency. The output power and power density are shown to depend on the loading for a given heat input. The loading condition for maximum output power is different from that required for maximum power density.

Hygrothermomechanical fracture stress criteria for fiber composites with sense-parity

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Ginty, C. A.

1983-01-01

Hygrothermomechanical fracture stress criteria are developed and evaluated for unidirectional composites (plies) with sense-parity. These criteria explicity quantify the individual contributions of applied, hygral and thermal stresses as well as couplings among these stresses. The criteria are for maximum stress, maximum strain, internal friction, work-to-fracture and combined-stress fracture. Predicted results obtained indicate that first ply failure will occur at stress levels lower than those predicted using criteria currently available in the literature. Also, the contribution of the various stress couplings (predictable only by fracture criteria with sense-parity) is significant to first ply failure and attendant fracture modes.

Optimisation of steam distillation extraction oil from onion by response surface methodology and its chemical composition.

PubMed

Wang, Zhao Dan; Li, Li Hua; Xia, Hui; Wang, Feng; Yang, Li Gang; Wang, Shao Kang; Sun, Gui Ju

2018-01-01

Oil extraction from onion was performed by steam distillation. Response surface methodology was applied to evaluate the effects of ratio of water to raw material, extraction time, zymolysis temperature and distillation times on yield of onion oil. The maximum extraction yield (1.779%) was obtained as following conditions: ratio of water to raw material was 1, extraction time was 2.5 h, zymolysis temperature was 36° and distillation time was 2.6 h. The experimental values agreed well with those predicted by regression model. The chemical composition of extracted onion oil under the optimum conditions was analysed by gas chromatography-mass spectrometry technology. The results showed that sulphur compounds, like alkanes, sulphide, alkenes, ester and alcohol, were the major components of onion oil.

Time-optimal excitation of maximum quantum coherence: Physical limits and pulse sequences

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

Köcher, S. S.; Institute of Energy and Climate Research; Heydenreich, T.

Here we study the optimum efficiency of the excitation of maximum quantum (MaxQ) coherence using analytical and numerical methods based on optimal control theory. The theoretical limit of the achievable MaxQ amplitude and the minimum time to achieve this limit are explored for a set of model systems consisting of up to five coupled spins. In addition to arbitrary pulse shapes, two simple pulse sequence families of practical interest are considered in the optimizations. Compared to conventional approaches, substantial gains were found both in terms of the achieved MaxQ amplitude and in pulse sequence durations. For a model system, theoreticallymore » predicted gains of a factor of three compared to the conventional pulse sequence were experimentally demonstrated. Motivated by the numerical results, also two novel analytical transfer schemes were found: Compared to conventional approaches based on non-selective pulses and delays, double-quantum coherence in two-spin systems can be created twice as fast using isotropic mixing and hard spin-selective pulses. Also it is proved that in a chain of three weakly coupled spins with the same coupling constants, triple-quantum coherence can be created in a time-optimal fashion using so-called geodesic pulses.« less

Energetics of emergence in the cicadas, Cyclochila australasiae and Abricta curvicosta (Homoptera: Cicadidae).

PubMed

Harvey, Prudence M; Thompson, Michael B

2006-09-01

The final moult in cicadas marks a major transition in lifestyle and is a behaviour that makes the cicada vulnerable to predation. Consequently, emergence times are short and, we predict, therefore the rate of energy consumption would be high. Hence, we measured the energetic cost of emergence in Cyclochila australasiae (green grocer) and Abricta curvicosta (floury baker) cicadas during the final moult from nymph to adult cicada. Maximum energy expended whilst emerging was compared between the sexes and species. Even though C. australasiae take longer to emerge than A. curvicosta, the mass-specific cost of emergence is not different between the two species (C. australasiae: 11.34+/-2.55 J g(-1); A. curvicosta: 12.91+/-1.90 J g(-1)). The mass-specific metabolic rates of fully emerged adults of both species are approximately twice those of the nymphs and the maximum metabolic rate during emergence is about 1.5 times higher than the resting metabolic rate of emerged adults. Emergence times, as indicated by rates of oxygen consumption, are longer than expected and probably reflect limitations in the oxygen capacity of the cicadas during moulting.

Validation of the Kp Geomagnetic Index Forecast at CCMC

NASA Astrophysics Data System (ADS)

Frechette, B. P.; Mays, M. L.

2017-12-01

The Community Coordinated Modeling Center (CCMC) Space Weather Research Center (SWRC) sub-team provides space weather services to NASA robotic mission operators and science campaigns and prototypes new models, forecasting techniques, and procedures. The Kp index is a measure of geomagnetic disturbances for space weather in the magnetosphere such as geomagnetic storms and substorms. In this study, we performed validation on the Newell et al. (2007) Kp prediction equation from December 2010 to July 2017. The purpose of this research is to understand the Kp forecast performance because it's critical for NASA missions to have confidence in the space weather forecast. This research was done by computing the Kp error for each forecast (average, minimum, maximum) and each synoptic period. Then to quantify forecast performance we computed the mean error, mean absolute error, root mean square error, multiplicative bias and correlation coefficient. A contingency table was made for each forecast and skill scores were computed. The results are compared to the perfect score and reference forecast skill score. In conclusion, the skill score and error results show that the minimum of the predicted Kp over each synoptic period from the Newell et al. (2007) Kp prediction equation performed better than the maximum or average of the prediction. However, persistence (reference forecast) outperformed all of the Kp forecasts (minimum, maximum, and average). Overall, the Newell Kp prediction still predicts within a range of 1, even though persistence beats it.

Forecasting the timing of peak mandibular growth in males by using skeletal age.

PubMed

Hunter, W Stuart; Baumrind, Sheldon; Popovich, Frank; Jorgensen, Gertrud

2007-03-01

It is generally believed that the orthodontic treatment of a patient with a Class II malocclusion and a small mandible is enhanced by good growth at puberty, so that the timing of peak mandibular growth at puberty becomes of interest. To test the belief that skeletal age, whether early, average, or late, can be used to predict the timing of maximum growth of the mandible, whether early, average, or late, the predictive relationship between skeletal age and peak mandibular growth velocity (PMdV) at puberty was evaluated in 94 boys by using their longitudinal records from 4 to 18 years of age. Skeletal age was determined for each subject at ages 9 through 14 by using the method of Greulich and Pyle. At age 9, the Greulich and Pyle measurements predicted that 30 of the 94 subjects would have delayed PMdV equal to or exceeding 1 SD (of the mean age for PMdV), and 10 would have advanced PMdV equal to or exceeding 1 SD. When the actual age of PMdV was determined retrospectively from plots of annual mandibular growth increments, it was found that only 4 of the 30 in the delayed group had actually experienced delays in PMdV, and only 2 of the 10 in the advanced group had experienced accelerated PMdV. Skeletal age is not a reliable predictor of the timing of PMdV.

A Health-Based Metric for Evaluating the Effectiveness of Noise Barrier Mitigation Associated With Transport Infrastructure Noise.

PubMed

Prendergast, Geoffrey P; Staff, Michael

2017-01-01

This study examines the use of the number of night-time sleep disturbances as a health-based metric to assess the cost effectiveness of rail noise mitigation strategies for situations, wherein high-intensity noises dominate such as freight train pass-bys and wheel squeal. Twenty residential properties adjacent to the existing and proposed rail tracks in a noise catchment area of the Epping to Thornleigh Third Track project were used as a case study. Awakening probabilities were calculated for individual's awakening 1, 3 and 5 times a night when subjected to 10 independent freight train pass-by noise events using internal maximum sound pressure levels (LAFmax). Awakenings were predicted using a random intercept multivariate logistic regression model. With source mitigation in place, the majority of the residents were still predicted to be awoken at least once per night (median 88.0%), although substantial reductions in the median probabilities of awakening three and five times per night from 50.9 to 29.4% and 9.2 to 2.7%, respectively, were predicted. This resulted in a cost-effective estimate of 7.6-8.8 less people being awoken at least three times per night per A$1 million spent on noise barriers. The study demonstrates that an easily understood metric can be readily used to assist making decisions related to noise mitigation for large-scale transport projects.

A climate-based spatiotemporal prediction for dengue fever epidemics: a case study in southern Taiwan

NASA Astrophysics Data System (ADS)

Yu, H.-L.; Yang, S.-J.; Lin, Y.-C.

2012-04-01

Dengue Fever (DF) has been identified by the World Health organization (WHO) as one of the most serious vector-borne infectious diseases in tropical and sub-tropical areas. DF has been one of the most important epidemics in Taiwan which occur annually especially in southern Taiwan during summer and autumn. Most DF studies have focused mainly on temporal DF patterns and its close association with climatic covariates, whereas few studies have investigated the spatial DF patterns (spatial dependence and clustering) and composite space-time effects of the DF epidemics. The present study proposes a spatio-temporal DF prediction approach based on stochastic Bayesian Maximum Entropy (BME) analysis. Core and site-specific knowledge bases are considered, including climate and health datasets under conditions of uncertainty, space-time dependence functions, and a Poisson regression model of climatic variables contributing to DF occurrences in southern Taiwan during 2007, when the highest number of DF cases was recorded in the history of Taiwan epidemics (over 2000). The obtained results show that the DF outbreaks in the study area are highly influenced by climatic conditions. Furthermore, the analysis can provide the required "one-week-ahead" outbreak warnings based on spatio-temporal predictions of DF distributions. Therefore, the proposed analysis can provide the Taiwan Disease Control Agency with a valuable tool to timely identify, control, and even efficiently prevent DF spreading across space-time.

Application of the Maximum Amplitude-Early Rise Correlation to Cycle 23

NASA Technical Reports Server (NTRS)

Willson, Robert M.; Hathaway, David H.

2004-01-01

On the basis of the maximum amplitude-early rise correlation, cycle 23 could have been predicted to be about the size of the mean cycle as early as 12 mo following cycle minimum. Indeed, estimates for the size of cycle 23 throughout its rise consistently suggested a maximum amplitude that would not differ appreciably from the mean cycle, contrary to predictions based on precursor information. Because cycle 23 s average slope during the rising portion of the solar cycle measured 2.4, computed as the difference between the conventional maximum (120.8) and minimum (8) amplitudes divided by the ascent duration in months (47), statistically speaking, it should be a cycle of shorter period. Hence, conventional sunspot minimum for cycle 24 should occur before December 2006, probably near July 2006 (+/-4 mo). However, if cycle 23 proves to be a statistical outlier, then conventional sunspot minimum for cycle 24 would be delayed until after July 2007, probably near December 2007 (+/-4 mo). In anticipation of cycle 24, a chart and table are provided for easy monitoring of the nearness and size of its maximum amplitude once onset has occurred (with respect to the mean cycle and using the updated maximum amplitude-early rise relationship).

Inferences on mass composition and tests of hadronic interactions from 0.3 to 100 EeV using the water-Cherenkov detectors of the Pierre Auger Observatory

NASA Astrophysics Data System (ADS)

Aab, A.; Abreu, P.; Aglietta, M.; Al Samarai, I.; Albuquerque, I. F. M.; Allekotte, I.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Anastasi, G. A.; Anchordoqui, L.; Andrada, B.; Andringa, S.; Aramo, C.; Arqueros, F.; Arsene, N.; Asorey, H.; Assis, P.; Aublin, J.; Avila, G.; Badescu, A. M.; Balaceanu, A.; Barbato, F.; Barreira Luz, R. J.; Beatty, J. J.; Becker, K. H.; Bellido, J. A.; Berat, C.; Bertaina, M. E.; Bertou, X.; Biermann, P. L.; Biteau, J.; Blaess, S. G.; Blanco, A.; Blazek, J.; Bleve, C.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Borodai, N.; Botti, A. M.; Brack, J.; Brancus, I.; Bretz, T.; Bridgeman, A.; Briechle, F. L.; Buchholz, P.; Bueno, A.; Buitink, S.; Buscemi, M.; Caballero-Mora, K. S.; Caccianiga, L.; Cancio, A.; Canfora, F.; Caramete, L.; Caruso, R.; Castellina, A.; Catalani, F.; Cataldi, G.; Cazon, L.; Chavez, A. G.; Chinellato, J. A.; Chudoba, J.; Clay, R. W.; Cobos, A.; Colalillo, R.; Coleman, A.; Collica, L.; Coluccia, M. R.; Conceição, R.; Consolati, G.; Contreras, F.; Cooper, M. J.; Coutu, S.; Covault, C. E.; Cronin, J.; D'Amico, S.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; de Jong, S. J.; De Mauro, G.; de Mello Neto, J. R. T.; De Mitri, I.; de Oliveira, J.; de Souza, V.; Debatin, J.; Deligny, O.; Díaz Castro, M. L.; Diogo, F.; Dobrigkeit, C.; D'Olivo, J. C.; Dorosti, Q.; dos Anjos, R. C.; Dova, M. T.; Dundovic, A.; Ebr, J.; Engel, R.; Erdmann, M.; Erfani, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Falcke, H.; Farmer, J.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Fenu, F.; Fick, B.; Figueira, J. M.; Filipčič, A.; Fratu, O.; Freire, M. M.; Fujii, T.; Fuster, A.; Gaior, R.; García, B.; Garcia-Pinto, D.; Gaté, F.; Gemmeke, H.; Gherghel-Lascu, A.; Ghia, P. L.; Giaccari, U.; Giammarchi, M.; Giller, M.; Głas, D.; Glaser, C.; Golup, G.; Gómez Berisso, M.; Gómez Vitale, P. F.; González, N.; Gorgi, A.; Gorham, P.; Grillo, A. F.; Grubb, T. D.; Guarino, F.; Guedes, G. P.; Halliday, R.; Hampel, M. R.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Heimann, P.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Holt, E.; Homola, P.; Hörandel, J. R.; Horvath, P.; Hrabovský, M.; Huege, T.; Hulsman, J.; Insolia, A.; Isar, P. G.; Jandt, I.; Johnsen, J. A.; Josebachuili, M.; Jurysek, J.; Kääpä, A.; Kambeitz, O.; Kampert, K. H.; Keilhauer, B.; Kemmerich, N.; Kemp, E.; Kemp, J.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Krause, R.; Krohm, N.; Kuempel, D.; Kukec Mezek, G.; Kunka, N.; Kuotb Awad, A.; Lago, B. L.; LaHurd, D.; Lang, R. G.; Lauscher, M.; Legumina, R.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; Lo Presti, D.; Lopes, L.; López, R.; López Casado, A.; Lorek, R.; Luce, Q.; Lucero, A.; Malacari, M.; Mallamaci, M.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Mariş, I. C.; Marsella, G.; Martello, D.; Martinez, H.; Martínez Bravo, O.; Masías Meza, J. J.; Mathes, H. J.; Mathys, S.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Mayotte, E.; Mazur, P. O.; Medina, C.; Medina-Tanco, G.; Melo, D.; Menshikov, A.; Merenda, K.-D.; Michal, S.; Micheletti, M. I.; Middendorf, L.; Miramonti, L.; Mitrica, B.; Mockler, D.; Mollerach, S.; Montanet, F.; Morello, C.; Mostafá, M.; Müller, A. L.; Müller, G.; Muller, M. A.; Müller, S.; Mussa, R.; Naranjo, I.; Nellen, L.; Nguyen, P. H.; Niculescu-Oglinzanu, M.; Niechciol, M.; Niemietz, L.; Niggemann, T.; Nitz, D.; Nosek, D.; Novotny, V.; Nožka, L.; Núñez, L. A.; Ochilo, L.; Oikonomou, F.; Olinto, A.; Palatka, M.; Pallotta, J.; Papenbreer, P.; Parente, G.; Parra, A.; Paul, T.; Pech, M.; Pedreira, F.; Pekala, J.; Pelayo, R.; Peña-Rodriguez, J.; Pereira, L. A. S.; Perlin, M.; Perrone, L.; Peters, C.; Petrera, S.; Phuntsok, J.; Piegaia, R.; Pierog, T.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Porowski, C.; Prado, R. R.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Quinn, S.; Ramos-Pollan, R.; Rautenberg, J.; Ravignani, D.; Ridky, J.; Riehn, F.; Risse, M.; Ristori, P.; Rizi, V.; Rodrigues de Carvalho, W.; Rodriguez Fernandez, G.; Rodriguez Rojo, J.; Rogozin, D.; Roncoroni, M. J.; Roth, M.; Roulet, E.; Rovero, A. C.; Ruehl, P.; Saffi, S. J.; Saftoiu, A.; Salamida, F.; Salazar, H.; Saleh, A.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Sanchez-Lucas, P.; Santos, E. M.; Santos, E.; Sarazin, F.; Sarmento, R.; Sarmiento-Cano, C.; Sato, R.; Schauer, M.; Scherini, V.; Schieler, H.; Schimp, M.; Schmidt, D.; Scholten, O.; Schovánek, P.; Schröder, F. G.; Schröder, S.; Schulz, A.; Schumacher, J.; Sciutto, S. J.; Segreto, A.; Shadkam, A.; Shellard, R. C.; Sigl, G.; Silli, G.; Sima, O.; Śmiałkowski, A.; Šmída, R.; Smith, B.; Snow, G. R.; Sommers, P.; Sonntag, S.; Squartini, R.; Stanca, D.; Stanič, S.; Stasielak, J.; Stassi, P.; Stolpovskiy, M.; Strafella, F.; Streich, A.; Suarez, F.; Suarez Durán, M.; Sudholz, T.; Suomijärvi, T.; Supanitsky, A. D.; Šupík, J.; Swain, J.; Szadkowski, Z.; Taboada, A.; Taborda, O. A.; Theodoro, V. M.; Timmermans, C.; Todero Peixoto, C. J.; Tomankova, L.; Tomé, B.; Torralba Elipe, G.; Travnicek, P.; Trini, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van Aar, G.; van Bodegom, P.; van den Berg, A. M.; van Vliet, A.; Varela, E.; Vargas Cárdenas, B.; Varner, G.; Vázquez, R. A.; Veberič, D.; Ventura, C.; Vergara Quispe, I. D.; Verzi, V.; Vicha, J.; Villaseñor, L.; Vorobiov, S.; Wahlberg, H.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weindl, A.; Wiencke, L.; Wilczyński, H.; Wileman, C.; Wirtz, M.; Wittkowski, D.; Wundheiler, B.; Yang, L.; Yushkov, A.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zepeda, A.; Zimmermann, B.; Ziolkowski, M.; Zong, Z.; Zuccarello, F.; Pierre Auger Collaboration

2017-12-01

We present a new method for probing the hadronic interaction models at ultrahigh energy and extracting details about mass composition. This is done using the time profiles of the signals recorded with the water-Cherenkov detectors of the Pierre Auger Observatory. The profiles arise from a mix of the muon and electromagnetic components of air showers. Using the risetimes of the recorded signals, we define a new parameter, which we use to compare our observations with predictions from simulations. We find, first, inconsistencies between our data and predictions over a greater energy range and with substantially more events than in previous studies. Second, by calibrating the new parameter with fluorescence measurements from observations made at the Auger Observatory, we can infer the depth of shower maximum Xmax for a sample of over 81,000 events extending from 0.3 to over 100 EeV. Above 30 EeV, the sample is nearly 14 times larger than what is currently available from fluorescence measurements and extending the covered energy range by half a decade. The energy dependence of ⟨Xmax⟩ is compared to simulations and interpreted in terms of the mean of the logarithmic mass. We find good agreement with previous work and extend the measurement of the mean depth of shower maximum to greater energies than before, reducing significantly the statistical uncertainty associated with the inferences about mass composition.

Modeling and verification of process parameters for the production of tannase by Aspergillus oryzae under submerged fermentation using agro-wastes.

PubMed

Varadharajan, Venkatramanan; Vadivel, Sudhan Shanmuga; Ramaswamy, Arulvel; Sundharamurthy, Venkatesaprabhu; Chandrasekar, Priyadharshini

2017-01-01

Tannase production by Aspergillus oryzae using various agro-wastes as substrates by submerged fermentation was studied in this research. The microbe was isolated from degrading corn kernel obtained from the corn fields at Tiruchengode, India. The microbial identification was done using 18S rRNA gene analysis. The agro-wastes chosen for the study were pomegranate rind, Cassia auriculata flower, black gram husk, and tea dust. The process parameters chosen for optimization study were substrate concentration, pH, temperature, and incubation period. During one variable at a time optimization, the pomegranate rind extract produced maximum tannase activity of 138.12 IU/mL and it was chosen as the best substrate for further experiments. The quadratic model was found to be the effective model for prediction of tannase production by A. oryzae. The optimized conditions predicted by response surface methodology (RSM) with genetic algorithm (GA) were 1.996% substrate concentration, pH of 4.89, temperature of 34.91 °C, and an incubation time of 70.65 H with maximum tannase activity of 138.363 IU/mL. The confirmatory experiment under optimized conditions showed tannase activity of 139.22 IU/mL. Hence, RSM-GA pair was successfully used in this study to optimize the process parameters required for the production of tannase using pomegranate rind. © 2015 International Union of Biochemistry and Molecular Biology, Inc.

Statistical self-similarity of width function maxima with implications to floods

USGS Publications Warehouse

Veitzer, S.A.; Gupta, V.K.

2001-01-01

Recently a new theory of random self-similar river networks, called the RSN model, was introduced to explain empirical observations regarding the scaling properties of distributions of various topologic and geometric variables in natural basins. The RSN model predicts that such variables exhibit statistical simple scaling, when indexed by Horton-Strahler order. The average side tributary structure of RSN networks also exhibits Tokunaga-type self-similarity which is widely observed in nature. We examine the scaling structure of distributions of the maximum of the width function for RSNs for nested, complete Strahler basins by performing ensemble simulations. The maximum of the width function exhibits distributional simple scaling, when indexed by Horton-Strahler order, for both RSNs and natural river networks extracted from digital elevation models (DEMs). We also test a powerlaw relationship between Horton ratios for the maximum of the width function and drainage areas. These results represent first steps in formulating a comprehensive physical statistical theory of floods at multiple space-time scales for RSNs as discrete hierarchical branching structures. ?? 2001 Published by Elsevier Science Ltd.

Improving a free air breathing proton exchange membrane fuel cell through the Maximum Efficiency Point Tracking method

NASA Astrophysics Data System (ADS)

Higuita Cano, Mauricio; Mousli, Mohamed Islam Aniss; Kelouwani, Sousso; Agbossou, Kodjo; Hammoudi, Mhamed; Dubé, Yves

2017-03-01

This work investigates the design and validation of a fuel cell management system (FCMS) which can perform when the fuel cell is at water freezing temperature. This FCMS is based on a new tracking technique with intelligent prediction, which combined the Maximum Efficiency Point Tracking with variable perturbation-current step and the fuzzy logic technique (MEPT-FL). Unlike conventional fuel cell control systems, our proposed FCMS considers the cold-weather conditions, the reduction of fuel cell set-point oscillations. In addition, the FCMS is built to respond quickly and effectively to the variations of electric load. A temperature controller stage is designed in conjunction with the MEPT-FL in order to operate the FC at low-temperature values whilst tracking at the same time the maximum efficiency point. The simulation results have as well experimental validation suggest that propose approach is effective and can achieve an average efficiency improvement up to 8%. The MEPT-FL is validated using a Proton Exchange Membrane Fuel Cell (PEMFC) of 500 W.

Hierarchical Star Formation in Turbulent Media: Evidence from Young Star Clusters

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

Grasha, K.; Calzetti, D.; Elmegreen, B. G.

We present an analysis of the positions and ages of young star clusters in eight local galaxies to investigate the connection between the age difference and separation of cluster pairs. We find that star clusters do not form uniformly but instead are distributed so that the age difference increases with the cluster pair separation to the 0.25–0.6 power, and that the maximum size over which star formation is physically correlated ranges from ∼200 pc to ∼1 kpc. The observed trends between age difference and separation suggest that cluster formation is hierarchical both in space and time: clusters that are closemore » to each other are more similar in age than clusters born further apart. The temporal correlations between stellar aggregates have slopes that are consistent with predictions of turbulence acting as the primary driver of star formation. The velocity associated with the maximum size is proportional to the galaxy’s shear, suggesting that the galactic environment influences the maximum size of the star-forming structures.« less

Use of global assays to understand clinical phenotype in congenital factor VII deficiency.

PubMed

Greene, L A; Goldenberg, N A; Simpson, M L; Villalobos-Menuey, E; Bombardier, C; Acharya, S S; Santiago-Borrero, P J; Cambara, A; DiMichele, D M

2013-09-01

Congenital factor VII (FVII) deficiency is characterized by genotypic variability and phenotypic heterogeneity. Traditional screening and factor assays are unable to reliably predict clinical bleeding phenotype and guide haemorrhage prevention strategy. Global assays of coagulation and fibrinolysis may better characterize overall haemostatic balance and aid in haemorrhagic risk assessment. We evaluated the ability of novel global assays to better understand clinical bleeding severity in congenital FVII deficiency. Subjects underwent central determination of factor VII activity (FVII:C) as well as clot formation and lysis (CloFAL) and simultaneous thrombin and plasmin generation (STP) global assay analysis. A bleeding score was assigned to each subject through medical chart review. Global assay parameters were analysed with respect to bleeding score and FVII:C. Subgroup analyses were performed on paediatric subjects and subjects with FVII ≥ 1 IU dL(-1). CloFAL fibrinolytic index (FI2 ) inversely correlated with FVII:C while CloFAL maximum amplitude (MA) and STP maximum velocity of thrombin generation (VT max) varied directly with FVII:C. CloFAL FI2 directly correlated with bleeding score among subjects in both the total cohort and paediatric subcohort, but not among subjects with FVII ≥ 1 IU dL(-1) . Among subjects with FVII ≥ 1 IU dL(-1), STP time to maximum velocity of thrombin generation and time to maximum velocity of plasmin generation inversely correlated with bleeding score. These preliminary findings suggest a novel potential link between a hyperfibrinolytic state in bleeding severity and congenital FVII deficiency, an observation that should be further explored. © 2013 John Wiley & Sons Ltd.

Assessing cutoff values for increased exercise blood pressure to predict incident hypertension in a general population.

PubMed

Lorbeer, Roberto; Ittermann, Till; Völzke, Henry; Gläser, Sven; Ewert, Ralf; Felix, Stephan B; Dörr, Marcus

2015-07-01

Cutoff values for increased exercise blood pressure (BP) are not established in hypertension guidelines. The aim of the study was to assess optimal cutoff values for increased exercise BP to predict incident hypertension. Data of 661 normotensive participants (386 women) aged 25-77 years from the Study of Health in Pomerania (SHIP-1) with a 5-year follow-up were used. Exercise BP was measured at a submaximal level of 100 W and at maximum level of a symptom-limited cycle ergometry test. Cutoff values for increased exercise BP were defined at the maximum sum of sensitivity and specificity for the prediction of incident hypertension. The area under the receiver-operating characteristic curve (AUC) and net reclassification index (NRI) were calculated to investigate whether increased exercise BP adds predictive value for incident hypertension beyond established cardiovascular risk factors. In men, values of 160  mmHg (100  W level; AUC = 0.7837; NRI = 0.534, P < 0.001) and 210  mmHg (maximum level; AUC = 0.7677; NRI = 0.340, P = 0.003) were detected as optimal cutoff values for the definition of increased exercise SBP. A value of 190  mmHg (AUC = 0.8347; NRI = 0.519, P < 0.001) showed relevance for the definition of increased exercise SBP in women at the maximum level. According to our analyses, 190 and 210  mmHg are clinically relevant cutoff values for increased exercise SBP at the maximum exercise level of cycle ergometry test for women and men, respectively. In addition, for men, our analyses provided a cutoff value of 160  mmHg for increased exercise SBP at the 100  W level.

Predicting forest insect flight activity: A Bayesian network approach

PubMed Central

Pawson, Stephen M.; Marcot, Bruce G.; Woodberry, Owen G.

2017-01-01

Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight activity of three exotic insects, Hylurgus ligniperda, Hylastes ater, and Arhopalus ferus in a managed plantation forest context. Models were built from 7,144 individual hours of insect sampling, temperature, wind speed, relative humidity, photon flux density, and temporal data. Discretized meteorological and temporal variables were used to build naïve Bayes tree augmented networks. Calibration results suggested that the H. ater and A. ferus Bayesian network models had the best fit for low Type I and overall errors, and H. ligniperda had the best fit for low Type II errors. Maximum hourly temperature and time since sunrise had the largest influence on H. ligniperda flight activity predictions, whereas time of day and year had the greatest influence on H. ater and A. ferus activity. Type II model errors for the prediction of no flight activity is improved by increasing the model’s predictive threshold. Improvements in model performance can be made by further sampling, increasing the sensitivity of the flight intercept traps, and replicating sampling in other regions. Predicting insect flight informs an assessment of the potential phytosanitary risks of wood exports. Quantifying this risk allows mitigation treatments to be targeted to prevent the spread of invasive species via international trade pathways. PMID:28953904

Early Detection of Postoperative Acute Kidney Injury in Acute Stanford Type A Aortic Dissection With Doppler Renal Resistive Index.

PubMed

Qin, Huai; Wu, Haibo; Chen, Yi; Zhang, Nan; Fan, Zhanming

2017-10-01

This study aimed to evaluate the early efficiency of Doppler renal resistive index (DRRI) in prediction of acute kidney injury (AKI) after surgery in acute Stanford Type A aortic dissection (AAAD) patients. Sixty-one AAAD patients who planned to receive Sun's surgical management were prospectively enrolled. The DRRI was measured by ultrasonography Doppler on the day before surgery (DRRI pre ), on admission to the intensive care unit (DRRI T0 ), 6 hours after surgery (DRRI T6 ), 24 hours after surgery (DRRI T24 ), and 48 hours after surgery (DRRI T48 ). The maximum DRRI value (DRRI max ) was recorded. The AKI was evaluated according to the classifications of the Acute Kidney Injury Network. The DRRI and serum creatinine (sCr) were compared between the pre- and postoperative time stations, as well as between the AKI and no-AKI groups. Thirty-nine (63.9%) patients suffered from AKI, and 12 (19.6%) patients received dialysis. No significant difference was found in DRRI pre (0.63 ± 0.04 versus 0.65 ± 0.06, P = .059) and sCr pre (84.13 ± 23.77 versus 94.29 ± 51.11, P = .383) between the two groups with and without AKI. Both the DRRI and sCr increased significantly after surgery in the AKI groups (P < .001). However, the DRRI reached its maximum 6 hours after surgery, whereas the sCr reached its maximum after 24 hours. Both the DRRI and sCr improved 48 hours after surgery. The area under the receiver operating characteristic curve for DRRI max (0.864, 95% confidence interval: 0.770-0.957) and DRRI T6 (0.861, 95% confidence interval: 0.766-0.957) was larger than the other three DRRIs measured at different time points. The cutoff value of DRRI max was 0.71, a sensitivity of 76.9% and specificity of 95.5%. Postoperative DRRI predicts the AKI earlier than sCr after AAAD surgery. The best time to detect DRRI was 6 hours after surgery. © 2017 by the American Institute of Ultrasound in Medicine.

Recent Shift in Climate Relationship Enables Prediction of the Timing of Bird Breeding

PubMed Central

Bellamy, Paul E.; Hill, Ross A.; Ferns, Peter N.

2016-01-01

Large-scale climate processes influence many aspects of ecology including breeding phenology, reproductive success and survival across a wide range of taxa. Some effects are direct, for example, in temperate-zone birds, ambient temperature is an important cue enabling breeding effort to coincide with maximum food availability, and earlier breeding in response to warmer springs has been documented in many species. In other cases, time-lags of up to several years in ecological responses have been reported, with effects mediated through biotic mechanisms such as growth rates or abundance of food supplies. Here we use 23 years of data for a temperate woodland bird species, the great tit (Parus major), breeding in deciduous woodland in eastern England to demonstrate a time-lagged linear relationship between the on-set of egg laying and the winter index of the North Atlantic Oscillation such that timing can be predicted from the winter index for the previous year. Thus the timing of bird breeding (and, by inference, the timing of spring events in general) can be predicted one year in advance. We also show that the relationship with the winter index appears to arise through an abiotic time-lag with local spring warmth in our study area. Examining this link between local conditions and larger-scale processes in the longer-term showed that, in the past, significant relationships with the immediately preceding winter index were more common than those with the time-lagged index, and especially so from the late 1930s to the early 1970s. However, from the mid 1970s onwards, the time-lagged relationship has become the most significant, suggesting a recent change in climate patterns. The strength of the current time-lagged relationship suggests that it might have relevance for other temperature-dependent ecological relationships. PMID:27182711

Improved GIA Correction and Antarctic Contribution to Sea-level Rise Observed by GRACE

NASA Astrophysics Data System (ADS)

Ivins, Erik; James, Thomas; Wahr, John; Schrama, Ernst; Landerer, Felix; Simon, Karen

2013-04-01

Measurement of continent-wide glacial isostatic adjustment (GIA) is needed to interpret satellite-based trends for the grounded ice mass change of the Antarctic ice sheet (AIS). This is especially true for trends determined from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. Three data sets have matured to the point where they can be used to shrink the range of possible GIA models for Antarctica: the glacial geological record has expanded to include exposure ages using 10Be,26Al measurements that constrain past thickness of the ice sheet, modelled ice core records now better constrain the temporal variation in past rates of snow accumulation, and Global Positioning System (GPS) vertical rate trends from across the continent are now available. The volume changes associated with Antarctic ice loading and unloading during the past 21 thousand years (21 ka) are smaller than previously thought, generating model present-day uplift rates that are consistent with GPS observations. We construct an ice sheet history that is designed to predict maximum volume changes, and in particular, maximum Holocene change. This ice sheet model drives a forward model prediction of GIA gravity signal, that in turn, should give maximum GIA response predictions. The apparent surface mass change component of GIA is re-evaluated to be +55 ± 13 Gt/yr by considering a revised ice history model and a parameter search for vertical motion predictions that best-fit the GPS observations at 18 high-quality stations. Although the GIA model spans a wide range of possible earth rheological structure values, the data are not yet sufficient for solving for a preferred value of upper and lower mantle viscosity, nor for a preferred lithospheric thickness. GRACE monthly solutions from CSR-RL04 release time series from Jan. 2003 through the beginning of Jan. 2012, uncorrected for GIA, yield an ice mass rate of +2.9 ± 34 Gt/yr. A new rough upper bound to the GIA correction is about 60-65 Gt/yr. The new correction increases the solved-for ice mass imbalance of Antarctica to -57 ± 34 Gt/yr. The revised GIA correction is smaller than past GRACE estimates by about 50 to 90 Gt/yr. The new upper bound to sea-level rise from AIS mass loss averaged over the time span 2003.0 - 2012.0 is about 0.16 ± 0.09 mm/yr. We discuss the differences in spatio-temporal character of the gain-loss regimes of Antarctica over the observing period.

Predicting moisture and economic value of solid forest fuel piles for improving the profitability of bioenergy use

NASA Astrophysics Data System (ADS)

Lauren, Ari; Kinnunen, Jyrki-Pekko; Sikanen, Lauri

2016-04-01

Bioenergy contributes 26 % of the total energy use in Finland, and 60 % of this is provided by solid forest fuel consisting of small stems and logging residues such as tops, branches, roots and stumps. Typically the logging residues are stored as piles on site before transporting to regional combined heat and power plants for combustion. Profitability of forest fuel use depends on smart control of the feedstock. Fuel moisture, dry matter loss, and the rate of interest during the storing are the key variables affecting the economic value of the fuel. The value increases with drying, but decreases with wetting, dry matter loss and positive rate of interest. We compiled a simple simulation model computing the moisture change, dry matter loss, transportation costs and present value of feedstock piles. The model was used to predict the time of the maximum value of the stock, and to compose feedstock allocation strategies under the question: how should we choose the piles and the combustion time so that total energy yield and the economic value of the energy production is maximized? The question was assessed concerning the demand of the energy plant. The model parameterization was based on field scale studies. The initial moisture, and the rates of daily moisture change and dry matter loss in the feedstock piles depended on the day of the year according to empirical field measurements. Time step of the computation was one day. Effects of pile use timing on the total energy yield and profitability was studied using combinatorial optimization. Results show that the storing increases the pile maximum value if the natural drying onsets soon after the harvesting; otherwise dry matter loss and the capital cost of the storing overcome the benefits gained by drying. Optimized timing of the pile use can improve slightly the profitability, based on the increased total energy yield and because the energy unit based transportation costs decrease when water content in the biomass is decreased.

Support Vector Machines for Differential Prediction

PubMed Central

Kuusisto, Finn; Santos Costa, Vitor; Nassif, Houssam; Burnside, Elizabeth; Page, David; Shavlik, Jude

2015-01-01

Machine learning is continually being applied to a growing set of fields, including the social sciences, business, and medicine. Some fields present problems that are not easily addressed using standard machine learning approaches and, in particular, there is growing interest in differential prediction. In this type of task we are interested in producing a classifier that specifically characterizes a subgroup of interest by maximizing the difference in predictive performance for some outcome between subgroups in a population. We discuss adapting maximum margin classifiers for differential prediction. We first introduce multiple approaches that do not affect the key properties of maximum margin classifiers, but which also do not directly attempt to optimize a standard measure of differential prediction. We next propose a model that directly optimizes a standard measure in this field, the uplift measure. We evaluate our models on real data from two medical applications and show excellent results. PMID:26158123

Support Vector Machines for Differential Prediction.

PubMed

Kuusisto, Finn; Santos Costa, Vitor; Nassif, Houssam; Burnside, Elizabeth; Page, David; Shavlik, Jude

Machine learning is continually being applied to a growing set of fields, including the social sciences, business, and medicine. Some fields present problems that are not easily addressed using standard machine learning approaches and, in particular, there is growing interest in differential prediction . In this type of task we are interested in producing a classifier that specifically characterizes a subgroup of interest by maximizing the difference in predictive performance for some outcome between subgroups in a population. We discuss adapting maximum margin classifiers for differential prediction. We first introduce multiple approaches that do not affect the key properties of maximum margin classifiers, but which also do not directly attempt to optimize a standard measure of differential prediction. We next propose a model that directly optimizes a standard measure in this field, the uplift measure. We evaluate our models on real data from two medical applications and show excellent results.

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

Lian, J; Yuan, L; Wu, Q

Purpose: The quality and efficiency of radiotherapy treatment planning are highly planer dependent. Previously we have developed a statistical model to correlate anatomical features with dosimetry features of head and neck Tomotherapy treatment. The model enables us to predict the best achievable dosimetry for individual patient prior to treatment planning. The purpose of this work is to study if the prediction model can facilitate the treatment planning in both the efficiency and dosimetric quality. Methods: The anatomy-dosimetry correlation model was used to calculate the expected DVH for nine patients formerly treated. In Group A (3 patients), the model prediction agreedmore » with the clinic plan; in Group B (3 patients), the model predicted lower larynx mean dose than the clinic plan; in Group C (3 patients), the model suggested the brainstem could be further spared. Guided by the prior knowledge, we re-planned all 9 cases. The number of interactions during the optimization process and dosimetric endpoints between the original clinical plan and model-guided re-plan were compared. Results: For Group A, the difference of target coverage and organs-at-risk sparing is insignificant (p>0.05) between the replan and the clinical plan. For Group B, the clinical plan larynx median dose is 49.4±4.7 Gy, while the prediction suggesting 40.0±6.2 Gy (p<0.05). The re-plan achieved 41.5±6.6 Gy, with similar dose on other structures as clinical plan. For Group C, the clinical plan brainstem maximum dose is 44.7±5.5 Gy. The model predicted lower value 32.2±3.8 Gy (p<0.05). The re-plans reduced brainstem maximum dose to 31.8±4.1 Gy without affecting the dosimetry of other structures. In the replanning of the 9 cases, the times operator interacted with TPS are reduced on average about 50% compared to the clinical plan. Conclusion: We have demonstrated that the prior expert knowledge embedded model improved the efficiency and quality of Tomotherapy treatment planning.« less

Application of Artificial Intelligence to the Prediction of the Antimicrobial Activity of Essential Oils.

PubMed

Daynac, Mathieu; Cortes-Cabrera, Alvaro; Prieto, Jose M

2015-01-01

Essential oils (EOs) are vastly used as natural antibiotics in Complementary and Alternative Medicine (CAM). Their intrinsic chemical variability and synergisms/antagonisms between its components make difficult to ensure consistent effects through different batches. Our aim is to evaluate the use of artificial neural networks (ANNs) for the prediction of their antimicrobial activity. Methods. The chemical composition and antimicrobial activity of 49 EOs, extracts, and/or fractions was extracted from NCCLS compliant works. The fast artificial neural networks (FANN) software was used and the output data reflected the antimicrobial activity of these EOs against four common pathogens: Staphylococcus aureus, Escherichia coli, Candida albicans, and Clostridium perfringens as measured by standardised disk diffusion assays. Results. ANNs were able to predict >70% of the antimicrobial activities within a 10 mm maximum error range. Similarly, ANNs were able to predict 2 or 3 different bioactivities at the same time. The accuracy of the prediction was only limited by the inherent errors of the popular antimicrobial disk susceptibility test and the nature of the pathogens. Conclusions. ANNs can be reliable, fast, and cheap tools for the prediction of the antimicrobial activity of EOs thus improving their use in CAM.

Application of Artificial Intelligence to the Prediction of the Antimicrobial Activity of Essential Oils

PubMed Central

Daynac, Mathieu; Cortes-Cabrera, Alvaro; Prieto, Jose M.

2015-01-01

Essential oils (EOs) are vastly used as natural antibiotics in Complementary and Alternative Medicine (CAM). Their intrinsic chemical variability and synergisms/antagonisms between its components make difficult to ensure consistent effects through different batches. Our aim is to evaluate the use of artificial neural networks (ANNs) for the prediction of their antimicrobial activity. Methods. The chemical composition and antimicrobial activity of 49 EOs, extracts, and/or fractions was extracted from NCCLS compliant works. The fast artificial neural networks (FANN) software was used and the output data reflected the antimicrobial activity of these EOs against four common pathogens: Staphylococcus aureus, Escherichia coli, Candida albicans, and Clostridium perfringens as measured by standardised disk diffusion assays. Results. ANNs were able to predict >70% of the antimicrobial activities within a 10 mm maximum error range. Similarly, ANNs were able to predict 2 or 3 different bioactivities at the same time. The accuracy of the prediction was only limited by the inherent errors of the popular antimicrobial disk susceptibility test and the nature of the pathogens. Conclusions. ANNs can be reliable, fast, and cheap tools for the prediction of the antimicrobial activity of EOs thus improving their use in CAM. PMID:26457111

Electrical signal transmission and gap junction regulation in a bone cell network: a cable model for an osteon

NASA Technical Reports Server (NTRS)

Zhang, D.; Cowin, S. C.; Weinbaum, S.

1997-01-01

A cable model is formulated to estimate the spatial distribution of intracellular electric potential and current, from the cement line to the lumen of an osteon, as the frequency of the loading and the conductance of the gap junction are altered. The model predicts that the characteristic diffusion time for the spread of current along the membrane of the osteocytic processes, 0.03 sec, is nearly the same as the predicted pore pressure relaxation time in Zeng et al. (Annals of Biomedical Engineering. 1994) for the draining of the bone fluid into the osteonal canal. This approximate equality of characteristic times causes the cable to behave as a high-pass, low-pass filter cascade with a maximum in the spectral response for the intracellular potential at approximately 30 Hz. This behavior could be related to the experiments of Rubin and McLeod (Osteoporosis, Academic Press, 1996) which show that live bone appears to be selectively responsive to mechanical loading in a specific frequency range (15-30 Hz) for several species.

Variability in Heat Strain in Fully Encapsulated Impermeable Suits in Different Climates and at Different Work Loads.

PubMed

DenHartog, Emiel A; Rubenstein, Candace D; Deaton, A Shawn; Bogerd, Cornelis Peter

2017-03-01

A major concern for responders to hazardous materials (HazMat) incidents is the heat strain that is caused by fully encapsulated impermeable (NFPA 1991) suits. In a research project, funded by the US Department of Defense, the thermal strain experienced when wearing these suits was studied. Forty human subjects between the ages of 25 and 50 participated in a protocol approved by the local ethical committee. Six different fully encapsulated impermeable HazMat suits were evaluated in three climates: moderate (24°C, 50% RH, 20°C WBGT), warm-wet (32°C, 60% RH, 30°C WBGT), and hot-dry (45°C, 20% RH, 37°C WBGT, 200 W m-2 radiant load) and at three walking speeds: 2.5, 4, and 5.5 km h-1. The medium speed, 4 km h-1, was tested in all three climates and the other two walking speeds were only tested in the moderate climate. Prior to the test a submaximal exercise test in normal clothing was performed to determine a relationship between heart rate and oxygen consumption (pretest). In total, 163 exposures were measured. Tolerance time ranged from as low as 20 min in the hot-dry condition to 60 min (the maximum) in the moderate climate, especially common at the lowest walking speed. Between the six difference suits limited differences were found, a two-layered aluminized suit exhibited significant shorter tolerance times in the moderate climate, but no other major significant differences were found for the other climates or workloads. An important characteristic of the overall dataset is the large variability between the subjects. Although the average responses seem suitable to be predicted, the variability in the warmer strain conditions ranged from 20 min up to 60 min. The work load in these encapsulated impermeable suits was also significantly higher than working in normal clothing and higher than predicted by the Pandolf equation. Heart rate showed a very strong correlation to body core temperature and was in many cases the limiting factor. Setting the heart rate maximum at 80% of predicted individual maximum (age based) would have prevented 95% of the cases with excessive heat strain. Monitoring of heart rate under operational conditions would further allow individually optimize working times and help in preventing exertional heat stroke. © The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

A Score to Identify Patients with Brain Metastases from Colorectal Cancer Who May Benefit from Whole-brain Radiotherapy in Addition to Stereotactic Radiosurgery/Radiotherapy.

PubMed

Rades, Dirk; Dziggel, Liesa; Blanck, Oliver; Gebauer, Niklas; Bartscht, Tobias; Schild, Steven E

2018-05-01

To design a tool to predict the probability of new cerebral lesions after stereotactic radiosurgery/radiotherapy for patients with 1-3 brain metastases from colorectal cancer. In 21 patients, nine factors were evaluated for freedom from new brain metastases, namely age, gender, Karnofsky performance score (KPS), tumor type, number, maximum total diameter of all lesions and sites of cerebral lesions, extra-cranial metastases, and time from cancer diagnosis to irradiation. Freedom from new lesions was positively associated with KPS of 90-100 (p=0.013); maximum total diameter ≤15 mm showed a trend for positive association (p=0.09). Points were assigned as: KPS 70-80=1 point, KPS 90-100=2 points, maximum diameter ≤15 mm=2 points and maximum diameter >15 mm=1 point. Six-month rates of freedom from new lesions were 29%, 45% and 100% for those with total scores of 2, 3 and 4 points, respectively, with corresponding 12-month rates of 0%, 45% and 100% (p=0.027). This study identified three risk groups regarding new brain metastases after stereotactic irradiation. Patients with 2 points could benefit from additional whole-brain radiotherapy. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Wetting state and maximum spreading factor of microdroplets impacting on superhydrophobic textured surfaces with anisotropic arrays of pillars

NASA Astrophysics Data System (ADS)

Kwon, Dae Hee; Huh, Hyung Kyu; Lee, Sang Joon

2013-07-01

The dynamic behaviors of microdroplets that impact on textured surfaces with various patterns of microscale pillars are experimentally investigated in this study. A piezoelectric inkjet is used to generate the microdroplets that have a diameter of less than 46 μm and a controlled Weber number. The impact and spreading dynamics of an individual droplet are captured by using a high-speed imaging system. The anisotropic and directional wettability and the wetting states on the textured surfaces with anisotropically arranged pillars are revealed for the first time in this study. The impalement transition from the Cassie-Baxter state to the partially impaled state is evaluated by balancing the wetting pressure P wet and the capillary pressure P C even on the anisotropic textured surfaces. The maximum spreading factor is measured and compared with the theoretical prediction to elucidate the wettability of the textured surfaces. For a given Weber number, the maximum spreading factor decreases as the texture area fraction of the textured surface decreases. In addition, the maximum spreading factors along the direction of longer inter-pillar spacing always have smaller values than those along the direction of shorter inter-pillar spacing when a droplet impacts on the anisotropic arrays of pillars.

Evolution of sediment plumes in the Chesapeake bay and implications of climate variability.

PubMed

Zheng, Guangming; DiGiacomo, Paul M; Kaushal, Sujay S; Yuen-Murphy, Marilyn A; Duan, Shuiwang

2015-06-02

Fluvial sediment transport impacts fisheries, marine ecosystems, and human health. In the upper Chesapeake Bay, river-induced sediment plumes are generally known as either a monotonic spatial shape or a turbidity maximum. Little is known about plume evolution in response to variation in streamflow and extreme discharge of sediment. Here we propose a typology of sediment plumes in the upper Chesapeake Bay using a 17 year time series of satellite-derived suspended sediment concentration. On the basis of estimated fluvial and wind contributions, we define an intermittent/wind-dominated type and a continuous type, the latter of which is further divided into four subtypes based on spatial features of plumes, which we refer to as Injection, Transport, Temporary Turbidity-Maximum, and Persistent Turbidity-Maximum. The four continuous types exhibit a consistent sequence of evolution within 1 week to 1 month following flood events. We also identify a "shift" in typology with increased frequency of Turbidity-Maximum types before and after Hurricane Ivan (2004), which implies that extreme events have longer-lasting effects upon estuarine suspended sediment than previously considered. These results can serve as a diagnostic tool to better predict distribution and impacts of estuarine suspended sediment in response to changes in climate and land use.

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

Yang, X. H.; Fu, J. N.; Zha, Q., E-mail: jnfu@bnu.edu.cn

Time-series photometric observations were made for the SX Phoenicis star XX Cyg between 2007 and 2011 at the Xinglong Station of National Astronomical Observatories of China. With the light curves derived from the new observations, we do not detect any secondary maximum in the descending portion of the light curves of XX Cyg, as reported in some previous work. Frequency analysis of the light curves confirms a fundamental frequency f{sub 0} = 7.4148 cycles day{sup -1} and up to 19 harmonics, 11 of which are newly detected. However, no secondary mode of pulsation is detected from the light curves. Themore » O-C diagram, produced from 46 newly determined times of maximum light combined with those derived from the literature, reveals a continuous period increase with the rate of (1/P)(dP/dt) = 1.19(13) Multiplication-Sign 10{sup -8} yr{sup -1}. Theoretical rates of period change due to the stellar evolution were calculated with a modeling code. The result shows that the observed rate of period change is fully consistent with period change caused by evolutionary behavior predicted by standard theoretical models.« less

Optimal HRF and smoothing parameters for fMRI time series within an autoregressive modeling framework.

PubMed

Galka, Andreas; Siniatchkin, Michael; Stephani, Ulrich; Groening, Kristina; Wolff, Stephan; Bosch-Bayard, Jorge; Ozaki, Tohru

2010-12-01

The analysis of time series obtained by functional magnetic resonance imaging (fMRI) may be approached by fitting predictive parametric models, such as nearest-neighbor autoregressive models with exogeneous input (NNARX). As a part of the modeling procedure, it is possible to apply instantaneous linear transformations to the data. Spatial smoothing, a common preprocessing step, may be interpreted as such a transformation. The autoregressive parameters may be constrained, such that they provide a response behavior that corresponds to the canonical haemodynamic response function (HRF). We present an algorithm for estimating the parameters of the linear transformations and of the HRF within a rigorous maximum-likelihood framework. Using this approach, an optimal amount of both the spatial smoothing and the HRF can be estimated simultaneously for a given fMRI data set. An example from a motor-task experiment is discussed. It is found that, for this data set, weak, but non-zero, spatial smoothing is optimal. Furthermore, it is demonstrated that activated regions can be estimated within the maximum-likelihood framework.

Sonic-boom measurements in the focus region during the ascent of Apollo 17. [maximum positive overpressure, positive impulse, signature duration, and bow-shock rise time

NASA Technical Reports Server (NTRS)

Henderson, H. R.; Hilton, D. A.

1974-01-01

Sonic-boom pressure signatures recorded during the ascent phase of Apollo 17 are presented. The measurements were obtained onboard six U.S. Navy ships positioned along the ground track of the spacecraft vehicle in the area of expected focus resulting from the flight path and acceleration of the vehicle. Tracings of the measured signatures are presented along with values of the maximum positive overpressure, positive impulse, signature duration, and bowshock rise time. Also included are brief descriptions of the ships and their location, the deployment of the sonic-boom instrumentation, flight profiles and operating conditions for the launch vehicle and spacecraft, surface-weather and sea-state information at the measuring sites, and high-altitude weather information for the general measurement areas. Comparisons of the measured and predicted sonic-boom overpressures for the Apollo 17 mission are presented. The measured data are also compared with data from the Apollo 15 and 16 missions and data from flight test programs of various aircraft.

Intrarectal pressures and balloon expulsion related to evacuation proctography.

PubMed Central

Halligan, S; Thomas, J; Bartram, C

1995-01-01

Seventy four patients with constipation were examined by standard evacuation proctography and then attempted to expel a small, non-deformable rectal balloon, connected to a pressure transducer to measure intrarectal pressure. Simultaneous imaging related the intrarectal position of the balloon to rectal deformity. Inability to expel the balloon was associated proctographically with prolonged evacuation, incomplete evacuation, reduced anal canal diameter, and acute anorectal angulation during evacuation. The presence and size of rectocoele or intussusception was unrelated to voiding of paste or balloon. An independent linear combination of pelvic floor descent and evacuation time on proctography correctly predicted maximum intrarectal pressure in 74% of cases. No patient with both prolonged evacuation and reduced pelvic floor descent on proctography could void the balloon, as maximum intrarectal pressure was reduced in this group. A prolonged evacuation time on proctography, in combination with reduced pelvic floor descent, suggests defecatory disorder may be caused by inability to raise intrarectal pressure. A diagnosis of anismus should not be made on proctography solely on the basis of incomplete/prolonged evacuation, as this may simply reflect inadequate straining. PMID:7672656

By-product identification and phytotoxicity of biodegraded Direct Yellow 4 dye.

PubMed

Nouren, Shazia; Bhatti, Haq Nawaz; Iqbal, Munawar; Bibi, Ismat; Kamal, Shagufta; Sadaf, Sana; Sultan, Misbah; Kausar, Abida; Safa, Yusra

2017-02-01

Citrus limon peroxidase mediated decolourization of Direct Yellow 4 (DY4) was investigated. The process variables (pH, temperature, incubation time, enzyme dose, H 2 O 2 amount, dye concentration, co-metal ions and surfactants) were optimized for maximum degradation of dye. Maximum dye decolourization of 89.47% was achieved at pH 5.0, temperature 50 °C, enzyme dose 24 U/mL, H 2 O 2 concentration 0.25 mM and DY4 concentration 18.75 mg/L and incubation time 10 min. The co-metal ions and surfactants did not affect the dye decolourization significantly. Response surface analysis revealed that predicted values were in agreement with experimentally determined responses. The degradation products were identified by UPLC/MS analysis and degradation pathway was proposed. Besides, phytotoxicity assay revealed a considerable detoxification in response of biodegradation of DY4 dye. C. limon showed promising efficiency for DY4 degradation and could possibly be used for the remediation of textile effluents. Copyright © 2016 Elsevier Ltd. All rights reserved.

Obliquely Incident Solitary Wave onto a Vertical Wall

NASA Astrophysics Data System (ADS)

Yeh, Harry

2012-10-01

When a solitary wave impinges obliquely onto a reflective vertical wall, it can take the formation of a Mach reflection (a geometrically similar reflection from acoustics). The mathematical theory predicts that the wave at the reflection can amplify not twice, but as high as four times the incident wave amplitude. Nevertheless, this theoretical four-fold amplification has not been verified by numerical or laboratory experiments. We discuss the discrepancies between the theory and the experiments; then, improve the theory with higher-order corrections. The modified theory results in substantial improvement and is now in good agreement with the numerical as well as our laboratory results. Our laboratory experiments indicate that the wave amplitude along the reflective wall can reach 0.91 times the quiescent water depth, which is higher than the maximum of a freely propagating solitary wave. Hence, this maximum runup 0.91 h would be possible even if the amplitude of the incident solitary wave were as small as 0.24 h. This wave behavior could provide an explanation for local variability of tsunami runup as well as for sneaker waves.

Evaluating Upper-Body Strength and Power From a Single Test: The Ballistic Push-up.

PubMed

Wang, Ran; Hoffman, Jay R; Sadres, Eliahu; Bartolomei, Sandro; Muddle, Tyler W D; Fukuda, David H; Stout, Jeffrey R

2017-05-01

Wang, R, Hoffman, JR, Sadres, E, Bartolomei, S, Muddle, TWD, Fukuda, DH, and Stout, JR. Evaluating upper-body strength and power from a single test: the ballistic push-up. J Strength Cond Res 31(5): 1338-1345, 2017-The purpose of this study was to examine the reliability of the ballistic push-up (BPU) exercise and to develop a prediction model for both maximal strength (1 repetition maximum [1RM]) in the bench press exercise and upper-body power. Sixty recreationally active men completed a 1RM bench press and 2 BPU assessments in 3 separate testing sessions. Peak and mean force, peak and mean rate of force development, net impulse, peak velocity, flight time, and peak and mean power were determined. Intraclass correlation coefficients were used to examine the reliability of the BPU. Stepwise linear regression was used to develop 1RM bench press and power prediction equations. Intraclass correlation coefficient's ranged from 0.849 to 0.971 for the BPU measurements. Multiple regression analysis provided the following 1RM bench press prediction equation: 1RM = 0.31 × Mean Force - 1.64 × Body Mass + 0.70 (R = 0.837, standard error of the estimate [SEE] = 11 kg); time-based power prediction equation: Peak Power = 11.0 × Body Mass + 2012.3 × Flight Time - 338.0 (R = 0.658, SEE = 150 W), Mean Power = 6.7 × Body Mass + 1004.4 × Flight Time - 224.6 (R = 0.664, SEE = 82 W); and velocity-based power prediction equation: Peak Power = 8.1 × Body Mass + 818.6 × Peak Velocity - 762.0 (R = 0.797, SEE = 115 W); Mean Power = 5.2 × Body Mass + 435.9 × Peak Velocity - 467.7 (R = 0.838, SEE = 57 W). The BPU is a reliable test for both upper-body strength and power. Results indicate that the mean force generated from the BPU can be used to predict 1RM bench press, whereas peak velocity and flight time measured during the BPU can be used to predict upper-body power. These findings support the potential use of the BPU as a valid method to evaluate upper-body strength and power.

Assessment of macroseismic intensity in the Nile basin, Egypt

NASA Astrophysics Data System (ADS)

Fergany, Elsayed

2018-01-01

This work intends to assess deterministic seismic hazard and risk analysis in terms of the maximum expected intensity map of the Egyptian Nile basin sector. Seismic source zone model of Egypt was delineated based on updated compatible earthquake catalog in 2015, focal mechanisms, and the common tectonic elements. Four effective seismic source zones were identified along the Nile basin. The observed macroseismic intensity data along the basin was used to develop intensity prediction equation defined in terms of moment magnitude. Expected maximum intensity map was proven based on the developed intensity prediction equation, identified effective seismic source zones, and maximum expected magnitude for each zone along the basin. The earthquake hazard and risk analysis was discussed and analyzed in view of the maximum expected moment magnitude and the maximum expected intensity values for each effective source zone. Moderate expected magnitudes are expected to put high risk at Cairo and Aswan regions. The results of this study could be a recommendation for the planners in charge to mitigate the seismic risk at these strategic zones of Egypt.

Effect of acoustic frequency and power density on the aqueous ultrasonic-assisted extraction of grape pomace (Vitis vinifera L.) - a response surface approach.

PubMed

González-Centeno, María Reyes; Knoerzer, Kai; Sabarez, Henry; Simal, Susana; Rosselló, Carmen; Femenia, Antoni

2014-11-01

Aqueous ultrasound-assisted extraction (UAE) of grape pomace was investigated by Response Surface Methodology (RSM) to evaluate the effect of acoustic frequency (40, 80, 120kHz), ultrasonic power density (50, 100, 150W/L) and extraction time (5, 15, 25min) on total phenolics, total flavonols and antioxidant capacity. All the process variables showed a significant effect on the aqueous UAE of grape pomace (p<0.05). The Box-Behnken Design (BBD) generated satisfactory mathematical models which accurately explain the behavior of the system; allowing to predict both the extraction yield of phenolic and flavonol compounds, and also the antioxidant capacity of the grape pomace extracts. The optimal UAE conditions for all response factors were a frequency of 40kHz, a power density of 150W/L and 25min of extraction time. Under these conditions, the aqueous UAE would achieve a maximum of 32.31mg GA/100g fw for total phenolics and 2.04mg quercetin/100g fw for total flavonols. Regarding the antioxidant capacity, the maximum predicted values were 53.47 and 43.66mg Trolox/100g fw for CUPRAC and FRAP assays, respectively. When comparing with organic UAE, in the present research, from 12% to 38% of total phenolic bibliographic values were obtained, but using only water as the extraction solvent, and applying lower temperatures and shorter extraction times. To the best of the authors' knowledge, no studies specifically addressing the optimization of both acoustic frequency and power density during aqueous-UAE of plant materials have been previously published. Copyright © 2014 Elsevier B.V. All rights reserved.

Are Equilibrium Multichannel Networks Predictable? the Case of the Indus River, Pakistan

NASA Astrophysics Data System (ADS)

Darby, S. E.; Carling, P. A.

2017-12-01

Focusing on the specific case of the Indus River, we argue that the equilibrium planform network structure of large, multi-channel, rivers is predictable. Between Chashma and Taunsa, Pakistan, the Indus is a 264 km long multiple-channel reach. Remote sensing imagery, including a period of time that encompasses the occurrence of major floods in 2007 and 2010, shows that Indus has a minimum of two and a maximum of nine channels, with on average four active channels during the dry season and five during the monsoon. We show that the network structure, if not detailed planform, remains stable, even for the record 2010 flood (27,100 m3s-1; recurrence interval > 100 years). Bankline recession is negligible for discharges less than a peak annual discharge of 6,000 m3s-1 ( 80% of mean annual flow). Maximum Flow Efficiency (MFE) principle demonstrates the channel network is insensitive to the monsoon floods, which typically peak at 13,200 m3s-1. Rather, the network is in near-equilibrium with the mean annual flood (7,530 m3s-1). MFE principle indicates stable networks have three to four channels, thus the observed stability in the number of active channels accords with the presence of a near-equilibrium reach-scale channel network. Insensitivity to the annual hydrological cycle demonstrates that the time-scale for network adjustment is much longer than the time-scale of the monsoon hydrograph, with the annual excess water being stored on floodplains, rather than being conveyed in an enlarged channel network. The analysis explains the lack of significant channel adjustment following the largest flood in 40 years and the extensive Indus flooding experienced on an annual basis, with its substantial impacts on the populace and agricultural production.

Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection.

PubMed

Ma, Xin; Guo, Jing; Sun, Xiao

2015-01-01

The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR) method, followed by incremental feature selection (IFS). We incorporated features of conjoint triad features and three novel features: binding propensity (BP), nonbinding propensity (NBP), and evolutionary information combined with physicochemical properties (EIPP). The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient). High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.

Factors affecting red blood cell storage age at the time of transfusion.

PubMed

Dzik, Walter H; Beckman, Neil; Murphy, Michael F; Delaney, Meghan; Flanagan, Peter; Fung, Mark; Germain, Marc; Haspel, Richard L; Lozano, Miguel; Sacher, Ronald; Szczepiorkowski, Zbigniew; Wendel, Silvano

2013-12-01

Clinical trials are investigating the potential benefit resulting from a reduced maximum storage interval for red blood cells (RBCs). The key drivers that determine RBC age at the time of issue vary among individual hospitals. Although progressive reduction in the maximum storage period of RBCs would be expected to result in smaller hospital inventories and reduced blood availability, the magnitude of the effect is unknown. Data on current hospital blood inventories were collected from 11 hospitals and three blood centers in five nations. A general predictive model for the age of RBCs at the time of issue was developed based on considerations of demand for RBCs in the hospital. Age of RBCs at issue is sensitive to the following factors: ABO group, storage age at the time of receipt by the hospital, the restock interval, inventory reserve, mean demand, and variation in demand. A simple model, based on hospital demand, may serve as the basis for examining factors affecting the storage age of RBCs in hospital inventories. The model suggests that the age of RBCs at the time of their issue to the patient depends on factors external to the hospital transfusion service. Any substantial change in the expiration date of stored RBCs will need to address the broad variation in demand for RBCs while attempting to balance considerations of availability and blood wastage. © 2013 American Association of Blood Banks.

Impacts of tides on tsunami propagation due to potential Nankai Trough earthquakes in the Seto Inland Sea, Japan

NASA Astrophysics Data System (ADS)

Lee, Han Soo; Shimoyama, Tomohisa; Popinet, Stéphane

2015-10-01

The impacts of tides on extreme tsunami propagation due to potential Nankai Trough earthquakes in the Seto Inland Sea (SIS), Japan, are investigated through numerical experiments. Tsunami experiments are conducted based on five scenarios that consider tides at four different phases, such as flood, high, ebb, and low tides. The probes that were selected arbitrarily in the Bungo and Kii Channels show less significant effects of tides on tsunami heights and the arrival times of the first waves than those that experience large tidal ranges in inner basins and bays of the SIS. For instance, the maximum tsunami height and the arrival time at Toyomaesi differ by more than 0.5 m and nearly 1 h, respectively, depending on the tidal phase. The uncertainties defined in terms of calculated maximum tsunami heights due to tides illustrate that the calculated maximum tsunami heights in the inner SIS with standing tides have much larger uncertainties than those of two channels with propagating tides. Particularly in Harima Nada, the uncertainties due to the impacts of tides are greater than 50% of the tsunami heights without tidal interaction. The results recommend simulate tsunamis together with tides in shallow water environments to reduce the uncertainties involved with tsunami modeling and predictions for tsunami hazards preparedness. This article was corrected on 26 OCT 2015. See the end of the full text for details.

A comparison of heart rate responses in racquet games.

PubMed Central

Docherty, D.

1982-01-01

The present study investigated the heart rate response to playing tennis with special reference to the skill levels and ages of the participants. Data obtained in a similar manner during earlier studies of badminton and squash players were compared with that obtained during tennis. The number of rallies, mean rally time and actual playing time in 30 minutes of play was also compared for the different skill levels and sports. Results showed that playing tennis raised the players' heart rates to 68-70% of their predicted maximum heart rate (PMHR). Playing squash and badminton could raise heart rates to 80-85% of the players' PMHR which was significantly higher than the values obtained for tennis. The actual skill level of the participants within their chosen sport did not have a significant effect in predicting the physical demands of squash or tennis but was important in predicting the heart rate response of badminton players. The more skillful the badminton player the greater the cardiac response as a result of game play. Analysis of time spent in actual play revealed that tennis players were involved in play for only five of the thirty minutes of game play, compared to 15 and 10 min respectively for squash and badminton. Skill level within each sport was only a significant factor in predicting length of play for squash players in which the medium and highly skilled groups played significantly longer than those of a lower level of skill. Images p96-a PMID:7104564

Distillation Time as Tool for Improved Antimalarial Activity and Differential Oil Composition of Cumin Seed Oil.

PubMed

Zheljazkov, Valtcho D; Gawde, Archana; Cantrell, Charles L; Astatkie, Tess; Schlegel, Vicki

2015-01-01

A steam distillation extraction kinetics experiment was conducted to estimate essential oil yield, composition, antimalarial, and antioxidant capacity of cumin (Cuminum cyminum L.) seed (fruits). Furthermore, regression models were developed to predict essential oil yield and composition for a given duration of the steam distillation time (DT). Ten DT durations were tested in this study: 5, 7.5, 15, 30, 60, 120, 240, 360, 480, and 600 min. Oil yields increased with an increase in the DT. Maximum oil yield (content, 2.3 g/100 seed), was achieved at 480 min; longer DT did not increase oil yields. The concentrations of the major oil constituents α-pinene (0.14-0.5% concentration range), β-pinene (3.7-10.3% range), γ-cymene (5-7.3% range), γ-terpinene (1.8-7.2% range), cumin aldehyde (50-66% range), α-terpinen-7-al (3.8-16% range), and β-terpinen-7-al (12-20% range) varied as a function of the DT. The concentrations of α-pinene, β-pinene, γ-cymene, γ-terpinene in the oil increased with the increase of the duration of the DT; α-pinene was highest in the oil obtained at 600 min DT, β-pinene and γ-terpinene reached maximum concentrations in the oil at 360 min DT; γ-cymene reached a maximum in the oil at 60 min DT, cumin aldehyde was high in the oils obtained at 5-60 min DT, and low in the oils obtained at 240-600 min DT, α-terpinen-7-al reached maximum in the oils obtained at 480 or 600 min DT, whereas β-terpinen-7-al reached a maximum concentration in the oil at 60 min DT. The yield of individual oil constituents (calculated from the oil yields and the concentration of a given compound at a particular DT) increased and reached a maximum at 480 or 600 min DT. The antimalarial activity of the cumin seed oil obtained during the 0-5 and at 5-7.5 min DT timeframes was twice higher than the antimalarial activity of the oils obtained at the other DT. This study opens the possibility for distinct marketing and utilization for these improved oils. The antioxidant capacity of the oil was highest in the oil obtained at 30 min DT and lowest in the oil from 360 min DT. The Michaelis-Menton and the Power nonlinear regression models developed in this study can be utilized to predict essential oil yield and composition of cumin seed at any given duration of DT and may also be useful to compare previous reports on cumin oil yield and composition. DT can be utilized to obtain cumin seed oil with improved antimalarial activity, improved antioxidant capacity, and with various compositions.

Predicting tropical cyclone intensity using satellite measured equivalent blackbody temperatures of cloud tops. [regression analysis

NASA Technical Reports Server (NTRS)

Gentry, R. C.; Rodgers, E.; Steranka, J.; Shenk, W. E.

1978-01-01

A regression technique was developed to forecast 24 hour changes of the maximum winds for weak (maximum winds less than or equal to 65 Kt) and strong (maximum winds greater than 65 Kt) tropical cyclones by utilizing satellite measured equivalent blackbody temperatures around the storm alone and together with the changes in maximum winds during the preceding 24 hours and the current maximum winds. Independent testing of these regression equations shows that the mean errors made by the equations are lower than the errors in forecasts made by the peristence techniques.

A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA

USGS Publications Warehouse

Nolan, Bernard T.; Fienen, Michael N.; Lorenz, David L.

2015-01-01

We used a statistical learning framework to evaluate the ability of three machine-learning methods to predict nitrate concentration in shallow groundwater of the Central Valley, California: boosted regression trees (BRT), artificial neural networks (ANN), and Bayesian networks (BN). Machine learning methods can learn complex patterns in the data but because of overfitting may not generalize well to new data. The statistical learning framework involves cross-validation (CV) training and testing data and a separate hold-out data set for model evaluation, with the goal of optimizing predictive performance by controlling for model overfit. The order of prediction performance according to both CV testing R2 and that for the hold-out data set was BRT > BN > ANN. For each method we identified two models based on CV testing results: that with maximum testing R2 and a version with R2 within one standard error of the maximum (the 1SE model). The former yielded CV training R2 values of 0.94–1.0. Cross-validation testing R2 values indicate predictive performance, and these were 0.22–0.39 for the maximum R2 models and 0.19–0.36 for the 1SE models. Evaluation with hold-out data suggested that the 1SE BRT and ANN models predicted better for an independent data set compared with the maximum R2 versions, which is relevant to extrapolation by mapping. Scatterplots of predicted vs. observed hold-out data obtained for final models helped identify prediction bias, which was fairly pronounced for ANN and BN. Lastly, the models were compared with multiple linear regression (MLR) and a previous random forest regression (RFR) model. Whereas BRT results were comparable to RFR, MLR had low hold-out R2 (0.07) and explained less than half the variation in the training data. Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley.

Spectral sensitivity of the photointrinsic iris in the red-eared slider turtle (Trachemys scripta elegans).

PubMed

Sipe, Grayson O; Dearworth, James R; Selvarajah, Brian P; Blaum, Justin F; Littlefield, Tory E; Fink, Deborah A; Casey, Corinne N; McDougal, David H

2011-01-01

Our goal in this study was to examine the red-eared slider turtle for a photomechanical response (PMR) and define its spectral sensitivity. Pupils of enucleated eyes constricted to light by ∼11%, which was one-third the response measured in alert behaving turtles at ∼33%. Rates of constriction in enucleated eyes that were measured by time constants (1.44-3.70 min) were similar to those measured in turtles at 1.97 min. Dilation recovery rates during dark adaptation for enucleated eyes were predicted using line equations and computed times for reaching maximum sizes between 26 and 44 min. Times were comparable to the measures in turtles where maximum pupil size occurred within 40 min and possessed a time constant of 12.78 min. Hill equations were used to derive irradiance threshold values from enucleated hemisected eyes and then plot a spectral sensitivity curve. The analysis of the slopes and maximum responses revealed contribution from at least two different photopigments, one with a peak at 410 nm and another with a peak at 480 nm. Fits by template equations suggest that contractions are triggered by multiple photopigments in the iris including an opsin-based visual pigment and some other novel photopigment, or a cryptochrome with an absorbance spectrum significantly different from that used in our model. In addition to being regulated by retinal feedback via parasympathetic nervous pathways, the results support that the iris musculature is photointrinsically responsive. In the turtle, the control of its direct pupillary light response (dPLR) includes photoreceptive mechanisms occurring both in its iris and in its retina. Copyright © 2010 Elsevier Ltd. All rights reserved.

Utilizing Crochet to Showcase Temporal Patterns in Temperature Records from One Location and to Spark a Climate Conversation

NASA Astrophysics Data System (ADS)

Guertin, L. A.

2017-12-01

Scientists that seek to show temperature changes over time will typically select a line graph as the tool for data communication. However, one non-traditional way to showcase variations in data can be through an artistic visualization created with yarn. For several years, amateur and professional artisans have been using needlework (crocheting/knitting) to represent weather/climate records in scarves and blankets, sharing their work in online communities. Since the Sky Scarf project in 2011, a temporal record of data represented in yarn can include precipitation/snowfall to the air quality index. Here is an example of how crochet is being utilized to show maximum air temperature records over time for one location. Maximum daily temperature values have been collected for January through April in Philadelphia in fifty-year intervals (1917, 1967, 2017). This four-month interval was selected to match with the location and timing of a university's spring semester, as the target audience for this particular visualization is undergraduate students. Instead of trying to read differences in temperature across line graphs plotted for each year, three mini-temperature tapestries have been crocheted. A temperature scale has been developed with rainbow colors of yarn, where the purple and blue represent the coldest temperatures, and the orange and red represent the warmest temperatures. By using the same yarn temperature scale across the three mini-tapestries, the increase in daily maximum temperature in Philadelphia for a set time period can quickly and easily be observed. This form of science art, when presented to students, generates a series of questions, stories and predictions of a scientific and personal nature that are not typically part of a climate science instructional unit.

Fretting Fatigue with Cylindrical-On-Flat Contact: Crack Nucleation, Crack Path and Fatigue Life

PubMed Central

Noraphaiphipaksa, Nitikorn; Manonukul, Anchalee; Kanchanomai, Chaosuan

2017-01-01

Fretting fatigue experiments and finite element analysis were carried out to investigate the influence of cylindrical-on-flat contact on crack nucleation, crack path and fatigue life of medium-carbon steel. The location of crack nucleation was predicted using the maximum shear stress range criterion and the maximum relative slip amplitude criterion. The prediction using the maximum relative slip amplitude criterion gave the better agreement with the experimental result, and should be used for the prediction of the location of crack nucleation. Crack openings under compressive bulk stresses were found in the fretting fatigues with flat-on-flat contact and cylindrical-on-flat contacts, i.e., fretting-contact-induced crack openings. The crack opening stress of specimen with flat-on-flat contact was lower than those of specimens with cylindrical-on-flat contacts, while that of specimen with 60-mm radius contact pad was lower than that of specimen with 15-mm radius contact pad. The fretting fatigue lives were estimated by integrating the fatigue crack growth curve from an initial propagating crack length to a critical crack length. The predictions of fretting fatigue life with consideration of crack opening were in good agreement with the experimental results. PMID:28772522

Optimization of Photooxidative Removal of Phenazopyridine from Water

NASA Astrophysics Data System (ADS)

Saeid, Soudabeh; Behnajady, Mohammad A.; Tolvanen, Pasi; Salmi, Tapio

2018-05-01

The photooxidative removal of analgesic pharmaceutical compound phenazopyridine (PhP) from aqueous solutions by UV/H2O2 system with a re-circulated photoreactor was investigated. Response surface methodology (RSM) was employed to optimize the effect of operational parameters on the photooxidative removal efficiency. The investigated variables were: the initial PhP and H2O2 concentrations, irradiation time, volume of solution and pH. The analysis of variance (ANOVA) of quadratic model demonstrated that the described model was highly significant. The predicted values of the photooxidative removal efficiency were found to be in a fair agreement with experimental values ( R 2 = 0.9832, adjusted R 2 = 0.9716). The model predicted that the optimal reaction conditions for a maximum removal of PhP (>98%) were: initial PhP concentration less than 23 mg L-1, initial concentration of H2O2 higher than 470 mg L-1, solution volume less than 500 mL, pH close to 2 and irradiation time longer than 6 min.

Statistical properties of cross-correlation in the Korean stock market

NASA Astrophysics Data System (ADS)

Oh, G.; Eom, C.; Wang, F.; Jung, W.-S.; Stanley, H. E.; Kim, S.

2011-01-01

We investigate the statistical properties of the cross-correlation matrix between individual stocks traded in the Korean stock market using the random matrix theory (RMT) and observe how these affect the portfolio weights in the Markowitz portfolio theory. We find that the distribution of the cross-correlation matrix is positively skewed and changes over time. We find that the eigenvalue distribution of original cross-correlation matrix deviates from the eigenvalues predicted by the RMT, and the largest eigenvalue is 52 times larger than the maximum value among the eigenvalues predicted by the RMT. The β_{473} coefficient, which reflect the largest eigenvalue property, is 0.8, while one of the eigenvalues in the RMT is approximately zero. Notably, we show that the entropy function E(σ) with the portfolio risk σ for the original and filtered cross-correlation matrices are consistent with a power-law function, E( σ) σ^{-γ}, with the exponent γ 2.92 and those for Asian currency crisis decreases significantly.

Whistler Mode Based Explanation for the Fast Reconnection Rate Measured in the MIT Versatile Toroidal Facility

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

Singh, Nagendra

2011-12-09

Despite the widely discussed role of whistler waves in mediating magnetic reconnection (MR), the direct connection between such waves and the MR has not been demonstrated by comparing the characteristic temporal and spatial features of the waves and the MR process. Using the whistler wave dispersion relation, we theoretically predict the experimentally measured rise time ({tau}{sub rise}) of a few microseconds for the fast rising MR rate in the Versatile Toroidal Facility at MIT. The rise time is closely given by the inverse of the frequency bandwidth of the whistler waves generated in the evolving current sheet. The wave frequenciesmore » lie much above the ion cyclotron frequency, but they are limited to less than 0.1% of the electron cyclotron frequency in the argon plasma. The maximum normalized MR rate R=0.35 measured experimentally is precisely predicted by the angular dispersion of the whistler waves.« less

Rollover risk prediction of heavy vehicles by reliability index and empirical modelling

NASA Astrophysics Data System (ADS)

Sellami, Yamine; Imine, Hocine; Boubezoul, Abderrahmane; Cadiou, Jean-Charles

2018-03-01

This paper focuses on a combination of a reliability-based approach and an empirical modelling approach for rollover risk assessment of heavy vehicles. A reliability-based warning system is developed to alert the driver to a potential rollover before entering into a bend. The idea behind the proposed methodology is to estimate the rollover risk by the probability that the vehicle load transfer ratio (LTR) exceeds a critical threshold. Accordingly, a so-called reliability index may be used as a measure to assess the vehicle safe functioning. In the reliability method, computing the maximum of LTR requires to predict the vehicle dynamics over the bend which can be in some cases an intractable problem or time-consuming. With the aim of improving the reliability computation time, an empirical model is developed to substitute the vehicle dynamics and rollover models. This is done by using the SVM (Support Vector Machines) algorithm. The preliminary obtained results demonstrate the effectiveness of the proposed approach.

The emergence of modern sea ice cover in the Arctic Ocean.

PubMed

Knies, Jochen; Cabedo-Sanz, Patricia; Belt, Simon T; Baranwal, Soma; Fietz, Susanne; Rosell-Melé, Antoni

2014-11-28

Arctic sea ice coverage is shrinking in response to global climate change and summer ice-free conditions in the Arctic Ocean are predicted by the end of the century. The validity of this prediction could potentially be tested through the reconstruction of the climate of the Pliocene epoch (5.33-2.58 million years ago), an analogue of a future warmer Earth. Here we show that, in the Eurasian sector of the Arctic Ocean, ice-free conditions prevailed in the early Pliocene until sea ice expanded from the central Arctic Ocean for the first time ca. 4 million years ago. Amplified by a rise in topography in several regions of the Arctic and enhanced freshening of the Arctic Ocean, sea ice expanded progressively in response to positive ice-albedo feedback mechanisms. Sea ice reached its modern winter maximum extension for the first time during the culmination of the Northern Hemisphere glaciation, ca. 2.6 million years ago.

Laminar and turbulent heating predictions for mars entry vehicles

NASA Astrophysics Data System (ADS)

Wang, Xiaoyong; Yan, Chao; Zheng, Weilin; Zhong, Kang; Geng, Yunfei

2016-11-01

Laminar and turbulent heating rates play an important role in the design of Mars entry vehicles. Two distinct gas models, thermochemical non-equilibrium (real gas) model and perfect gas model with specified effective specific heat ratio, are utilized to investigate the aerothermodynamics of Mars entry vehicle named Mars Science Laboratory (MSL). Menter shear stress transport (SST) turbulent model with compressible correction is implemented to take account of the turbulent effect. The laminar and turbulent heating rates of the two gas models are compared and analyzed in detail. The laminar heating rates predicted by the two gas models are nearly the same at forebody of the vehicle, while the turbulent heating environments predicted by the real gas model are severer than the perfect gas model. The difference of specific heat ratio between the two gas models not only induces the flow structure's discrepancy but also increases the heating rates at afterbody of the vehicle obviously. Simple correlations for turbulent heating augmentation in terms of laminar momentum thickness Reynolds number, which can be employed as engineering level design and analysis tools, are also developed from numerical results. At the time of peak heat flux on the +3σ heat load trajectory, the maximum value of momentum thickness Reynolds number at the MSL's forebody is about 500, and the maximum value of turbulent augmentation factor (turbulent heating rates divided by laminar heating rates) is 5 for perfect gas model and 8 for real gas model.

Climate change and health: Indoor heat exposure in vulnerable populations

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

White-Newsome, Jalonne L., E-mail: jalonne@umich.edu; Sanchez, Brisa N., E-mail: brisa@umich.edu; Jolliet, Olivier, E-mail: ojolliet@umich.edu

2012-01-15

Introduction: Climate change is increasing the frequency of heat waves and hot weather in many urban environments. Older people are more vulnerable to heat exposure but spend most of their time indoors. Few published studies have addressed indoor heat exposure in residences occupied by an elderly population. The purpose of this study is to explore the relationship between outdoor and indoor temperatures in homes occupied by the elderly and determine other predictors of indoor temperature. Materials and methods: We collected hourly indoor temperature measurements of 30 different homes; outdoor temperature, dewpoint temperature, and solar radiation data during summer 2009 inmore » Detroit, MI. We used mixed linear regression to model indoor temperatures' responsiveness to weather, housing and environmental characteristics, and evaluated our ability to predict indoor heat exposures based on outdoor conditions. Results: Average maximum indoor temperature for all locations was 34.85 Degree-Sign C, 13.8 Degree-Sign C higher than average maximum outdoor temperature. Indoor temperatures of single family homes constructed of vinyl paneling or wood siding were more sensitive than brick homes to outdoor temperature changes and internal heat gains. Outdoor temperature, solar radiation, and dewpoint temperature predicted 38% of the variability of indoor temperatures. Conclusions: Indoor exposures to heat in Detroit exceed the comfort range among elderly occupants, and can be predicted using outdoor temperatures, characteristics of the housing stock and surroundings to improve heat exposure assessment for epidemiological investigations. Weatherizing homes and modifying home surroundings could mitigate indoor heat exposure among the elderly.« less

Validation of the FAST skating protocol to predict aerobic power in ice hockey players.

PubMed

Petrella, Nicholas J; Montelpare, William J; Nystrom, Murray; Plyley, Michael; Faught, Brent E

2007-08-01

Few studies have reported a sport-specific protocol to measure the aerobic power of ice hockey players using a predictive process. The purpose of our study was to validate an ice hockey aerobic field test on players of varying ages, abilities, and levels. The Faught Aerobic Skating Test (FAST) uses an on-ice continuous skating protocol on a course measuring 160 feet (48.8 m) using a CD to pace the skater with a beep signal to cross the starting line at each end of the course. The FAST incorporates the principle of increasing workload at measured time intervals during a continuous skating exercise. Step-wise multiple regression modelling was used to determine the estimate of aerobic power. Participants completed a maximal aerobic power test using a modified Bruce incremental treadmill protocol, as well as the on-ice FAST. Normative data were collected on 406 ice hockey players (291 males, 115 females) ranging in age from 9 to 25 y. A regression to predict maximum aerobic power was developed using body mass (kg), height (m), age (y), and maximum completed lengths of the FAST as the significant predictors of skating aerobic power (adjusted R2 = 0.387, SEE = 7.25 mL.kg-1.min-1, p < 0.0001). These results support the application of the FAST in estimating aerobic power among male and female competitive ice hockey players between the ages of 9 and 25 years.

An early prediction of 25th solar cycle using Hurst exponent

NASA Astrophysics Data System (ADS)

Singh, A. K.; Bhargawa, Asheesh

2017-11-01

The analysis of long memory processes in solar activity, space weather and other geophysical phenomena has been a major issue even after the availability of enough data. We have examined the data of various solar parameters like sunspot numbers, 10.7 cm radio flux, solar magnetic field, proton flux and Alfven Mach number observed for the year 1976-2016. We have done the statistical test for persistence of solar activity based on the value of Hurst exponent (H) which is one of the most classical applied methods known as rescaled range analysis. We have discussed the efficiency of this methodology as well as prediction content for next solar cycle based on long term memory. In the present study, Hurst exponent analysis has been used to investigate the persistence of above mentioned (five) solar activity parameters and a simplex projection analysis has been used to predict the ascension time and the maximum number of counts for 25th solar cycle. For available dataset of the year 1976-2016, we have calculated H = 0.86 and 0.82 for sunspot number and 10.7 cm radio flux respectively. Further we have calculated maximum number of counts for sunspot numbers and F10.7 cm index as 102.8± 24.6 and 137.25± 8.9 respectively. Using the simplex projection analysis, we have forecasted that the solar cycle 25th would start in the year 2021 (January) and would last up to the year 2031 (September) with its maxima in June 2024.

Predicting the Size and Timing of Sunspot Maximum for Cycle 24

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

2010-01-01

For cycle 24, the minimum value of the 12-month moving average (12-mma) of the AA-geomagnetic index in the vicinity of sunspot minimum (AAm) appears to have occurred in September 2009, measuring about 8.4 nT and following sunspot minimum by 9 months. This is the lowest value of AAm ever recorded, falling below that of 8.9 nT, previously attributed to cycle 14, which also is the smallest maximum amplitude (RM) cycle of the modern era (RM = 64.2). Based on the method of Ohl (the preferential association between RM and AAm for an ongoing cycle), one expects cycle 24 to have RM = 55+/-17 (the +/-1 - sigma prediction interval). Instead, using a variation of Ohl's method, one based on using 2-cycle moving averages (2-cma), one expects cycle 23's 2-cma of RM to be about 115.5+/-8.7 (the +/-1 - sigma prediction interval), inferring an RM of about 62+/-35 for cycle 24. Hence, it seems clear that cycle 24 will be smaller in size than was seen in cycle 23 (RM = 120.8) and, likely, will be comparable in size to that of cycle 14. From the Waldmeier effect (the preferential association between the ascent duration (ASC) and RM for an ongoing cycle), one expects cycle 24 to be a slow-rising cycle (ASC > or equal to 48 months), having RM occurrence after December 2012, unless it turns out to be a statistical outlier.

Life prediction methodology for thermal-mechanical fatigue and elevated temperature creep design

NASA Astrophysics Data System (ADS)

Annigeri, Ravindra

Nickel-based superalloys are used for hot section components of gas turbine engines. Life prediction techniques are necessary to assess service damage in superalloy components resulting from thermal-mechanical fatigue (TMF) and elevated temperature creep. A new TMF life model based on continuum damage mechanics has been developed and applied to IN 738 LC substrate material with and without coating. The model also characterizes TMF failure in bulk NiCoCrAlY overlay and NiAl aluminide coatings. The inputs to the TMF life model are mechanical strain range, hold time, peak cycle temperatures and maximum stress measured from the stabilized or mid-life hysteresis loops. A viscoplastic model is used to predict the stress-strain hysteresis loops. A flow rule used in the viscoplastic model characterizes the inelastic strain rate as a function of the applied stress and a set of three internal stress variables known as back stress, drag stress and limit stress. Test results show that the viscoplastic model can reasonably predict time-dependent stress-strain response of the coated material and stress relaxation during hold times. In addition to the TMF life prediction methodology, a model has been developed to characterize the uniaxial and multiaxial creep behavior. An effective stress defined as the applied stress minus the back stress is used to characterize the creep recovery and primary creep behavior. The back stress has terms representing strain hardening, dynamic recovery and thermal recovery. Whenever the back stress is greater than the applied stress, the model predicts a negative creep rate observed during multiple stress and multiple temperature cyclic tests. The model also predicted the rupture time and the remaining life that are important for life assessment. The model has been applied to IN 738 LC, Mar-M247, bulk NiCoCrAlY overlay coating and 316 austenitic stainless steel. The proposed model predicts creep response with a reasonable accuracy for wide range of loading cases such as uniaxial tension, tension-torsion and tension-internal pressure loading.

Understanding spatial variability in extreme estuarine water levels to inform better coastal management practise.

NASA Astrophysics Data System (ADS)

Lyddon, Charlotte; Plater, Andy, ,, Prof.; Brown, Jenny, ,, Dr.; Leonardi, Nicoletta, ,, Dr.

2017-04-01

Coastal zones worldwide are subject to short term, local variations in sea-level, particularly communities and industries developed on estuaries. Astronomical high tides, meteorological storm surges and increased river flow present a combined flood hazard. This can elevate water level at the coast above predicted levels, generating extreme water levels. These contributions can also interact to alter the phase and amplitude of tides and surges, and thus cause significant mismatches between the predicted and observed water level. The combined effect of tide, surge, river flow and their interactions are the key to understanding and assessing flood risk in estuarine environments for design purposes. Delft3D-FLOW, a hydrodynamic model which solves the unsteady shallow-water equation, is used to access spatial variability in extreme water levels for a range of historical events of different severity within the Severn Estuary, southwest England. Long-term tide gauge records from Ilfracombe and Mumbles and river level data from Sandhurst are analysed to generate a series of extreme water level events, representing the 90th, 95th and 99th percentile conditions, to force the model boundaries. To separate out the time-varying contributions of tidal, fluvial, meteorological processes and their interactions the model is run with different physical forcing. A low pass filter is applied to "de-tide" the residual water elevation, to separate out the time-varying meteorological residual and the tide-surge interactions within the surge. The filtered surge is recombined with the predicted tide so the peak occurs at different times relative to high water. The resulting time series are used to force the model boundary to identify how the interactive processes influence the timing of extreme water level across the estuarine domain. This methodology is first validated using the most extreme event on record to ensure that modelled extreme water levels can be predicted with confidence. Changes in maximum water level are observed in areas where nuclear assets are located (Hinkley, Oldbury & Berkeley) and further upstream, e.g., close to the tidal limit of the Severn Estuary at Epney. Change in crest shape (area and duration above the MSHW) are analysed to understand changes to flood hazard around the peak of the tide. The work concludes that changes in maximum water level can be attributed to the change in time of the peak of the surge relative to high water, the surge shape (classified by skew and kurtosis) and severity of the event. The results can be used to understand the spatial variability in extreme water levels relative to a tide gauge location, which can then be applied to other management needs in hypertidal estuaries worldwide.

Probability of stress-corrosion fracture under random loading.

NASA Technical Reports Server (NTRS)

Yang, J.-N.

1972-01-01

A method is developed for predicting the probability of stress-corrosion fracture of structures under random loadings. The formulation is based on the cumulative damage hypothesis and the experimentally determined stress-corrosion characteristics. Under both stationary and nonstationary random loadings, the mean value and the variance of the cumulative damage are obtained. The probability of stress-corrosion fracture is then evaluated using the principle of maximum entropy. It is shown that, under stationary random loadings, the standard deviation of the cumulative damage increases in proportion to the square root of time, while the coefficient of variation (dispersion) decreases in inversed proportion to the square root of time. Numerical examples are worked out to illustrate the general results.

Prediction of climate change in Brunei Darussalam using statistical downscaling model

NASA Astrophysics Data System (ADS)

Hasan, Dk. Siti Nurul Ain binti Pg. Ali; Ratnayake, Uditha; Shams, Shahriar; Nayan, Zuliana Binti Hj; Rahman, Ena Kartina Abdul

2017-06-01

Climate is changing and evidence suggests that the impact of climate change would influence our everyday lives, including agriculture, built environment, energy management, food security and water resources. Brunei Darussalam located within the heart of Borneo will be affected both in terms of precipitation and temperature. Therefore, it is crucial to comprehend and assess how important climate indicators like temperature and precipitation are expected to vary in the future in order to minimise its impact. This study assesses the application of a statistical downscaling model (SDSM) for downscaling General Circulation Model (GCM) results for maximum and minimum temperatures along with precipitation in Brunei Darussalam. It investigates future climate changes based on numerous scenarios using Hadley Centre Coupled Model, version 3 (HadCM3), Canadian Earth System Model (CanESM2) and third-generation Coupled Global Climate Model (CGCM3) outputs. The SDSM outputs were improved with the implementation of bias correction and also using a monthly sub-model instead of an annual sub-model. The outcomes of this assessment show that monthly sub-model performed better than the annual sub-model. This study indicates a satisfactory applicability for generation of maximum temperatures, minimum temperatures and precipitation for future periods of 2017-2046 and 2047-2076. All considered models and the scenarios were consistent in predicting increasing trend of maximum temperature, increasing trend of minimum temperature and decreasing trend of precipitations. Maximum overall trend of Tmax was also observed for CanESM2 with Representative Concentration Pathways (RCP) 8.5 scenario. The increasing trend is 0.014 °C per year. Accordingly, by 2076, the highest prediction of average maximum temperatures is that it will increase by 1.4 °C. The same model predicts an increasing trend of Tmin of 0.004 °C per year, while the highest trend is seen under CGCM3-A2 scenario which is 0.009 °C per year. The highest change predicted for the Tmin is therefore 0.9 °C by 2076. The precipitation showed a maximum trend of decrease of 12.7 mm year. It is also seen in the output using CanESM2 data that precipitation will be more chaotic with some reaching 4800 mm per year and also producing low rainfall about 1800 mm per year. All GCMs considered are consistent in predicting it is very likely that Brunei is expected to experience more warming as well as less frequent precipitation events but with a possibility of intensified and drastically high rainfalls in the future.

Adaptive design of an X-ray magnetic circular dichroism spectroscopy experiment with Gaussian process modelling

NASA Astrophysics Data System (ADS)

Ueno, Tetsuro; Hino, Hideitsu; Hashimoto, Ai; Takeichi, Yasuo; Sawada, Masahiro; Ono, Kanta

2018-01-01

Spectroscopy is a widely used experimental technique, and enhancing its efficiency can have a strong impact on materials research. We propose an adaptive design for spectroscopy experiments that uses a machine learning technique to improve efficiency. We examined X-ray magnetic circular dichroism (XMCD) spectroscopy for the applicability of a machine learning technique to spectroscopy. An XMCD spectrum was predicted by Gaussian process modelling with learning of an experimental spectrum using a limited number of observed data points. Adaptive sampling of data points with maximum variance of the predicted spectrum successfully reduced the total data points for the evaluation of magnetic moments while providing the required accuracy. The present method reduces the time and cost for XMCD spectroscopy and has potential applicability to various spectroscopies.

Estimation of the Friction Coefficient of a Nanostructured Composite Coating

NASA Astrophysics Data System (ADS)

Shil'ko, S. V.; Chernous, D. A.; Ryabchenko, T. V.; Hat'ko, V. V.

2017-11-01

The frictional-mechanical properties of a thin polymer-ceramic coating obtained by gas-phase impregnation of nanoporous anodic alumina with a fluoropolymer (octafluorocyclobutane) have been investigated. The coefficient of sliding friction of the coating is predicted based on an analysis of contact deformation within the framework of the Winkler elastic foundation hypothesis and a three-phase micromechanical model. It is shown that an acceptable prediction accuracy can be obtained considering the uniaxial strain state of the coating. It was found that, on impregnation by the method of plasmachemical treatment, the relative depth of penetration of the polymer increased almost in proportion to the processing time. The rate and maximum possible depth of penetration of the polymer into nanoscale pores grew with increasing porosity of the alumina substrate.

Nonlinearity of resistive impurity effects on van der Pauw measurements

NASA Astrophysics Data System (ADS)

Koon, D. W.

2006-09-01

The dependence of van der Pauw resistivity measurements on local macroscopic inhomogeneities is shown to be nonlinear. A resistor grid network models a square laminar specimen, enabling the investigation of both positive and negative local perturbations in resistivity. The effect of inhomogeneity is measured both experimentally, for an 11×11 grid, and computationally, for both 11×11 and 101×101 grids. The maximum "shortlike" perturbation produces 3.1±0.2 times the effect predicted by the linear approximation, regardless of its position within the specimen, while all "openlike" perturbations produce a smaller effect than predicted. An empirical nonlinear correction for f(x ,y) is presented which provides excellent fit over the entire range of both positive and negative perturbations for the entire specimen.

Experimental Study of Large-Amplitude Faraday Waves in Rectangular Cylinders

NASA Technical Reports Server (NTRS)

Iek, Chanthy; Alexander, Iwan J.; Tin, Padetha; Adamovsky, Gregory

2005-01-01

Experiment on single-mode Faraday waves having two, thee, and four wavelengths across a rectangular cylinder of high aspect ratio is the subject of discussion. Previous experiments recently done by Henderson & Miles (1989) and by Lei Jiang et. a1 (1996) focused on Faraday waves with one and two wavelengths across rectangular cylinders. In this experimental study the waves steepness ranges from small at threshold levels to a large amplitude which according to Penny & Price theory (1952) approaches the maximum sustainable amplitude for a standing wave. The waves characteristics for small amplitudes are evaluated against an existing well known linear theory by Benjamin & Ursell (l954) and against a weakly nonlinear theory by J. Miles (1984) which includes the effect of viscous damping. The evaluation includes the wave neutral stability and damping rate. In addition, a wave amplitude differential equation of a linear theory including viscous effect by Cerda & Tirapegui (1998) is solved numerically to yield prediction of temporal profiles of both wave damping and wave formation at the threshold. An interesting finding from this exercise is that the fluid kinematic viscosity needs to increase ten times in order to obtain good agreement between the theoretical prediction and the experimental data for both wave damping and wave starting. For large amplitude waves, the experimental data are evaluated against the theory of Penny & Price which predicts wave characteristics of any amplitude up to the point at which the wave reaches its maximum amplitude attainable for a standing wave. The theory yields two criteria to show the maximum wave steepness, the vertical acceleration at the wave crest of half the earth gravity field acceleration and the including angle at the crest of 90 degrees. Comparison with experimental data shows close agreement for the wave crest acceleration but a large discrepancy for the including angle. Additional information is included in the original extended abstract.

Preshot Predictions for Defect Induced Mix (DIME) Capsules

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

Bradley, Paul A.; Krasheninnikova, Natalia S.; Tregillis, Ian L.

2012-07-31

In this memo, we evaluate the most probable yield and other results for the Defect Induced Mix (DIME-12A) Polar Direct Drive (PDD) capsule-only shots. We evaluate the expected yield, bang time, burn averaged ion temperature, and the average electron temperature of the Ge line-emitting region. We also include synthetic images of the capsule backlit by Cu K-{alpha} emission (8.39 keV) and core self-emission synthetic images. This memo is a companion to the maximum credible yield memo (LA-UR-12-00287) published earlier.

Neutral changes during divergent evolution of hemoglobins

NASA Technical Reports Server (NTRS)

Jukes, T. H.

1978-01-01

A comparison of the mRNAs for rabbit and human beta-hemoglobins shows that synonymous changes in codons have accumulated three times as rapidly as nucleotide replacements that produced changes in amino acids. This agrees with predictions based on the so-called neutral theory. In addition, seven codon changes that appear to be single-base changes (according to maximum parsimony) are actually two-base changes. This indicates that the construction of primordial sequences is of limited significance when based on inferences that assume minimum base changes for amino acid replacements.

Jovian ultraviolet auroral activity, 1981-1991

NASA Technical Reports Server (NTRS)

Livengood, T. A.; Moos, H. W.; Ballester, G. E.; Prange, R. M.

1992-01-01

IUE observations of H2 UV emissions for the 1981-1991 period are presently used to investigate the auroral brightness distribution on the surface of Jupiter. The brightness, which is diagnostic of energy input to the atmosphere as well as of magnetospheric processes, is determined by comparing model-predicted brightnesses against empirical ones. The north and south aurorae appear to be correlated in brightness and in variations of the longitude of peak brightness. There are strong fluctuations in all the parameters of the brightness distribution on much shorter time scales than those of solar maximum-minimum.

Brownian motion of a circle swimmer in a harmonic trap

NASA Astrophysics Data System (ADS)

Jahanshahi, Soudeh; Löwen, Hartmut; ten Hagen, Borge

2017-02-01

We study the dynamics of a Brownian circle swimmer with a time-dependent self-propulsion velocity in an external temporally varying harmonic potential. For several situations, the noise-free swimming paths, the noise-averaged mean trajectories, and the mean-square displacements are calculated analytically or by computer simulation. Based on our results, we discuss optimal swimming strategies in order to explore a maximum spatial range around the trap center. In particular, we find a resonance situation for the maximum escape distance as a function of the various frequencies in the system. Moreover, the influence of the Brownian noise is analyzed by comparing noise-free trajectories at zero temperature with the corresponding noise-averaged trajectories at finite temperature. The latter reveal various complex self-similar spiral or rosette-like patterns. Our predictions can be tested in experiments on artificial and biological microswimmers under dynamical external confinement.

Relationship Between Frequency and Deflection Angle in the DNA Prism

PubMed Central

Chen, Zhen; Dorfman, Kevin D.

2013-01-01

The DNA prism is a modification of the standard pulsed-field electrophoresis protocol to provide a continuous separation, where the DNA are deflected at an angle that depends on their molecular weight. The standard switchback model for the DNA prism predicts a monotonic increase in the deflection angle as a function of the frequency for switching the field until a plateau regime is reached. However, experiments indicate that the deflection angle achieves a maximum value before decaying to a size-independent value at high frequencies. Using Brownian dynamics simulations, we show that the maximum in the deflection angle is related to the reorientation time for the DNA and the decay in deflection angle at high frequencies is due to inadequate stretching. The generic features of the dependence of the deflection angle on molecular weight, switching frequency, and electric field strength explain a number of experimental phenomena. PMID:23410375

Comparison of Forecast and Observed Energetics

NASA Technical Reports Server (NTRS)

Baker, W. E.; Brin, Y.

1984-01-01

An energetics analysis scheme was developed to compare the observed kinetic energy balance over North America with that derived from forecast fields of the GLAS fourth order model for the 13 to 15 January 1979 cyclone case. It is found that: (1) the observed and predicted kinetic energy and eddy conversion are in good qualitative agreement, although the model eddy conversion tends to be 2 to 3 times stronger than the observed values. The eddy conversion which is stronger in the 12 h forecast than in observations and may be due to several factors is studied; (2) vertical profiles of kinetic energy generation and dissipation exhibit lower and upper tropospheric maxima in both the forecast and observations; (3) a lag in the observational analysis with the maximum in the observed kinetic energy occurring at 0000 GMT 14 January over the same region as the maximum ddy conversion 12 h earlier is noted.

Time-course measurements of drug concentrations in hair and toenails after single administrations of pharmaceutical products.

PubMed

Kuwayama, Kenji; Miyaguchi, Hajime; Iwata, Yuko T; Kanamori, Tatsuyuki; Tsujikawa, Kenji; Yamamuro, Tadashi; Segawa, Hiroki; Inoue, Hiroyuki

2017-04-01

Hair and nails are often used to prove long-term intake of drugs in forensic drug testing. The aim of this study was to evaluate the effectiveness of drug testing using hair and nails and the feasibility of determining when drugs were ingested by measuring the time-courses of drug concentrations in hair and toenails after single administrations of various drugs. Healthy subjects ingested four pharmaceutical products containing eight active ingredients in single doses. Hair and toenails were collected at predetermined intervals, and drug concentrations in hair and nails were measured for 12 months. The administered drugs and their main metabolites were extracted using micropulverized extraction with a stainless steel bullet and were analyzed using liquid chromatography/tandem mass spectrometry. Acidic compounds such as ibuprofen and its metabolites were not detected in both specimens. Acetaminophen, a weakly acidic compound, was detected in nails more frequently than in hair. The maximum concentration of allyl isopropyl acetylurea, a neutral compound, in nails was significantly higher than in hair. Nails are an effective specimen to detect neutral and weakly acidic compounds. For fexofenadine, a zwitterionic compound, and for most basic compounds, the maximum concentrations in hair segments tended to be higher than those in nails. The hair segments showing the maximum concentrations varied between drugs, samples, and subjects. Drug concentrations in hair segments greatly depended on the selection of the hair. Careful interpretation of analytical results is required to predict the time of drug intake. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The application of a Grey Markov Model to forecasting annual maximum water levels at hydrological stations

NASA Astrophysics Data System (ADS)

Dong, Sheng; Chi, Kun; Zhang, Qiyi; Zhang, Xiangdong

2012-03-01

Compared with traditional real-time forecasting, this paper proposes a Grey Markov Model (GMM) to forecast the maximum water levels at hydrological stations in the estuary area. The GMM combines the Grey System and Markov theory into a higher precision model. The GMM takes advantage of the Grey System to predict the trend values and uses the Markov theory to forecast fluctuation values, and thus gives forecast results involving two aspects of information. The procedure for forecasting annul maximum water levels with the GMM contains five main steps: 1) establish the GM (1, 1) model based on the data series; 2) estimate the trend values; 3) establish a Markov Model based on relative error series; 4) modify the relative errors caused in step 2, and then obtain the relative errors of the second order estimation; 5) compare the results with measured data and estimate the accuracy. The historical water level records (from 1960 to 1992) at Yuqiao Hydrological Station in the estuary area of the Haihe River near Tianjin, China are utilized to calibrate and verify the proposed model according to the above steps. Every 25 years' data are regarded as a hydro-sequence. Eight groups of simulated results show reasonable agreement between the predicted values and the measured data. The GMM is also applied to the 10 other hydrological stations in the same estuary. The forecast results for all of the hydrological stations are good or acceptable. The feasibility and effectiveness of this new forecasting model have been proved in this paper.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling.

PubMed

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2016-09-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling

PubMed Central

Wang, Sheng; Sun, Siqi

2017-01-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC. PMID:28884168

Soil- and crop-dependent variation in correlation lag between precipitation and agricultural drought indices as predicted by the SWAP model

NASA Astrophysics Data System (ADS)

Wright, Azin; Cloke, Hannah; Verhoef, Anne

2017-04-01

Droughts have a devastating impact on agriculture and economy. The risk of more frequent and more severe droughts is increasing due to global warming and certain anthropogenic activities. At the same time, the global population continues to rise and the need for sustainable food production is becoming more and more pressing. In light of this, drought prediction can be of great value; in the context of early warning, preparedness and mitigation of drought impacts. Prediction of meteorological drought is associated with uncertainties around precipitation variability. As meteorological drought propagates, it can transform into agricultural drought. Determination of the maximum correlation lag between precipitation and agricultural drought indices can be useful for prediction of agricultural drought. However, the influence of soil and crop type on the lag needs to be considered, which we explored using a 1-D Soil-Vegetation-Atmosphere-Transfer model (SWAP (http://www.swap.alterra.nl/), with the following configurations, all forced with ERA-Interim weather data (1979 to 2014): i) different crop types in the UK; ii) three generic soil types (clay, loam and sand) were considered. A Sobol sensitivity analysis was carried out (perturbing the SWAP model van Genuchten soil hydraulic parameters) to study the effect of soil type uncertainty on the water balance variables. Based on the sensitivity analysis results, a few variations of each soil type were selected. Agricultural drought indices including Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) were calculated. The maximum correlation lag between precipitation and these drought indices was calculated, and analysed in the context of crop and soil model parameters. The findings of this research can be useful to UK farming, by guiding government bodies such as the Environment Agency when issuing drought warnings and implementing drought measures.

Global Solar Magnetology and Reference Points of the Solar Cycle

NASA Astrophysics Data System (ADS)

Obridko, V. N.; Shelting, B. D.

2003-11-01

The solar cycle can be described as a complex interaction of large-scale/global and local magnetic fields. In general, this approach agrees with the traditional dynamo scheme, although there are numerous discrepancies in the details. Integrated magnetic indices introduced earlier are studied over long time intervals, and the epochs of the main reference points of the solar cycles are refined. A hypothesis proposed earlier concerning global magnetometry and the natural scale of the cycles is verified. Variations of the heliospheric magnetic field are determined by both the integrated photospheric i(B r )ph and source surface i(B r )ss indices, however, their roles are different. Local fields contribute significantly to the photospheric index determining the total increase in the heliospheric magnetic field. The i(B r )ss index (especially the partial index ZO, which is related to the quasi-dipolar field) determines narrow extrema. These integrated indices supply us with a “passport” for reference points, making it possible to identify them precisely. A prominent dip in the integrated indices is clearly visible at the cycle maximum, resulting in the typical double-peak form (the Gnevyshev dip), with the succeeding maximum always being higher than the preceding maximum. At the source surface, this secondary maximum significantly exceeds the primary maximum. Using these index data, we can estimate the progression expected for the 23rd cycle and predict the dates of the ends of the 23rd and 24th cycles (the middle of 2007 and December 2018, respectively).

Complex network approach to fractional time series

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

Manshour, Pouya

In order to extract correlation information inherited in stochastic time series, the visibility graph algorithm has been recently proposed, by which a time series can be mapped onto a complex network. We demonstrate that the visibility algorithm is not an appropriate one to study the correlation aspects of a time series. We then employ the horizontal visibility algorithm, as a much simpler one, to map fractional processes onto complex networks. The degree distributions are shown to have parabolic exponential forms with Hurst dependent fitting parameter. Further, we take into account other topological properties such as maximum eigenvalue of the adjacencymore » matrix and the degree assortativity, and show that such topological quantities can also be used to predict the Hurst exponent, with an exception for anti-persistent fractional Gaussian noises. To solve this problem, we take into account the Spearman correlation coefficient between nodes' degrees and their corresponding data values in the original time series.« less

Time-dependent response of filamentary composite spherical pressure vessels

NASA Technical Reports Server (NTRS)

Dozier, J. D.

1983-01-01

A filamentary composite spherical pressure vessel is modeled as a pseudoisotropic (or transversely isotropic) composite shell, with the effects of the liner and fill tubes omitted. Equations of elasticity, macromechanical and micromechanical formulations, and laminate properties are derived for the application of an internally pressured spherical composite vessel. Viscoelastic properties for the composite matrix are used to characterize time-dependent behavior. Using the maximum strain theory of failure, burst pressure and critical strain equations are formulated, solved in the Laplace domain with an associated elastic solution, and inverted back into the time domain using the method of collocation. Viscoelastic properties of HBFR-55 resin are experimentally determined and a Kevlar/HBFR-55 system is evaluated with a FORTRAN program. The computed reduction in burst pressure with respect to time indicates that the analysis employed may be used to predict the time-dependent response of a filamentary composite spherical pressure vessel.

Evaluating principal surrogate endpoints with time-to-event data accounting for time-varying treatment efficacy.

PubMed

Gabriel, Erin E; Gilbert, Peter B

2014-04-01

Principal surrogate (PS) endpoints are relatively inexpensive and easy to measure study outcomes that can be used to reliably predict treatment effects on clinical endpoints of interest. Few statistical methods for assessing the validity of potential PSs utilize time-to-event clinical endpoint information and to our knowledge none allow for the characterization of time-varying treatment effects. We introduce the time-dependent and surrogate-dependent treatment efficacy curve, ${\\mathrm {TE}}(t|s)$, and a new augmented trial design for assessing the quality of a biomarker as a PS. We propose a novel Weibull model and an estimated maximum likelihood method for estimation of the ${\\mathrm {TE}}(t|s)$ curve. We describe the operating characteristics of our methods via simulations. We analyze data from the Diabetes Control and Complications Trial, in which we find evidence of a biomarker with value as a PS.

Solar maximum: Solar array degradation

NASA Technical Reports Server (NTRS)

Miller, T.

1985-01-01

The 5-year in-orbit power degradation of the silicon solar array aboard the Solar Maximum Satellite was evaluated. This was the first spacecraft to use Teflon R FEP as a coverglass adhesive, thus avoiding the necessity of an ultraviolet filter. The peak power tracking mode of the power regulator unit was employed to ensure consistent maximum power comparisons. Telemetry was normalized to account for the effects of illumination intensity, charged particle irradiation dosage, and solar array temperature. Reference conditions of 1.0 solar constant at air mass zero and 301 K (28 C) were used as a basis for normalization. Beginning-of-life array power was 2230 watts. Currently, the array output is 1830 watts. This corresponds to a 16 percent loss in array performance over 5 years. Comparison of Solar Maximum Telemetry and predicted power levels indicate that array output is 2 percent less than predictions based on an annual 1.0 MeV equivalent election fluence of 2.34 x ten to the 13th power square centimeters space environment.

Testing the assumption in ergonomics software that overall shoulder strength can be accurately calculated by treating orthopedic axes as independent.

PubMed

Hodder, Joanne N; La Delfa, Nicholas J; Potvin, Jim R

2016-08-01

To predict shoulder strength, most current ergonomics software assume independence of the strengths about each of the orthopedic axes. Using this independent axis approach (IAA), the shoulder can be predicted to have strengths as high as the resultant of the maximum moment about any two or three axes. We propose that shoulder strength is not independent between axes, and propose an approach that calculates the weighted average (WAA) between the strengths of the axes involved in the demand. Fifteen female participants performed maximum isometric shoulder exertions with their right arm placed in a rigid adjustable brace affixed to a tri-axial load cell. Maximum exertions were performed in 24 directions, including four primary directions, horizontal flexion-extension, abduction-adduction, and at 15° increments in between those axes. Moments were computed and comparisons made between the experimentally collected strengths and those predicted by the IAA and WAA methods. The IAA over-predicted strength in 14 of 20 non-primary exertions directions, while the WAA underpredicted strength in only 2 of these directions. Therefore, it is not valid to assume that shoulder axes are independent when predicting shoulder strengths between two orthopedic axes, and the WAA is an improvement over current methods for the posture tested. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia

NASA Astrophysics Data System (ADS)

Deo, Ravinesh C.; Şahin, Mehmet

2015-02-01

The prediction of future drought is an effective mitigation tool for assessing adverse consequences of drought events on vital water resources, agriculture, ecosystems and hydrology. Data-driven model predictions using machine learning algorithms are promising tenets for these purposes as they require less developmental time, minimal inputs and are relatively less complex than the dynamic or physical model. This paper authenticates a computationally simple, fast and efficient non-linear algorithm known as extreme learning machine (ELM) for the prediction of Effective Drought Index (EDI) in eastern Australia using input data trained from 1957-2008 and the monthly EDI predicted over the period 2009-2011. The predictive variables for the ELM model were the rainfall and mean, minimum and maximum air temperatures, supplemented by the large-scale climate mode indices of interest as regression covariates, namely the Southern Oscillation Index, Pacific Decadal Oscillation, Southern Annular Mode and the Indian Ocean Dipole moment. To demonstrate the effectiveness of the proposed data-driven model a performance comparison in terms of the prediction capabilities and learning speeds was conducted between the proposed ELM algorithm and the conventional artificial neural network (ANN) algorithm trained with Levenberg-Marquardt back propagation. The prediction metrics certified an excellent performance of the ELM over the ANN model for the overall test sites, thus yielding Mean Absolute Errors, Root-Mean Square Errors, Coefficients of Determination and Willmott's Indices of Agreement of 0.277, 0.008, 0.892 and 0.93 (for ELM) and 0.602, 0.172, 0.578 and 0.92 (for ANN) models. Moreover, the ELM model was executed with learning speed 32 times faster and training speed 6.1 times faster than the ANN model. An improvement in the prediction capability of the drought duration and severity by the ELM model was achieved. Based on these results we aver that out of the two machine learning algorithms tested, the ELM was the more expeditious tool for prediction of drought and its related properties.

41 CFR 301-31.10 - How will my agency pay my subsistence expenses?

Code of Federal Regulations, 2010 CFR

2010-07-01

... applicable to the locality .75 times the maximum lodging amount applicable to the locality .5 times the maximum lodging amount applicable to the locality. Payment for lodging, meals, and other per diem expenses The maximum per diem rate applicable to the locality .75 times the maximum per diem rate applicable to...

26 CFR 1.410(a)-4 - Maximum age conditions and time of participation.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 26 Internal Revenue 5 2012-04-01 2011-04-01 true Maximum age conditions and time of participation.... § 1.410(a)-4 Maximum age conditions and time of participation. (a) Maximum age conditions—(1) General...) if the plan excludes from participation (on the basis of age) an employee who has attained an age...

26 CFR 1.410(a)-4 - Maximum age conditions and time of participation.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 26 Internal Revenue 5 2011-04-01 2011-04-01 false Maximum age conditions and time of participation.... § 1.410(a)-4 Maximum age conditions and time of participation. (a) Maximum age conditions—(1) General...) if the plan excludes from participation (on the basis of age) an employee who has attained an age...

26 CFR 1.410(a)-4 - Maximum age conditions and time of participation.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 26 Internal Revenue 5 2010-04-01 2010-04-01 false Maximum age conditions and time of participation... Maximum age conditions and time of participation. (a) Maximum age conditions—(1) General rule. A plan is... excludes from participation (on the basis of age) an employee who has attained an age specified by the plan...

Shock spectra applications to a class of multiple degree-of-freedom structures system

NASA Technical Reports Server (NTRS)

Hwang, Shoi Y.

1988-01-01

The demand on safety performance of launching structure and equipment system from impulsive excitations necessitates a study which predicts the maximum response of the system as well as the maximum stresses in the system. A method to extract higher modes and frequencies for a class of multiple degree-of-freedom (MDOF) Structure system is proposed. And, along with the shock spectra derived from a linear oscillator model, a procedure to obtain upper bound solutions for maximum displacement and maximum stresses in the MDOF system is presented.

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

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

Bramer, Lisa M.; Rounds, J.; Burleyson, C. D.

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions were examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and combinations of predictive variables were examined. A penalized logistic regression model which wasmore » fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at various time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. In conclusion, the methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.« less

[Evaluating the performance of species distribution models Biomod2 and MaxEnt using the giant panda distribution data].

PubMed

Luo, Mei; Wang, Hao; Lyu, Zhi

2017-12-01

Species distribution models (SDMs) are widely used by researchers and conservationists. Results of prediction from different models vary significantly, which makes users feel difficult in selecting models. In this study, we evaluated the performance of two commonly used SDMs, the Biomod2 and Maximum Entropy (MaxEnt), with real presence/absence data of giant panda, and used three indicators, i.e., area under the ROC curve (AUC), true skill statistics (TSS), and Cohen's Kappa, to evaluate the accuracy of the two model predictions. The results showed that both models could produce accurate predictions with adequate occurrence inputs and simulation repeats. Comparedto MaxEnt, Biomod2 made more accurate prediction, especially when occurrence inputs were few. However, Biomod2 was more difficult to be applied, required longer running time, and had less data processing capability. To choose the right models, users should refer to the error requirements of their objectives. MaxEnt should be considered if the error requirement was clear and both models could achieve, otherwise, we recommend the use of Biomod2 as much as possible.

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

DOE PAGES

Bramer, Lisa M.; Rounds, J.; Burleyson, C. D.; ...

2017-09-22

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions were examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and combinations of predictive variables were examined. A penalized logistic regression model which wasmore » fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at various time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. In conclusion, the methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.« less

Multifractality and autoregressive processes of dry spell lengths in Europe: an approach to their complexity and predictability

NASA Astrophysics Data System (ADS)

Lana, X.; Burgueño, A.; Serra, C.; Martínez, M. D.

2017-01-01

Dry spell lengths, DSL, defined as the number of consecutive days with daily rain amounts below a given threshold, may provide relevant information about drought regimes. Taking advantage of a daily pluviometric database covering a great extension of Europe, a detailed analysis of the multifractality of the dry spell regimes is achieved. At the same time, an autoregressive process is applied with the aim of predicting DSL. A set of parameters, namely Hurst exponent, H, estimated from multifractal spectrum, f( α), critical Hölder exponent, α 0, for which f( α) reaches its maximum value, spectral width, W, and spectral asymmetry, B, permits a first clustering of European rain gauges in terms of the complexity of their DSL series. This set of parameters also allows distinguishing between time series describing fine- or smooth-structure of the DSL regime by using the complexity index, CI. Results of previous monofractal analyses also permits establishing comparisons between smooth-structures, relatively low correlation dimensions, notable predictive instability and anti-persistence of DSL for European areas, sometimes submitted to long droughts. Relationships are also found between the CI and the mean absolute deviation, MAD, and the optimum autoregressive order, OAO, of an ARIMA( p, d,0) autoregressive process applied to the DSL series. The detailed analysis of the discrepancies between empiric and predicted DSL underlines the uncertainty over predictability of long DSL, particularly for the Mediterranean region.

Sudden temperature changes in the Sydney Basin: climatology and case studies during the Olympic months of September and October

NASA Astrophysics Data System (ADS)

Buckley, Bruce W.; Leslie, Lance M.

2000-03-01

The accurate prediction of sudden large changes in the maximum temperature from one day to the next remains one of the major challenges for operational forecasters. It is probably the meteorological parameter most commonly verified and used as a measure of the skill of a meteorological service and one that is immediately evident to the general public. Marked temperature changes over a short period of time have widespread social, economic, health and safety effects on the community. The first part of this paper describes a 40-year climatology for Sydney, Australia, of sudden temperature rises and falls, defined as maximum temperature changes of 5°C or more from one day to the next, for the months of September and October. The nature of the forecasting challenge during the period of the Olympic and Paralympic Games to be held in Sydney in the year 2000 will be described as a special application. The international importance of the accurate prediction of all types of significant weather phenomena during this period has been recognized by the World Meteorological Organisation's Commission for Atmospheric Science. The first World Weather Research Program forecast demonstration project is to be established in the Sydney Office of the Bureau of Meteorology over this period in order to test the ability of existing systems to predict such phenomena. The second part of this study investigates two case studies from the Olympic months in which there were both abrupt temperature rises and falls over a 4-day interval. Currently available high resolution numerical weather prediction systems are found to have significant skill several days ahead in predicting a large amount of the detail of these events, provided they are run at an appropriate resolution. The limitations of these systems are also discussed, with areas requiring further development being identified if the desired levels of accuracy of predictions are to be reliably delivered. Differences between the predictability of sudden temperature rises and sudden temperature falls are also explored.

Predicting procedural pain after ureteroscopy: does hydrodistention play a role?

PubMed Central

Gul, Zeynep; Alazem, Kareem; Li, Ina; Monga, Manoj

2016-01-01

ABSTRACT Purpose: To identify perioperative predictors of immediate pain after ureteroscopy, specifically evaluating the impact of hydrodistention from irrigation on pain. Materials and Methods: We retrospectively identified patients who underwent ureteroscopy for the treatment of calculi. Data recorded for these patients included their maximum pain score in the post-anesthesia care unit (PACU), average flow rate of irrigant used during the procedure, patient and stone characteristics, operative procedure, and details of patients' immediate, post-operative course. Spearman's rho was used to determine the relationship between non-parametric, continuous variables. Then, a linear regression was performed to assess which variables could predict the peak pain score. Results: A total of 131 patients were included in the study. A non-parametric correlation analysis revealed that maximum pain score was negatively correlated with being male (r = −0.18, p=0.04), age (r = −0.34, p<0.001), and post-op foley placement (r = −0.20, p=0.02) but positively correlated with the preoperative pain score (r = 0.41, p<0.001), time in the PACU (r = 0.19, p = 0.03), and the morphine equivalent dose (MED) of narcotics administered in the PACU (r = 0.67, p<0.001). On linear regression, the significant variables were age, preoperative pain score, and stent placement. For every ten-year increase in age post-operative pain score decreased by 4/10 of a point (p = 0.03). For every 1 point increase in preoperative pain score there was a 3/10 of a point increase in the maximum pain score (p = 0.01), and leaving a stent in place post-operatively was associated with a 1.6 point increase in the maximum pain score. Conclusions: Hydrodistention does not play a role in post-ureteroscopy pain. Patients who are younger, have higher preoperative pain scores, or who are stented will experience more post-operative pain after ureteroscopy. PMID:27564284