Classification of new-ice in the Greenland Sea using Satellite SSM/I radiometer and SeaWinds scatterometer data and comparison with ice model

DEFF Research Database (Denmark)

Tonboe, Rasmus; Pedersen, Leif Toudal

2005-01-01

In the ice covered waters of the Greenland Sea the polarisation ratio of QuikSCAT SeaWinds Ku-band (13.4 GHz) scatterometer measurements and the polarisation ratio of DMSP-SSM/I 19 GHz radiometer measurements are used in combination to classify new-ice and mature ice. In particular, the formation...... to the physical transition of the ice cover from pancake ice to a consolidated young-ice sheet. The classification of each pixel into ice or water is done using two scatterometer parameters, namely the polarisation ratio and the daily standard deviation of the backscatter. (C) 2005 Elsevier Inc. All rights...

The relationship between the microwave radar cross section and both wind speed and stress: Model function studies using Frontal Air-Sea Interaction Experiment data

Science.gov (United States)

Weissman, David E.; Davidson, Kenneth L.; Brown, Robert A.; Friehe, Carl A.; Li, Fuk

1994-01-01

The Frontal Air-Sea Interaction Experiment (FASINEX) provided a unique data set with coincident airborne scatterometer measurements of the ocean surface radar cross section (RCS)(at Ku band) and near-surface wind and wind stress. These data have been analyzed to study new model functions which relate wind speed and surface friction velocity (square root of the kinematic wind stress) to the radar cross section and to better understand the processes in the boundary layer that have a strong influence on the radar backscatter. Studies of data from FASINEX indicate that the RCS has a different relation to the friction velocity than to the wind speed. The difference between the RCS models using these two variables depends on the polarization and the incidence angle. The radar data have been acquired from the Jet Propulsion Laboratory airborne scatterometer. These data span 10 different flight days. Stress measurements were inferred from shipboard instruments and from aircraft flying at low altitudes, closely following the scatterometer. Wide ranges of radar incidence angles and environmental conditions needed to fully develop algorithms are available from this experiment.

Estimates of oceanic surface wind speed and direction using orthogonal beam scatterometer measurements and comparison of recent sea scattering theories

Science.gov (United States)

Moore, R. K.; Fung, A. K.; Dome, G. J.; Birrer, I. J.

1978-01-01

The wind direction properties of radar backscatter from the sea were empirically modelled using a cosine Fourier series through the 4th harmonic in wind direction (referenced to upwind). A comparison with 1975 JONSWAP (Joint North Sea Wave Project) scatterometer data, at incidence angles of 40 and 65, indicates that effects to third and fourth harmonics are negligible. Another important result is that the Fourier coefficients through the second harmonic are related to wind speed by a power law expression. A technique is also proposed to estimate the wind speed and direction over the ocean from two orthogonal scattering measurements. A comparison between two different types of sea scatter theories, one type presented by the work of Wright and the other by that of Chan and Fung, was made with recent scatterometer measurements. It demonstrates that a complete scattering model must include some provisions for the anisotropic characteristics of the sea scatter, and use a sea spectrum which depends upon wind speed.

Annual and interannual variability of scatterometer ocean surface wind over the South China Sea

DEFF Research Database (Denmark)

Zhang, GS; Xu, Q.; Gong, Z.

2014-01-01

To investigate the annual and interannual variability of ocean surface wind over the South China Sea (SCS), the vector empirical orthogonal function (VEOF) method and the Hilbert-Huang transform (HHT) method were employed to analyze a set of combined satellite scatterometer wind data during.......3% of the total variance and represents the East Asian monsoon features. The second mode of VEOF corresponds to a spring-autumn oscillation which accounts for 8.3% of the total variance. To analyze the interannual variability, the annual signal was removed from the wind data set and the VEOFs of the residuals...

Polar Sea Ice Monitoring Using HY-2A Scatterometer Measurements

Directory of Open Access Journals (Sweden)

Mingming Li

2016-08-01

Full Text Available A sea ice detection algorithm based on Fisher’s linear discriminant analysis is developed to segment sea ice and open water for the Ku-band scatterometer onboard the China’s Hai Yang 2A Satellite (HY-2A/SCAT. Residual classification errors are reduced through image erosion/dilation techniques and sea ice growth/retreat constraint methods. The arctic sea-ice-type classification is estimated via a time-dependent threshold derived from the annual backscatter trends based on previous HY-2A/SCAT derived sea ice extent. The extent and edge of the sea ice obtained in this study is compared with the Special Sensor Microwave Imager/Sounder (SSMIS sea ice concentration data and the Sentinel-1 SAR imagery for verification, respectively. Meanwhile, the classified sea ice type is compared with a multi-sensor sea ice type product based on data from the Advanced Scatterometer (ASCAT and SSMIS. Results show that HY-2A/SCAT is powerful in providing sea ice extent and type information, while differences in the sensitivities of active/passive products are found. In addition, HY-2A/SCAT derived sea ice products are also proved to be valuable complements for existing polar sea ice data products.

Prediction of tropical cyclone over North Indian Ocean using WRF model: sensitivity to scatterometer winds, ATOVS and ATMS radiances

KAUST Repository

Dodla, Venkata B.

2016-05-03

Tropical cyclone prediction, in terms of intensification and movement, is important for disaster management and mitigation. Hitherto, research studies were focused on this issue that lead to improvement in numerical models, initial data with data assimilation, physical parameterizations and application of ensemble prediction. Weather Research and Forecasting (WRF) model is the state-of-art model for cyclone prediction. In the present study, prediction of tropical cyclone (Phailin, 2013) that formed in the North Indian Ocean (NIO) with and without data assimilation using WRF model has been made to assess impacts of data assimilation. WRF model was designed to have nested two domains of 15 and 5 km resolutions. In the present study, numerical experiments are made without and with the assimilation of scatterometer winds, and radiances from ATOVS and ATMS. The model performance was assessed in respect to the movement and intensification of cyclone. ATOVS data assimilation experiment had produced the best prediction with least errors less than 100 km up to 60 hours and producing pre-deepening and deepening periods accurately. The Control and SCAT wind assimilation experiments have shown good track but the errors were 150-200 km and gradual deepening from the beginning itself instead of sudden deepening.

Evaluation of HY-2A Scatterometer Wind Vectors Using Data from Buoys, ERA-Interim and ASCAT during 2012–2014

Directory of Open Access Journals (Sweden)

Jianyong Xing

2016-05-01

Full Text Available The first Chinese operational Ku-band scatterometer on board Haiyang-2A (HY-2A, launched in August 2011, is designed for monitoring the global ocean surface wind. This study estimates the quality of the near-real-time (NRT retrieval wind speed and wind direction from the HY-2A scatterometer for 36 months from 2012 to 2014. We employed three types of sea-surface wind data from oceanic moored buoys operated by the National Data Buoy Center (NDBC and the Tropical Atmospheric Ocean project (TAO, the European Centre for Medium Range Weather Forecasting (ECMWF reanalysis data (ERA-Interim, and the advanced scatterometer (ASCAT to calculate the error statistics including mean bias, root mean square error (RMSE, and standard deviation. In addition, the rain effects on the retrieval winds were investigated using collocated Climate Prediction Center morphing method (CMORPH precipitation data. All data were collocated with the HY-2A scatterometer wind data for comparison. The quality performances of the HY-2A NRT wind vectors data (especially the wind speeds were satisfactory throughout the service period. The RMSEs of the HY-2A wind speeds relative to the NDBC, TAO, ERA-Interim, and ASCAT data were 1.94, 1.73, 2.25, and 1.62 m·s−1, respectively. The corresponding RMSEs of the wind direction were 46.63°, 43.11°, 39.93°, and 47.47°, respectively. The HY-2A scatterometer overestimated low wind speeds, especially under rainy conditions. Rain exerted a diminishing effect on the wind speed retrievals with increasing wind speed, but its effect on wind direction was robust at low and moderate wind speeds. Relative to the TAO buoy data, the RMSEs without rain effect were reduced to 1.2 m·s−1 and 39.68° for the wind speed direction, respectively, regardless of wind speed. By investigating the objective laws between rain and the retrieval winds from HY-2A, we could improve the quality of wind retrievals through future studies.

A study of the feasibility of using sea and wind information from the ERS-1 satellite. Part 1: Wind scatterometer data

Science.gov (United States)

Anderson, D.; Hollingsworth, A.; Uppala, S.; Woiceshyn, P.

1987-01-01

The use of scatterometer and altimeter data in wind and wave assimilation, and the benefits this offers for quality assurance and validation of ERS-1 data were examined. Real time use of ERS-1 data was simulated through assimilation of Seasat scatterometer data. The potential for quality assurance and validation is demonstrated by documenting a series of substantial problems with the scatterometer data, which are known but took years to establish, or are new. A data impact study, and an analysis of the performance of ambiguity removal algorithms on real and simulated data were conducted. The impact of the data on analyses and forecasts is large in the Southern Hemisphere, generally small in the Northern Hemisphere, and occasionally large in the Tropics. Tests with simulated data give more optimistic results than tests with real data. Errors in ambiguity removal results occur in clusters. The probabilities which can be calculated for the ambiguous wind directions on ERS-1 contain more information than is given by a simple ranking of the directions.

Spatial variability and trends of seasonal snowmelt processes over Antarctic sea ice observed by satellite scatterometers

Science.gov (United States)

Arndt, S.; Haas, C.

2017-12-01

Snow is one of the key drivers determining the seasonal energy and mass budgets of sea ice in the Southern Ocean. Here, we analyze radar backscatter time series from the European Remote Sensing Satellites (ERS)-1 and-2 scatterometers, from the Quick Scatterometer (QSCAT), and from the Advanced Scatterometer (ASCAT) in order to observe the regional and inter-annual variability of Antarctic snowmelt processes from 1992 to 2014. On perennial ice, seasonal backscatter changes show two different snowmelt stages: A weak backscatter rise indicating the initial warming and metamorphosis of the snowpack (pre-melt), followed by a rapid rise indicating the onset of internal snowmelt and thaw-freeze cycles (snowmelt). In contrast, similar seasonal backscatter cycles are absent on seasonal ice, preventing the periodic retrieval of spring/summer transitions. This may be due to the dominance of ice bottom melt over snowmelt, leading to flooding and ice disintegration before strong snowmelt sets in. Resulting snowmelt onset dates on perennial sea ice show the expected latitudinal gradient from early melt onsets (mid-November) in the northern Weddell Sea towards late (end-December) or even absent snowmelt conditions further south. This result is likely related to seasonal variations in solar shortwave radiation (absorption). In addition, observations with different microwave frequencies allow to detect changing snow properties at different depths. We show that short wavelengths of passive microwave observations indicate earlier pre-melt and snowmelt onset dates than longer wavelength scatterometer observations, in response to earlier warming of upper snow layers compared to lower snow layers. Similarly, pre-melt and snowmelt onset dates retrieved from Ku-Band radars were earlier by an average of 11 and 23 days, respectively, than those retrieved from C-Band. This time difference was used to correct melt onset dates retrieved from Ku-Band to compile a consistent time series from

Antecedent wetness conditions based on ERS scatterometer data

Science.gov (United States)

Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.

2009-01-01

SummarySoil moisture is widely recognized as a key parameter in environmental processes mainly for the role of rainfall partitioning into runoff and infiltration. Therefore, for storm rainfall-runoff modeling the estimation of the antecedent wetness conditions ( AWC) is one of the most important aspect. In this context, this study investigates the potential of scatterometer on board of the ERS satellites for the assessment of wetness conditions in three Tiber sub-catchments (Central Italy), of which one includes an experimental area for soil moisture monitoring. The satellite soil moisture data are taken from the ERS/METOP soil moisture archive. First, the scatterometer-derived soil wetness index ( SWI) data are compared with two on-site soil moisture data sets acquired by different methodologies on areas of different extension ranging from 0.01 km 2 to ˜60 km 2. Moreover, the reliability of SWI to estimate the AWC at a catchment scale is investigated considering the relationship between SWI and the soil potential maximum retention parameter, S, of the Soil Conservation Service-Curve Number (SCS-CN) method for abstraction. Several flood events occurred from 1992 to 2005 are selected for this purpose. Specifically, the performance of the SWI for S estimation is compared with two antecedent precipitation indices ( API) and one base flow index ( BFI). The S values obtained through the observed direct runoff volume and rainfall depth are used as benchmark. Results show the great reliability of the SWI for the estimation of wetness conditions both at the plot and catchment scale despite the complex orography of the investigated areas. As far as the comparison with on site soil moisture data set is concerned, the SWI is found quite reliable in representing the soil moisture at layer depth of 15 cm, with a mean correlation coefficient equal to 0.81. The characteristic time length parameter variations, as expected, is depended on soil type, with values in accordance with

Butterfly wing coloration studied with a novel imaging scatterometer

Science.gov (United States)

Stavenga, Doekele

2010-03-01

Animal coloration functions for display or camouflage. Notably insects provide numerous examples of a rich variety of the applied optical mechanisms. For instance, many butterflies feature a distinct dichromatism, that is, the wing coloration of the male and the female differ substantially. The male Brimstone, Gonepteryx rhamni, has yellow wings that are strongly UV iridescent, but the female has white wings with low reflectance in the UV and a high reflectance in the visible wavelength range. In the Small White cabbage butterfly, Pieris rapae crucivora, the wing reflectance of the male is low in the UV and high at visible wavelengths, whereas the wing reflectance of the female is higher in the UV and lower in the visible. Pierid butterflies apply nanosized, strongly scattering beads to achieve their bright coloration. The male Pipevine Swallowtail butterfly, Battus philenor, has dorsal wings with scales functioning as thin film gratings that exhibit polarized iridescence; the dorsal wings of the female are matte black. The polarized iridescence probably functions in intraspecific, sexual signaling, as has been demonstrated in Heliconius butterflies. An example of camouflage is the Green Hairstreak butterfly, Callophrys rubi, where photonic crystal domains exist in the ventral wing scales, resulting in a matte green color that well matches the color of plant leaves. The spectral reflection and polarization characteristics of biological tissues can be rapidly and with unprecedented detail assessed with a novel imaging scatterometer-spectrophotometer, built around an elliptical mirror [1]. Examples of butterfly and damselfly wings, bird feathers, and beetle cuticle will be presented. [4pt] [1] D.G. Stavenga, H.L. Leertouwer, P. Pirih, M.F. Wehling, Optics Express 17, 193-202 (2009)

Eight years of wind measurements from scatterometer for wind resource mapping in the Mediterranean Sea

DEFF Research Database (Denmark)

Furevik, Birgitte R.; Sempreviva, Anna Maria; Cavaleri, Luigi

2011-01-01

that the scatterometer is able to provide similar long-term statistics as available from buoy data, such as annual and monthly wind indexes. Such statistics is useful to give an overview of the climatology in the different areas. The correlation between QuikScat and in situ observations is degraded towards the coast...

Global composites of surface wind speeds in tropical cyclones based on a 12 year scatterometer database

Science.gov (United States)

Klotz, Bradley W.; Jiang, Haiyan

2016-10-01

A 12 year global database of rain-corrected satellite scatterometer surface winds for tropical cyclones (TCs) is used to produce composites of TC surface wind speed distributions relative to vertical wind shear and storm motion directions in each TC-prone basin and various TC intensity stages. These composites corroborate ideas presented in earlier studies, where maxima are located right of motion in the Earth-relative framework. The entire TC surface wind asymmetry is down motion left for all basins and for lower strength TCs after removing the motion vector. Relative to the shear direction, the motion-removed composites indicate that the surface wind asymmetry is located down shear left for the outer region of all TCs, but for the inner-core region it varies from left of shear to down shear right for different basin and TC intensity groups. Quantification of the surface wind asymmetric structure in further stratifications is a necessary next step for this scatterometer data set.

Validation and downscaling of Advanced Scatterometer (ASCAT) soil moisture using ground measurements in the Western Cape, South Africa

CSIR Research Space (South Africa)

Moller, J

2017-09-01

Full Text Available Satellite-based remote sensing of soil water content (SWC) is a promising technology for hydrological applications to overcome large spatiotemporal variabilities of SWC. This study investigated the performance of the Advanced Scatterometer (ASCAT...

Application of the nonlinear time series prediction method of genetic algorithm for forecasting surface wind of point station in the South China Sea with scatterometer observations

International Nuclear Information System (INIS)

Zhong Jian; Dong Gang; Sun Yimei; Zhang Zhaoyang; Wu Yuqin

2016-01-01

The present work reports the development of nonlinear time series prediction method of genetic algorithm (GA) with singular spectrum analysis (SSA) for forecasting the surface wind of a point station in the South China Sea (SCS) with scatterometer observations. Before the nonlinear technique GA is used for forecasting the time series of surface wind, the SSA is applied to reduce the noise. The surface wind speed and surface wind components from scatterometer observations at three locations in the SCS have been used to develop and test the technique. The predictions have been compared with persistence forecasts in terms of root mean square error. The predicted surface wind with GA and SSA made up to four days (longer for some point station) in advance have been found to be significantly superior to those made by persistence model. This method can serve as a cost-effective alternate prediction technique for forecasting surface wind of a point station in the SCS basin. (paper)

Application of Tikhonov regularization method to wind retrieval from scatterometer data II: cyclone wind retrieval with consideration of rain

International Nuclear Information System (INIS)

Zhong Jian; Huang Si-Xun; Fei Jian-Fang; Du Hua-Dong; Zhang Liang

2011-01-01

According to the conclusion of the simulation experiments in paper I, the Tikhonov regularization method is applied to cyclone wind retrieval with a rain-effect-considering geophysical model function (called GMF+Rain). The GMF+Rain model which is based on the NASA scatterometer-2 (NSCAT2) GMF is presented to compensate for the effects of rain on cyclone wind retrieval. With the multiple solution scheme (MSS), the noise of wind retrieval is effectively suppressed, but the influence of the background increases. It will cause a large wind direction error in ambiguity removal when the background error is large. However, this can be mitigated by the new ambiguity removal method of Tikhonov regularization as proved in the simulation experiments. A case study on an extratropical cyclone of hurricane observed with SeaWinds at 25-km resolution shows that the retrieved wind speed for areas with rain is in better agreement with that derived from the best track analysis for the GMF+Rain model, but the wind direction obtained with the two-dimensional variational (2DVAR) ambiguity removal is incorrect. The new method of Tikhonov regularization effectively improves the performance of wind direction ambiguity removal through choosing appropriate regularization parameters and the retrieved wind speed is almost the same as that obtained from the 2DVAR. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

Science.gov (United States)

Yueh, Simon H.

2004-01-01

Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

Studies of radar backscatter as a function of wave properties and the winds in the turbulent marine atmosphere

Science.gov (United States)

Pierson, Willard J., Jr.; Sylvester, Winfield B.

1995-01-01

The research on model functions for ADEOS and ERS-1 are summarized and an analysis of the differences between the three kinds of models is provided in this final report. The success of the AMI on ERS-1 obtained at GSFC and NMC is highlighted. The problem of wind stress description is reviewed within and the scatterometer model being developed for high winds monitoring for the AMI on ERS-1 and ERS-2 is described.

Large-scale analysis and forecast experiments with wind data from the Seasat A scatterometer

Science.gov (United States)

Baker, W. E.; Atlas, R.; Kalnay, E.; Halem, M.; Woiceshyn, P. M.; Peteherych, S.; Edelmann, D.

1984-01-01

A series of data assimilation experiments is performed to assess the impact of Seasat A satellite scatterometer (SASS) wind data on Goddard Laboratory for Atmospheric Sciences (GLAS) model forecasts. The SASS data are dealiased as part of an objective analysis system utilizing a three-pass procedure. The impact of the SASS data is evaluated with and without temperature soundings from the NOAA 4 Vertical Temperature Profile Radiometer (VTPR) instrument in order to study possible redundancy between surface wind data and upper air temperature data. In the northern hemisphere the SASS data are generally found to have a negligible effect on the forecasts. In the southern hemisphere the forecast impact from SASS data is somewhat larger and primarily beneficial in the absence of VTPR data. However, the inclusion of VTPR data effectively eliminates the positive impact over Australia and South America. This indicates that SASS data can be beneficial for numerical weather prediction in regions with large data gaps, but in the presence of satellite soundings the usefulness of SASS data is significantly reduced.

Wind scatterometry with improved ambiguity selection and rain modeling

Science.gov (United States)

Draper, David Willis

Although generally accurate, the quality of SeaWinds on QuikSCAT scatterometer ocean vector winds is compromised by certain natural phenomena and retrieval algorithm limitations. This dissertation addresses three main contributors to scatterometer estimate error: poor ambiguity selection, estimate uncertainty at low wind speeds, and rain corruption. A quality assurance (QA) analysis performed on SeaWinds data suggests that about 5% of SeaWinds data contain ambiguity selection errors and that scatterometer estimation error is correlated with low wind speeds and rain events. Ambiguity selection errors are partly due to the "nudging" step (initialization from outside data). A sophisticated new non-nudging ambiguity selection approach produces generally more consistent wind than the nudging method in moderate wind conditions. The non-nudging method selects 93% of the same ambiguities as the nudged data, validating both techniques, and indicating that ambiguity selection can be accomplished without nudging. Variability at low wind speeds is analyzed using tower-mounted scatterometer data. According to theory, below a threshold wind speed, the wind fails to generate the surface roughness necessary for wind measurement. A simple analysis suggests the existence of the threshold in much of the tower-mounted scatterometer data. However, the backscatter does not "go to zero" beneath the threshold in an uncontrolled environment as theory suggests, but rather has a mean drop and higher variability below the threshold. Rain is the largest weather-related contributor to scatterometer error, affecting approximately 4% to 10% of SeaWinds data. A simple model formed via comparison of co-located TRMM PR and SeaWinds measurements characterizes the average effect of rain on SeaWinds backscatter. The model is generally accurate to within 3 dB over the tropics. The rain/wind backscatter model is used to simultaneously retrieve wind and rain from SeaWinds measurements. The simultaneous

Optimization of a dual-rotating-retarder polarimeter as applied to a tunable infrared Mueller-matrix scatterometer

International Nuclear Information System (INIS)

Vap, J C; Nauyoks, S E; Marciniak, M A

2013-01-01

The value of Mueller-matrix (Mm) scatterometers lies in their ability to simultaneously characterize the polarimetric and directional scatter properties of a sample. To extend their utility to characterizing modern optical materials in the infrared (IR), which often have very narrow resonances yet interesting polarization and directional properties, the addition of tunable IR lasers and an achromatic dual-rotating-retarder (DRR) polarimeter is necessary. An optimization method has been developed for use with the tunable IR Mm scatterometer. This method is rooted in the application of random error analysis to three different DRR retardances, λ/5, λ/4 and λ/3, for three different analyzer (A)-to-generator (G) retarder rotation ratios, θ A :θ G = 34:26, 25:5 and 37.5:7.5, and a variable number of intensity measurements. The product of the error analysis is in terms of the level of error that could be expected from a free-space Mm extraction for the various retardances, retarder rotation ratios and number of intensity measurements of the DRR. The optimal DRR specifications identified are a λ/3 retardance and a Fourier rotation ratio, with the number of required collected measurements dependent on the level of error acceptable to the user. Experimental results corroborate this error analysis using an achromatic 110-degree retardance-configured DRR polarimeter at 5 µm wavelength, which resulted in consistent 1% error in its free-space Mm extractions. (paper)

A preliminary study of the impact of the ERS 1 C band scatterometer wind data on the European Centre for Medium-Range Weather Forecasts global data assimilation system

Science.gov (United States)

Hoffman, Ross N.

1993-01-01

A preliminary assessment of the impact of the ERS 1 scatterometer wind data on the current European Centre for Medium-Range Weather Forecasts analysis and forecast system has been carried out. Although the scatterometer data results in changes to the analyses and forecasts, there is no consistent improvement or degradation. Our results are based on comparing analyses and forecasts from assimilation cycles. The two sets of analyses are very similar except for the low level wind fields over the ocean. Impacts on the analyzed wind fields are greater over the southern ocean, where other data are scarce. For the most part the mass field increments are too small to balance the wind increments. The effect of the nonlinear normal mode initialization on the analysis differences is quite small, but we observe that the differences tend to wash out in the subsequent 6-hour forecast. In the Northern Hemisphere, analysis differences are very small, except directly at the scatterometer locations. Forecast comparisons reveal large differences in the Southern Hemisphere after 72 hours. Notable differences in the Northern Hemisphere do not appear until late in the forecast. Overall, however, the Southern Hemisphere impacts are neutral. The experiments described are preliminary in several respects. We expect these data to ultimately prove useful for global data assimilation.

Application of the Tikhonov regularization method to wind retrieval from scatterometer data I. Sensitivity analysis and simulation experiments

International Nuclear Information System (INIS)

Zhong Jian; Huang Si-Xun; Du Hua-Dong; Zhang Liang

2011-01-01

Scatterometer is an instrument which provides all-day and large-scale wind field information, and its application especially to wind retrieval always attracts meteorologists. Certain reasons cause large direction error, so it is important to find where the error mainly comes. Does it mainly result from the background field, the normalized radar cross-section (NRCS) or the method of wind retrieval? It is valuable to research. First, depending on SDP2.0, the simulated ‘true’ NRCS is calculated from the simulated ‘true’ wind through the geophysical model function NSCAT2. The simulated background field is configured by adding a noise to the simulated ‘true’ wind with the non-divergence constraint. Also, the simulated ‘measured’ NRCS is formed by adding a noise to the simulated ‘true’ NRCS. Then, the sensitivity experiments are taken, and the new method of regularization is used to improve the ambiguity removal with simulation experiments. The results show that the accuracy of wind retrieval is more sensitive to the noise in the background than in the measured NRCS; compared with the two-dimensional variational (2DVAR) ambiguity removal method, the accuracy of wind retrieval can be improved with the new method of Tikhonov regularization through choosing an appropriate regularization parameter, especially for the case of large error in the background. The work will provide important information and a new method for the wind retrieval with real data. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

Scatterometer Observes Extratropical Transition of Pacific Typhoons

Science.gov (United States)

Liu, W. Timothy; Tang, Wenqing; Dunbar, R. Scott

1997-01-01

From September 15 to 25, 1996, NASA's scatterometer (NSCAT) monitored the evolution of twin typhoons, Violet and Tom, as they moved north from the western tropical Pacific, acquiring features of mid-latitude storms. The typhoons developed frontal structures, increased asymmetry, and dry air was introduced into their cores. Violet hit Japan, causing death and destruction (Figure 1), and Tom merged with a mid-latitude trough and evolved into a large extratropical storm with gale-force winds (Figure 2). We understand relatively little about the extratropical transition of tropical cyclones because of the complex thermodynamics involved [e.g., Sinclair, 1993], but we do know that the mid-latitude storms resulting from tropical cyclones usually generate strong winds and heavy precipitation. Since the transition usually occurs over the ocean, few measurements have been made. The transition is a fascinating science problem, but it also has important economic consequences. The transition occurs over the busiest trans-ocean shipping lanes, and when the resulting storms hit land, they usually devastate populated areas. NSCAT was successfully launched into a near-polar, sun-synchronous orbit on the Japanese Advanced Earth Observing Satellite (ADEOS) in August 1996 from Tanegashima Space Center in Japan. NSCAT's six antennas send microwave pulses at a frequency of 14 GHz to the Earth's surface and measure the backscatter. The antennas scan two 600-km bands of the ocean, which are separated by a 330-km data gap. From NSCAT observations, surface wind vectors can be derived at 25-km spatial resolution, covering 77% of the ice-free ocean in one day and 97% of the ocean in two days, under both clear and cloudy conditions.

Development and usage of a false color display technique for presenting Seasat-A scatterometer data

Science.gov (United States)

Jackson, C. B.

1980-01-01

A computer generated false color program which creates digital multicolor graphics to display geophysical surface parameters measured by the Seasat-A satellite scatterometer (SASS) is described. The data is incrementally scaled over the range of acceptable values and each increment and its data points are assigned a color. The advantage of the false color display is that it visually infers cool or weak data versus hot or intense data by using the rainbow of colors. For example, with wind speeds, levels of yellow and red could be used to imply high winds while green and blue could imply calmer air. The SASS data is sorted into geographic regions and the final false color images are projected onto various world maps with superimposed land/water boundaries.

Offshore wind power resource assessment using Oceansat-2 scatterometer data at a regional scale

International Nuclear Information System (INIS)

Gadad, Sanjeev; Deka, Paresh Chandra

2016-01-01

Highlights: • Accuracy assessment of Oceansat-2 scatterometer (OSCAT) winds by the in situ real-time ship observations for study area. • OSCAT data for two years (2011 and 2012) were used to evaluate the offshore wind power potential for the Karnataka state. • Wind speed and power atlases are developed to study the spatial distribution over study area. • 9,091 MW potential was estimated using 5 MW wind turbine in the Monopile region. • Recommend development of 10% of the estimated potential, 116% of energy deficit for 2012–13 can be met. - Abstract: In the offshore region the scarcity of in situ wind data in space proves to be a major setback for wind power potential assessments. Satellite data effectively overcomes this setback by providing continuous and total spatial coverage. The study intends to assess the offshore wind power resource of the Karnataka state, which is located on the west coast of India. Oceansat-2 scatterometer (OSCAT) wind data and GIS based methodology were adopted in the study. The OSCAT data accuracy was assessed using INCOIS Realtime All Weather Station (IRAWS) data. Wind speed maps at 10 m, 90 m and wind power density maps using OSCAT data were developed to understand the spatial distribution of winds over the study area. Bathymetric map was developed based on the available foundation types and demarking various exclusion zones to help in minimizing conflicts. The wind power generation capacity estimation performed using REpower 5 MW turbine, based on the water depth classes was found to be 9,091 MW in Monopile (0–35 m), 11,709 MW in Jacket (35–50 m), 23,689 MW in Advanced Jacket (50–100 m) and 117,681 MW in Floating (100–1000 m) foundation technology. In Indian scenario major thrust for wind farm development in Monopile region is required. Therefore as first phase of development, if 10% of the estimated potential in the region can be developed then, 116% of energy deficit for FY 2011–12 could be met. Also, up to 79

Electrical properties of Titan's surface from Cassini RADAR scatterometer measurements

Science.gov (United States)

Wye, Lauren C.; Zebker, Howard A.; Ostro, Steven J.; West, Richard D.; Gim, Yonggyu; Lorenz, Ralph D.; The Cassini Radar Team

2007-06-01

We report regional-scale low-resolution backscatter images of Titan's surface acquired by the Cassini RADAR scatterometer at a wavelength of 2.18-cm. We find that the average angular dependence of the backscatter from large regions and from specific surface features is consistent with a model composed of a quasi-specular Hagfors term plus a diffuse cosine component. A Gaussian quasi-specular term also fits the data, but less well than the Hagfors term. We derive values for the mean dielectric constant and root-mean-square (rms) slope of the surface from the quasi-specular term, which we ascribe to scattering from the surface interface only. The diffuse term accommodates contributions from volume scattering, multiple scattering, or wavelength-scale near-surface structure. The Hagfors model results imply a surface with regional mean dielectric constants between 1.9 and 3.6 and regional surface roughness that varies between 5.3° and 13.4° in rms-slope. Dielectric constants between 2 and 3 are expected for a surface composed of solid simple hydrocarbons, water ice, or a mixture of both. Smaller dielectric constants, between 1.6 and 1.9, are consistent with liquid hydrocarbons, while larger dielectric constants, near 4.5, may indicate the presence of water-ammonia ice [Lorenz, R.D., 1998. Icarus 136, 344-348] or organic heteropolymers [Thompson, W.R., Squyres, S.W., 1990. Icarus 86, 336-354]. We present backscatter images corrected for angular effects using the model residuals, which show strong features that correspond roughly to those in 0.94-μm ISS images. We model the localized backscatter from specific features to estimate dielectric constant and rms slope when the angular coverage is within the quasi-specular part of the backscatter curve. Only two apparent surface features are scanned with angular coverage sufficient for accurate modeling. Data from the bright albedo feature Quivira suggests a dielectric constant near 2.8 and rms slope near 10.1°. The dark

Application of Spaceborne Scatterometer for Mapping Freeze-Thaw State in Northern Landscapes as a Measure of Ecological and Hydrological Processes

Science.gov (United States)

McDonald, Kyle; Kimball, John; Zimmermann, Reiner; Way, JoBea; Frolking, Steve; Running, Steve

1999-01-01

Landscape freeze/thaw transitions coincide with marked shifts in albedo, surface energy and mass exchange, and associated snow dynamics. Monitoring landscape freeze/thaw dynamics would improve our ability to quantify the interannual variability of boreal hydrology and river runoff/flood dynamics. The annual duration of frost-free period also bounds the period of photosynthetic activity in boreal and arctic regions thus affecting the annual carbon budget and the interannual variability of regional carbon fluxes. In this study, we use the NASA scatterometer (NSCAT) to monitor the temporal change in the radar backscatter signature across selected ecoregions of the boreal zone. We have measured vegetation tissue temperatures, soil temperature profiles, and micrometeorological parameters in situ at selected sites along a north-south transect extending across Alaska from Prudhoe Bay to the Kenai Peninsula and in Siberia near the Yenisey River. Data from these stations have been used to quantify the scatterometer's sensitivity to freeze/thaw state under a variety of terrain and landcover conditions. Analysis of the NSCAT temporal response over the 1997 spring thaw cycle shows a 3 to 5 dB change in measured backscatter that is well correlated with the landscape springtime thaw process. Having verified the instrument's capability to monitor freeze/thaw transitions, regional scale mosaicked data are applied to derive temporal series of freeze/thaw transition maps for selected circumpolar high latitude regions. These maps are applied to derive areal extent of frozen and thawed landscape and demonstrate the utility of spaceborne radar for operational monitoring of seasonal freeze-thaw dynamics and associated biophysical processes for the circumpolar high latitudes.

A Novel Integrated Algorithm for Wind Vector Retrieval from Conically Scanning Scatterometers

Directory of Open Access Journals (Sweden)

Xuetong Xie

2013-11-01

Full Text Available Due to the lower efficiency and the larger wind direction error of traditional algorithms, a novel integrated wind retrieval algorithm is proposed for conically scanning scatterometers. The proposed algorithm has the dual advantages of less computational cost and higher wind direction retrieval accuracy by integrating the wind speed standard deviation (WSSD algorithm and the wind direction interval retrieval (DIR algorithm. It adopts wind speed standard deviation as a criterion for searching possible wind vector solutions and retrieving a potential wind direction interval based on the change rate of the wind speed standard deviation. Moreover, a modified three-step ambiguity removal method is designed to let more wind directions be selected in the process of nudging and filtering. The performance of the new algorithm is illustrated by retrieval experiments using 300 orbits of SeaWinds/QuikSCAT L2A data (backscatter coefficients at 25 km resolution and co-located buoy data. Experimental results indicate that the new algorithm can evidently enhance the wind direction retrieval accuracy, especially in the nadir region. In comparison with the SeaWinds L2B Version 2 25 km selected wind product (retrieved wind fields, an improvement of 5.1° in wind direction retrieval can be made by the new algorithm for that region.

Comparison of the ocean surface vector winds from atmospheric reanalysis and scatterometer-based wind products over the Nordic Seas and the northern North Atlantic and their application for ocean modeling

Science.gov (United States)

Dukhovskoy, Dmitry S.; Bourassa, Mark A.; Petersen, Gudrún Nína; Steffen, John

2017-03-01

Ocean surface vector wind fields from reanalysis data sets and scatterometer-derived gridded products are analyzed over the Nordic Seas and the northern North Atlantic for the time period from 2000 to 2009. The data sets include the National Center for Environmental Prediction Reanalysis 2 (NCEPR2), Climate Forecast System Reanalysis (CFSR), Arctic System Reanalysis (ASR), Cross-Calibrated Multiplatform (CCMP) wind product version 1.1 and recently released version 2.0, and QuikSCAT. The goal of the study is to assess discrepancies across the wind vector fields in the data sets and demonstrate possible implications of these differences for ocean modeling. Large-scale and mesoscale characteristics of winds are compared at interannual, seasonal, and synoptic timescales. A cyclone tracking methodology is developed and applied to the wind fields to compare cyclone characteristics in the data sets. Additionally, the winds are evaluated against observations collected from meteorological buoys deployed in the Iceland and Irminger Seas. The agreement among the wind fields is better for longer time and larger spatial scales. The discrepancies are clearly apparent for synoptic timescales and mesoscales. CCMP, ASR, and CFSR show the closest overall agreement with each other. Substantial biases are found in the NCEPR2 winds. Numerical sensitivity experiments are conducted with a coupled ice-ocean model forced by different wind fields. The experiments demonstrate differences in the net surface heat fluxes during storms. In the experiment forced by NCEPR2 winds, there are discrepancies in the large-scale wind-driven ocean dynamics compared to the other experiments.

Polarimetric and angular light-scattering from dense media: Comparison of a vectorial radiative transfer model with analytical, stochastic and experimental approaches

International Nuclear Information System (INIS)

Riviere, Nicolas; Ceolato, Romain; Hespel, Laurent

2013-01-01

Our work presents computations via a vectorial radiative transfer model of the polarimetric and angular light scattered by a stratified dense medium with small and intermediate optical thickness. We report the validation of this model using analytical results and different computational methods like stochastic algorithms. Moreover, we check the model with experimental data from a specific scatterometer developed at the Onera. The advantages and disadvantages of a radiative approach are discussed. This paper represents a step toward the characterization of particles in dense media involving multiple scattering. -- Highlights: • A vectorial radiative transfer model to simulate the light scattered by stratified layers is developed. • The vectorial radiative transfer equation is solved using an adding–doubling technique. • The results are compared to analytical and stochastic data. • Validation with experimental data from a scatterometer developed at Onera is presented

Synoptic Storms in the North Atlantic in the Atmospheric Reanalysis and Scatterometer-Based Wind Products

Science.gov (United States)

Dukhovskoy, D. S.; Bourassa, M. A.

2016-12-01

The study compares and analyses the characteristics of synoptic storms in the Subpolar North Atlantic over the time period from 2000 through 2009 derived from reanalysis data sets and scatterometer-based gridded wind products. The analysis is performed for ocean 10-m winds derived from the following wind data sets: NCEP/DOE AMIP-II reanalysis (NCEPR2), NCAR/CFSR, Arctic System Reanalysis (ASR) version 1, Cross-Calibrated Multi-Platform (CCMP) wind product versions 1.1 and recently released version 2.0 prepared by the Remote Sensing Systems, and QuikSCAT. A cyclone tracking algorithm employed in this study for storm identification is based on average vorticity fields derived from the wind data. The study discusses storm characteristics such as storm counts, trajectories, intensity, integrated kinetic energy, spatial scale. Interannal variability of these characteristics in the data sets is compared. The analyses demonstrates general agreement among the wind data products on the characteristics of the storms, their spatial distribution and trajectories. On average, the NCEPR2 storms are more energetic mostly due to large spatial scales and stronger winds. There is noticeable interannual variability in the storm characteristics, yet no obvious trend in storms is observed in the data sets.

Imaging scatterometry of butterfly wing scales

NARCIS (Netherlands)

Stavenga, D. G.; Leertouwer, H. L.; Pirih, P.; Wehling, M. F.

2009-01-01

We describe an imaging scatterometer allowing hemispherical reflectance measurements as a function of the angle of incidence. The heart of the scatterometer is an ellipsoidal reflector, which compresses the hemispherical reflection into a cone-shaped beam that can be imaged by a normal optical

Assessing Climate-Induced Change in River Flow Using Satellite Remote Sensing and Process Modeling in High Mountain Asia

Science.gov (United States)

McDonald, K. C.

2017-12-01

Snow- and glacier-fed river systems originating from High Mountain Asia (HMA) support diverse ecosystems and provide the basis for food and energy production for more than a billion people living downstream. Climate-driven changes in the melting of snow and glaciers and in precipitation patterns are expected to significantly alter the flow of the rivers in the HMA region at various temporal scales, which in turn could heavily affect the socioeconomics of the region. Hence, climate change effects on seasonal and long-term hydrological conditions may have far reaching economic impact annually and over the century. We are developing a decision support tool utilizing integrated microwave remote sensing datasets, process modeling and economic models to inform water resource management decisions and ecosystem sustainability as related to the High Mountain Asia (HMA) region's response to climate change. The availability of consistent time-series microwave remote sensing datasets from Earth-orbiting scatterometers, radiometers and synthetic aperture radar (SAR) imagery provides the basis for the observational framework of this monitoring system. We discuss the assembly, processing and application of scatterometer and SAR data sets from the Advanced Scatterometer (ASCAT) and Sentinal-1 SARs, and the enlistment of these data to monitor seasonal melt and thaw status of glacier-dominated and surrounding regions. We present current status and future plans for this effort. Our team's study emphasizes processes and economic modeling within the Trishuli basin; our remote sensing analysis supports analyses across the HiMAT domain.

Extended volume and surface scatterometer for optical characterization of 3D-printed elements

Science.gov (United States)

Dannenberg, Florian; Uebeler, Denise; Weiß, Jürgen; Pescoller, Lukas; Weyer, Cornelia; Hahlweg, Cornelius

2015-09-01

The use of 3d printing technology seems to be a promising way for low cost prototyping, not only of mechanical, but also of optical components or systems. It is especially useful in applications where customized equipment repeatedly is subject to immediate destruction, as in experimental detonics and the like. Due to the nature of the 3D-printing process, there is a certain inner texture and therefore inhomogeneous optical behaviour to be taken into account, which also indicates mechanical anisotropy. Recent investigations are dedicated to quantification of optical properties of such printed bodies and derivation of corresponding optimization strategies for the printing process. Beside mounting, alignment and illumination means, also refractive and reflective elements are subject to investigation. The proposed measurement methods are based on an imaging nearfield scatterometer for combined volume and surface scatter measurements as proposed in previous papers. In continuation of last year's paper on the use of near field imaging, which basically is a reflective shadowgraph method, for characterization of glossy surfaces like printed matter or laminated material, further developments are discussed. The device has been extended for observation of photoelasticity effects and therefore homogeneity of polarization behaviour. A refined experimental set-up is introduced. Variation of plane of focus and incident angle are used for separation of various the images of the layers of the surface under test, cross and parallel polarization techniques are applied. Practical examples from current research studies are included.

Assimilation of the QuikScat satellite data into models of oil spill path analysis; Assimilacao dos dados do satelite QuikScat em modelos de analise de trajetoria de derrames de oleo

Energy Technology Data Exchange (ETDEWEB)

Baptista, Marlos Carneiro; Cabral, Alexandre Pereira; Silva Junior, Carlos Leandro [OCEANSAT - Tecnologia Espacial para Monitoramento Ambiental S/C Ltda., Rio de Janeiro, RJ (Brazil)]. E-mail: oceansat@inc.coppe.ufrj.br; Landau, Luiz [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia]. E-mail: landau@lamce.ufrj.br

2001-07-01

This work analyses the performance and reliability of the wind data measured by the QuikScat satellite. The Scatterometer data was compared with previously published results, based on data from ERS-1/2 Wind Scatterometer, meteo-ocean buoys and from re-analysis of NCEP model. To validate and applied the QuikScat data a case study was performed, on which those data was used to improve the performance of an oil trajectory analysis model, simulating and oil spill in the Campos Basin region. It was observed that the results of the modelling reached better results when wind data collected by the QuikScat satellite was used as a forcing mechanism. Together with other applications, the assimilation of these data into models can be seen as an essential tool in environmental monitoring. (author)

Empirical wind retrieval model based on SAR spectrum measurements

Science.gov (United States)

Panfilova, Maria; Karaev, Vladimir; Balandina, Galina; Kanevsky, Mikhail; Portabella, Marcos; Stoffelen, Ad

The present paper considers polarimetric SAR wind vector applications. Remote-sensing measurements of the near-surface wind over the ocean are of great importance for the understanding of atmosphere-ocean interaction. In recent years investigations for wind vector retrieval using Synthetic Aperture Radar (SAR) data have been performed. In contrast with scatterometers, a SAR has a finer spatial resolution that makes it a more suitable microwave instrument to explore wind conditions in the marginal ice zones, coastal regions and lakes. The wind speed retrieval procedure from scatterometer data matches the measured radar backscattering signal with the geophysical model function (GMF). The GMF determines the radar cross section dependence on the wind speed and direction with respect to the azimuthal angle of the radar beam. Scatterometers provide information on wind speed and direction simultaneously due to the fact that each wind vector cell (WVC) is observed at several azimuth angles. However, SAR is not designed to be used as a high resolution scatterometer. In this case, each WVC is observed at only one single azimuth angle. That is why for wind vector determination additional information such as wind streak orientation over the sea surface is required. It is shown that the wind vector can be obtained using polarimetric SAR without additional information. The main idea is to analyze the spectrum of a homogeneous SAR image area instead of the backscattering normalized radar cross section. Preliminary numerical simulations revealed that SAR image spectral maxima positions depend on the wind vector. Thus the following method for wind speed retrieval is proposed. In the first stage of the algorithm, the SAR spectrum maxima are determined. This procedure is carried out to estimate the wind speed and direction with ambiguities separated by 180 degrees due to the SAR spectrum symmetry. The second stage of the algorithm allows us to select the correct wind direction

Extreme wind-wave modeling and analysis in the south Atlantic ocean

Science.gov (United States)

Campos, R. M.; Alves, J. H. G. M.; Guedes Soares, C.; Guimaraes, L. G.; Parente, C. E.

2018-04-01

A set of wave hindcasts is constructed using two different types of wind calibration, followed by an additional test retuning the input source term Sin in the wave model. The goal is to improve the simulation in extreme wave events in the South Atlantic Ocean without compromising average conditions. Wind fields are based on Climate Forecast System Reanalysis (CFSR/NCEP). The first wind calibration applies a simple linear regression model, with coefficients obtained from the comparison of CFSR against buoy data. The second is a method where deficiencies of the CFSR associated with severe sea state events are remedied, whereby "defective" winds are replaced with satellite data within cyclones. A total of six wind datasets forced WAVEWATCH-III and additional three tests with modified Sin in WAVEWATCH III lead to a total of nine wave hindcasts that are evaluated against satellite and buoy data for ambient and extreme conditions. The target variable considered is the significant wave height (Hs). The increase of sea-state severity shows a progressive increase of the hindcast underestimation which could be calculated as a function of percentiles. The wind calibration using a linear regression function shows similar results to the adjustments to Sin term (increase of βmax parameter) in WAVEWATCH-III - it effectively reduces the average bias of Hs but cannot avoid the increase of errors with percentiles. The use of blended scatterometer winds within cyclones could reduce the increasing wave hindcast errors mainly above the 93rd percentile and leads to a better representation of Hs at the peak of the storms. The combination of linear regression calibration of non-cyclonic winds with scatterometer winds within the cyclones generated a wave hindcast with small errors from calm to extreme conditions. This approach led to a reduction of the percentage error of Hs from 14% to less than 8% for extreme waves, while also improving the RMSE.

BRDF profile of Tyvek and its implementation in the Geant4 simulation toolkit.

Science.gov (United States)

Nozka, Libor; Pech, Miroslav; Hiklova, Helena; Mandat, Dusan; Hrabovsky, Miroslav; Schovanek, Petr; Palatka, Miroslav

2011-02-28

Diffuse and specular characteristics of the Tyvek 1025-BL material are reported with respect to their implementation in the Geant4 Monte Carlo simulation toolkit. This toolkit incorporates the UNIFIED model. Coefficients defined by the UNIFIED model were calculated from the bidirectional reflectance distribution function (BRDF) profiles measured with a scatterometer for several angles of incidence. Results were amended with profile measurements made by a profilometer.

NASA 3D Models: QuikSCAT

Data.gov (United States)

National Aeronautics and Space Administration — NASA's Quick Scatterometer (QuikSCAT) is equipped with a specialized microwave radar that measures near-surface wind speed and direction under all weather and cloud...

Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions

Science.gov (United States)

Morelli, Eugene A.

2013-01-01

A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.

Nonparametric Transfer Function Models

Science.gov (United States)

Liu, Jun M.; Chen, Rong; Yao, Qiwei

2009-01-01

In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between ‘input’ and ‘output’ time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modeling the correlation in the noise, the transfer function can be estimated more efficiently. The parsimonious ARMA structure improves the estimation efficiency in finite samples. The asymptotic properties of the estimators are investigated. The finite-sample properties are illustrated through simulations and one empirical example. PMID:20628584

Comparisons of Satellite Soil Moisture, an Energy Balance Model Driven by LST Data and Point Measurements

Science.gov (United States)

Laiolo, Paola; Gabellani, Simone; Rudari, Roberto; Boni, Giorgio; Puca, Silvia

2013-04-01

Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.

Cross-polarization microwave radar return at severe wind conditions: laboratory model and geophysical model function.

Science.gov (United States)

Troitskaya, Yuliya; Abramov, Victor; Ermoshkin, Alexey; Zuikova, Emma; Kazakov, Vassily; Sergeev, Daniil; Kandaurov, Alexandr

2014-05-01

Satellite remote sensing is one of the main techniques of monitoring severe weather conditions over the ocean. The principal difficulty of the existing algorithms of retrieving wind based on dependence of microwave backscattering cross-section on wind speed (Geophysical Model Function, GMF) is due to its saturation at winds exceeding 25 - 30 m/s. Recently analysis of dual- and quad-polarization C-band radar return measured from satellite Radarsat-2 suggested that the cross-polarized radar return has much higher sensitivity to the wind speed than co-polarized back scattering [1] and conserved sensitivity to wind speed at hurricane conditions [2]. Since complete collocation of these data was not possible and time difference in flight legs and SAR images acquisition was up to 3 hours, these two sets of data were compared in [2] only statistically. The main purpose of this paper is investigation of the functional dependence of cross-polarized radar cross-section on the wind speed in laboratory experiment. Since cross-polarized radar return is formed due to scattering at small-scale structures of the air-sea interface (short-crested waves, foam, sprays, etc), which are well reproduced in laboratory conditions, then the approach based on laboratory experiment on radar scattering of microwaves at the water surface under hurricane wind looks feasible. The experiments were performed in the Wind-wave flume located on top of the Large Thermostratified Tank of the Institute of Applied Physics, where the airflow was produced in the flume with the straight working part of 10 m and operating cross section 0.40?0.40 sq. m, the axis velocity can be varied from 5 to 25 m/s. Microwave measurements were carried out by a coherent Doppler X-band (3.2 cm) scatterometer with the consequent receive of linear polarizations. Experiments confirmed higher sensitivity to the wind speed of the cross-polarized radar return. Simultaneously parameters of the air flow in the turbulent boundary layer

Structure functions from chiral soliton models

International Nuclear Information System (INIS)

Weigel, H.; Reinhardt, H.; Gamberg, L.

1997-01-01

We study nucleon structure functions within the bosonized Nambu-Jona-Lasinio (NJL) model where the nucleon emerges as a chiral soliton. We discuss the model predictions on the Gottfried sum rule for electron-nucleon scattering. A comparison with a low-scale parametrization shows that the model reproduces the gross features of the empirical structure functions. We also compute the leading twist contributions of the polarized structure functions g 1 and g 2 in this model. We compare the model predictions on these structure functions with data from the E143 experiment by GLAP evolving them from the scale characteristic for the NJL-model to the scale of the data

Enhanced Ocean Scatterometry

NARCIS (Netherlands)

Fois, F.

2015-01-01

An ocean scatterometer is an active microwave instrument which is designed to determine the normalized radar cross section (NRCS) of the sea surface. Scatterometers transmit pulses towards the sea surface and measure the reflected energy. The primary objective of spaceborne scatterometers is to

On the conversion of functional models : Bridging differences between functional taxonomies in the modeling of user actions

NARCIS (Netherlands)

Van Eck, D.

2009-01-01

In this paper, I discuss a methodology for the conversion of functional models between functional taxonomies developed by Kitamura et al. (2007) and Ookubo et al. (2007). They apply their methodology to the conversion of functional models described in terms of the Functional Basis taxonomy into

Statistical modelling with quantile functions

CERN Document Server

Gilchrist, Warren

2000-01-01

Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen used them in the 60s and 70s in describing populations. Since then, the authors of many papers, both theoretical and practical, have used various aspects of quantiles in their work. Until now, however, no one put all the ideas together to form what turns out to be a general approach to statistics.Statistical Modelling with Quantile Functions does just that. It systematically examines the entire process of statistical modelling, starting with using the quantile function to define continuous distributions. The author shows that by using this approach, it becomes possible to develop complex distributional models from simple components. A modelling kit can be developed that applies to the whole model - deterministic and stochastic components - and this kit operates by adding, multiplying, and transforming distributions rather than data.Statistical Modelling with Quantile Functions adds a new dimension to the practice of stati...

Function Model for Community Health Service Information

Science.gov (United States)

Yang, Peng; Pan, Feng; Liu, Danhong; Xu, Yongyong

In order to construct a function model of community health service (CHS) information for development of CHS information management system, Integration Definition for Function Modeling (IDEF0), an IEEE standard which is extended from Structured Analysis and Design(SADT) and now is a widely used function modeling method, was used to classifying its information from top to bottom. The contents of every level of the model were described and coded. Then function model for CHS information, which includes 4 super-classes, 15 classes and 28 sub-classed of business function, 43 business processes and 168 business activities, was established. This model can facilitate information management system development and workflow refinement.

Functional model of biological neural networks.

Science.gov (United States)

Lo, James Ting-Ho

2010-12-01

A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.

Idealized models of the joint probability distribution of wind speeds

Science.gov (United States)

Monahan, Adam H.

2018-05-01

The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables.

Characterization Of Ocean Wind Vector Retrievals Using ERS-2 High-Resolution Long-Term Dataset And Buoy Measurements

Science.gov (United States)

Polverari, F.; Talone, M.; Crapolicchio, R. Levy, G.; Marzano, F.

2013-12-01

The European Remote-sensing Satellite (ERS)-2 scatterometer provides wind retrievals over Ocean. To satisfy the needs of high quality and homogeneous set of scatterometer measurements, the European Space Agency (ESA) has developed the project Advanced Scatterometer Processing System (ASPS) with which a long-term dataset of new ERS-2 wind products, with an enhanced resolution of 25km square, has been generated by the reprocessing of the entire ERS mission. This paper presents the main results of the validation work of such new dataset using in situ measurements provided by the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA). The comparison indicates that, on average, the scatterometer data agree well with buoys measurements, however the scatterometer tends to overestimates lower winds and underestimates higher winds.

Value function in economic growth model

Science.gov (United States)

Bagno, Alexander; Tarasyev, Alexandr A.; Tarasyev, Alexander M.

2017-11-01

Properties of the value function are examined in an infinite horizon optimal control problem with an unlimited integrand index appearing in the quality functional with a discount factor. Optimal control problems of such type describe solutions in models of economic growth. Necessary and sufficient conditions are derived to ensure that the value function satisfies the infinitesimal stability properties. It is proved that value function coincides with the minimax solution of the Hamilton-Jacobi equation. Description of the growth asymptotic behavior for the value function is provided for the logarithmic, power and exponential quality functionals and an example is given to illustrate construction of the value function in economic growth models.

Functional State Modelling of Saccharomyces cerevisiae Cultivations

Directory of Open Access Journals (Sweden)

Iasen Hristozov

2004-10-01

Full Text Available The implementation of functional state approach for modelling of yeast cultivation is considered in this paper. This concept helps in monitoring and control of complex processes such as bioprocesses. Using of functional state modelling approach for fermentation processes aims to overcome the main disadvantage of using global process model, namely complex model structure and big number of model parameters. The main advantage of functional state modelling is that the parameters of each local model can be separately estimated from other local models parameters. The results achieved from batch, as well as from fed-batch, cultivations are presented.

Correlation functions of the Ising model and the eight-vertex model

International Nuclear Information System (INIS)

Ko, L.F.

1986-01-01

Calculations for the two-point correlation functions in the scaling limit for two statistical models are presented. In Part I, the Ising model with a linear defect is studied for T T/sub c/. The transfer matrix method of Onsager and Kaufman is used. The energy-density correlation is given by functions related to the modified Bessel functions. The dispersion expansion for the spin-spin correlation functions are derived. The dominant behavior for large separations at T not equal to T/sub c/ is extracted. It is shown that these expansions lead to systems of Fredholm integral equations. In Part II, the electric correlation function of the eight-vertex model for T < T/sub c/ is studied. The eight vertex model decouples to two independent Ising models when the four spin coupling vanishes. To first order in the four-spin coupling, the electric correlation function is related to a three-point function of the Ising model. This relation is systematically investigated and the full dispersion expansion (to first order in four-spin coupling) is obtained. The results is a new kind of structure which, unlike those of many solvable models, is apparently not expressible in terms of linear integral equations

Off-nadir antenna bias correction using Amazon rain forest sigma deg data. [Brazil

Science.gov (United States)

Birrer, I. J.; Bracalente, E. M.; Dome, G. J.; Sweet, J.; Berthold, G.; Moore, R. K. (Principal Investigator)

1981-01-01

The radar response from the Amazon rain forest was studied to determine the suitability of this region for use as a standard target to calibrate a scatterometer like that proposed for the National Ocean Satellite System (NOSS). Backscattering observations made by the SEASAT-1 scatterometer system show the Amazon rain forest to be a homogeneous, azimuthally-isotropic, radar target which is insensitive to polarization. The variation with angle of incidence may be adequately modeled as sigma deg (dB) = alpha theta + beta with typical values for the incidence-angle coefficient from 0.07 dB deg to 0.15 dB/deg. A small diurnal effect occurs, with measurements at sunrise being 0.5 dB to 1 dB higher than the rest of the day. Maximum likelihood estimation algorithms are presented which permit determination of relative bias and true pointing angle for each beam. Specific implementation of these algorithms for the proposed NOSS scatterometer system is also discussed.

Off-nadir antenna bias correction using Amazon rain sigma(0) data

Science.gov (United States)

Birrer, I. J.; Dome, G. J.; Sweet, J.; Berthold, G.; Moore, R. K.

1982-01-01

The radar response from the Amazon rain forest was studied to determine the suitability of this region for use as a standard target to calibrate a scatterometer like that proposed for the National Oceanic Satellite System (NOSS). Backscattering observations made by the SEASAT Scatterometer System (SASS) showed the Amazon rain forest to be a homogeneous, azimuthally-isotropic, radar target which was insensitive to polarization. The variation with angle of incidence was adequately modeled as scattering coefficient (dB) = a theta b with typical values for the incidence-angle coefficient from 0.07 to 0.15 dB/deg. A small diurnal effect occurs, with measurements at sunrise being 0.5 dB to 1 dB higher than the rest of the day. Maximum-likelihood estimation algorithms presented here permit determination of relative bias and true pointing angle for each beam. Specific implementation of these algorithms for the proposed NOSS scatterometer system is also discussed.

Variance Function Partially Linear Single-Index Models1.

Science.gov (United States)

Lian, Heng; Liang, Hua; Carroll, Raymond J

2015-01-01

We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.

Functionalized anatomical models for EM-neuron Interaction modeling

Science.gov (United States)

Neufeld, Esra; Cassará, Antonino Mario; Montanaro, Hazael; Kuster, Niels; Kainz, Wolfgang

2016-06-01

The understanding of interactions between electromagnetic (EM) fields and nerves are crucial in contexts ranging from therapeutic neurostimulation to low frequency EM exposure safety. To properly consider the impact of in vivo induced field inhomogeneity on non-linear neuronal dynamics, coupled EM-neuronal dynamics modeling is required. For that purpose, novel functionalized computable human phantoms have been developed. Their implementation and the systematic verification of the integrated anisotropic quasi-static EM solver and neuronal dynamics modeling functionality, based on the method of manufactured solutions and numerical reference data, is described. Electric and magnetic stimulation of the ulnar and sciatic nerve were modeled to help understanding a range of controversial issues related to the magnitude and optimal determination of strength-duration (SD) time constants. The results indicate the importance of considering the stimulation-specific inhomogeneous field distributions (especially at tissue interfaces), realistic models of non-linear neuronal dynamics, very short pulses, and suitable SD extrapolation models. These results and the functionalized computable phantom will influence and support the development of safe and effective neuroprosthetic devices and novel electroceuticals. Furthermore they will assist the evaluation of existing low frequency exposure standards for the entire population under all exposure conditions.

Function modeling: improved raster analysis through delayed reading and function raster datasets

Science.gov (United States)

John S. Hogland; Nathaniel M. Anderson; J .Greg Jones

2013-01-01

Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space, often limiting the types of analyses that can be performed. To address this issue, we have developed Function Modeling. Function Modeling is a new modeling framework that streamlines the...

Exploitation of geoinformatics at modelling of functional effects of forest functions

International Nuclear Information System (INIS)

Sitko, R.

2005-01-01

From point of view of space modelling geoinformatics has wide application in group of ecologic function of forest because they directly depend on natural conditions of site. A causa de cy modelling application was realised on the territory of TANAP (Tatras National Park), West Tatras, in the part Liptovske Kopy. The size of this territory is about 4,900 hectares and forests there subserve the first of all significant ecological functions, what are soil protection from erosion, water management, and anti-avalanche function. Of environmental functions they have recreational role of the forest and function of nature protection. Anti-avalanche and anti-erosion function of forest is evaluated in this presentation

Measurement of Function Post Hip Fracture: Testing a Comprehensive Measurement Model of Physical Function.

Science.gov (United States)

Resnick, Barbara; Gruber-Baldini, Ann L; Hicks, Gregory; Ostir, Glen; Klinedinst, N Jennifer; Orwig, Denise; Magaziner, Jay

2016-07-01

Measurement of physical function post hip fracture has been conceptualized using multiple different measures. This study tested a comprehensive measurement model of physical function. This was a descriptive secondary data analysis including 168 men and 171 women post hip fracture. Using structural equation modeling, a measurement model of physical function which included grip strength, activities of daily living, instrumental activities of daily living, and performance was tested for fit at 2 and 12 months post hip fracture, and among male and female participants. Validity of the measurement model of physical function was evaluated based on how well the model explained physical activity, exercise, and social activities post hip fracture. The measurement model of physical function fit the data. The amount of variance the model or individual factors of the model explained varied depending on the activity. Decisions about the ideal way in which to measure physical function should be based on outcomes considered and participants. The measurement model of physical function is a reliable and valid method to comprehensively measure physical function across the hip fracture recovery trajectory. © 2015 Association of Rehabilitation Nurses.

Local and Global Function Model of the Liver

Energy Technology Data Exchange (ETDEWEB)

Wang, Hesheng, E-mail: hesheng@umich.edu [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Feng, Mary [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Jackson, Andrew [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Ten Haken, Randall K.; Lawrence, Theodore S. [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Cao, Yue [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Department of Radiology, University of Michigan, Ann Arbor, Michigan (United States); Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan (United States)

2016-01-01

Purpose: To develop a local and global function model in the liver based on regional and organ function measurements to support individualized adaptive radiation therapy (RT). Methods and Materials: A local and global model for liver function was developed to include both functional volume and the effect of functional variation of subunits. Adopting the assumption of parallel architecture in the liver, the global function was composed of a sum of local function probabilities of subunits, varying between 0 and 1. The model was fit to 59 datasets of liver regional and organ function measures from 23 patients obtained before, during, and 1 month after RT. The local function probabilities of subunits were modeled by a sigmoid function in relating to MRI-derived portal venous perfusion values. The global function was fitted to a logarithm of an indocyanine green retention rate at 15 minutes (an overall liver function measure). Cross-validation was performed by leave-m-out tests. The model was further evaluated by fitting to the data divided according to whether the patients had hepatocellular carcinoma (HCC) or not. Results: The liver function model showed that (1) a perfusion value of 68.6 mL/(100 g · min) yielded a local function probability of 0.5; (2) the probability reached 0.9 at a perfusion value of 98 mL/(100 g · min); and (3) at a probability of 0.03 [corresponding perfusion of 38 mL/(100 g · min)] or lower, the contribution to global function was lost. Cross-validations showed that the model parameters were stable. The model fitted to the data from the patients with HCC indicated that the same amount of portal venous perfusion was translated into less local function probability than in the patients with non-HCC tumors. Conclusions: The developed liver function model could provide a means to better assess individual and regional dose-responses of hepatic functions, and provide guidance for individualized treatment planning of RT.

Load function modelling for light impact

International Nuclear Information System (INIS)

Klingmueller, O.

1982-01-01

For Pile Integrity Testing light weight drop hammers are used to induce stress waves. In the computational analysis of one-dimensional wave propagation a load function has to be used. Several mechanical models and corresponding load functions are discussed. It is shown that a bell-shaped function which does not correspond to a mechanical model is in best accordance with test results and does not lead to numerical disturbances in the computational results. (orig.) [de

A Memristor Model with Piecewise Window Function

Directory of Open Access Journals (Sweden)

J. Yu

2013-12-01

Full Text Available In this paper, we present a memristor model with piecewise window function, which is continuously differentiable and consists of three nonlinear pieces. By introducing two parameters, the shape of this window function can be flexibly adjusted to model different types of memristors. Using this model, one can easily obtain an expression of memristance depending on charge, from which the numerical value of memristance can be readily calculated for any given charge, and eliminate the error occurring in the simulation of some existing window function models.

Numerical model of the influence function of deformable mirrors based on Bessel Fourier orthogonal functions

International Nuclear Information System (INIS)

Li Shun; Zhang Sijiong

2014-01-01

A numerical model is presented to simulate the influence function of deformable mirror actuators. The numerical model is formed by Bessel Fourier orthogonal functions, which are constituted of Bessel orthogonal functions and a Fourier basis. A detailed comparison is presented between the new Bessel Fourier model, the Zernike model, the Gaussian influence function and the modified Gaussian influence function. Numerical experiments indicate that the new numerical model is easy to use and more accurate compared with other numerical models. The new numerical model can be used for describing deformable mirror performances and numerical simulations of adaptive optics systems. (research papers)

Assessment of tropospheric delay mapping function models in Egypt: Using PTD database model

Science.gov (United States)

Abdelfatah, M. A.; Mousa, Ashraf E.; El-Fiky, Gamal S.

2018-06-01

For space geodetic measurements, estimates of tropospheric delays are highly correlated with site coordinates and receiver clock biases. Thus, it is important to use the most accurate models for the tropospheric delay to reduce errors in the estimates of the other parameters. Both the zenith delay value and mapping function should be assigned correctly to reduce such errors. Several mapping function models can treat the troposphere slant delay. The recent models were not evaluated for the Egyptian local climate conditions. An assessment of these models is needed to choose the most suitable one. The goal of this paper is to test the quality of global mapping function which provides high consistency with precise troposphere delay (PTD) mapping functions. The PTD model is derived from radiosonde data using ray tracing, which consider in this paper as true value. The PTD mapping functions were compared, with three recent total mapping functions model and another three separate dry and wet mapping function model. The results of the research indicate that models are very close up to zenith angle 80°. Saastamoinen and 1/cos z model are behind accuracy. Niell model is better than VMF model. The model of Black and Eisner is a good model. The results also indicate that the geometric range error has insignificant effect on slant delay and the fluctuation of azimuth anti-symmetric is about 1%.

Maximum entropy models of ecosystem functioning

International Nuclear Information System (INIS)

Bertram, Jason

2014-01-01

Using organism-level traits to deduce community-level relationships is a fundamental problem in theoretical ecology. This problem parallels the physical one of using particle properties to deduce macroscopic thermodynamic laws, which was successfully achieved with the development of statistical physics. Drawing on this parallel, theoretical ecologists from Lotka onwards have attempted to construct statistical mechanistic theories of ecosystem functioning. Jaynes’ broader interpretation of statistical mechanics, which hinges on the entropy maximisation algorithm (MaxEnt), is of central importance here because the classical foundations of statistical physics do not have clear ecological analogues (e.g. phase space, dynamical invariants). However, models based on the information theoretic interpretation of MaxEnt are difficult to interpret ecologically. Here I give a broad discussion of statistical mechanical models of ecosystem functioning and the application of MaxEnt in these models. Emphasising the sample frequency interpretation of MaxEnt, I show that MaxEnt can be used to construct models of ecosystem functioning which are statistical mechanical in the traditional sense using a savanna plant ecology model as an example

Maximum entropy models of ecosystem functioning

Energy Technology Data Exchange (ETDEWEB)

Bertram, Jason, E-mail: jason.bertram@anu.edu.au [Research School of Biology, The Australian National University, Canberra ACT 0200 (Australia)

2014-12-05

Using organism-level traits to deduce community-level relationships is a fundamental problem in theoretical ecology. This problem parallels the physical one of using particle properties to deduce macroscopic thermodynamic laws, which was successfully achieved with the development of statistical physics. Drawing on this parallel, theoretical ecologists from Lotka onwards have attempted to construct statistical mechanistic theories of ecosystem functioning. Jaynes’ broader interpretation of statistical mechanics, which hinges on the entropy maximisation algorithm (MaxEnt), is of central importance here because the classical foundations of statistical physics do not have clear ecological analogues (e.g. phase space, dynamical invariants). However, models based on the information theoretic interpretation of MaxEnt are difficult to interpret ecologically. Here I give a broad discussion of statistical mechanical models of ecosystem functioning and the application of MaxEnt in these models. Emphasising the sample frequency interpretation of MaxEnt, I show that MaxEnt can be used to construct models of ecosystem functioning which are statistical mechanical in the traditional sense using a savanna plant ecology model as an example.

Prediction of Chemical Function: Model Development and ...

Science.gov (United States)

The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

Functioning with a Sticky Model.

Science.gov (United States)

Reys, Robert E.

1981-01-01

A model that can be effectively used to develop the notion of function and provide varied practice by using "real world" examples and concrete objects is covered. The use of Popsicle-sticks is featured, with some suggestions for tasks involving functions with one operation, two operations, and inverse operations covered. (MP)

Functional Modeling of Neural-Glia Interaction

DEFF Research Database (Denmark)

Postnov, D.E.; Brazhe, N.A.; Sosnovtseva, Olga

2012-01-01

Functional modeling is an approach that focuses on the representation of the qualitative dynamics of the individual components (e.g. cells) of a system and on the structure of the interaction network.......Functional modeling is an approach that focuses on the representation of the qualitative dynamics of the individual components (e.g. cells) of a system and on the structure of the interaction network....

Kaon fragmentation function from NJL-jet model

International Nuclear Information System (INIS)

Matevosyan, Hrayr H.; Thomas, Anthony W.; Bentz, Wolfgang

2010-01-01

The NJL-jet model provides a sound framework for calculating the fragmentation functions in an effective chiral quark theory, where the momentum and isospin sum rules are satisfied without the introduction of ad hoc parameters [1]. Earlier studies of the pion fragmentation functions using the Nambu-Jona-Lasinio (NJL) model within this framework showed good qualitative agreement with the empirical parameterizations. Here we extend the NJL-jet model by including the strange quark. The corrections to the pion fragmentation function and corresponding kaon fragmentation functions are calculated using the elementary quark to quark-meson fragmentation functions from NJL. The results for the kaon fragmentation function exhibit a qualitative agreement with the empirical parameterizations, while the unfavored strange quark fragmentation to pions is shown to be of the same order of magnitude as the unfavored light quark's. The results of these studies are expected to provide important guidance for the analysis of a large variety of semi-inclusive data.

Functional summary statistics for the Johnson-Mehl model

DEFF Research Database (Denmark)

Møller, Jesper; Ghorbani, Mohammad

The Johnson-Mehl germination-growth model is a spatio-temporal point process model which among other things have been used for the description of neurotransmitters datasets. However, for such datasets parametric Johnson-Mehl models fitted by maximum likelihood have yet not been evaluated by means...... of functional summary statistics. This paper therefore invents four functional summary statistics adapted to the Johnson-Mehl model, with two of them based on the second-order properties and the other two on the nuclei-boundary distances for the associated Johnson-Mehl tessellation. The functional summary...... statistics theoretical properties are investigated, non-parametric estimators are suggested, and their usefulness for model checking is examined in a simulation study. The functional summary statistics are also used for checking fitted parametric Johnson-Mehl models for a neurotransmitters dataset....

A deterministic width function model

Directory of Open Access Journals (Sweden)

C. E. Puente

2003-01-01

Full Text Available Use of a deterministic fractal-multifractal (FM geometric method to model width functions of natural river networks, as derived distributions of simple multifractal measures via fractal interpolating functions, is reported. It is first demonstrated that the FM procedure may be used to simulate natural width functions, preserving their most relevant features like their overall shape and texture and their observed power-law scaling on their power spectra. It is then shown, via two natural river networks (Racoon and Brushy creeks in the United States, that the FM approach may also be used to closely approximate existing width functions.

Model wave functions for the deuteron

International Nuclear Information System (INIS)

Certov, A.; Mathelitsch, L.; Moravcsik, M.J.

1987-01-01

Model wave functions are constructed for the deuteron to facilitate the unambiguous exploration of dependencies on the percentage D state and on the small-, medium-, and large-distance parts of the deuteron wave function. The wave functions are constrained by those deuteron properties which are accurately known experimentally, and are in an analytic form which is easily integrable in expressions usually encountered in the use of such wave functions

PSA Model Improvement Using Maintenance Rule Function Mapping

Energy Technology Data Exchange (ETDEWEB)

Seo, Mi Ro [KHNP-CRI, Nuclear Safety Laboratory, Daejeon (Korea, Republic of)

2011-10-15

The Maintenance Rule (MR) program, in nature, is a performance-based program. Therefore, the risk information derived from the Probabilistic Safety Assessment model is introduced into the MR program during the Safety Significance determination and Performance Criteria selection processes. However, this process also facilitates the determination of the vulnerabilities in currently utilized PSA models and offers means of improving them. To find vulnerabilities in an existing PSA model, an initial review determines whether the safety-related MR functions are included in the PSA model. Because safety-related MR functions are related to accident prevention and mitigation, it is generally necessary for them to be included in the PSA model. In the process of determining the safety significance of each functions, quantitative risk importance levels are determined through a process known as PSA model basic event mapping to MR functions. During this process, it is common for some inadequate and overlooked models to be uncovered. In this paper, the PSA model and the MR program of Wolsong Unit 1 were used as references

Computational Models for Calcium-Mediated Astrocyte Functions

Directory of Open Access Journals (Sweden)

Tiina Manninen

2018-04-01

Full Text Available The computational neuroscience field has heavily concentrated on the modeling of neuronal functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes. Despite the short history of modeling astrocytic functions, we were delighted about the hundreds of models developed so far to study the role of astrocytes, most often in calcium dynamics, synchronization, information transfer, and plasticity in vitro, but also in vascular events, hyperexcitability, and homeostasis. Our goal here is to present the state-of-the-art in computational modeling of astrocytes in order to facilitate better understanding of the functions and dynamics of astrocytes in the brain. Due to the large number of models, we concentrated on a hundred models that include biophysical descriptions for calcium signaling and dynamics in astrocytes. We categorized the models into four groups: single astrocyte models, astrocyte network models, neuron-astrocyte synapse models, and neuron-astrocyte network models to ease their use in future modeling projects. We characterized the models based on which earlier models were used for building the models and which type of biological entities were described in the astrocyte models. Features of the models were compared and contrasted so that similarities and differences were more readily apparent. We discovered that most of the models were basically generated from a small set of previously published models with small variations. However, neither citations to all the previous models with similar core structure nor explanations of what was built on top of the previous models were provided, which made it possible, in some cases, to have the same models published several times without an explicit intention to make new predictions about the roles of astrocytes in brain functions. Furthermore, only a few of the models are available online which makes it difficult to reproduce the simulation results and further develop

Computational Models for Calcium-Mediated Astrocyte Functions.

Science.gov (United States)

Manninen, Tiina; Havela, Riikka; Linne, Marja-Leena

2018-01-01

The computational neuroscience field has heavily concentrated on the modeling of neuronal functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes. Despite the short history of modeling astrocytic functions, we were delighted about the hundreds of models developed so far to study the role of astrocytes, most often in calcium dynamics, synchronization, information transfer, and plasticity in vitro , but also in vascular events, hyperexcitability, and homeostasis. Our goal here is to present the state-of-the-art in computational modeling of astrocytes in order to facilitate better understanding of the functions and dynamics of astrocytes in the brain. Due to the large number of models, we concentrated on a hundred models that include biophysical descriptions for calcium signaling and dynamics in astrocytes. We categorized the models into four groups: single astrocyte models, astrocyte network models, neuron-astrocyte synapse models, and neuron-astrocyte network models to ease their use in future modeling projects. We characterized the models based on which earlier models were used for building the models and which type of biological entities were described in the astrocyte models. Features of the models were compared and contrasted so that similarities and differences were more readily apparent. We discovered that most of the models were basically generated from a small set of previously published models with small variations. However, neither citations to all the previous models with similar core structure nor explanations of what was built on top of the previous models were provided, which made it possible, in some cases, to have the same models published several times without an explicit intention to make new predictions about the roles of astrocytes in brain functions. Furthermore, only a few of the models are available online which makes it difficult to reproduce the simulation results and further develop the models. Thus

AN APPLICATION OF FUNCTIONAL MULTIVARIATE REGRESSION MODEL TO MULTICLASS CLASSIFICATION

OpenAIRE

Krzyśko, Mirosław; Smaga, Łukasz

2017-01-01

In this paper, the scale response functional multivariate regression model is considered. By using the basis functions representation of functional predictors and regression coefficients, this model is rewritten as a multivariate regression model. This representation of the functional multivariate regression model is used for multiclass classification for multivariate functional data. Computational experiments performed on real labelled data sets demonstrate the effectiveness of the proposed ...

Comparison of optical methods for surface roughness characterization

DEFF Research Database (Denmark)

Feidenhans'l, Nikolaj Agentoft; Hansen, Poul Erik; Pilny, Lukas

2015-01-01

We report a study of the correlation between three optical methods for characterizing surface roughness: a laboratory scatterometer measuring the bi-directional reflection distribution function (BRDF instrument), a simple commercial scatterometer (rBRDF instrument), and a confocal optical profiler....... For each instrument, the effective range of spatial surface wavelengths is determined, and the common bandwidth used when comparing the evaluated roughness parameters. The compared roughness parameters are: the root-mean-square (RMS) profile deviation (Rq), the RMS profile slope (Rdq), and the variance...... of the scattering angle distribution (Aq). The twenty-two investigated samples were manufactured with several methods in order to obtain a suitable diversity of roughness patterns.Our study shows a one-to-one correlation of both the Rq and the Rdq roughness values when obtained with the BRDF and the confocal...

Quantifying offshore wind resources from satellite wind maps: Study area the North Sea

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Barthelmie, Rebecca Jane; Christiansen, Merete B.

2006-01-01

Offshore wind resources are quantified from satellite synthetic aperture radar (SAR) and satellite scatterometer observations at local and regional scale respectively at the Horns Rev site in Denmark. The method for wind resource estimation from satellite observations interfaces with the wind atlas...... of the Horns Rev wind farm is quantified from satellite SAR images and compared with state-of-the-art wake model results with good agreement. It is a unique method using satellite observations to quantify the spatial extent of the wake behind large offshore wind farms. Copyright © 2006 John Wiley & Sons, Ltd....... analysis and application program (WAsP). An estimate of the wind resource at the new project site at Horns Rev is given based on satellite SAR observations. The comparison of offshore satellite scatterometer winds, global model data and in situ data shows good agreement. Furthermore, the wake effect...

The universal function in color dipole model

Science.gov (United States)

Jalilian, Z.; Boroun, G. R.

2017-10-01

In this work we review color dipole model and recall properties of the saturation and geometrical scaling in this model. Our primary aim is determining the exact universal function in terms of the introduced scaling variable in different distance than the saturation radius. With inserting the mass in calculation we compute numerically the contribution of heavy productions in small x from the total structure function by the fraction of universal functions and show the geometrical scaling is established due to our scaling variable in this study.

NJL-jet model for quark fragmentation functions

International Nuclear Information System (INIS)

Ito, T.; Bentz, W.; Cloeet, I. C.; Thomas, A. W.; Yazaki, K.

2009-01-01

A description of fragmentation functions which satisfy the momentum and isospin sum rules is presented in an effective quark theory. Concentrating on the pion fragmentation function, we first explain why the elementary (lowest order) fragmentation process q→qπ is completely inadequate to describe the empirical data, although the crossed process π→qq describes the quark distribution functions in the pion reasonably well. Taking into account cascadelike processes in a generalized jet-model approach, we then show that the momentum and isospin sum rules can be satisfied naturally, without the introduction of ad hoc parameters. We present results for the Nambu-Jona-Lasinio (NJL) model in the invariant mass regularization scheme and compare them with the empirical parametrizations. We argue that the NJL-jet model, developed herein, provides a useful framework with which to calculate the fragmentation functions in an effective chiral quark theory.

Factorisations for partition functions of random Hermitian matrix models

International Nuclear Information System (INIS)

Jackson, D.M.; Visentin, T.I.

1996-01-01

The partition function Z N , for Hermitian-complex matrix models can be expressed as an explicit integral over R N , where N is a positive integer. Such an integral also occurs in connection with random surfaces and models of two dimensional quantum gravity. We show that Z N can be expressed as the product of two partition functions, evaluated at translated arguments, for another model, giving an explicit connection between the two models. We also give an alternative computation of the partition function for the φ 4 -model.The approach is an algebraic one and holds for the functions regarded as formal power series in the appropriate ring. (orig.)

Predictive assessment of models for dynamic functional connectivity

DEFF Research Database (Denmark)

Nielsen, Søren Føns Vind; Schmidt, Mikkel Nørgaard; Madsen, Kristoffer Hougaard

2018-01-01

represent functional brain networks as a meta-stable process with a discrete number of states; however, there is a lack of consensus on how to perform model selection and learn the number of states, as well as a lack of understanding of how different modeling assumptions influence the estimated state......In neuroimaging, it has become evident that models of dynamic functional connectivity (dFC), which characterize how intrinsic brain organization changes over time, can provide a more detailed representation of brain function than traditional static analyses. Many dFC models in the literature...... dynamics. To address these issues, we consider a predictive likelihood approach to model assessment, where models are evaluated based on their predictive performance on held-out test data. Examining several prominent models of dFC (in their probabilistic formulations) we demonstrate our framework...

Correlation functions of two-matrix models

International Nuclear Information System (INIS)

Bonora, L.; Xiong, C.S.

1993-11-01

We show how to calculate correlation functions of two matrix models without any approximation technique (except for genus expansion). In particular we do not use any continuum limit technique. This allows us to find many solutions which are invisible to the latter technique. To reach our goal we make full use of the integrable hierarchies and their reductions which were shown in previous papers to naturally appear in multi-matrix models. The second ingredient we use, even though to a lesser extent, are the W-constraints. In fact an explicit solution of the relevant hierarchy, satisfying the W-constraints (string equation), underlies the explicit calculation of the correlation functions. The correlation functions we compute lend themselves to a possible interpretation in terms of topological field theories. (orig.)

Multinomial-exponential reliability function: a software reliability model

International Nuclear Information System (INIS)

Saiz de Bustamante, Amalio; Saiz de Bustamante, Barbara

2003-01-01

The multinomial-exponential reliability function (MERF) was developed during a detailed study of the software failure/correction processes. Later on MERF was approximated by a much simpler exponential reliability function (EARF), which keeps most of MERF mathematical properties, so the two functions together makes up a single reliability model. The reliability model MERF/EARF considers the software failure process as a non-homogeneous Poisson process (NHPP), and the repair (correction) process, a multinomial distribution. The model supposes that both processes are statistically independent. The paper discusses the model's theoretical basis, its mathematical properties and its application to software reliability. Nevertheless it is foreseen model applications to inspection and maintenance of physical systems. The paper includes a complete numerical example of the model application to a software reliability analysis

Assimilation of global radar backscatter and radiometer brightness temperature observations to improve soil moisture and land evaporation estimates

NARCIS (Netherlands)

Lievens, H.; Martens, B.; Verhoest, N.E.C.; Hahn, S.; Reichle, R.H.; Gonzalez Miralles, D.

2016-01-01

Active radar backscatter (σ°) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model

Modeling Functional Neuroanatomy for an Anatomy Information System

Science.gov (United States)

Niggemann, Jörg M.; Gebert, Andreas; Schulz, Stefan

2008-01-01

Objective Existing neuroanatomical ontologies, databases and information systems, such as the Foundational Model of Anatomy (FMA), represent outgoing connections from brain structures, but cannot represent the “internal wiring” of structures and as such, cannot distinguish between different independent connections from the same structure. Thus, a fundamental aspect of Neuroanatomy, the functional pathways and functional systems of the brain such as the pupillary light reflex system, is not adequately represented. This article identifies underlying anatomical objects which are the source of independent connections (collections of neurons) and uses these as basic building blocks to construct a model of functional neuroanatomy and its functional pathways. Design The basic representational elements of the model are unnamed groups of neurons or groups of neuron segments. These groups, their relations to each other, and the relations to the objects of macroscopic anatomy are defined. The resulting model can be incorporated into the FMA. Measurements The capabilities of the presented model are compared to the FMA and the Brain Architecture Management System (BAMS). Results Internal wiring as well as functional pathways can correctly be represented and tracked. Conclusion This model bridges the gap between representations of single neurons and their parts on the one hand and representations of spatial brain structures and areas on the other hand. It is capable of drawing correct inferences on pathways in a nervous system. The object and relation definitions are related to the Open Biomedical Ontology effort and its relation ontology, so that this model can be further developed into an ontology of neuronal functional systems. PMID:18579841

On Support Functions for the Development of MFM Models

DEFF Research Database (Denmark)

Heussen, Kai; Lind, Morten

2012-01-01

a review of MFM applications, and contextualizes the model development with respect to process design and operation knowledge. Developing a perspective for an environment for MFM-oriented model- and application-development a tool-chain is outlined and relevant software functions are discussed......A modeling environment and methodology are necessary to ensure quality and reusability of models in any domain. For MFM in particular, as a tool for modeling complex systems, awareness has been increasing for this need. Introducing the context of modeling support functions, this paper provides....... With a perspective on MFM-modeling for existing processes and automation design, modeling stages and corresponding formal model properties are identified. Finally, practically feasible support functions and model-checks to support the model-development are suggested....

Function of dynamic models in systems biology: linking structure to behaviour.

Science.gov (United States)

Knüpfer, Christian; Beckstein, Clemens

2013-10-08

Dynamic models in Systems Biology are used in computational simulation experiments for addressing biological questions. The complexity of the modelled biological systems and the growing number and size of the models calls for computer support for modelling and simulation in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments. In this paper we describe different functional aspects of dynamic models. This description is conceptually embedded in our "meaning facets" framework which systematises the interpretation of dynamic models in structural, functional and behavioural facets. Here we focus on how function links the structure and the behaviour of a model. Models play a specific role (teleological function) in the scientific process of finding explanations for dynamic phenomena. In order to fulfil this role a model has to be used in simulation experiments (pragmatical function). A simulation experiment always refers to a specific situation and a state of the model and the modelled system (conditional function). We claim that the function of dynamic models refers to both the simulation experiment executed by software (intrinsic function) and the biological experiment which produces the phenomena under investigation (extrinsic function). We use the presented conceptual framework for the function of dynamic models to review formal accounts for functional aspects of models in Systems Biology, such as checklists, ontologies, and formal languages. Furthermore, we identify missing formal accounts for some of the functional aspects. In order to fill one of these gaps we propose an ontology for the teleological function of models. We have thoroughly analysed the role and use of models in Systems Biology. The resulting conceptual framework for the function of models is an important first step towards a comprehensive formal representation of the functional knowledge involved in the modelling and simulation process

A DSM-based framework for integrated function modelling

DEFF Research Database (Denmark)

Eisenbart, Boris; Gericke, Kilian; Blessing, Lucienne T. M.

2017-01-01

an integrated function modelling framework, which specifically aims at relating between the different function modelling perspectives prominently addressed in different disciplines. It uses interlinked matrices based on the concept of DSM and MDM in order to facilitate cross-disciplinary modelling and analysis...... of the functionality of a system. The article further presents the application of the framework based on a product example. Finally, an empirical study in industry is presented. Therein, feedback on the potential of the proposed framework to support interdisciplinary design practice as well as on areas of further...

Composite spectral functions for solving Volterra's population model

International Nuclear Information System (INIS)

Ramezani, M.; Razzaghi, M.; Dehghan, M.

2007-01-01

An approximate method for solving Volterra's population model for population growth of a species in a closed system is proposed. Volterra's model is a nonlinear integro-differential equation, where the integral term represents the effect of toxin. The approach is based upon composite spectral functions approximations. The properties of composite spectral functions consisting of few terms of orthogonal functions are presented and are utilized to reduce the solution of the Volterra's model to the solution of a system of algebraic equations. The method is easy to implement and yields very accurate result

Exact 2-point function in Hermitian matrix model

International Nuclear Information System (INIS)

Morozov, A.; Shakirov, Sh.

2009-01-01

J. Harer and D. Zagier have found a strikingly simple generating function [1,2] for exact (all-genera) 1-point correlators in the Gaussian Hermitian matrix model. In this paper we generalize their result to 2-point correlators, using Toda integrability of the model. Remarkably, this exact 2-point correlation function turns out to be an elementary function - arctangent. Relation to the standard 2-point resolvents is pointed out. Some attempts of generalization to 3-point and higher functions are described.

Zhang functions and various models

CERN Document Server

Zhang, Yunong

2015-01-01

This book focuses on solving different types of time-varying problems. It presents various Zhang dynamics (ZD) models by defining various Zhang functions (ZFs) in real and complex domains. It then provides theoretical analyses of such ZD models and illustrates their results. It also uses simulations to substantiate their efficacy and show the feasibility of the presented ZD approach (i.e., different ZFs leading to different ZD models), which is further applied to the repetitive motion planning (RMP) of redundant robots, showing its application potential.

Mathematical modeling and visualization of functional neuroimages

DEFF Research Database (Denmark)

Rasmussen, Peter Mondrup

This dissertation presents research results regarding mathematical modeling in the context of the analysis of functional neuroimages. Specifically, the research focuses on pattern-based analysis methods that recently have become popular analysis tools within the neuroimaging community. Such methods...... neuroimaging data sets are characterized by relatively few data observations in a high dimensional space. The process of building models in such data sets often requires strong regularization. Often, the degree of model regularization is chosen in order to maximize prediction accuracy. We focus on the relative...... be carefully selected, so that the model and its visualization enhance our ability to interpret brain function. The second part concerns interpretation of nonlinear models and procedures for extraction of ‘brain maps’ from nonlinear kernel models. We assess the performance of the sensitivity map as means...

Structure functions in the chiral bag model

International Nuclear Information System (INIS)

Sanjose, V.; Vento, V.; Centro Mixto CSIC/Valencia Univ., Valencia

1989-01-01

We calculate the structure functions of an isoscalar nuclear target for the deep inelastic scattering by leptons in an extended version of the chiral bag model which incorporates the qanti q structure of the pions in the cloud. Bjorken scaling and Regge behavior are satisfied. The model calculation reproduces the low-x behavior of the data but fails to explain the medium- to large-x behavior. Evolution of the quark structure functions seem inevitable to attempt a connection between the low-energy models and the high-energy behavior of quantum chromodynamics. (orig.)

Structure functions in the chiral bag model

Energy Technology Data Exchange (ETDEWEB)

Sanjose, V.; Vento, V.

1989-07-13

We calculate the structure functions of an isoscalar nuclear target for the deep inelastic scattering by leptons in an extended version of the chiral bag model which incorporates the qanti q structure of the pions in the cloud. Bjorken scaling and Regge behavior are satisfied. The model calculation reproduces the low-x behavior of the data but fails to explain the medium- to large-x behavior. Evolution of the quark structure functions seem inevitable to attempt a connection between the low-energy models and the high-energy behavior of quantum chromodynamics. (orig.).

Hazard identification based on plant functional modelling

International Nuclear Information System (INIS)

Rasmussen, B.; Whetton, C.

1993-10-01

A major objective of the present work is to provide means for representing a process plant as a socio-technical system, so as to allow hazard identification at a high level. The method includes technical, human and organisational aspects and is intended to be used for plant level hazard identification so as to identify critical areas and the need for further analysis using existing methods. The first part of the method is the preparation of a plant functional model where a set of plant functions link together hardware, software, operations, work organisation and other safety related aspects of the plant. The basic principle of the functional modelling is that any aspect of the plant can be represented by an object (in the sense that this term is used in computer science) based upon an Intent (or goal); associated with each Intent are Methods, by which the Intent is realized, and Constraints, which limit the Intent. The Methods and Constraints can themselves be treated as objects and decomposed into lower-level Intents (hence the procedure is known as functional decomposition) so giving rise to a hierarchical, object-oriented structure. The plant level hazard identification is carried out on the plant functional model using the Concept Hazard Analysis method. In this, the user will be supported by checklists and keywords and the analysis is structured by pre-defined worksheets. The preparation of the plant functional model and the performance of the hazard identification can be carried out manually or with computer support. (au) (4 tabs., 10 ills., 7 refs.)

Annotation and retrieval system of CAD models based on functional semantics

Science.gov (United States)

Wang, Zhansong; Tian, Ling; Duan, Wenrui

2014-11-01

CAD model retrieval based on functional semantics is more significant than content-based 3D model retrieval during the mechanical conceptual design phase. However, relevant research is still not fully discussed. Therefore, a functional semantic-based CAD model annotation and retrieval method is proposed to support mechanical conceptual design and design reuse, inspire designer creativity through existing CAD models, shorten design cycle, and reduce costs. Firstly, the CAD model functional semantic ontology is constructed to formally represent the functional semantics of CAD models and describe the mechanical conceptual design space comprehensively and consistently. Secondly, an approach to represent CAD models as attributed adjacency graphs(AAG) is proposed. In this method, the geometry and topology data are extracted from STEP models. On the basis of AAG, the functional semantics of CAD models are annotated semi-automatically by matching CAD models that contain the partial features of which functional semantics have been annotated manually, thereby constructing CAD Model Repository that supports model retrieval based on functional semantics. Thirdly, a CAD model retrieval algorithm that supports multi-function extended retrieval is proposed to explore more potential creative design knowledge in the semantic level. Finally, a prototype system, called Functional Semantic-based CAD Model Annotation and Retrieval System(FSMARS), is implemented. A case demonstrates that FSMARS can successfully botain multiple potential CAD models that conform to the desired function. The proposed research addresses actual needs and presents a new way to acquire CAD models in the mechanical conceptual design phase.

A Generic Modeling Process to Support Functional Fault Model Development

Science.gov (United States)

Maul, William A.; Hemminger, Joseph A.; Oostdyk, Rebecca; Bis, Rachael A.

2016-01-01

Functional fault models (FFMs) are qualitative representations of a system's failure space that are used to provide a diagnostic of the modeled system. An FFM simulates the failure effect propagation paths within a system between failure modes and observation points. These models contain a significant amount of information about the system including the design, operation and off nominal behavior. The development and verification of the models can be costly in both time and resources. In addition, models depicting similar components can be distinct, both in appearance and function, when created individually, because there are numerous ways of representing the failure space within each component. Generic application of FFMs has the advantages of software code reuse: reduction of time and resources in both development and verification, and a standard set of component models from which future system models can be generated with common appearance and diagnostic performance. This paper outlines the motivation to develop a generic modeling process for FFMs at the component level and the effort to implement that process through modeling conventions and a software tool. The implementation of this generic modeling process within a fault isolation demonstration for NASA's Advanced Ground System Maintenance (AGSM) Integrated Health Management (IHM) project is presented and the impact discussed.

Quark fragmentation function and the nonlinear chiral quark model

International Nuclear Information System (INIS)

Zhu, Z.K.

1993-01-01

The scaling law of the fragmentation function has been proved in this paper. With that, we show that low-P T quark fragmentation function can be studied as a low energy physocs in the light-cone coordinate frame. We therefore use the nonlinear chiral quark model which is able to study the low energy physics under scale Λ CSB to study such a function. Meanwhile the formalism for studying the quark fragmentation function has been established. The nonlinear chiral quark model is quantized on the light-front. We then use old-fashioned perturbation theory to study the quark fragmentation function. Our first order result for such a function shows in agreement with the phenomenological model study of e + e - jet. The probability for u,d pair formation in the e + e - jet from our calculation is also in agreement with the phenomenological model results

Modelling of Functional States during Saccharomyces cerevisiae Fed-batch Cultivation

Directory of Open Access Journals (Sweden)

Stoyan Tzonkov

2005-04-01

Full Text Available An implementation of functional state approach for modelling of yeast fed-batch cultivation is presented in this paper. Using of functional state modelling approach aims to overcome the main disadvantage of using global process model, namely complex model structure and big number of model parameters, which complicate the model simulation and parameter estimation. This approach has computational advantages, such as the possibility to use the estimated values from the previous state as starting values for estimation of parameters of a new state. The functional state modelling approach is applied here for fedbatch cultivation of Saccharomyces cerevisiae. Four functional states are recognised and parameter estimation of local models is presented as well.

Quark fragmentation functions in NJL-jet model

Science.gov (United States)

Bentz, Wolfgang; Matevosyan, Hrayr; Thomas, Anthony

2014-09-01

We report on our studies of quark fragmentation functions in the Nambu-Jona-Lasinio (NJL) - jet model. The results of Monte-Carlo simulations for the fragmentation functions to mesons and nucleons, as well as to pion and kaon pairs (dihadron fragmentation functions) are presented. The important role of intermediate vector meson resonances for those semi-inclusive deep inelastic production processes is emphasized. Our studies are very relevant for the extraction of transverse momentum dependent quark distribution functions from measured scattering cross sections. We report on our studies of quark fragmentation functions in the Nambu-Jona-Lasinio (NJL) - jet model. The results of Monte-Carlo simulations for the fragmentation functions to mesons and nucleons, as well as to pion and kaon pairs (dihadron fragmentation functions) are presented. The important role of intermediate vector meson resonances for those semi-inclusive deep inelastic production processes is emphasized. Our studies are very relevant for the extraction of transverse momentum dependent quark distribution functions from measured scattering cross sections. Supported by Grant in Aid for Scientific Research, Japanese Ministry of Education, Culture, Sports, Science and Technology, Project No. 20168769.

Diagnostics for Linear Models With Functional Responses

OpenAIRE

Xu, Hongquan; Shen, Qing

2005-01-01

Linear models where the response is a function and the predictors are vectors are useful in analyzing data from designed experiments and other situations with functional observations. Residual analysis and diagnostics are considered for such models. Studentized residuals are defined and their properties are studied. Chi-square quantile-quantile plots are proposed to check the assumption of Gaussian error process and outliers. Jackknife residuals and an associated test are proposed to det...

FUNCTIONAL MODELLING FOR FAULT DIAGNOSIS AND ITS APPLICATION FOR NPP

Directory of Open Access Journals (Sweden)

MORTEN LIND

2014-12-01

Full Text Available The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM, which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.

Functional Modelling for fault diagnosis and its application for NPP

Energy Technology Data Exchange (ETDEWEB)

Lind, Morten; Zhang, Xin Xin [Dept. of Electrical Engineering, Technical University of Denmark, Kongens Lyngby (Denmark)

2014-12-15

The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM), which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.

Functional Modelling for fault diagnosis and its application for NPP

International Nuclear Information System (INIS)

Lind, Morten; Zhang, Xin Xin

2014-01-01

The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM), which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.

Modeling phytoplankton community in reservoirs. A comparison between taxonomic and functional groups-based models.

Science.gov (United States)

Di Maggio, Jimena; Fernández, Carolina; Parodi, Elisa R; Diaz, M Soledad; Estrada, Vanina

2016-01-01

In this paper we address the formulation of two mechanistic water quality models that differ in the way the phytoplankton community is described. We carry out parameter estimation subject to differential-algebraic constraints and validation for each model and comparison between models performance. The first approach aggregates phytoplankton species based on their phylogenetic characteristics (Taxonomic group model) and the second one, on their morpho-functional properties following Reynolds' classification (Functional group model). The latter approach takes into account tolerance and sensitivity to environmental conditions. The constrained parameter estimation problems are formulated within an equation oriented framework, with a maximum likelihood objective function. The study site is Paso de las Piedras Reservoir (Argentina), which supplies water for consumption for 450,000 population. Numerical results show that phytoplankton morpho-functional groups more closely represent each species growth requirements within the group. Each model performance is quantitatively assessed by three diagnostic measures. Parameter estimation results for seasonal dynamics of the phytoplankton community and main biogeochemical variables for a one-year time horizon are presented and compared for both models, showing the functional group model enhanced performance. Finally, we explore increasing nutrient loading scenarios and predict their effect on phytoplankton dynamics throughout a one-year time horizon. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multivariate Heteroscedasticity Models for Functional Brain Connectivity

Directory of Open Access Journals (Sweden)

Christof Seiler

2017-12-01

Full Text Available Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI. We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.

Evaluation-Function-based Model-free Adaptive Fuzzy Control

Directory of Open Access Journals (Sweden)

Agus Naba

2016-12-01

Full Text Available Designs of adaptive fuzzy controllers (AFC are commonly based on the Lyapunov approach, which requires a known model of the controlled plant. They need to consider a Lyapunov function candidate as an evaluation function to be minimized. In this study these drawbacks were handled by designing a model-free adaptive fuzzy controller (MFAFC using an approximate evaluation function defined in terms of the current state, the next state, and the control action. MFAFC considers the approximate evaluation function as an evaluative control performance measure similar to the state-action value function in reinforcement learning. The simulation results of applying MFAFC to the inverted pendulum benchmark verified the proposed scheme’s efficacy.

Model Penentuan Nilai Target Functional Requirement Berbasis Utilitas

Directory of Open Access Journals (Sweden)

Cucuk Nur Rosyidi

2012-01-01

Full Text Available In a product design and development process, a designer faces a problem to decide functional requirement (FR target values. That decision is made under a risk since it is conducted in the early design phase using incomplete information. Utility function can be used to reflect the decision maker attitude towards the risk in making such decision. In this research, we develop a utility-based model to determine FR target values using quadratic utility function and information from Quality Function Deployment (QFD. A pencil design is used as a numerical example using quadratic utility function for each FR. The model can be applied for balancing customer and designer interest in determining FR target values.

Towards refactoring the Molecular Function Ontology with a UML profile for function modeling.

Science.gov (United States)

Burek, Patryk; Loebe, Frank; Herre, Heinrich

2017-10-04

Gene Ontology (GO) is the largest resource for cataloging gene products. This resource grows steadily and, naturally, this growth raises issues regarding the structure of the ontology. Moreover, modeling and refactoring large ontologies such as GO is generally far from being simple, as a whole as well as when focusing on certain aspects or fragments. It seems that human-friendly graphical modeling languages such as the Unified Modeling Language (UML) could be helpful in connection with these tasks. We investigate the use of UML for making the structural organization of the Molecular Function Ontology (MFO), a sub-ontology of GO, more explicit. More precisely, we present a UML dialect, called the Function Modeling Language (FueL), which is suited for capturing functions in an ontologically founded way. FueL is equipped, among other features, with language elements that arise from studying patterns of subsumption between functions. We show how to use this UML dialect for capturing the structure of molecular functions. Furthermore, we propose and discuss some refactoring options concerning fragments of MFO. FueL enables the systematic, graphical representation of functions and their interrelations, including making information explicit that is currently either implicit in MFO or is mainly captured in textual descriptions. Moreover, the considered subsumption patterns lend themselves to the methodical analysis of refactoring options with respect to MFO. On this basis we argue that the approach can increase the comprehensibility of the structure of MFO for humans and can support communication, for example, during revision and further development.

Scatterometry

Science.gov (United States)

Stoffelen, Adrianus Cornelis Maria

1996-10-01

weer sterk afhankelijk van de amplitude van de capillaire golven. Bovendien blijken de capillaire golfjes over het algemeen gericht in lijn met de windrichting. Aldus bestaat er een verband tussen de hoeveelheid teruggestrooide energie en de windsterkte en -richting op enige hoogte. Een scatterometer instrument wordt zo ontworpen dat uit diverse metingen van het teruggestrooide vermogen, windsterkte en -richting afgeleid kunnen worden. Deze metingen kunnen dan eenvoudig vergeleken worden met bestaande windgegevens van boeien, schepen en weermodellen ter calibratie en validatie.?SAMENVATTING viii Overzicht In de loop der jaren zijn scatterometer instrumenten aan boord van verscheidene satellieten gelanceerd. De scatterometers op de ERS-1 en ERS-2 ("European Remote-sensing Satellite") hebben de langste staat van dienst en zijn sinds 1991 operationeel. Deze scatterometers (die identiek zijn) hebben ieder drie antennes, waarmee het oceaanoppervlak in drie verschillende richtingen bemeten wordt. Een punt op het aardoppervlak wordt eerst door de naar voren gerichte bundel belicht, dan door de naar opzij gerichte bundel, en als laatste door de naar achteren gerichte bundel. De drie metingen, verder kortweg aangeduid als trits, kunnen tegen elkaar worden uitgezet, hetgeen resulteert in een ruimtelijk (3D) plaatje. Door uitgekiende doorsneden te maken van deze ruimte kan de samenhang van de drie metingen kwalitatief worden bestudeerd. De drie metingen blijken dan inderdaad een sterke samenhang te vertonen die verklaard kan worden uit twee geofysische parameters. De drie metingen liggen namelijk in het algemeen dichtbij een hoornvormig (2D) oppervlak. De lengterichting van de hoorn blijkt voornamelijk te corresponderen met een variërende windsterkte (of ruwheid van de zee), en de kortste omtrek van de hoorn met een variërende windrichting (ofwel oriëntatie van de capillaire golfjes). De karakterisatie en modellering van dit oppervlak heeft geleid tot een aanzienlijke

Group-ICA model order highlights patterns of functional brain connectivity

Directory of Open Access Journals (Sweden)

Ahmed eAbou Elseoud

2011-06-01

Full Text Available Resting-state networks (RSNs can be reliably and reproducibly detected using independent component analysis (ICA at both individual subject and group levels. Altering ICA dimensionality (model order estimation can have a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Recent evidence from several neuroimaging studies suggests that the human brain has a modular hierarchical organization which resembles the hierarchy depicted by different ICA model orders. We hypothesized that functional connectivity between-group differences measured with ICA might be affected by model order selection. We investigated differences in functional connectivity using so-called dual-regression as a function of ICA model order in a group of unmedicated seasonal affective disorder (SAD patients compared to normal healthy controls. The results showed that the detected disease-related differences in functional connectivity alter as a function of ICA model order. The volume of between-group differences altered significantly as a function of ICA model order reaching maximum at model order 70 (which seems to be an optimal point that conveys the largest between-group difference then stabilized afterwards. Our results show that fine-grained RSNs enable better detection of detailed disease-related functional connectivity changes. However, high model orders show an increased risk of false positives that needs to be overcome. Our findings suggest that multilevel ICA exploration of functional connectivity enables optimization of sensitivity to brain disorders.

Neural modeling of prefrontal executive function

Energy Technology Data Exchange (ETDEWEB)

Levine, D.S. [Univ. of Texas, Arlington, TX (United States)

1996-12-31

Brain executive function is based in a distributed system whereby prefrontal cortex is interconnected with other cortical. and subcortical loci. Executive function is divided roughly into three interacting parts: affective guidance of responses; linkage among working memory representations; and forming complex behavioral schemata. Neural network models of each of these parts are reviewed and fit into a preliminary theoretical framework.

Symmetries and modelling functions for diffusion processes

International Nuclear Information System (INIS)

Nikitin, A G; Spichak, S V; Vedula, Yu S; Naumovets, A G

2009-01-01

A constructive approach to the theory of diffusion processes is proposed, which is based on application of both symmetry analysis and the method of modelling functions. An algorithm for construction of the modelling functions is suggested. This algorithm is based on the error function expansion (ERFEX) of experimental concentration profiles. The high-accuracy analytical description of the profiles provided by ERFEX approximation allows a convenient extraction of the concentration dependence of diffusivity from experimental data and prediction of the diffusion process. Our analysis is exemplified by its employment in experimental results obtained for surface diffusion of lithium on the molybdenum (1 1 2) surface precovered with dysprosium. The ERFEX approximation can be directly extended to many other diffusion systems.

Functional linear models for association analysis of quantitative traits.

Science.gov (United States)

Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

2013-11-01

Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY

Enabling Cross-Discipline Collaboration Via a Functional Data Model

Science.gov (United States)

Lindholm, D. M.; Wilson, A.; Baltzer, T.

2016-12-01

Many research disciplines have very specialized data models that are used to express the detailed semantics that are meaningful to that community and easily utilized by their data analysis tools. While invaluable to members of that community, such expressive data structures and metadata are of little value to potential collaborators from other scientific disciplines. Many data interoperability efforts focus on the difficult task of computationally mapping concepts from one domain to another to facilitate discovery and use of data. Although these efforts are important and promising, we have found that a great deal of discovery and dataset understanding still happens at the level of less formal, personal communication. However, a significant barrier to inter-disciplinary data sharing that remains is one of data access.Scientists and data analysts continue to spend inordinate amounts of time simply trying to get data into their analysis tools. Providing data in a standard file format is often not sufficient since data can be structured in many ways. Adhering to more explicit community standards for data structure and metadata does little to help those in other communities.The Functional Data Model specializes the Relational Data Model (used by many database systems)by defining relations as functions between independent (domain) and dependent (codomain) variables. Given that arrays of data in many scientific data formats generally represent functionally related parameters (e.g. temperature as a function of space and time), the Functional Data Model is quite relevant for these datasets as well. The LaTiS software framework implements the Functional Data Model and provides a mechanism to expose an existing data source as a LaTiS dataset. LaTiS datasets can be manipulated using a Functional Algebra and output in any number of formats.LASP has successfully used the Functional Data Model and its implementation in the LaTiS software framework to bridge the gap between

Towards aspect-oriented functional--structural plant modelling.

Science.gov (United States)

Cieslak, Mikolaj; Seleznyova, Alla N; Prusinkiewicz, Przemyslaw; Hanan, Jim

2011-10-01

Functional-structural plant models (FSPMs) are used to integrate knowledge and test hypotheses of plant behaviour, and to aid in the development of decision support systems. A significant amount of effort is being put into providing a sound methodology for building them. Standard techniques, such as procedural or object-oriented programming, are not suited for clearly separating aspects of plant function that criss-cross between different components of plant structure, which makes it difficult to reuse and share their implementations. The aim of this paper is to present an aspect-oriented programming approach that helps to overcome this difficulty. The L-system-based plant modelling language L+C was used to develop an aspect-oriented approach to plant modelling based on multi-modules. Each element of the plant structure was represented by a sequence of L-system modules (rather than a single module), with each module representing an aspect of the element's function. Separate sets of productions were used for modelling each aspect, with context-sensitive rules facilitated by local lists of modules to consider/ignore. Aspect weaving or communication between aspects was made possible through the use of pseudo-L-systems, where the strict-predecessor of a production rule was specified as a multi-module. The new approach was used to integrate previously modelled aspects of carbon dynamics, apical dominance and biomechanics with a model of a developing kiwifruit shoot. These aspects were specified independently and their implementation was based on source code provided by the original authors without major changes. This new aspect-oriented approach to plant modelling is well suited for studying complex phenomena in plant science, because it can be used to integrate separate models of individual aspects of plant development and function, both previously constructed and new, into clearly organized, comprehensive FSPMs. In a future work, this approach could be further

Model validation and calibration based on component functions of model output

International Nuclear Information System (INIS)

Wu, Danqing; Lu, Zhenzhou; Wang, Yanping; Cheng, Lei

2015-01-01

The target in this work is to validate the component functions of model output between physical observation and computational model with the area metric. Based on the theory of high dimensional model representations (HDMR) of independent input variables, conditional expectations are component functions of model output, and the conditional expectations reflect partial information of model output. Therefore, the model validation of conditional expectations tells the discrepancy between the partial information of the computational model output and that of the observations. Then a calibration of the conditional expectations is carried out to reduce the value of model validation metric. After that, a recalculation of the model validation metric of model output is taken with the calibrated model parameters, and the result shows that a reduction of the discrepancy in the conditional expectations can help decrease the difference in model output. At last, several examples are employed to demonstrate the rationality and necessity of the methodology in case of both single validation site and multiple validation sites. - Highlights: • A validation metric of conditional expectations of model output is proposed. • HDRM explains the relationship of conditional expectations and model output. • An improved approach of parameter calibration updates the computational models. • Validation and calibration process are applied at single site and multiple sites. • Validation and calibration process show a superiority than existing methods

Cost functions of greenhouse models

International Nuclear Information System (INIS)

Linderoth, H.

2000-01-01

The benchmark is equal to the cost (D) caused by an increase in temperature since the middle of the nineteenth century (T) of nearly 2.5 deg. C. According to mainstream economists, the benchmark is 1-2% of GDP, but very different estimates can also be found. Even though there appears to be agreement among a number of economists that the benchmark is 1-2% of GDP, major differences exist when it comes to estimating D for different sectors. One of the main problems is how to estimate non-market activities. Normally, the benchmark is the best guess, but due to the possibility of catastrophic events this can be considerable smaller than the mean. Certainly, the cost function is skewed to the right. The benchmark is just one point on the cost curve. To a great extent, cost functions are alike in greenhouse models (D = α ''.T'' λ). Cost functions are region and sector dependent in several models. In any case, both α (benchmark) and λ are rough estimates. Besides being dependent on α and λ, the marginal emission cost depends on the discount rate. In fact, because emissions have effects continuing for many years, the discount rate is clearly the most important parameter. (au) (au)

Using Lambert W function and error function to model phase change on microfluidics

Science.gov (United States)

Bermudez Garcia, Anderson

2014-05-01

Solidification and melting modeling on microfluidics are solved using Lambert W's function and error's functions. Models are formulated using the heat's diffusion equation. The generic posed case is the melting of a slab with time dependent surface temperature, having a micro or nano-fluid liquid phase. At the beginning the solid slab is at melting temperature. A slab's face is put and maintained at temperature greater than the melting limit and varying in time. Lambert W function and error function are applied via Maple to obtain the analytic solution evolution of the front of microfluidic-solid interface, it is analytically computed and slab's corresponding melting time is determined. It is expected to have analytical results to be useful for food engineering, cooking engineering, pharmaceutical engineering, nano-engineering and bio-medical engineering.

Mathematical Models of Cardiac Pacemaking Function

Science.gov (United States)

Li, Pan; Lines, Glenn T.; Maleckar, Mary M.; Tveito, Aslak

2013-10-01

Over the past half century, there has been intense and fruitful interaction between experimental and computational investigations of cardiac function. This interaction has, for example, led to deep understanding of cardiac excitation-contraction coupling; how it works, as well as how it fails. However, many lines of inquiry remain unresolved, among them the initiation of each heartbeat. The sinoatrial node, a cluster of specialized pacemaking cells in the right atrium of the heart, spontaneously generates an electro-chemical wave that spreads through the atria and through the cardiac conduction system to the ventricles, initiating the contraction of cardiac muscle essential for pumping blood to the body. Despite the fundamental importance of this primary pacemaker, this process is still not fully understood, and ionic mechanisms underlying cardiac pacemaking function are currently under heated debate. Several mathematical models of sinoatrial node cell membrane electrophysiology have been constructed as based on different experimental data sets and hypotheses. As could be expected, these differing models offer diverse predictions about cardiac pacemaking activities. This paper aims to present the current state of debate over the origins of the pacemaking function of the sinoatrial node. Here, we will specifically review the state-of-the-art of cardiac pacemaker modeling, with a special emphasis on current discrepancies, limitations, and future challenges.

The Schroedinger functional for Gross-Neveu models

International Nuclear Information System (INIS)

Leder, B.

2007-01-01

Gross-Neveu type models with a finite number of fermion flavours are studied on a two-dimensional Euclidean space-time lattice. The models are asymptotically free and are invariant under a chiral symmetry. These similarities to QCD make them perfect benchmark systems for fermion actions used in large scale lattice QCD computations. The Schroedinger functional for the Gross-Neveu models is defined for both, Wilson and Ginsparg-Wilson fermions, and shown to be renormalisable in 1-loop lattice perturbation theory. In two dimensions four fermion interactions of the Gross-Neveu models have dimensionless coupling constants. The symmetry properties of the four fermion interaction terms and the relations among them are discussed. For Wilson fermions chiral symmetry is explicitly broken and additional terms must be included in the action. Chiral symmetry is restored up to cut-off effects by tuning the bare mass and one of the couplings. The critical mass and the symmetry restoring coupling are computed to second order in lattice perturbation theory. This result is used in the 1-loop computation of the renormalised couplings and the associated beta-functions. The renormalised couplings are defined in terms of suitable boundary-to-boundary correlation functions. In the computation the known first order coefficients of the beta-functions are reproduced. One of the couplings is found to have a vanishing betafunction. The calculation is repeated for the recently proposed Schroedinger functional with exact chiral symmetry, i.e. Ginsparg-Wilson fermions. The renormalisation pattern is found to be the same as in the Wilson case. Using the regularisation dependent finite part of the renormalised couplings, the ratio of the Lambda-parameters is computed. (orig.)

The SOS model partition function and the elliptic weight functions

International Nuclear Information System (INIS)

Pakuliak, S; Silantyev, A; Rubtsov, V

2008-01-01

We generalized a recent observation (Khoroshkin and Pakuliak 2005 Theor. Math. Phys. 145 1373) that the partition function of the six-vertex model with domain wall boundary conditions can be obtained from a calculation of projections of the product of total currents in the quantum affine algebra U q (sl 2 -hat) in its current realization. A generalization is done for the elliptic current algebra (Enriquez and Felder 1998 Commun. Math. Phys. 195 651, Enriquez and Rubtsov 1997 Ann. Sci. Ecole Norm. Sup. 30 821). The projections of the product of total currents in this case are calculated explicitly and are presented as integral transforms of a product of the total currents. It is proved that the integral kernel of this transform is proportional to the partition function of the SOS model with domain wall boundary conditions

Ab initio derivation of model energy density functionals

International Nuclear Information System (INIS)

Dobaczewski, Jacek

2016-01-01

I propose a simple and manageable method that allows for deriving coupling constants of model energy density functionals (EDFs) directly from ab initio calculations performed for finite fermion systems. A proof-of-principle application allows for linking properties of finite nuclei, determined by using the nuclear nonlocal Gogny functional, to the coupling constants of the quasilocal Skyrme functional. The method does not rely on properties of infinite fermion systems but on the ab initio calculations in finite systems. It also allows for quantifying merits of different model EDFs in describing the ab initio results. (letter)

BioModels: Content, Features, Functionality, and Use

Science.gov (United States)

Juty, N; Ali, R; Glont, M; Keating, S; Rodriguez, N; Swat, MJ; Wimalaratne, SM; Hermjakob, H; Le Novère, N; Laibe, C; Chelliah, V

2015-01-01

BioModels is a reference repository hosting mathematical models that describe the dynamic interactions of biological components at various scales. The resource provides access to over 1,200 models described in literature and over 140,000 models automatically generated from pathway resources. Most model components are cross-linked with external resources to facilitate interoperability. A large proportion of models are manually curated to ensure reproducibility of simulation results. This tutorial presents BioModels' content, features, functionality, and usage. PMID:26225232

Deep inelastic structure functions in the chiral bag model

International Nuclear Information System (INIS)

Sanjose, V.; Vento, V.; Centro Mixto CSIC/Valencia Univ., Valencia

1989-01-01

We calculate the structure functions for deep inelastic scattering on baryons in the cavity approximation to the chiral bag model. The behavior of these structure functions is analyzed in the Bjorken limit. We conclude that scaling is satisfied, but not Regge behavior. A trivial extension as a parton model can be achieved by introducing the structure function for the pion in a convolution picture. In this extended version of the model not only scaling but also Regge behavior is satisfied. Conclusions are drawn from the comparison of our results with experimental data. (orig.)

Deep inelastic structure functions in the chiral bag model

Energy Technology Data Exchange (ETDEWEB)

Sanjose, V. (Valencia Univ. (Spain). Dept. de Didactica de las Ciencias Experimentales); Vento, V. (Valencia Univ. (Spain). Dept. de Fisica Teorica; Centro Mixto CSIC/Valencia Univ., Valencia (Spain). Inst. de Fisica Corpuscular)

1989-10-02

We calculate the structure functions for deep inelastic scattering on baryons in the cavity approximation to the chiral bag model. The behavior of these structure functions is analyzed in the Bjorken limit. We conclude that scaling is satisfied, but not Regge behavior. A trivial extension as a parton model can be achieved by introducing the structure function for the pion in a convolution picture. In this extended version of the model not only scaling but also Regge behavior is satisfied. Conclusions are drawn from the comparison of our results with experimental data. (orig.).

Diet models with linear goal programming: impact of achievement functions.

Science.gov (United States)

Gerdessen, J C; de Vries, J H M

2015-11-01

Diet models based on goal programming (GP) are valuable tools in designing diets that comply with nutritional, palatability and cost constraints. Results derived from GP models are usually very sensitive to the type of achievement function that is chosen.This paper aims to provide a methodological insight into several achievement functions. It describes the extended GP (EGP) achievement function, which enables the decision maker to use either a MinSum achievement function (which minimizes the sum of the unwanted deviations) or a MinMax achievement function (which minimizes the largest unwanted deviation), or a compromise between both. An additional advantage of EGP models is that from one set of data and weights multiple solutions can be obtained. We use small numerical examples to illustrate the 'mechanics' of achievement functions. Then, the EGP achievement function is demonstrated on a diet problem with 144 foods, 19 nutrients and several types of palatability constraints, in which the nutritional constraints are modeled with fuzzy sets. Choice of achievement function affects the results of diet models. MinSum achievement functions can give rise to solutions that are sensitive to weight changes, and that pile all unwanted deviations on a limited number of nutritional constraints. MinMax achievement functions spread the unwanted deviations as evenly as possible, but may create many (small) deviations. EGP comprises both types of achievement functions, as well as compromises between them. It can thus, from one data set, find a range of solutions with various properties.

Global sensitivity analysis of computer models with functional inputs

International Nuclear Information System (INIS)

Iooss, Bertrand; Ribatet, Mathieu

2009-01-01

Global sensitivity analysis is used to quantify the influence of uncertain model inputs on the response variability of a numerical model. The common quantitative methods are appropriate with computer codes having scalar model inputs. This paper aims at illustrating different variance-based sensitivity analysis techniques, based on the so-called Sobol's indices, when some model inputs are functional, such as stochastic processes or random spatial fields. In this work, we focus on large cpu time computer codes which need a preliminary metamodeling step before performing the sensitivity analysis. We propose the use of the joint modeling approach, i.e., modeling simultaneously the mean and the dispersion of the code outputs using two interlinked generalized linear models (GLMs) or generalized additive models (GAMs). The 'mean model' allows to estimate the sensitivity indices of each scalar model inputs, while the 'dispersion model' allows to derive the total sensitivity index of the functional model inputs. The proposed approach is compared to some classical sensitivity analysis methodologies on an analytical function. Lastly, the new methodology is applied to an industrial computer code that simulates the nuclear fuel irradiation.

Reduced Rank Mixed Effects Models for Spatially Correlated Hierarchical Functional Data

KAUST Repository

Zhou, Lan

2010-03-01

Hierarchical functional data are widely seen in complex studies where sub-units are nested within units, which in turn are nested within treatment groups. We propose a general framework of functional mixed effects model for such data: within unit and within sub-unit variations are modeled through two separate sets of principal components; the sub-unit level functions are allowed to be correlated. Penalized splines are used to model both the mean functions and the principal components functions, where roughness penalties are used to regularize the spline fit. An EM algorithm is developed to fit the model, while the specific covariance structure of the model is utilized for computational efficiency to avoid storage and inversion of large matrices. Our dimension reduction with principal components provides an effective solution to the difficult tasks of modeling the covariance kernel of a random function and modeling the correlation between functions. The proposed methodology is illustrated using simulations and an empirical data set from a colon carcinogenesis study. Supplemental materials are available online.

Statistical Modelling of Resonant Cross Section Structure in URR, Model of the Characteristic Function

International Nuclear Information System (INIS)

Koyumdjieva, N.

2006-01-01

A statistical model for the resonant cross section structure in the Unresolved Resonance Region has been developed in the framework of the R-matrix formalism in Reich Moore approach with effective accounting of the resonance parameters fluctuations. The model uses only the average resonance parameters and can be effectively applied for analyses of cross sections functional, averaged over many resonances. Those are cross section moments, transmission and self-indication functions measured through thick sample. In this statistical model the resonant cross sections structure is accepted to be periodic and the R-matrix is a function of ε=E/D with period 0≤ε≤N; R nc (ε)=π/2√(S n *S c )1/NΣ(i=1,N)(β in *β ic *ctg[π(ε i - = ε-iS i )/N]; Here S n ,S c ,S i is respectively neutron strength function, strength function for fission or inelastic channel and strength function for radiative capture, N is the number of resonances (ε i ,β i ) that obey the statistic of Porter-Thomas and Wigner's one. The simple case of this statistical model concerns the resonant cross section structure for non-fissile nuclei under the threshold for inelastic scattering - the model of the characteristic function with HARFOR program. In the above model some improvements of calculation of the phases and logarithmic derivatives of neutron channels have been done. In the parameterization we use the free parameter R l ∞ , which accounts the influence of long-distant resonances. The above scheme for statistical modelling of the resonant cross section structure has been applied for evaluation of experimental data for total, capture and inelastic cross sections for 232 Th in the URR (4-150) keV and also the transmission and self-indication functions in (4-175) keV. The set of evaluated average resonance parameters have been obtained. The evaluated average resonance parameters in the URR are consistent with those in the Resolved Resonance Region (CRP for Th-U cycle, Vienna, 2006

Driver steering model for closed-loop steering function analysis

Science.gov (United States)

Bolia, Pratiksh; Weiskircher, Thomas; Müller, Steffen

2014-05-01

In this paper, a two level preview driver steering control model for the use in numerical vehicle dynamics simulation is introduced. The proposed model is composed of cascaded control loops: The outer loop is the path following layer based on potential field framework. The inner loop tries to capture the driver's physical behaviour. The proposed driver model allows easy implementation of different driving situations to simulate a wide range of different driver types, moods and vehicle types. The expediency of the proposed driver model is shown with the help of developed driver steering assist (DSA) function integrated with a conventional series production (Electric Power steering System with rack assist servo unit) system. With the help of the DSA assist function, the driver is prevented from over saturating the front tyre forces and loss of stability and controllability during cornering. The simulation results show different driver reactions caused by the change in the parameters or properties of the proposed driver model if the DSA assist function is activated. Thus, the proposed driver model is useful for the advanced driver steering and vehicle stability assist function evaluation in the early stage of vehicle dynamics handling and stability evaluation.

Distinguishing Differential Testlet Functioning from Differential Bundle Functioning Using the Multilevel Measurement Model

Science.gov (United States)

Beretvas, S. Natasha; Walker, Cindy M.

2012-01-01

This study extends the multilevel measurement model to handle testlet-based dependencies. A flexible two-level testlet response model (the MMMT-2 model) for dichotomous items is introduced that permits assessment of differential testlet functioning (DTLF). A distinction is made between this study's conceptualization of DTLF and that of…

A general phenomenological model for work function

Science.gov (United States)

Brodie, I.; Chou, S. H.; Yuan, H.

2014-07-01

A general phenomenological model is presented for obtaining the zero Kelvin work function of any crystal facet of metals and semiconductors, both clean and covered with a monolayer of electropositive atoms. It utilizes the known physical structure of the crystal and the Fermi energy of the two-dimensional electron gas assumed to form on the surface. A key parameter is the number of electrons donated to the surface electron gas per surface lattice site or adsorbed atom, which is taken to be an integer. Initially this is found by trial and later justified by examining the state of the valence electrons of the relevant atoms. In the case of adsorbed monolayers of electropositive atoms a satisfactory justification could not always be found, particularly for cesium, but a trial value always predicted work functions close to the experimental values. The model can also predict the variation of work function with temperature for clean crystal facets. The model is applied to various crystal faces of tungsten, aluminium, silver, and select metal oxides, and most demonstrate good fits compared to available experimental values.

Functional results-oriented healthcare leadership: a novel leadership model.

Science.gov (United States)

Al-Touby, Salem Said

2012-03-01

This article modifies the traditional functional leadership model to accommodate contemporary needs in healthcare leadership based on two findings. First, the article argues that it is important that the ideal healthcare leadership emphasizes the outcomes of the patient care more than processes and structures used to deliver such care; and secondly, that the leadership must strive to attain effectiveness of their care provision and not merely targeting the attractive option of efficient operations. Based on these premises, the paper reviews the traditional Functional Leadership Model and the three elements that define the type of leadership an organization has namely, the tasks, the individuals, and the team. The article argues that concentrating on any one of these elements is not ideal and proposes adding a new element to the model to construct a novel Functional Result-Oriented healthcare leadership model. The recommended Functional-Results Oriented leadership model embosses the results element on top of the other three elements so that every effort on healthcare leadership is directed towards attaining excellent patient outcomes.

Mathematical Models of Cardiac Pacemaking Function

Directory of Open Access Journals (Sweden)

Pan eLi

2013-10-01

Full Text Available Over the past half century, there has been intense and fruitful interaction between experimental and computational investigations of cardiac function. This interaction has, for example, led to deep understanding of cardiac excitation-contraction coupling; how it works, as well as how it fails. However, many lines of inquiry remain unresolved, among them the initiation of each heartbeat. The sinoatrial node, a cluster of specialized pacemaking cells in the right atrium of the heart, spontaneously generates an electro-chemical wave that spreads through the atria and through the cardiac conduction system to the ventricles, initiating the contraction of cardiac muscle essential for pumping blood to the body. Despite the fundamental importance of this primary pacemaker, this process is still not fully understood, and ionic mechanisms underlying cardiac pacemaking function are currently under heated debate. Several mathematical models of sinoatrial node cell membrane electrophysiology have been constructed as based on different experimental data sets and hypotheses. As could be expected, these differing models offer diverse predictions about cardiac pacemaking activities. This paper aims to present the current state of debate over the origins of the pacemaking function of the sinoatrial node. Here, we will specifically review the state-of-the-art of cardiac pacemaker modeling, with a special emphasis on current discrepancies, limitations, and future challenges.

Hierarchical functional model for automobile development; Jidosha kaihatsu no tame no kaisogata kino model

Energy Technology Data Exchange (ETDEWEB)

Sumida, S [U-shin Ltd., Tokyo (Japan); Nagamatsu, M; Maruyama, K [Hokkaido Institute of Technology, Sapporo (Japan); Hiramatsu, S [Mazda Motor Corp., Hiroshima (Japan)

1997-10-01

A new approach on modeling is put forward in order to compose the virtual prototype which is indispensable for fully computer integrated concurrent development of automobile product. A basic concept of the hierarchical functional model is proposed as the concrete form of this new modeling technology. This model is used mainly for explaining and simulating functions and efficiencies of both the parts and the total product of automobile. All engineers who engage themselves in design and development of automobile can collaborate with one another using this model. Some application examples are shown, and usefulness of this model is demonstrated. 5 refs., 5 figs.

Apply Functional Modelling to Consequence Analysis in Supervision Systems

DEFF Research Database (Denmark)

Zhang, Xinxin; Lind, Morten; Gola, Giulio

2013-01-01

This paper will first present the purpose and goals of applying functional modelling approach to consequence analysis by adopting Multilevel Flow Modelling (MFM). MFM Models describe a complex system in multiple abstraction levels in both means-end dimension and whole-part dimension. It contains...... consequence analysis to practical or online applications in supervision systems. It will also suggest a multiagent solution as the integration architecture for developing tools to facilitate the utilization results of functional consequence analysis. Finally a prototype of the multiagent reasoning system...... causal relations between functions and goals. A rule base system can be developed to trace the causal relations and perform consequence propagations. This paper will illustrate how to use MFM for consequence reasoning by using rule base technology and describe the challenges for integrating functional...

Laboratory-based bidirectional reflectance distribution functions of radiometric tarps

International Nuclear Information System (INIS)

Georgiev, Georgi T.; Butler, James J.

2008-01-01

Laboratory-based bidirectional reflectance distribution functions (BRDFs) of radiometric tarp samples used in the vicarious calibration of Earth remote sensing satellite instruments are presented in this paper. The results illustrate the BRDF dependence on the orientation of the tarps' weft and warp threads. The study was performed using the GSFC scatterometer at incident zenith angles of 0 deg., 10 deg., and 30 deg.; scatter zenith angles from 0 deg. to 60 deg.; and scatter azimuth angles of 0 deg., 45 deg., 90 deg., 135 deg., and 180 deg.. The wavelengths were 485 nm, 550 nm, 633 nm, and 800 nm. The tarp's weft and warp dependence on BRDF is well defined at all measurement geometries and wavelengths. The BRDF difference can be as high as 8% at 0 deg. incident angle and 12% at 30 deg. incident angle. The fitted BRDF data show a very small discrepancy from the measured ones. New data on the forward and backscatter properties of radiometric tarps are reported. The backward scatter is well pronounced for the white samples. The black sample has well-pronounced forward scatter. The provided BRDF characterization of radiometric tarps is an excellent reference for anyone interested in using tarps for radiometric calibrations. The results are NIST traceable

Laboratory-based bidirectional reflectance distribution functions of radiometric tarps.

Science.gov (United States)

Georgiev, Georgi T; Butler, James J

2008-06-20

Laboratory-based bidirectional reflectance distribution functions (BRDFs) of radiometric tarp samples used in the vicarious calibration of Earth remote sensing satellite instruments are presented in this paper. The results illustrate the BRDF dependence on the orientation of the tarps' weft and warp threads. The study was performed using the GSFC scatterometer at incident zenith angles of 0 degrees, 10 degrees, and 30 degrees; scatter zenith angles from 0 degrees to 60 degrees; and scatter azimuth angles of 0 degrees, 45 degrees, 90 degrees, 135 degrees, and 180 degrees. The wavelengths were 485 nm, 550 nm, 633 nm, and 800 nm. The tarp's weft and warp dependence on BRDF is well defined at all measurement geometries and wavelengths. The BRDF difference can be as high as 8% at 0 degrees incident angle and 12% at 30 degrees incident angle. The fitted BRDF data show a very small discrepancy from the measured ones. New data on the forward and backscatter properties of radiometric tarps are reported. The backward scatter is well pronounced for the white samples. The black sample has well-pronounced forward scatter. The provided BRDF characterization of radiometric tarps is an excellent reference for anyone interested in using tarps for radiometric calibrations. The results are NIST traceable.

Function-centered modeling of engineering systems using the goal tree-success tree technique and functional primitives

International Nuclear Information System (INIS)

Modarres, Mohammad; Cheon, Se Woo

1999-01-01

Most of the complex systems are formed through some hierarchical evolution. Therefore, those systems can be best described through hierarchical frameworks. This paper describes some fundamental attributes of complex physical systems and several hierarchies such as functional, behavioral, goal/condition, and event hierarchies, then presents a function-centered approach to system modeling. Based on the function-centered concept, this paper describes the joint goal tree-success tree (GTST) and the master logic diagram (MLD) as a framework for developing models of complex physical systems. A function-based lexicon for classifying the most common elements of engineering systems for use in the GTST-MLD framework has been proposed. The classification is based on the physical conservation laws that govern the engineering systems. Functional descriptions based on conservation laws provide a simple and rich vocabulary for modeling complex engineering systems

Functional form diagnostics for Cox's proportional hazards model.

Science.gov (United States)

León, Larry F; Tsai, Chih-Ling

2004-03-01

We propose a new type of residual and an easily computed functional form test for the Cox proportional hazards model. The proposed test is a modification of the omnibus test for testing the overall fit of a parametric regression model, developed by Stute, González Manteiga, and Presedo Quindimil (1998, Journal of the American Statistical Association93, 141-149), and is based on what we call censoring consistent residuals. In addition, we develop residual plots that can be used to identify the correct functional forms of covariates. We compare our test with the functional form test of Lin, Wei, and Ying (1993, Biometrika80, 557-572) in a simulation study. The practical application of the proposed residuals and functional form test is illustrated using both a simulated data set and a real data set.

Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

KAUST Repository

Wong, Aloysius Tze

2015-06-09

Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

KAUST Repository

Wong, Aloysius Tze; Gehring, Christoph A; Irving, Helen R.

2015-01-01

Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

Modeling multivariate time series on manifolds with skew radial basis functions.

Science.gov (United States)

Jamshidi, Arta A; Kirby, Michael J

2011-01-01

We present an approach for constructing nonlinear empirical mappings from high-dimensional domains to multivariate ranges. We employ radial basis functions and skew radial basis functions for constructing a model using data that are potentially scattered or sparse. The algorithm progresses iteratively, adding a new function at each step to refine the model. The placement of the functions is driven by a statistical hypothesis test that accounts for correlation in the multivariate range variables. The test is applied on training and validation data and reveals nonstatistical or geometric structure when it fails. At each step, the added function is fit to data contained in a spatiotemporally defined local region to determine the parameters--in particular, the scale of the local model. The scale of the function is determined by the zero crossings of the autocorrelation function of the residuals. The model parameters and the number of basis functions are determined automatically from the given data, and there is no need to initialize any ad hoc parameters save for the selection of the skew radial basis functions. Compactly supported skew radial basis functions are employed to improve model accuracy, order, and convergence properties. The extension of the algorithm to higher-dimensional ranges produces reduced-order models by exploiting the existence of correlation in the range variable data. Structure is tested not just in a single time series but between all pairs of time series. We illustrate the new methodologies using several illustrative problems, including modeling data on manifolds and the prediction of chaotic time series.

Modelling the Impact of Soil Management on Soil Functions

Science.gov (United States)

Vogel, H. J.; Weller, U.; Rabot, E.; Stößel, B.; Lang, B.; Wiesmeier, M.; Urbanski, L.; Wollschläger, U.

2017-12-01

Due to an increasing soil loss and an increasing demand for food and energy there is an enormous pressure on soils as the central resource for agricultural production. Besides the importance of soils for biomass production there are other essential soil functions, i.e. filter and buffer for water, carbon sequestration, provision and recycling of nutrients, and habitat for biological activity. All these functions have a direct feed back to biogeochemical cycles and climate. To render agricultural production efficient and sustainable we need to develop model tools that are capable to predict quantitatively the impact of a multitude of management measures on these soil functions. These functions are considered as emergent properties produced by soils as complex systems. The major challenge is to handle the multitude of physical, chemical and biological processes interacting in a non-linear manner. A large number of validated models for specific soil processes are available. However, it is not possible to simulate soil functions by coupling all the relevant processes at the detailed (i.e. molecular) level where they are well understood. A new systems perspective is required to evaluate the ensemble of soil functions and their sensitivity to external forcing. Another challenge is that soils are spatially heterogeneous systems by nature. Soil processes are highly dependent on the local soil properties and, hence, any model to predict soil functions needs to account for the site-specific conditions. For upscaling towards regional scales the spatial distribution of functional soil types need to be taken into account. We propose a new systemic model approach based on a thorough analysis of the interactions between physical, chemical and biological processes considering their site-specific characteristics. It is demonstrated for the example of soil compaction and the recovery of soil structure, water capacity and carbon stocks as a result of plant growth and biological

Refined functional relations for the elliptic SOS model

Energy Technology Data Exchange (ETDEWEB)

Galleas, W., E-mail: w.galleas@uu.nl [ARC Centre of Excellence for the Mathematics and Statistics of Complex Systems, University of Melbourne, VIC 3010 (Australia)

2013-02-21

In this work we refine the method presented in Galleas (2012) [1] and obtain a novel kind of functional equation determining the partition function of the elliptic SOS model with domain wall boundaries. This functional relation arises from the dynamical Yang-Baxter relation and its solution is given in terms of multiple contour integrals.

Refined functional relations for the elliptic SOS model

International Nuclear Information System (INIS)

Galleas, W.

2013-01-01

In this work we refine the method presented in Galleas (2012) [1] and obtain a novel kind of functional equation determining the partition function of the elliptic SOS model with domain wall boundaries. This functional relation arises from the dynamical Yang–Baxter relation and its solution is given in terms of multiple contour integrals.

The 2015-16 El Niño - Birth, Evolution and Teleconnections from Scatterometer Observations of the Ocean Surface Winds

Science.gov (United States)

Hristova-Veleva, S. M.; Lee, T.; Stiles, B. W.; Rodriguez, E.; Turk, J.; Haddad, Z. S.

2016-12-01

The 2015-16 El Niño is one of the strongest events observed during the modern instrumentation period, rivaling the two big ones observed by satellites during 1982-83 and 1997-98. Yet, the precipitation anomalies differ from the expectations that were based on these two events. While El Niño events have a significant impact on the entire Earth System, they are most easily visible in measurements of sea surface temperature (SST), sea surface height (SSH) and ocean winds near the surface. In fact, the signature eastward-blowing anomalous surface winds in the Western and Central Tropical Pacific are the pre-cursor and the main driver of the El Nino events. Here we use observations from NASA's RapidScat, EUMETSAT's ASCAT and also from collocated ECMWF analysis to monitor the evolution of the anomalous winds associated with the 2015-16 El Niño. To detect the El Nino signal, we first compute monthly means of the wind speed, wind components and wind convergence. We then perform a low-pass filter to extract the components of the larger-scale circulation and compute the 2015-2016 anomalies with respect to the corresponding months of 2014-2015. We find fast-evolving wind anomalies and relate them to the evolution of the SST field as depicted in the observations-based OSTIA product. Furthermore, we investigate the relationship between the GPM-observed precipitation and the surface wind convergence observed by the scatterometers. El Niño is known to have basin to global scale teleconnections. In addition to the characterization of the changes in the tropical Pacific, we will also describe the associated changes in the North and South Pacific. In particular, a strong anticyclonic anomaly is observed in the north-eastern Pacific. This anomalous circulation is likely associated with the subsidence (divergent) region of a stronger-than-normal Hadley cell, leading to modification of the midlatitude storm tracks and the related precipitation anomalies. Furthermore, these

Bifurcations in a discrete time model composed of Beverton-Holt function and Ricker function.

Science.gov (United States)

Shang, Jin; Li, Bingtuan; Barnard, Michael R

2015-05-01

We provide rigorous analysis for a discrete-time model composed of the Ricker function and Beverton-Holt function. This model was proposed by Lewis and Li [Bull. Math. Biol. 74 (2012) 2383-2402] in the study of a population in which reproduction occurs at a discrete instant of time whereas death and competition take place continuously during the season. We show analytically that there exists a period-doubling bifurcation curve in the model. The bifurcation curve divides the parameter space into the region of stability and the region of instability. We demonstrate through numerical bifurcation diagrams that the regions of periodic cycles are intermixed with the regions of chaos. We also study the global stability of the model. Copyright © 2015 Elsevier Inc. All rights reserved.

Scatterometry measurement of nested lines, dual space, and rectangular contact CD on phase-shift masks

Science.gov (United States)

Lee, Kyung M.; Yedur, Sanjay; Henrichs, Sven; Tavassoli, Malahat; Baik, Kiho

2007-03-01

Evaluation of lithography process or stepper involves very large quantity of CD measurements and measurement time. In this paper, we report on a application of Scatterometry based metrology for evaluation of binary photomask lithography. Measurements were made on mask level with ODP scatterometer then on wafer with CD-SEM. 4 to 1 scaling from mask to wafer means 60nm line on wafer translates to 240nm on mask, easily measurable on ODP. Calculation of scatterometer profile information was performed by a in-situ library-based analysis (5sec/site). We characterized the CD uniformity, linearity, and metal film thickness uniformity. Results show that linearity measured from fixed-pitch, varying line/space ratio targets show good correlation to top-down CD-SEM with R2 of more than 0.99. ODP-SEM correlation results for variable pitch shows that careful examination of scatterometer profile results in order to obtain better correlation to CD SEM, since both tools react differently to the target profile variation. ODP results show that global CD distribution is clearly measurable with less outliers compared to CD SEM data. This is thought to be due to 'averaging' effect of scatterometer. The data show that Scatterometry provides a nondestructive and faster mean of characterizing lithography stepper performanceprofiles. APSM 1st level (before Cr removal) 'dual-space' CDs and EPSM rectangular contacts were also measured with and results demonstrates that Scatterometer is capable of measuring these targets with reasonable correlation to SEM.

Correlation functions of heisenberg-mattis model in one dimension

International Nuclear Information System (INIS)

Azeeem, W.

1991-01-01

The technique of real-space renormalization to the dynamics of Heisenberg-Mattis model, which represents a random magnetic system with competing ferromagnetic and antiferromagnetic interactions has been applied. The renormalization technique, which has been in use for calculating density of states, is extended to calculate dynamical response function from momentum energy dependent Green's functions. Our numerical results on density of states and structure function of one-dimensional Heisenberg-Mattis model come out to be in good agreement with computer simulation results. The numerical scheme worked out in this thesis has the advantage that it can also provide a complete map of momentum and energy dependence of the structure function. (author)

Generalized Functional Linear Models With Semiparametric Single-Index Interactions

KAUST Repository

Li, Yehua

2010-06-01

We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are pre-determined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance, due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical data set, where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.

Generalized Functional Linear Models With Semiparametric Single-Index Interactions

KAUST Repository

Li, Yehua; Wang, Naisyin; Carroll, Raymond J.

2010-01-01

We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are pre-determined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance, due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical data set, where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.

Optimal hemodynamic response model for functional near-infrared spectroscopy.

Science.gov (United States)

Kamran, Muhammad A; Jeong, Myung Yung; Mannan, Malik M N

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive brain imaging technique and measures brain activities by means of near-infrared light of 650-950 nm wavelengths. The cortical hemodynamic response (HR) differs in attributes at different brain regions and on repetition of trials, even if the experimental paradigm is kept exactly the same. Therefore, an HR model that can estimate such variations in the response is the objective of this research. The canonical hemodynamic response function (cHRF) is modeled by two Gamma functions with six unknown parameters (four of them to model the shape and other two to scale and baseline respectively). The HRF model is supposed to be a linear combination of HRF, baseline, and physiological noises (amplitudes and frequencies of physiological noises are supposed to be unknown). An objective function is developed as a square of the residuals with constraints on 12 free parameters. The formulated problem is solved by using an iterative optimization algorithm to estimate the unknown parameters in the model. Inter-subject variations in HRF and physiological noises have been estimated for better cortical functional maps. The accuracy of the algorithm has been verified using 10 real and 15 simulated data sets. Ten healthy subjects participated in the experiment and their HRF for finger-tapping tasks have been estimated and analyzed. The statistical significance of the estimated activity strength parameters has been verified by employing statistical analysis (i.e., t-value > t critical and p-value < 0.05).

Finite-element modeling of the human neurocranium under functional anatomical aspects.

Science.gov (United States)

Mall, G; Hubig, M; Koebke, J; Steinbuch, R

1997-08-01

Due to its functional significance the human skull plays an important role in biomechanical research. The present work describes a new Finite-Element model of the human neurocranium. The dry skull of a middle-aged woman served as a pattern. The model was developed using only the preprocessor (Mentat) of a commercial FE-system (Marc). Unlike that of other FE models of the human skull mentioned in the literature, the geometry in this model was designed according to functional anatomical findings. Functionally important morphological structures representing loci minoris resistentiae, especially the foramina and fissures of the skull base, were included in the model. The results of two linear static loadcase analyses in the region of the skull base underline the importance of modeling from the functional anatomical point of view.

Parisi function for two spin glass models

International Nuclear Information System (INIS)

Sibani, P.; Hertz, J.A.

1984-01-01

The probability distribution function P(q) for the overlap of pairs of metastable states and the associated Parisi order function q(x) are calculated exactly at zero temperature for two simple models. The first is a chain in which each spin interacts randomly with the sum of all the spins between it and one end of the chain; the second is an infinite-range limit of a spin glass version of Dyson's hierarchical model. Both have nontrivial overlap distributions: In the first case the problem reduces to a variable-step-length random walk problem, leading to q(x)=sin(πx). In the second model P(q) can be calculated by a simple recursion relation which generates devil's staircase structure in q(x). If the fraction p of antiferromagnetic bonds is less than 1/√2, the staircase is complete and the fractal dimensionality of the complement of the domain where q(x) is flat is log 2/log (1/p 2 ). In both models the space of metastable states can be described in terms of Cayley trees, which however have a different physical interpretation than in the S.K. model. (orig.)

A functional-dynamic reflection on participatory processes in modeling projects.

Science.gov (United States)

Seidl, Roman

2015-12-01

The participation of nonscientists in modeling projects/studies is increasingly employed to fulfill different functions. However, it is not well investigated if and how explicitly these functions and the dynamics of a participatory process are reflected by modeling projects in particular. In this review study, I explore participatory modeling projects from a functional-dynamic process perspective. The main differences among projects relate to the functions of participation-most often, more than one per project can be identified, along with the degree of explicit reflection (i.e., awareness and anticipation) on the dynamic process perspective. Moreover, two main approaches are revealed: participatory modeling covering diverse approaches and companion modeling. It becomes apparent that the degree of reflection on the participatory process itself is not always explicit and perfectly visible in the descriptions of the modeling projects. Thus, the use of common protocols or templates is discussed to facilitate project planning, as well as the publication of project results. A generic template may help, not in providing details of a project or model development, but in explicitly reflecting on the participatory process. It can serve to systematize the particular project's approach to stakeholder collaboration, and thus quality management.

A Multivariate Approach to Functional Neuro Modeling

DEFF Research Database (Denmark)

Mørch, Niels J.S.

1998-01-01

by the application of linear and more flexible, nonlinear microscopic regression models to a real-world dataset. The dependency of model performance, as quantified by generalization error, on model flexibility and training set size is demonstrated, leading to the important realization that no uniformly optimal model......, provides the basis for a generalization theoretical framework relating model performance to model complexity and dataset size. Briefly summarized the major topics discussed in the thesis include: - An introduction of the representation of functional datasets by pairs of neuronal activity patterns...... exists. - Model visualization and interpretation techniques. The simplicity of this task for linear models contrasts the difficulties involved when dealing with nonlinear models. Finally, a visualization technique for nonlinear models is proposed. A single observation emerges from the thesis...

Collins fragmentation function for pions and kaons in a spectator model

Energy Technology Data Exchange (ETDEWEB)

Bacchetta, A. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Gamberg, L.P. [Penn State Univ., Berks, PA (United States). Dept. of Physics; Goldstein, G.R. [Tufts Univ., Medford, MA (United States). Dept. of Physics and Astronomy; Mukherjee, A. [Indian Institute of Technology Bombay, Mumbai (India). Physics Dept.

2007-07-15

We calculate the Collins fragmentation function in the framework of a spectator model with pseudoscalar pion-quark coupling and a Gaussian form factor at the vertex. We determine the model parameters by fitting the unpolarized fragmentation function for pions and kaons. We show that the Collins function for the pions in this model is in reasonable agreement with recent parametrizations obtained by fits of the available data. In addition, we compute for the first time the Collins function for the kaons. (orig.)

Function-based payment model for inpatient medical rehabilitation: an evaluation.

Science.gov (United States)

Sutton, J P; DeJong, G; Wilkerson, D

1996-07-01

To describe the components of a function-based prospective payment model for inpatient medical rehabilitation that parallels diagnosis-related groups (DRGs), to evaluate this model in relation to stakeholder objectives, and to detail the components of a quality of care incentive program that, when combined with this payment model, creates an incentive for provides to maximize functional outcomes. This article describes a conceptual model, involving no data collection or data synthesis. The basic payment model described parallels DRGs. Information on the potential impact of this model on medical rehabilitation is gleaned from the literature evaluating the impact of DRGs. The conceptual model described is evaluated against the results of a Delphi Survey of rehabilitation providers, consumers, policymakers, and researchers previously conducted by members of the research team. The major shortcoming of a function-based prospective payment model for inpatient medical rehabilitation is that it contains no inherent incentive to maximize functional outcomes. Linkage of reimbursement to outcomes, however, by withholding a fixed proportion of the standard FRG payment amount, placing that amount in a "quality of care" pool, and distributing that pool annually among providers whose predesignated, facility-level, case-mix-adjusted outcomes are attained, may be one strategy for maximizing outcome goals.

Data Acquisition for Quality Loss Function Modelling

DEFF Research Database (Denmark)

Pedersen, Søren Nygaard; Howard, Thomas J.

2016-01-01

Quality loss functions can be a valuable tool when assessing the impact of variation on product quality. Typically, the input for the quality loss function would be a measure of the varying product performance and the output would be a measure of quality. While the unit of the input is given by t...... by the product function in focus, the quality output can be measured and quantified in a number of ways. In this article a structured approach for acquiring stakeholder satisfaction data for use in quality loss function modelling is introduced.......Quality loss functions can be a valuable tool when assessing the impact of variation on product quality. Typically, the input for the quality loss function would be a measure of the varying product performance and the output would be a measure of quality. While the unit of the input is given...

Hypnosis as a model of functional neurologic disorders.

Science.gov (United States)

Deeley, Q

2016-01-01

In the 19th century it was recognized that neurologic symptoms could be caused by "morbid ideation" as well as organic lesions. The subsequent observation that hysteric (now called "functional") symptoms could be produced and removed by hypnotic suggestion led Charcot to hypothesize that suggestion mediated the effects of ideas on hysteric symptoms through as yet unknown effects on brain activity. The advent of neuroimaging 100 years later revealed strikingly similar neural correlates in experiments matching functional symptoms with clinical analogs created by suggestion. Integrative models of suggested and functional symptoms regard these alterations in brain function as the endpoint of a broader set of changes in information processing due to suggestion. These accounts consider that suggestions alter experience by mobilizing representations from memory systems, and altering causal attributions, during preconscious processing which alters the content of what is provided to our highly edited subjective version of the world. Hypnosis as a model for functional symptoms draws attention to how radical alterations in experience and behavior can conform to the content of mental representations through effects on cognition and brain function. Experimental study of functional symptoms and their suggested counterparts in hypnosis reveals the distinct and shared processes through which this can occur. © 2016 Elsevier B.V. All rights reserved.

A median filter approach for correcting errors in a vector field

Science.gov (United States)

Schultz, H.

1985-01-01

Techniques are presented for detecting and correcting errors in a vector field. These methods employ median filters which are frequently used in image processing to enhance edges and remove noise. A detailed example is given for wind field maps produced by a spaceborne scatterometer. The error detection and replacement algorithm was tested with simulation data from the NASA Scatterometer (NSCAT) project.

Medicare capitation model, functional status, and multiple comorbidities: model accuracy

Science.gov (United States)

Noyes, Katia; Liu, Hangsheng; Temkin-Greener, Helena

2012-01-01

Objective This study examined financial implications of CMS-Hierarchical Condition Categories (HCC) risk-adjustment model on Medicare payments for individuals with comorbid chronic conditions. Study Design The study used 1992-2000 data from the Medicare Current Beneficiary Survey and corresponding Medicare claims. The pairs of comorbidities were formed based on the prior evidence about possible synergy between these conditions and activities of daily living (ADL) deficiencies and included heart disease and cancer, lung disease and cancer, stroke and hypertension, stroke and arthritis, congestive heart failure (CHF) and osteoporosis, diabetes and coronary artery disease, CHF and dementia. Methods For each beneficiary, we calculated the actual Medicare cost ratio as the ratio of the individual’s annualized costs to the mean annual Medicare cost of all people in the study. The actual Medicare cost ratios, by ADLs, were compared to the HCC ratios under the CMS-HCC payment model. Using multivariate regression models, we tested whether having the identified pairs of comorbidities affects the accuracy of CMS-HCC model predictions. Results The CMS-HCC model underpredicted Medicare capitation payments for patients with hypertension, lung disease, congestive heart failure and dementia. The difference between the actual costs and predicted payments was partially explained by beneficiary functional status and less than optimal adjustment for these chronic conditions. Conclusions Information about beneficiary functional status should be incorporated in reimbursement models since underpaying providers for caring for population with multiple comorbidities may provide severe disincentives for managed care plans to enroll such individuals and to appropriately manage their complex and costly conditions. PMID:18837646

Monopoly models with time-varying demand function

Science.gov (United States)

Cavalli, Fausto; Naimzada, Ahmad

2018-05-01

We study a family of monopoly models for markets characterized by time-varying demand functions, in which a boundedly rational agent chooses output levels on the basis of a gradient adjustment mechanism. After presenting the model for a generic framework, we analytically study the case of cyclically alternating demand functions. We show that both the perturbation size and the agent's reactivity to profitability variation signals can have counterintuitive roles on the resulting period-2 cycles and on their stability. In particular, increasing the perturbation size can have both a destabilizing and a stabilizing effect on the resulting dynamics. Moreover, in contrast with the case of time-constant demand functions, the agent's reactivity is not just destabilizing, but can improve stability, too. This means that a less cautious behavior can provide better performance, both with respect to stability and to achieved profits. We show that, even if the decision mechanism is very simple and is not able to always provide the optimal production decisions, achieved profits are very close to those optimal. Finally, we show that in agreement with the existing empirical literature, the price series obtained simulating the proposed model exhibit a significant deviation from normality and large volatility, in particular when underlying deterministic dynamics become unstable and complex.

Longitudinal mixed-effects models for latent cognitive function

NARCIS (Netherlands)

van den Hout, Ardo; Fox, Gerardus J.A.; Muniz-Terrera, Graciela

2015-01-01

A mixed-effects regression model with a bent-cable change-point predictor is formulated to describe potential decline of cognitive function over time in the older population. For the individual trajectories, cognitive function is considered to be a latent variable measured through an item response

Weighted functional linear regression models for gene-based association analysis.

Science.gov (United States)

Belonogova, Nadezhda M; Svishcheva, Gulnara R; Wilson, James F; Campbell, Harry; Axenovich, Tatiana I

2018-01-01

Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced to give the advantage to more informative components. Allele-specific weights have been introduced to collapsing and kernel-based approaches to gene-based association analysis. Here we have for the first time introduced weights to functional linear regression models adapted for both independent and family samples. Using data simulated on the basis of GAW17 genotypes and weights defined by allele frequencies via the beta distribution, we demonstrated that type I errors correspond to declared values and that increasing the weights of causal variants allows the power of functional linear models to be increased. We applied the new method to real data on blood pressure from the ORCADES sample. Five of the six known genes with P models. Moreover, we found an association between diastolic blood pressure and the VMP1 gene (P = 8.18×10-6), when we used a weighted functional model. For this gene, the unweighted functional and weighted kernel-based models had P = 0.004 and 0.006, respectively. The new method has been implemented in the program package FREGAT, which is freely available at https://cran.r-project.org/web/packages/FREGAT/index.html.

Resolving Microzooplankton Functional Groups In A Size-Structured Planktonic Model

Science.gov (United States)

Taniguchi, D.; Dutkiewicz, S.; Follows, M. J.; Jahn, O.; Menden-Deuer, S.

2016-02-01

Microzooplankton are important marine grazers, often consuming a large fraction of primary productivity. They consist of a great diversity of organisms with different behaviors, characteristics, and rates. This functional diversity, and its consequences, are not currently reflected in large-scale ocean ecological simulations. How should these organisms be represented, and what are the implications for their biogeography? We develop a size-structured, trait-based model to characterize a diversity of microzooplankton functional groups. We compile and examine size-based laboratory data on the traits, revealing some patterns with size and functional group that we interpret with mechanistic theory. Fitting the model to the data provides parameterizations of key rates and properties, which we employ in a numerical ocean model. The diversity of grazing preference, rates, and trophic strategies enables the coexistence of different functional groups of micro-grazers under various environmental conditions, and the model produces testable predictions of the biogeography.

Production functions for climate policy modeling. An empirical analysis

International Nuclear Information System (INIS)

Van der Werf, Edwin

2008-01-01

Quantitative models for climate policy modeling differ in the production structure used and in the sizes of the elasticities of substitution. The empirical foundation for both is generally lacking. This paper estimates the parameters of 2-level CES production functions with capital, labour and energy as inputs, and is the first to systematically compare all nesting structures. Using industry-level data from 12 OECD countries, we find that the nesting structure where capital and labour are combined first, fits the data best, but for most countries and industries we cannot reject that all three inputs can be put into one single nest. These two nesting structures are used by most climate models. However, while several climate policy models use a Cobb-Douglas function for (part of the) production function, we reject elasticities equal to one, in favour of considerably smaller values. Finally we find evidence for factor-specific technological change. With lower elasticities and with factor-specific technological change, some climate policy models may find a bigger effect of endogenous technological change on mitigating the costs of climate policy. (author)

Descriptions and models of safety functions - a prestudy

International Nuclear Information System (INIS)

Harms-Ringdahl, L.

1999-09-01

A study has been made with the focus on different theories and applications concerning 'safety functions' and 'barriers'. In this report, a safety function is defined as a technical or organisational function with the aim to reduce probability and/or consequences associated with a hazard. The study contains a limited review of practice and theories related to safety, with a focus on applications from nuclear and industrial safety. The study is based on a literature review and interviews. A summary has been made of definitions and terminology, which shows a large variation. E.g. 'barrier' can have a precise physical and technical meaning, or it can include human, technical and organisational elements. Only a few theoretical models describing safety functions have been found. One section of the report summarises problems related to safety issues and procedures. They concern errors in procedure design and user compliance. A proposal for describing and structuring safety functions has been made. Dimensions in a description could be degree of abstraction, systems level, the different parts of the function, etc. A model for safety functions has been proposed, which includes the division of a safety function in a number connected 'safety function elements'. One conclusion is that there is a potential for improving theories and tools for safety work and procedures. Safety function could be a useful concept in such a development, and advantages and disadvantages with this is discussed. If further work should be done, it is recommended that this is made as a combination of theoretical analysis and case studies

Assimilation of remote sensing observations into a continuous distributed hydrological model: impacts on the hydrologic cycle

Science.gov (United States)

Laiolo, Paola; Gabellani, Simone; Campo, Lorenzo; Cenci, Luca; Silvestro, Francesco; Delogu, Fabio; Boni, Giorgio; Rudari, Roberto

2015-04-01

The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce in-situ data. This work investigates the impact of the assimilation of different remote sensing products on the hydrological cycle by using a continuous physically based distributed hydrological model. Three soil moisture products derived by ASCAT (Advanced SCATterometer) are used to update the model state variables. The satellite-derived products are assimilated into the hydrological model using different assimilation techniques: a simple nudging and the Ensemble Kalman Filter. Moreover two assimilation strategies are evaluated to assess the impact of assimilating the satellite products at model spatial resolution or at the satellite scale. The experiments are carried out for three Italian catchments on multi year period. The benefits on the model predictions of discharge, LST, evapotranspiration and soil moisture dynamics are tested and discussed.

String beta function equations from c=1 matrix model

CERN Document Server

Dhar, A; Wadia, S R; Dhar, Avinash; Mandal, Gautam; Wadia, Spenta R

1995-01-01

We derive the \\sigma-model tachyon \\beta-function equation of 2-dimensional string theory, in the background of flat space and linear dilaton, working entirely within the c=1 matrix model. The tachyon \\beta-function equation is satisfied by a \\underbar{nonlocal} and \\underbar{nonlinear} combination of the (massless) scalar field of the matrix model. We discuss the possibility of describing the `discrete states' as well as other possible gravitational and higher tensor backgrounds of 2-dimensional string theory within the c=1 matrix model. We also comment on the realization of the W-infinity symmetry of the matrix model in the string theory. The present work reinforces the viewpoint that a nonlocal (and nonlinear) transform is required to extract the space-time physics of 2-dimensional string theory from the c=1 matrix model.

Sea wind parameters retrieval using Y-configured Doppler navigation system data. Performance and accuracy

Science.gov (United States)

Khachaturian, A. B.; Nekrasov, A. V.; Bogachev, M. I.

2018-05-01

The authors report the results of the computer simulations of the performance and accuracy of the sea wind speed and direction retrieval. The analyzed measurements over the sea surface are made by the airborne microwave Doppler navigation system (DNS) with three Y-configured beams operated as a scatterometer enhancing its functionality. Single- and double-stage wind measurement procedures are proposed and recommendations for their implementation are described.

 Functional Results-Oriented Healthcare Leadership: A Novel Leadership Model

Directory of Open Access Journals (Sweden)

Salem Said Al-Touby

2012-03-01

Full Text Available  This article modifies the traditional functional leadership model to accommodate contemporary needs in healthcare leadership based on two findings. First, the article argues that it is important that the ideal healthcare leadership emphasizes the outcomes of the patient care more than processes and structures used to deliver such care; and secondly, that the leadership must strive to attain effectiveness of their care provision and not merely targeting the attractive option of efficient operations. Based on these premises, the paper reviews the traditional Functional Leadership Model and the three elements that define the type of leadership an organization has namely, the tasks, the individuals, and the team. The article argues that concentrating on any one of these elements is not ideal and proposes adding a new element to the model to construct a novel Functional Result-Oriented healthcare leadership model. The recommended Functional-Results Oriented leadership model embosses the results element on top of the other three elements so that every effort on healthcare leadership is directed towards attaining excellent patient outcomes.

A unified wall function for compressible turbulence modelling

Science.gov (United States)

Ong, K. C.; Chan, A.

2018-05-01

Turbulence modelling near the wall often requires a high mesh density clustered around the wall and the first cells adjacent to the wall to be placed in the viscous sublayer. As a result, the numerical stability is constrained by the smallest cell size and hence requires high computational overhead. In the present study, a unified wall function is developed which is valid for viscous sublayer, buffer sublayer and inertial sublayer, as well as including effects of compressibility, heat transfer and pressure gradient. The resulting wall function applies to compressible turbulence modelling for both isothermal and adiabatic wall boundary conditions with the non-zero pressure gradient. Two simple wall function algorithms are implemented for practical computation of isothermal and adiabatic wall boundary conditions. The numerical results show that the wall function evaluates the wall shear stress and turbulent quantities of wall adjacent cells at wide range of non-dimensional wall distance and alleviate the number and size of cells required.

Bread dough rheology: Computing with a damage function model

Science.gov (United States)

Tanner, Roger I.; Qi, Fuzhong; Dai, Shaocong

2015-01-01

We describe an improved damage function model for bread dough rheology. The model has relatively few parameters, all of which can easily be found from simple experiments. Small deformations in the linear region are described by a gel-like power-law memory function. A set of large non-reversing deformations - stress relaxation after a step of shear, steady shearing and elongation beginning from rest, and biaxial stretching, is used to test the model. With the introduction of a revised strain measure which includes a Mooney-Rivlin term, all of these motions can be well described by the damage function described in previous papers. For reversing step strains, larger amplitude oscillatory shearing and recoil reasonable predictions have been found. The numerical methods used are discussed and we give some examples.

Structural equation modeling of motor impairment, gross motor function, and the functional outcome in children with cerebral palsy.

Science.gov (United States)

Park, Eun-Young; Kim, Won-Ho

2013-05-01

Physical therapy intervention for children with cerebral palsy (CP) is focused on reducing neurological impairments, improving strength, and preventing the development of secondary impairments in order to improve functional outcomes. However, relationship between motor impairments and functional outcome has not been proved definitely. This study confirmed the construct of motor impairment and performed structural equation modeling (SEM) between motor impairment, gross motor function, and functional outcomes of regarding activities of daily living in children with CP. 98 children (59 boys, 39 girls) with CP participated in this cross-sectional study. Mean age was 11 y 5 mo (SD 1 y 9 mo). The Manual Muscle Test (MMT), the Modified Ashworth Scale (MAS), range of motion (ROM) measurement, and the selective motor control (SMC) scale were used to assess motor impairments. Gross motor function and functional outcomes were measured using the Gross Motor Function Measure (GMFM) and the Functional Skills domain of the Pediatric Evaluation of Disability Inventory (PEDI) respectively. Measurement of motor impairment was consisted of strength, spasticity, ROM, and SMC. The construct of motor impairment was confirmed though an examination of a measurement model. The proposed SEM model showed good fit indices. Motor impairment effected gross motor function (β=-.0869). Gross motor function and motor impairment affected functional outcomes directly (β=0.890) and indirectly (β=-0.773) respectively. We confirmed that the construct of motor impairment consist of strength, spasticity, ROM, and SMC and it was identified through measurement model analysis. Functional outcomes are best predicted by gross motor function and motor impairments have indirect effects on functional outcomes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Improved Wave-vessel Transfer Functions by Uncertainty Modelling

DEFF Research Database (Denmark)

Nielsen, Ulrik Dam; Fønss Bach, Kasper; Iseki, Toshio

2016-01-01

This paper deals with uncertainty modelling of wave-vessel transfer functions used to calculate or predict wave-induced responses of a ship in a seaway. Although transfer functions, in theory, can be calculated to exactly reflect the behaviour of the ship when exposed to waves, uncertainty in inp...

Comparison of TOPEX/Poseidon Sea Level and Linear Model Results forced by Various Wind Products for the Tropical Pacific

Science.gov (United States)

Hackert, Eric C.; Busalacchi, Antonio J.

1997-01-01

The goal of this paper is to compare TOPEX/Posaidon (T/P) sea level with sea level results from linear ocean model experiments forced by several different wind products for the tropical Pacific. During the period of this study (October 1992 - October 1995), available wind products include satellite winds from the ERS-1 scatterometer product of [HALP 97] and the passive microwave analysis of SSMI winds produced using the variational analysis method (VAM) of [ATLA 91]. In addition, atmospheric GCM winds from the NCEP reanalysis [KALN 96], ECMWF analysis [ECMW94], and the Goddard EOS-1 (GEOS-1) reanalysis experiment [SCHU 93] are available for comparison. The observed ship wind analysis of FSU [STRI 92] is also included in this study. The linear model of [CANE 84] is used as a transfer function to test the quality of each of these wind products for the tropical Pacific. The various wind products are judged by comparing the wind-forced model sea level results against the T/P sea level anomalies. Correlation and RMS difference maps show how well each wind product does in reproducing the T/P sea level signal. These results are summarized in a table showing area average correlations and RMS differences. The large-scale low-frequency temporal signal is reproduced by all of the wind products, However, significant differences exist in both amplitude and phase on regional scales. In general, the model results forced by satellite winds do a better job reproducing the T/P signal (i.e. have a higher average correlation and lower RMS difference) than the results forced by atmospheric model winds.

Functional Modelling for Fault Diagnosis and its application for NPP

DEFF Research Database (Denmark)

Lind, Morten; Zhang, Xinxin

2014-01-01

The paper presents functional modelling and its application for diagnosis in nuclear power plants.Functional modelling is defined and it is relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demon...... operating modes. The FBR example illustrates how the modeling development effort can be managed by proper strategies including decomposition and reuse....

Optimal hemodynamic response model for functional near-infrared spectroscopy

Directory of Open Access Journals (Sweden)

Muhammad Ahmad Kamran

2015-06-01

Full Text Available Functional near-infrared spectroscopy (fNIRS is an emerging non-invasive brain imaging technique and measures brain activities by means of near-infrared light of 650-950 nm wavelengths. The cortical hemodynamic response (HR differs in attributes at different brain regions and on repetition of trials, even if the experimental paradigm is kept exactly the same. Therefore, an HR model that can estimate such variations in the response is the objective of this research. The canonical hemodynamic response function (cHRF is modeled by using two Gamma functions with six unknown parameters. The HRF model is supposed to be linear combination of HRF, baseline and physiological noises (amplitudes and frequencies of physiological noises are supposed to be unknown. An objective function is developed as a square of the residuals with constraints on twelve free parameters. The formulated problem is solved by using an iterative optimization algorithm to estimate the unknown parameters in the model. Inter-subject variations in HRF and physiological noises have been estimated for better cortical functional maps. The accuracy of the algorithm has been verified using ten real and fifteen simulated data sets. Ten healthy subjects participated in the experiment and their HRF for finger-tapping tasks have been estimated and analyzed. The statistical significance of the estimated activity strength parameters has been verified by employing statistical analysis, i.e., (t-value >tcritical and p-value < 0.05.

Thresholding projection estimators in functional linear models

OpenAIRE

Cardot, Hervé; Johannes, Jan

2010-01-01

We consider the problem of estimating the regression function in functional linear regression models by proposing a new type of projection estimators which combine dimension reduction and thresholding. The introduction of a threshold rule allows to get consistency under broad assumptions as well as minimax rates of convergence under additional regularity hypotheses. We also consider the particular case of Sobolev spaces generated by the trigonometric basis which permits to get easily mean squ...

Functional Freedom: A Psychological Model of Freedom in Decision-Making.

Science.gov (United States)

Lau, Stephan; Hiemisch, Anette

2017-07-05

The freedom of a decision is not yet sufficiently described as a psychological variable. We present a model of functional decision freedom that aims to fill that role. The model conceptualizes functional freedom as a capacity of people that varies depending on certain conditions of a decision episode. It denotes an inner capability to consciously shape complex decisions according to one's own values and needs. Functional freedom depends on three compensatory dimensions: it is greatest when the decision-maker is highly rational, when the structure of the decision is highly underdetermined, and when the decision process is strongly based on conscious thought and reflection. We outline possible research questions, argue for psychological benefits of functional decision freedom, and explicate the model's implications on current knowledge and research. In conclusion, we show that functional freedom is a scientific variable, permitting an additional psychological foothold in research on freedom, and that is compatible with a deterministic worldview.

Root structural and functional dynamics in terrestrial biosphere models--evaluation and recommendations.

Science.gov (United States)

Warren, Jeffrey M; Hanson, Paul J; Iversen, Colleen M; Kumar, Jitendra; Walker, Anthony P; Wullschleger, Stan D

2015-01-01

There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction. No claim to original US Government works. New Phytologist © 2014 New Phytologist Trust.

Understanding Service Composition with Non-functional Properties Using Declarative Model-to-model Transformations

Directory of Open Access Journals (Sweden)

Max Mäuhlhäuser

2011-01-01

Full Text Available Developing applications comprising service composition is a complex task. Therefore, to lower the skill barrier for developers, it is important to describe the problem at hand on an abstract level and not to focus on implementation details. This can be done using declarative programming which allows to describe only the result of the problem (which is what the developer wants rather than the description of the implementation. We therefore use purely declarative model-to-model transformations written in a universal model transformation language which is capable of handling even non functional properties using optimization and mathematical programming. This makes it easier to understand and describe service composition and non-functional properties for the developer.

Comparing Transformation Possibilities of Topological Functioning Model and BPMN in the Context of Model Driven Architecture

Directory of Open Access Journals (Sweden)

Solomencevs Artūrs

2016-05-01

Full Text Available The approach called “Topological Functioning Model for Software Engineering” (TFM4SE applies the Topological Functioning Model (TFM for modelling the business system in the context of Model Driven Architecture. TFM is a mathematically formal computation independent model (CIM. TFM4SE is compared to an approach that uses BPMN as a CIM. The comparison focuses on CIM modelling and on transformation to UML Sequence diagram on the platform independent (PIM level. The results show the advantages and drawbacks the formalism of TFM brings into the development.

Sivers function in constituent quark models

CERN Document Server

Scopetta, S.; Fratini, F.; Vento, V.

2008-01-01

A formalism to evaluate the Sivers function, developed for calculations in constituent quark models, is applied to the Isgur-Karl model. A non-vanishing Sivers asymmetry, with opposite signs for the u and d flavor, is found; the Burkardt sum rule is fulfilled up to 2 %. Nuclear effects in the extraction of neutron single spin asymmetries in semi-inclusive deep inelastic scattering off 3He are also evaluated. In the kinematics of JLab, it is found that the nuclear effects described by an Impulse Approximation approach are under control.

A bayesian hierarchical model for classification with selection of functional predictors.

Science.gov (United States)

Zhu, Hongxiao; Vannucci, Marina; Cox, Dennis D

2010-06-01

In functional data classification, functional observations are often contaminated by various systematic effects, such as random batch effects caused by device artifacts, or fixed effects caused by sample-related factors. These effects may lead to classification bias and thus should not be neglected. Another issue of concern is the selection of functions when predictors consist of multiple functions, some of which may be redundant. The above issues arise in a real data application where we use fluorescence spectroscopy to detect cervical precancer. In this article, we propose a Bayesian hierarchical model that takes into account random batch effects and selects effective functions among multiple functional predictors. Fixed effects or predictors in nonfunctional form are also included in the model. The dimension of the functional data is reduced through orthonormal basis expansion or functional principal components. For posterior sampling, we use a hybrid Metropolis-Hastings/Gibbs sampler, which suffers slow mixing. An evolutionary Monte Carlo algorithm is applied to improve the mixing. Simulation and real data application show that the proposed model provides accurate selection of functional predictors as well as good classification.

Modelling pH-Optimized Degradation of Microgel-Functionalized Polyesters

Directory of Open Access Journals (Sweden)

Lisa Bürgermeister

2016-01-01

Full Text Available We establish a novel mathematical model to describe and analyze pH levels in the vicinity of poly(N-vinylcaprolactam-co-acetoacetoxyethyl methacrylate-co-N-vinylimidazole (VCL/AAEM/VIm microgel-functionalized polymers during biodegradation. Biodegradable polymers, especially aliphatic polyesters (polylactide/polyglycolide/polycaprolactone homo- and copolymers, have a large range of medical applications including delivery systems, scaffolds, or stents for the treatment of cardiovascular diseases. Most of those applications are limited by the inherent drop of pH level during the degradation process. The combination of polymers with VCL/AAEM/VIm-microgels, which aims at stabilizing pH levels, is innovative and requires new mathematical models for the prediction of pH level evaluation. The mathematical model consists of a diffusion-reaction PDE system for the degradation including reaction rate equations and diffusion of acidic degradation products into the vicinity. A system of algebraic equations is coupled to the degradation model in order to describe the buffering action of the microgel. The model is validated against the experimental pH-monitored biodegradation of microgel-functionalized polymer foils and is available for the design of microgel-functionalized polymer components.

Functional-derivative study of the Hubbard model. III. Fully renormalized Green's function

International Nuclear Information System (INIS)

Arai, T.; Cohen, M.H.

1980-01-01

The functional-derivative method of calculating the Green's function developed earlier for the Hubbard model is generalized and used to obtain a fully renormalized solution. Higher-order functional derivatives operating on the basic Green's functions, G and GAMMA, are all evaluated explicitly, thus making the solution applicable to the narrow-band region as well as the wide-band region. Correction terms Phi generated from functional derivatives of equal-time Green's functions of the type delta/sup n/ /deltaepsilon/sup n/, etc., with n > or = 2. It is found that the Phi's are, in fact, renormalization factors involved in the self-energy Σ and that the structure of the Phi's resembles that of Σ and contains the same renormalization factors Phi. The renormalization factors Phi are shown to satisfy a set of equations and can be evaluated self-consistently. In the presence of the Phi's, all difficulties found in the previous results (papers I and II) are removed, and the energy spectrum ω can now be evaluated for all occupations n. The Schwinger relation is the only basic relation used in generating this fully self-consistent Green's function, and the Baym-Kadanoff continuity condition is automatically satisfied

Functional State Modelling of Cultivation Processes: Dissolved Oxygen Limitation State

Directory of Open Access Journals (Sweden)

Olympia Roeva

2015-04-01

Full Text Available A new functional state, namely dissolved oxygen limitation state for both bacteria Escherichia coli and yeast Saccharomyces cerevisiae fed-batch cultivation processes is presented in this study. Functional state modelling approach is applied to cultivation processes in order to overcome the main disadvantages of using global process model, namely complex model structure and a big number of model parameters. Alongwith the newly introduced dissolved oxygen limitation state, second acetate production state and first acetate production state are recognized during the fed-batch cultivation of E. coli, while mixed oxidative state and first ethanol production state are recognized during the fed-batch cultivation of S. cerevisiae. For all mentioned above functional states both structural and parameter identification is here performed based on experimental data of E. coli and S. cerevisiae fed-batch cultivations.

Development on electromagnetic impedance function modeling and its estimation

Energy Technology Data Exchange (ETDEWEB)

Sutarno, D., E-mail: Sutarno@fi.itb.ac.id [Earth Physics and Complex System Division Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung (Indonesia)

2015-09-30

Today the Electromagnetic methods such as magnetotellurics (MT) and controlled sources audio MT (CSAMT) is used in a broad variety of applications. Its usefulness in poor seismic areas and its negligible environmental impact are integral parts of effective exploration at minimum cost. As exploration was forced into more difficult areas, the importance of MT and CSAMT, in conjunction with other techniques, has tended to grow continuously. However, there are obviously important and difficult problems remaining to be solved concerning our ability to collect process and interpret MT as well as CSAMT in complex 3D structural environments. This talk aim at reviewing and discussing the recent development on MT as well as CSAMT impedance functions modeling, and also some improvements on estimation procedures for the corresponding impedance functions. In MT impedance modeling, research efforts focus on developing numerical method for computing the impedance functions of three dimensionally (3-D) earth resistivity models. On that reason, 3-D finite elements numerical modeling for the impedances is developed based on edge element method. Whereas, in the CSAMT case, the efforts were focused to accomplish the non-plane wave problem in the corresponding impedance functions. Concerning estimation of MT and CSAMT impedance functions, researches were focused on improving quality of the estimates. On that objective, non-linear regression approach based on the robust M-estimators and the Hilbert transform operating on the causal transfer functions, were used to dealing with outliers (abnormal data) which are frequently superimposed on a normal ambient MT as well as CSAMT noise fields. As validated, the proposed MT impedance modeling method gives acceptable results for standard three dimensional resistivity models. Whilst, the full solution based modeling that accommodate the non-plane wave effect for CSAMT impedances is applied for all measurement zones, including near-, transition

Modelling the joint distribution of competing risks survival times using copula functions

OpenAIRE

Kaishev, V. K.; Haberman, S.; Dimitrova, D. S.

2005-01-01

The problem of modelling the joint distribution of survival times in a competing risks model, using copula functions is considered. In order to evaluate this joint distribution and the related overall survival function, a system of non-linear differential equations is solved, which relates the crude and net survival functions of the modelled competing risks, through the copula. A similar approach to modelling dependent multiple decrements was applied by Carriere (1994) who used a Gaussian cop...

Employee subjective well-being and physiological functioning: An integrative model.

Science.gov (United States)

Kuykendall, Lauren; Tay, Louis

2015-01-01

Research shows that worker subjective well-being influences physiological functioning-an early signal of poor health outcomes. While several theoretical perspectives provide insights on this relationship, the literature lacks an integrative framework explaining the relationship. We develop a conceptual model explaining the link between subjective well-being and physiological functioning in the context of work. Integrating positive psychology and occupational stress perspectives, our model explains the relationship between subjective well-being and physiological functioning as a result of the direct influence of subjective well-being on physiological functioning and of their common relationships with work stress and personal resources, both of which are influenced by job conditions.

Spatial and functional modeling of carnivore and insectivore molariform teeth.

Science.gov (United States)

Evans, Alistair R; Sanson, Gordon D

2006-06-01

The interaction between the two main competing geometric determinants of teeth (the geometry of function and the geometry of occlusion) were investigated through the construction of three-dimensional spatial models of several mammalian tooth forms (carnassial, insectivore premolar, zalambdodont, dilambdodont, and tribosphenic). These models aim to emulate the shape and function of mammalian teeth. The geometric principles of occlusion relating to single- and double-crested teeth are reviewed. Function was considered using engineering principles that relate tooth shape to function. Substantial similarity between the models and mammalian teeth were achieved. Differences between the two indicate the influence of tooth strength, geometric relations between upper and lower teeth (including the presence of the protocone), and wear on tooth morphology. The concept of "autocclusion" is expanded to include any morphological features that ensure proper alignment of cusps on the same tooth and other teeth in the tooth row. It is concluded that the tooth forms examined are auto-aligning, and do not require additional morphological guides for correct alignment. The model of therian molars constructed by Crompton and Sita-Lumsden ([1970] Nature 227:197-199) is reconstructed in 3D space to show that their hypothesis of crest geometry is erroneous, and that their model is a special case of a more general class of models. (c) 2004 Wiley-Liss, Inc.

Estimation of parameters of constant elasticity of substitution production functional model

Science.gov (United States)

Mahaboob, B.; Venkateswarlu, B.; Sankar, J. Ravi

2017-11-01

Nonlinear model building has become an increasing important powerful tool in mathematical economics. In recent years the popularity of applications of nonlinear models has dramatically been rising up. Several researchers in econometrics are very often interested in the inferential aspects of nonlinear regression models [6]. The present research study gives a distinct method of estimation of more complicated and highly nonlinear model viz Constant Elasticity of Substitution (CES) production functional model. Henningen et.al [5] proposed three solutions to avoid serious problems when estimating CES functions in 2012 and they are i) removing discontinuities by using the limits of the CES function and its derivative. ii) Circumventing large rounding errors by local linear approximations iii) Handling ill-behaved objective functions by a multi-dimensional grid search. Joel Chongeh et.al [7] discussed the estimation of the impact of capital and labour inputs to the gris output agri-food products using constant elasticity of substitution production function in Tanzanian context. Pol Antras [8] presented new estimates of the elasticity of substitution between capital and labour using data from the private sector of the U.S. economy for the period 1948-1998.

Mathematical modeling and visualization of functional neuroimages

DEFF Research Database (Denmark)

Rasmussen, Peter Mondrup

This dissertation presents research results regarding mathematical modeling in the context of the analysis of functional neuroimages. Specifically, the research focuses on pattern-based analysis methods that recently have become popular within the neuroimaging community. Such methods attempt...... sets are characterized by relatively few data observations in a high dimensional space. The process of building models in such data sets often requires strong regularization. Often, the degree of model regularization is chosen in order to maximize prediction accuracy. We focus on the relative influence...... be carefully selected, so that the model and its visualization enhance our ability to interpret the brain. The second part concerns interpretation of nonlinear models and procedures for extraction of ‘brain maps’ from nonlinear kernel models. We assess the performance of the sensitivity map as means...

Density Functional Theory and Materials Modeling at Atomistic Length Scales

Directory of Open Access Journals (Sweden)

Swapan K. Ghosh

2002-04-01

Full Text Available Abstract: We discuss the basic concepts of density functional theory (DFT as applied to materials modeling in the microscopic, mesoscopic and macroscopic length scales. The picture that emerges is that of a single unified framework for the study of both quantum and classical systems. While for quantum DFT, the central equation is a one-particle Schrodinger-like Kohn-Sham equation, the classical DFT consists of Boltzmann type distributions, both corresponding to a system of noninteracting particles in the field of a density-dependent effective potential, the exact functional form of which is unknown. One therefore approximates the exchange-correlation potential for quantum systems and the excess free energy density functional or the direct correlation functions for classical systems. Illustrative applications of quantum DFT to microscopic modeling of molecular interaction and that of classical DFT to a mesoscopic modeling of soft condensed matter systems are highlighted.

Functional dynamic factor models with application to yield curve forecasting

KAUST Repository

Hays, Spencer

2012-09-01

Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. Model estimation is achieved through an expectation- maximization algorithm, where the time series parameters and factor loading curves are simultaneously estimated in a single step. Efficient computing is implemented and a data-driven smoothing parameter is nicely incorporated. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting.

High resolution wind measurements for offshore wind energy development

Science.gov (United States)

Nghiem, Son Van (Inventor); Neumann, Gregory (Inventor)

2013-01-01

A method, apparatus, system, article of manufacture, and computer readable storage medium provide the ability to measure wind. Data at a first resolution (i.e., low resolution data) is collected by a satellite scatterometer. Thin slices of the data are determined. A collocation of the data slices are determined at each grid cell center to obtain ensembles of collocated data slices. Each ensemble of collocated data slices is decomposed into a mean part and a fluctuating part. The data is reconstructed at a second resolution from the mean part and a residue of the fluctuating part. A wind measurement is determined from the data at the second resolution using a wind model function. A description of the wind measurement is output.

Using Cultural Modeling to Inform a NEDSS-Compatible System Functionality Evaluation

Science.gov (United States)

Anderson, Olympia; Torres-Urquidy, Miguel

2013-01-01

Objective The culture by which public health professionals work defines their organizational objectives, expectations, policies, and values. These aspects of culture are often intangible and difficult to qualify. The introduction of an information system could further complicate the culture of a jurisdiction if the intangibles of a culture are not clearly understood. This report describes how cultural modeling can be used to capture intangible elements or factors that may affect NEDSS-compatible (NC) system functionalities within the culture of public health jurisdictions. Introduction The National Notifiable Disease Surveillance System (NNDSS) comprises many activities including collaborations, processes, standards, and systems which support gathering data from US states and territories. As part of NNDSS, the National Electronic Disease Surveillance System (NEDSS) provides the standards, tools, and resources to support reporting public health jurisdictions (jurisdictions). The NEDSS Base System (NBS) is a CDC-developed, software application available to jurisdictions to collect, manage, analyze and report national notifiable disease (NND) data. An evaluation of NEDSS with the objective of identifying the functionalities of NC systems and the impact of these features on the user’s culture is underway. Methods We used cultural models to capture additional NC system functionality gaps within the culture of the user. Cultural modeling is a process of graphically depicting people and organizations referred to as influencers and the intangible factors that affect the user’s operations or work as influences. Influencers are denoted as bubbles while influences are depicted as arrows penetrating the bubbles. In the cultural model, influence can be seen by the size and proximity (or lack of) in the model. We restricted the models to secondary data sources and interviews of CDC programs (data users) and public health jurisdictions (data reporters). Results Three cultural

Computer-controlled mechanical lung model for application in pulmonary function studies

NARCIS (Netherlands)

A.F.M. Verbraak (Anton); J.E.W. Beneken; J.M. Bogaard (Jan); A. Versprille (Adrian)

1995-01-01

textabstractA computer controlled mechanical lung model has been developed for testing lung function equipment, validation of computer programs and simulation of impaired pulmonary mechanics. The construction, function and some applications are described. The physical model is constructed from two

The functional neuroanatomy of bipolar disorder: a consensus model

Science.gov (United States)

Strakowski, Stephen M; Adler, Caleb M; Almeida, Jorge; Altshuler, Lori L; Blumberg, Hilary P; Chang, Kiki D; DelBello, Melissa P; Frangou, Sophia; McIntosh, Andrew; Phillips, Mary L; Sussman, Jessika E; Townsend, Jennifer D

2013-01-01

Objectives Functional neuroimaging methods have proliferated in recent years, such that functional magnetic resonance imaging, in particular, is now widely used to study bipolar disorder. However, discrepant findings are common. A workgroup was organized by the Department of Psychiatry, University of Cincinnati (Cincinnati, OH, USA) to develop a consensus functional neuroanatomic model of bipolar I disorder based upon the participants’ work as well as that of others. Methods Representatives from several leading bipolar disorder neuroimaging groups were organized to present an overview of their areas of expertise as well as focused reviews of existing data. The workgroup then developed a consensus model of the functional neuroanatomy of bipolar disorder based upon these data. Results Among the participants, a general consensus emerged that bipolar I disorder arises from abnormalities in the structure and function of key emotional control networks in the human brain. Namely, disruption in early development (e.g., white matter connectivity, prefrontal pruning) within brain networks that modulate emotional behavior leads to decreased connectivity among ventral prefrontal networks and limbic brain regions, especially amygdala. This developmental failure to establish healthy ventral prefrontal–limbic modulation underlies the onset of mania and ultimately, with progressive changes throughout these networks over time and with affective episodes, a bipolar course of illness. Conclusions This model provides a potential substrate to guide future investigations and areas needing additional focus are identified. PMID:22631617

Calculating kaon fragmentation functions from the Nambu-Jona-Lasinio jet model

International Nuclear Information System (INIS)

Matevosyan, Hrayr H.; Thomas, Anthony W.; Bentz, Wolfgang

2011-01-01

The Nambu-Jona-Lasinio (NJL)-jet model provides a sound framework for calculating the fragmentation functions in an effective chiral quark theory, where the momentum and isospin sum rules are satisfied without the introduction of ad hoc parameters. Earlier studies of the pion fragmentation functions using the NJL model within this framework showed qualitative agreement with the empirical parametrizations. Here we extend the NJL-jet model by including the strange quark. The corrections to the pion fragmentation functions and corresponding kaon fragmentation functions are calculated using the elementary quark to quark-meson fragmentation functions from NJL. The results for the kaon fragmentation functions exhibit a qualitative agreement with the empirical parametrizations, while the unfavored strange quark fragmentation to pions is shown to be of the same order of magnitude as the unfavored light quark. The results of these studies are expected to provide important guidance for the analysis of a large variety of semi-inclusive data.

Modeling the microstructure of surface by applying BRDF function

Science.gov (United States)

Plachta, Kamil

2017-06-01

The paper presents the modeling of surface microstructure using a bidirectional reflectance distribution function. This function contains full information about the reflectance properties of the flat surfaces - it is possible to determine the share of the specular, directional and diffuse components in the reflected luminous stream. The software is based on the authorial algorithm that uses selected elements of this function models, which allows to determine the share of each component. Basing on obtained data, the surface microstructure of each material can be modeled, which allows to determine the properties of this materials. The concentrator directs the reflected solar radiation onto the photovoltaic surface, increasing, at the same time, the value of the incident luminous stream. The paper presents an analysis of selected materials that can be used to construct the solar concentrator system. The use of concentrator increases the power output of the photovoltaic system by up to 17% as compared to the standard solution.

Joint Modelling of Structural and Functional Brain Networks

DEFF Research Database (Denmark)

Andersen, Kasper Winther; Herlau, Tue; Mørup, Morten

-parametric Bayesian network model which allows for joint modelling and integration of multiple networks. We demonstrate the model’s ability to detect vertices that share structure across networks jointly in functional MRI (fMRI) and diffusion MRI (dMRI) data. Using two fMRI and dMRI scans per subject, we establish...

Functionally unidimensional item response models for multivariate binary data

DEFF Research Database (Denmark)

Ip, Edward; Molenberghs, Geert; Chen, Shyh-Huei

2013-01-01

The problem of fitting unidimensional item response models to potentially multidimensional data has been extensively studied. The focus of this article is on response data that have a strong dimension but also contain minor nuisance dimensions. Fitting a unidimensional model to such multidimensio......The problem of fitting unidimensional item response models to potentially multidimensional data has been extensively studied. The focus of this article is on response data that have a strong dimension but also contain minor nuisance dimensions. Fitting a unidimensional model...... to such multidimensional data is believed to result in ability estimates that represent a combination of the major and minor dimensions. We conjecture that the underlying dimension for the fitted unidimensional model, which we call the functional dimension, represents a nonlinear projection. In this article we investigate...... tool. An example regarding a construct of desire for physical competency is used to illustrate the functional unidimensional approach....

Complex curve of the two-matrix model and its tau-function

International Nuclear Information System (INIS)

Kazakov, Vladimir A; Marshakov, Andrei

2003-01-01

We study the Hermitian and normal two-matrix models in planar approximation for an arbitrary number of eigenvalue supports. Its planar graph interpretation is given. The study reveals a general structure of the underlying analytic complex curve, different from the hyperelliptic curve of the one-matrix model. The matrix model quantities are expressed through the periods of meromorphic generating differential on this curve and the partition function of the multiple support solution, as a function of filling numbers and coefficients of the matrix potential, is shown to be a quasiclassical tau-function. The relation to N = 1 supersymmetric Yang-Mills theories is discussed. A general class of solvable multi-matrix models with tree-like interactions is considered

Zeros of the partition function for some generalized Ising models

International Nuclear Information System (INIS)

Dunlop, F.

1981-01-01

The author considers generalized Ising Models with two and four body interactions in a complex external field h such that Re h>=mod(Im h) + C, where C is an explicit function of the interaction parameters. The partition function Z(h) is then shown to satisfy mod(Z(h))>=Z(c), so that the pressure is analytic in h inside the given region. The method is applied to specific examples: the gauge invariant Ising Model, and the Widom Rowlinson model on the lattice. (Auth.)

Regional differences in prediction models of lung function in Germany

Directory of Open Access Journals (Sweden)

Schäper Christoph

2010-04-01

Full Text Available Abstract Background Little is known about the influencing potential of specific characteristics on lung function in different populations. The aim of this analysis was to determine whether lung function determinants differ between subpopulations within Germany and whether prediction equations developed for one subpopulation are also adequate for another subpopulation. Methods Within three studies (KORA C, SHIP-I, ECRHS-I in different areas of Germany 4059 adults performed lung function tests. The available data consisted of forced expiratory volume in one second, forced vital capacity and peak expiratory flow rate. For each study multivariate regression models were developed to predict lung function and Bland-Altman plots were established to evaluate the agreement between predicted and measured values. Results The final regression equations for FEV1 and FVC showed adjusted r-square values between 0.65 and 0.75, and for PEF they were between 0.46 and 0.61. In all studies gender, age, height and pack-years were significant determinants, each with a similar effect size. Regarding other predictors there were some, although not statistically significant, differences between the studies. Bland-Altman plots indicated that the regression models for each individual study adequately predict medium (i.e. normal but not extremely high or low lung function values in the whole study population. Conclusions Simple models with gender, age and height explain a substantial part of lung function variance whereas further determinants add less than 5% to the total explained r-squared, at least for FEV1 and FVC. Thus, for different adult subpopulations of Germany one simple model for each lung function measures is still sufficient.

A Review of Modeling Pedagogies: Pedagogical Functions, Discursive Acts, and Technology in Modeling Instruction

Science.gov (United States)

Campbell, Todd; Oh, Phil Seok; Maughn, Milo; Kiriazis, Nick; Zuwallack, Rebecca

2015-01-01

The current review examined modeling literature in top science education journals to better understand the pedagogical functions of modeling instruction reported over the last decade. Additionally, the review sought to understand the extent to which different modeling pedagogies were employed, the discursive acts that were identified as important,…

Bayesian Modelling of Functional Whole Brain Connectivity

DEFF Research Database (Denmark)

Røge, Rasmus

the prevalent strategy of standardizing of fMRI time series and model data using directional statistics or we model the variability in the signal across the brain and across multiple subjects. In either case, we use Bayesian nonparametric modeling to automatically learn from the fMRI data the number......This thesis deals with parcellation of whole-brain functional magnetic resonance imaging (fMRI) using Bayesian inference with mixture models tailored to the fMRI data. In the three included papers and manuscripts, we analyze two different approaches to modeling fMRI signal; either we accept...... of funcional units, i.e. parcels. We benchmark the proposed mixture models against state of the art methods of brain parcellation, both probabilistic and non-probabilistic. The time series of each voxel are most often standardized using z-scoring which projects the time series data onto a hypersphere...

Functional modelling for integration of human-software-hardware in complex physical systems

International Nuclear Information System (INIS)

Modarres, M.

1996-01-01

A framework describing the properties of complex physical systems composed of human-software-hardware interactions in terms of their functions is described. It is argued that such a framework is domain-general, so that functional primitives present a language that is more general than most other modeling methods such as mathematical simulation. The characteristics and types of functional models are described. Examples of uses of the framework in modeling physical systems composed of human-software-hardware (hereby we refer to them as only physical systems) are presented. It is concluded that a function-centered model of a physical system provides a capability for generating a high-level simulation of the system for intelligent diagnostic, control or other similar applications

Rationalisation of distribution functions for models of nanoparticle magnetism

International Nuclear Information System (INIS)

El-Hilo, M.; Chantrell, R.W.

2012-01-01

A formalism is presented which reconciles the use of different distribution functions of particle diameter in analytical models of the magnetic properties of nanoparticle systems. For the lognormal distribution a transformation is derived which shows that a distribution of volume fraction transforms into a lognormal distribution of particle number albeit with a modified median diameter. This transformation resolves an apparent discrepancy reported in Tournus and Tamion [Journal of Magnetism and Magnetic Materials 323 (2011) 1118]. - Highlights: ► We resolve a problem resulting from the misunderstanding of the nature. ► The nature of dispersion functions in models of nanoparticle magnetism. ► The derived transformation between distributions will be of benefit in comparing models and experimental results.

Using special functions to model the propagation of airborne diseases

Science.gov (United States)

Bolaños, Daniela

2014-06-01

Some special functions of the mathematical physics are using to obtain a mathematical model of the propagation of airborne diseases. In particular we study the propagation of tuberculosis in closed rooms and we model the propagation using the error function and the Bessel function. In the model, infected individual emit pathogens to the environment and this infect others individuals who absorb it. The evolution in time of the concentration of pathogens in the environment is computed in terms of error functions. The evolution in time of the number of susceptible individuals is expressed by a differential equation that contains the error function and it is solved numerically for different parametric simulations. The evolution in time of the number of infected individuals is plotted for each numerical simulation. On the other hand, the spatial distribution of the pathogen around the source of infection is represented by the Bessel function K0. The spatial and temporal distribution of the number of infected individuals is computed and plotted for some numerical simulations. All computations were made using software Computer algebra, specifically Maple. It is expected that the analytical results that we obtained allow the design of treatment rooms and ventilation systems that reduce the risk of spread of tuberculosis.

SASS wind ambiguity removal by direct minimization. II - Use of smoothness and dynamical constraints

Science.gov (United States)

Hoffman, R. N.

1984-01-01

A variational analysis method (VAM) is used to remove the ambiguity of the Seasat-A Satellite Scatterometer (SASS) winds. The VAM yields the best fit to the data by minimizing an objective function S which is a measure of the lack of fit. The SASS data are described and the function S and the analysis procedure are defined. Analyses of a single ship report which are analogous to Green's functions are presented. The analysis procedure is tuned and its sensitivity is described using the QE II storm. The procedure is then applied to a case study of September 6, 1978, south of Japan.

Features of Functioning the Integrated Building Thermal Model

Directory of Open Access Journals (Sweden)

Morozov Maxim N.

2017-01-01

Full Text Available A model of the building heating system, consisting of energy source, a distributed automatic control system, elements of individual heating unit and heating system is designed. Application Simulink of mathematical package Matlab is selected as a platform for the model. There are the specialized application Simscape libraries in aggregate with a wide range of Matlab mathematical tools allow to apply the “acausal” modeling concept. Implementation the “physical” representation of the object model gave improving the accuracy of the models. Principle of operation and features of the functioning of the thermal model is described. The investigations of building cooling dynamics were carried out.

Use of multi-frequency, multi-polarization, multi-angle airborne radars for class discrimination in a southern temperature forest

Science.gov (United States)

Mehta, N. C.

1984-01-01

The utility of radar scatterometers for discrimination and characterization of natural vegetation was investigated. Backscatter measurements were acquired with airborne multi-frequency, multi-polarization, multi-angle radar scatterometers over a test site in a southern temperate forest. Separability between ground cover classes was studied using a two-class separability measure. Very good separability is achieved between most classes. Longer wavelength is useful in separating trees from non-tree classes, while shorter wavelength and cross polarization are helpful for discrimination among tree classes. Using the maximum likelihood classifier, 50% overall classification accuracy is achieved using a single, short-wavelength scatterometer channel. Addition of multiple incidence angles and another radar band improves classification accuracy by 20% and 50%, respectively, over the single channel accuracy. Incorporation of a third radar band seems redundant for vegetation classification. Vertical transmit polarization is critically important for all classes.

"Shape function + memory mechanism"-based hysteresis modeling of magnetorheological fluid actuators

Science.gov (United States)

Qian, Li-Jun; Chen, Peng; Cai, Fei-Long; Bai, Xian-Xu

2018-03-01

A hysteresis model based on "shape function + memory mechanism" is presented and its feasibility is verified through modeling the hysteresis behavior of a magnetorheological (MR) damper. A hysteresis phenomenon in resistor-capacitor (RC) circuit is first presented and analyzed. In the hysteresis model, the "memory mechanism" originating from the charging and discharging processes of the RC circuit is constructed by adopting a virtual displacement variable and updating laws for the reference points. The "shape function" is achieved and generalized from analytical solutions of the simple semi-linear Duhem model. Using the approach, the memory mechanism reveals the essence of specific Duhem model and the general shape function provides a direct and clear means to fit the hysteresis loop. In the frame of the structure of a "Restructured phenomenological model", the original hysteresis operator, i.e., the Bouc-Wen operator, is replaced with the new hysteresis operator. The comparative work with the Bouc-Wen operator based model demonstrates superior performances of high computational efficiency and comparable accuracy of the new hysteresis operator-based model.

Partially linear varying coefficient models stratified by a functional covariate

KAUST Repository

Maity, Arnab

2012-10-01

We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric component and a profiling estimator of the parametric component of the model and derive their asymptotic properties. Specifically, we show the consistency of the nonparametric functional estimates and derive the asymptotic expansion of the estimates of the parametric component. We illustrate the performance of our methodology using a simulation study and a real data application.

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

Science.gov (United States)

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Medical Writing Competency Model - Section 1: Functions, Tasks, and Activities.

Science.gov (United States)

Clemow, David B; Wagner, Bertil; Marshallsay, Christopher; Benau, Dan; L'Heureux, Darryl; Brown, David H; Dasgupta, Devjani Ghosh; Girten, Eileen; Hubbard, Frank; Gawrylewski, Helle-Mai; Ebina, Hiroko; Stoltenborg, Janet; York, J P; Green, Kim; Wood, Linda Fossati; Toth, Lisa; Mihm, Michael; Katz, Nancy R; Vasconcelos, Nina-Maria; Sakiyama, Norihisa; Whitsell, Robin; Gopalakrishnan, Shobha; Bairnsfather, Susan; Wanderer, Tatyana; Schindler, Thomas M; Mikyas, Yeshi; Aoyama, Yumiko

2018-01-01

This article provides Section 1 of the 2017 Edition 2 Medical Writing Competency Model that describes the core work functions and associated tasks and activities related to professional medical writing within the life sciences industry. The functions in the Model are scientific communication strategy; document preparation, development, and finalization; document project management; document template, standard, format, and style development and maintenance; outsourcing, alliance partner, and client management; knowledge, skill, ability, and behavior development and sharing; and process improvement. The full Model also includes Section 2, which covers the knowledge, skills, abilities, and behaviors needed for medical writers to be effective in their roles; Section 2 is presented in a companion article. Regulatory, publication, and other scientific writing as well as management of writing activities are covered. The Model was developed to aid medical writers and managers within the life sciences industry regarding medical writing hiring, training, expectation and goal setting, performance evaluation, career development, retention, and role value sharing to cross-functional partners.

Modelling of Multi Input Transfer Function for Rainfall Forecasting in Batu City

OpenAIRE

Priska Arindya Purnama

2017-01-01

The aim of this research is to model and forecast the rainfall in Batu City using multi input transfer function model based on air temperature, humidity, wind speed and cloud. Transfer function model is a multivariate time series model which consists of an output series (Yt) sequence expected to be effected by an input series (Xt) and other inputs in a group called a noise series (Nt). Multi input transfer function model obtained is (b1,s1,r1) (b2,s2,r2) (b3,s3,r3) (b4,s4,r4)(pn,qn) = (0,0,0)...

Stability analysis of polynomial fuzzy models via polynomial fuzzy Lyapunov functions

OpenAIRE

Bernal Reza, Miguel Ángel; Sala, Antonio; JAADARI, ABDELHAFIDH; Guerra, Thierry-Marie

2011-01-01

In this paper, the stability of continuous-time polynomial fuzzy models by means of a polynomial generalization of fuzzy Lyapunov functions is studied. Fuzzy Lyapunov functions have been fruitfully used in the literature for local analysis of Takagi-Sugeno models, a particular class of the polynomial fuzzy ones. Based on a recent Taylor-series approach which allows a polynomial fuzzy model to exactly represent a nonlinear model in a compact set of the state space, it is shown that a refinemen...

Functional requirements of a mathematical model of the heart.

Science.gov (United States)

Palladino, Joseph L; Noordergraaf, Abraham

2009-01-01

Functional descriptions of the heart, especially the left ventricle, are often based on the measured variables pressure and ventricular outflow, embodied as a time-varying elastance. The fundamental difficulty of describing the mechanical properties of the heart with a time-varying elastance function that is set a priori is described. As an alternative, a new functional model of the heart is presented, which characterizes the ventricle's contractile state with parameters, rather than variables. Each chamber is treated as a pressure generator that is time and volume dependent. The heart's complex dynamics develop from a single equation based on the formation and relaxation of crossbridge bonds. This equation permits the calculation of ventricular elastance via E(v) = partial differentialp(v)/ partial differentialV(v). This heart model is defined independently from load properties, and ventricular elastance is dynamic and reflects changing numbers of crossbridge bonds. In this paper, the functionality of this new heart model is presented via computed work loops that demonstrate the Frank-Starling mechanism and the effects of preload, the effects of afterload, inotropic changes, and varied heart rate, as well as the interdependence of these effects. Results suggest the origin of the equivalent of Hill's force-velocity relation in the ventricle.

Pion-nucleon vertex function and the Chew-Low model

International Nuclear Information System (INIS)

Nutt, W.T.

1977-01-01

We provide an interpretation of the cutoff function used in the Chew-Low theory of pion-nucleon scattering. It is shown that this function may be related to the pion-pion interaction which is not explicitly considered in the Chew-Low approach. Using a previously developed model for the pion-nucleon vertex function, we then perform a ''parameter-free'' Chew-Low calculation which predicts the P 33 resonance quite well

Embedded systems development from functional models to implementations

CERN Document Server

Zeng, Haibo; Natale, Marco; Marwedel, Peter

2014-01-01

This book offers readers broad coverage of techniques to model, verify and validate the behavior and performance of complex distributed embedded systems.  The authors attempt to bridge the gap between the three disciplines of model-based design, real-time analysis and model-driven development, for a better understanding of the ways in which new development flows can be constructed, going from system-level modeling to the correct and predictable generation of a distributed implementation, leveraging current and future research results.     Describes integration of heterogeneous models; Discusses synthesis of task model implementations and code implementations; Compares model-based design vs. model-driven approaches; Explains how to enforce correctness by construction in the functional and time domains; Includes optimization techniques for control performance.

A Tensor Statistical Model for Quantifying Dynamic Functional Connectivity.

Science.gov (United States)

Zhu, Yingying; Zhu, Xiaofeng; Kim, Minjeong; Yan, Jin; Wu, Guorong

2017-06-01

Functional connectivity (FC) has been widely investigated in many imaging-based neuroscience and clinical studies. Since functional Magnetic Resonance Image (MRI) signal is just an indirect reflection of brain activity, it is difficult to accurately quantify the FC strength only based on signal correlation. To address this limitation, we propose a learning-based tensor model to derive high sensitivity and specificity connectome biomarkers at the individual level from resting-state fMRI images. First, we propose a learning-based approach to estimate the intrinsic functional connectivity. In addition to the low level region-to-region signal correlation, latent module-to-module connection is also estimated and used to provide high level heuristics for measuring connectivity strength. Furthermore, sparsity constraint is employed to automatically remove the spurious connections, thus alleviating the issue of searching for optimal threshold. Second, we integrate our learning-based approach with the sliding-window technique to further reveal the dynamics of functional connectivity. Specifically, we stack the functional connectivity matrix within each sliding window and form a 3D tensor where the third dimension denotes for time. Then we obtain dynamic functional connectivity (dFC) for each individual subject by simultaneously estimating the within-sliding-window functional connectivity and characterizing the across-sliding-window temporal dynamics. Third, in order to enhance the robustness of the connectome patterns extracted from dFC, we extend the individual-based 3D tensors to a population-based 4D tensor (with the fourth dimension stands for the training subjects) and learn the statistics of connectome patterns via 4D tensor analysis. Since our 4D tensor model jointly (1) optimizes dFC for each training subject and (2) captures the principle connectome patterns, our statistical model gains more statistical power of representing new subject than current state

Aircraft/Air Traffic Management Functional Analysis Model: Technical Description. 2.0

Science.gov (United States)

Etheridge, Melvin; Plugge, Joana; Retina, Nusrat

1998-01-01

The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) under a National Aeronautics and Space Administration (NASA) contract. This document provides a technical description of FAM 2.0 and its computer files to enable the modeler and programmer to make enhancements or modifications to the model. Those interested in a guide for using the model in analysis should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Users Manual.

Density-correlation functions in Calogero-Sutherland models

International Nuclear Information System (INIS)

Minahan, J.A.; Polychronakos, A.P.

1994-01-01

Using arguments from two-dimensional Yang-Mills theory and the collective coordinate formulation of the Calogero-Sutherland model, we conjecture the dynamical density-correlation function for coupling l and 1/l, where l is an integer. We present overwhelming evidence that the conjecture is indeed correct

Density correlation functions in Calogero-Sutherland models

CERN Document Server

Minahan, Joseph A.; Joseph A Minahan; Alexios P Polychronakos

1994-01-01

Using arguments from two dimensional Yang-Mills theory and the collective coordinate formulation of the Calogero-Sutherland model, we conjecture the dynamical density correlation function for coupling l and 1/l, where l is an integer. We present overwhelming evidence that the conjecture is indeed correct.

End to end distribution functions for a class of polymer models

International Nuclear Information System (INIS)

Khandekar, D.C.; Wiegel, F.W.

1988-01-01

The two point end-to-end distribution functions for a class of polymer models have been obtained within the first cumulant approximation. The trial distribution function this purpose is chosen to correspond to a general non-local quadratic functional. An Exact expression for the trial distribution function is obtained. It is pointed out that these trial distribution functions themselves can be used to study certain aspects of the configurational behaviours of polymers. These distribution functions are also used to obtain the averaged mean square size 2 > of a polymer characterized by the non-local quadratic potential energy functional. Finally, we derive an analytic expression for 2 > of a polyelectrolyte model and show that for a long polymer a weak electrostatic interaction does not change the behaviour of 2 > from that of a free polymer. (author). 16 refs

Infinite Relational Modeling of Functional Connectivity in Resting State fMRI

DEFF Research Database (Denmark)

Mørup, Morten; Madsen, Kristoffer H.; Dogonowski, Anne Marie

2010-01-01

Functional magnetic resonance imaging (fMRI) can be applied to study the functional connectivity of the neural elements which form complex network at a whole brain level. Most analyses of functional resting state networks (RSN) have been based on the analysis of correlation between the temporal...... dynamics of various regions of the brain. While these models can identify coherently behaving groups in terms of correlation they give little insight into how these groups interact. In this paper we take a different view on the analysis of functional resting state networks. Starting from the definition...... of resting state as functional coherent groups we search for functional units of the brain that communicate with other parts of the brain in a coherent manner as measured by mutual information. We use the infinite relational model (IRM) to quantify functional coherent groups of resting state networks...

DEFINE: A Service-Oriented Dynamically Enabling Function Model

Directory of Open Access Journals (Sweden)

Tan Wei-Yi

2017-01-01

In this paper, we introduce an innovative Dynamically Enable Function In Network Equipment (DEFINE to allow tenant get the network service quickly. First, DEFINE decouples an application into different functional components, and connects these function components in a reconfigurable method. Second, DEFINE provides a programmable interface to the third party, who can develop their own processing modules according to their own needs. To verify the effectiveness of this model, we set up an evaluating network with a FPGA-based OpenFlow switch prototype, and deployed several applications on it. Our results show that DEFINE has excellent flexibility and performance.

Green function of the model two-centre quantum-mechanical problem

International Nuclear Information System (INIS)

Khoma, M.V.; Lazur, V.Yu.

2002-01-01

The expansions of a Green function for the Simmons molecular potential (SMP) in terms of spheroidal function are built. The solutions of degenerate hypergeometric equation are used as basis function system while expanding regular and irregular model spheroidal functions into series. Rather simple three-terms recurrence relations are obtained for the coefficients of these expansions. Much attentions is given to different asymptotic representation as well as Sturmian expansions of the Green function of the two-centre SMP wave functions. In all cases considered the Green function is reduced to the form similar to the Hostler's representation of the Coulomb Green function

Cohesive fracture model for functionally graded fiber reinforced concrete

International Nuclear Information System (INIS)

Park, Kyoungsoo; Paulino, Glaucio H.; Roesler, Jeffery

2010-01-01

A simple, effective, and practical constitutive model for cohesive fracture of fiber reinforced concrete is proposed by differentiating the aggregate bridging zone and the fiber bridging zone. The aggregate bridging zone is related to the total fracture energy of plain concrete, while the fiber bridging zone is associated with the difference between the total fracture energy of fiber reinforced concrete and the total fracture energy of plain concrete. The cohesive fracture model is defined by experimental fracture parameters, which are obtained through three-point bending and split tensile tests. As expected, the model describes fracture behavior of plain concrete beams. In addition, it predicts the fracture behavior of either fiber reinforced concrete beams or a combination of plain and fiber reinforced concrete functionally layered in a single beam specimen. The validated model is also applied to investigate continuously, functionally graded fiber reinforced concrete composites.

Future of Plant Functional Types in Terrestrial Biosphere Models

Science.gov (United States)

Wullschleger, S. D.; Euskirchen, E. S.; Iversen, C. M.; Rogers, A.; Serbin, S.

2015-12-01

Earth system models describe the physical, chemical, and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models. Plant functional types (PFTs) have been adopted by modelers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current, and future distribution of vegetation. Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration, and shrub expansion. However, representation of above- and especially belowground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait-environment relationships. Surprisingly, despite being important to land-atmosphere interactions of carbon, water, and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology, and remote sensing will be

Asymptotic behaviour of two-point functions in multi-species models

Directory of Open Access Journals (Sweden)

Karol K. Kozlowski

2016-05-01

Full Text Available We extract the long-distance asymptotic behaviour of two-point correlation functions in massless quantum integrable models containing multi-species excitations. For such a purpose, we extend to these models the method of a large-distance regime re-summation of the form factor expansion of correlation functions. The key feature of our analysis is a technical hypothesis on the large-volume behaviour of the form factors of local operators in such models. We check the validity of this hypothesis on the example of the SU(3-invariant XXX magnet by means of the determinant representations for the form factors of local operators in this model. Our approach confirms the structure of the critical exponents obtained previously for numerous models solvable by the nested Bethe Ansatz.

An orbital-overlap model for minimal work functions of cesiated metal surfaces

International Nuclear Information System (INIS)

Chou, Sharon H; Bargatin, Igor; Howe, Roger T; Voss, Johannes; Vojvodic, Aleksandra; Abild-Pedersen, Frank

2012-01-01

We introduce a model for the effect of cesium adsorbates on the work function of transition metal surfaces. The model builds on the classical point-dipole equation by adding exponential terms that characterize the degree of orbital overlap between the 6s states of neighboring cesium adsorbates and its effect on the strength and orientation of electric dipoles along the adsorbate-substrate interface. The new model improves upon earlier models in terms of agreement with the work function-coverage curves obtained via first-principles calculations based on density functional theory. All the cesiated metal surfaces have optimal coverages between 0.6 and 0.8 monolayers, in accordance with experimental data. Of all the cesiated metal surfaces that we have considered, tungsten has the lowest minimum work function, also in accordance with experiments.

A functional integral approach without slave bosons to the Anderson model

International Nuclear Information System (INIS)

Nguyen Ngoc Thuan; Nguyen Toan Thang; Coqblin, B.; Bhattacharjee, A.; Hoang Anh Tuan.

1994-06-01

We developed the technique of the functional integral method without slave bosons for the Periodic Anderson Model (PAM) suggested by Sarker for treating the Hubbard Model. This technique allowed us to obtain an analytical expression of Green functions containing U-dependence that is omitted in the formalism with slave bosons. (author). 9 refs

A no extensive statistical model for the nucleon structure function

International Nuclear Information System (INIS)

Trevisan, Luis A.; Mirez, Carlos

2013-01-01

We studied an application of nonextensive thermodynamics to describe the structure function of nucleon, in a model where the usual Fermi-Dirac and Bose-Einstein energy distribution were replaced by the equivalent functions of the q-statistical. The parameters of the model are given by an effective temperature T, the q parameter (from Tsallis statistics), and two chemical potentials given by the corresponding up (u) and down (d) quark normalization in the nucleon.

The Potts model and flows. 1. The pair correlation function

International Nuclear Information System (INIS)

Essam, J.W.; Tsallis, C.

1985-01-01

It is shown that the partition function for the lambda-state Potts model with pair-interactions is related to the expected number of integer mod-lambda flows in a percolation model. The relation is generalised to the pair correlation function. The resulting high temperature expansion coefficients are shown to be the flow polynomials of graph theory. An observation of Tsallis and Levy concerning the equivalent transmissivity of a cluster is also proved. (Author) [pt

A more general model for testing measurement invariance and differential item functioning.

Science.gov (United States)

Bauer, Daniel J

2017-09-01

The evaluation of measurement invariance is an important step in establishing the validity and comparability of measurements across individuals. Most commonly, measurement invariance has been examined using 1 of 2 primary latent variable modeling approaches: the multiple groups model or the multiple-indicator multiple-cause (MIMIC) model. Both approaches offer opportunities to detect differential item functioning within multi-item scales, and thereby to test measurement invariance, but both approaches also have significant limitations. The multiple groups model allows 1 to examine the invariance of all model parameters but only across levels of a single categorical individual difference variable (e.g., ethnicity). In contrast, the MIMIC model permits both categorical and continuous individual difference variables (e.g., sex and age) but permits only a subset of the model parameters to vary as a function of these characteristics. The current article argues that moderated nonlinear factor analysis (MNLFA) constitutes an alternative, more flexible model for evaluating measurement invariance and differential item functioning. We show that the MNLFA subsumes and combines the strengths of the multiple group and MIMIC models, allowing for a full and simultaneous assessment of measurement invariance and differential item functioning across multiple categorical and/or continuous individual difference variables. The relationships between the MNLFA model and the multiple groups and MIMIC models are shown mathematically and via an empirical demonstration. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Employee subjective well-being and physiological functioning: An integrative model

Directory of Open Access Journals (Sweden)

Lauren Kuykendall

2015-06-01

Full Text Available Research shows that worker subjective well-being influences physiological functioning—an early signal of poor health outcomes. While several theoretical perspectives provide insights on this relationship, the literature lacks an integrative framework explaining the relationship. We develop a conceptual model explaining the link between subjective well-being and physiological functioning in the context of work. Integrating positive psychology and occupational stress perspectives, our model explains the relationship between subjective well-being and physiological functioning as a result of the direct influence of subjective well-being on physiological functioning and of their common relationships with work stress and personal resources, both of which are influenced by job conditions.

Correlation function of four spins in the percolation model

Directory of Open Access Journals (Sweden)

Vladimir S. Dotsenko

2016-10-01

It is known that the four-point functions define the actual fusion rules of a particular model. In this respect, we find that fusion of two spins, of dimension Δσ=596, produce a new channel, in the 4-point function, which is due to the operator with dimension Δ=5/8.

Diversity-interaction modeling: estimating contributions of species identities and interactions to ecosystem function

DEFF Research Database (Denmark)

Kirwan, L; Connolly, J; Finn, J A

2009-01-01

to the roles of evenness, functional groups, and functional redundancy. These more parsimonious descriptions can be especially useful in identifying general diversity-function relationships in communities with large numbers of species. We provide an example of the application of the modeling framework......We develop a modeling framework that estimates the effects of species identity and diversity on ecosystem function and permits prediction of the diversity-function relationship across different types of community composition. Rather than just measure an overall effect of diversity, we separately....... These models describe community-level performance and thus do not require separate measurement of the performance of individual species. This flexible modeling approach can be tailored to test many hypotheses in biodiversity research and can suggest the interaction mechanisms that may be acting....

Modelling of Multi Input Transfer Function for Rainfall Forecasting in Batu City

Directory of Open Access Journals (Sweden)

Priska Arindya Purnama

2017-11-01

Full Text Available The aim of this research is to model and forecast the rainfall in Batu City using multi input transfer function model based on air temperature, humidity, wind speed and cloud. Transfer function model is a multivariate time series model which consists of an output series (Yt sequence expected to be effected by an input series (Xt and other inputs in a group called a noise series (Nt. Multi input transfer function model obtained is (b1,s1,r1 (b2,s2,r2 (b3,s3,r3 (b4,s4,r4(pn,qn = (0,0,0 (23,0,0 (1,2,0 (0,0,0 ([5,8],2 and shows that air temperature on t-day affects rainfall on t-day, rainfall on t-day is influenced by air humidity in the previous 23 days, rainfall on t-day is affected by wind speed in the previous day , and rainfall on day t is affected by clouds on day t. The results of rainfall forecasting in Batu City with multi input transfer function model can be said to be accurate, because it produces relatively small RMSE value. The value of RMSE data forecasting training is 7.7921 while forecasting data testing is 4.2184. Multi-input transfer function model is suitable for rainfall in Batu City.

Regulator Loss Functions and Hierarchical Modeling for Safety Decision Making.

Science.gov (United States)

Hatfield, Laura A; Baugh, Christine M; Azzone, Vanessa; Normand, Sharon-Lise T

2017-07-01

Regulators must act to protect the public when evidence indicates safety problems with medical devices. This requires complex tradeoffs among risks and benefits, which conventional safety surveillance methods do not incorporate. To combine explicit regulator loss functions with statistical evidence on medical device safety signals to improve decision making. In the Hospital Cost and Utilization Project National Inpatient Sample, we select pediatric inpatient admissions and identify adverse medical device events (AMDEs). We fit hierarchical Bayesian models to the annual hospital-level AMDE rates, accounting for patient and hospital characteristics. These models produce expected AMDE rates (a safety target), against which we compare the observed rates in a test year to compute a safety signal. We specify a set of loss functions that quantify the costs and benefits of each action as a function of the safety signal. We integrate the loss functions over the posterior distribution of the safety signal to obtain the posterior (Bayes) risk; the preferred action has the smallest Bayes risk. Using simulation and an analysis of AMDE data, we compare our minimum-risk decisions to a conventional Z score approach for classifying safety signals. The 2 rules produced different actions for nearly half of hospitals (45%). In the simulation, decisions that minimize Bayes risk outperform Z score-based decisions, even when the loss functions or hierarchical models are misspecified. Our method is sensitive to the choice of loss functions; eliciting quantitative inputs to the loss functions from regulators is challenging. A decision-theoretic approach to acting on safety signals is potentially promising but requires careful specification of loss functions in consultation with subject matter experts.

Software Design Modelling with Functional Petri Nets | Bakpo ...

African Journals Online (AJOL)

Software Design Modelling with Functional Petri Nets. ... of structured programs and a FPN Software prototype proposed for the conventional programming construct: if-then-else statement. ... EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

Development and Validation of a Predictive Model for Functional Outcome After Stroke Rehabilitation: The Maugeri Model.

Science.gov (United States)

Scrutinio, Domenico; Lanzillo, Bernardo; Guida, Pietro; Mastropasqua, Filippo; Monitillo, Vincenzo; Pusineri, Monica; Formica, Roberto; Russo, Giovanna; Guarnaschelli, Caterina; Ferretti, Chiara; Calabrese, Gianluigi

2017-12-01

Prediction of outcome after stroke rehabilitation may help clinicians in decision-making and planning rehabilitation care. We developed and validated a predictive tool to estimate the probability of achieving improvement in physical functioning (model 1) and a level of independence requiring no more than supervision (model 2) after stroke rehabilitation. The models were derived from 717 patients admitted for stroke rehabilitation. We used multivariable logistic regression analysis to build each model. Then, each model was prospectively validated in 875 patients. Model 1 included age, time from stroke occurrence to rehabilitation admission, admission motor and cognitive Functional Independence Measure scores, and neglect. Model 2 included age, male gender, time since stroke onset, and admission motor and cognitive Functional Independence Measure score. Both models demonstrated excellent discrimination. In the derivation cohort, the area under the curve was 0.883 (95% confidence intervals, 0.858-0.910) for model 1 and 0.913 (95% confidence intervals, 0.884-0.942) for model 2. The Hosmer-Lemeshow χ 2 was 4.12 ( P =0.249) and 1.20 ( P =0.754), respectively. In the validation cohort, the area under the curve was 0.866 (95% confidence intervals, 0.840-0.892) for model 1 and 0.850 (95% confidence intervals, 0.815-0.885) for model 2. The Hosmer-Lemeshow χ 2 was 8.86 ( P =0.115) and 34.50 ( P =0.001), respectively. Both improvement in physical functioning (hazard ratios, 0.43; 0.25-0.71; P =0.001) and a level of independence requiring no more than supervision (hazard ratios, 0.32; 0.14-0.68; P =0.004) were independently associated with improved 4-year survival. A calculator is freely available for download at https://goo.gl/fEAp81. This study provides researchers and clinicians with an easy-to-use, accurate, and validated predictive tool for potential application in rehabilitation research and stroke management. © 2017 American Heart Association, Inc.

Functional Freedom: A Psychological Model of Freedom in Decision-Making

Science.gov (United States)

Lau, Stephan; Hiemisch, Anette

2017-01-01

The freedom of a decision is not yet sufficiently described as a psychological variable. We present a model of functional decision freedom that aims to fill that role. The model conceptualizes functional freedom as a capacity of people that varies depending on certain conditions of a decision episode. It denotes an inner capability to consciously shape complex decisions according to one’s own values and needs. Functional freedom depends on three compensatory dimensions: it is greatest when the decision-maker is highly rational, when the structure of the decision is highly underdetermined, and when the decision process is strongly based on conscious thought and reflection. We outline possible research questions, argue for psychological benefits of functional decision freedom, and explicate the model’s implications on current knowledge and research. In conclusion, we show that functional freedom is a scientific variable, permitting an additional psychological foothold in research on freedom, and that is compatible with a deterministic worldview. PMID:28678165

Improving the Functional Diagnostic Process using Dynamic Master Logic Diagram (DMLD) Modeling Strategy

International Nuclear Information System (INIS)

Mohamed, A.H.

2008-01-01

In recent years, state based functional diagnostic systems have gained a growing attention among the model based diagnostic systems. They have been used to diagnose the new faults of the complex systems. On the other hand, a main point considered against it is its subjective, and the inability of reusing the knowledge gathered from one engineer by others. Different methods have been' suggested to solve these problems. In the same way, the suggested functional diagnostic system introduces the uses of Dynamic Master Logic Diagram (DMLD) modeling strategy for the functional diagnostic systems. DMLD has proven its power as a good modeling strategy. It can model the functions of the system's components in terms of a set of defined primitives for the domain of applications. However, the suggested system can use the DMLD technique to model the small functions of the system according to the defined primitives of its domain. So, the modeling process of the system is relatively invariant from one modeler to another. Also, the functions defined can be reused by other users in the domain for solving different problems. Besides, it can deal with the complex system in a flexible manner. Thus, the proposed system can improve the performance of the state based functional diagnostic systems. It can be applied for a wide area of the complex systems. It has been applied for a fluid system as a case of the real-time systems. The suggested system has proved its success as a powerful practical state based functional diagnostic system

NCACO-score: An effective main-chain dependent scoring function for structure modeling

Directory of Open Access Journals (Sweden)

Dong Xiaoxi

2011-05-01

Full Text Available Abstract Background Development of effective scoring functions is a critical component to the success of protein structure modeling. Previously, many efforts have been dedicated to the development of scoring functions. Despite these efforts, development of an effective scoring function that can achieve both good accuracy and fast speed still presents a grand challenge. Results Based on a coarse-grained representation of a protein structure by using only four main-chain atoms: N, Cα, C and O, we develop a knowledge-based scoring function, called NCACO-score, that integrates different structural information to rapidly model protein structure from sequence. In testing on the Decoys'R'Us sets, we found that NCACO-score can effectively recognize native conformers from their decoys. Furthermore, we demonstrate that NCACO-score can effectively guide fragment assembly for protein structure prediction, which has achieved a good performance in building the structure models for hard targets from CASP8 in terms of both accuracy and speed. Conclusions Although NCACO-score is developed based on a coarse-grained model, it is able to discriminate native conformers from decoy conformers with high accuracy. NCACO is a very effective scoring function for structure modeling.

A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.

Science.gov (United States)

Huertas, Ismael; Oldehinkel, Marianne; van Oort, Erik S B; Garcia-Solis, David; Mir, Pablo; Beckmann, Christian F; Marquand, Andre F

2017-11-01

The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach

Simple model for low-frequency guitar function

DEFF Research Database (Denmark)

Christensen, Ove; Vistisen, Bo B.

1980-01-01

- frequency guitar function. The model predicts frequency responce of sound pressure and top plate mobility which are in close quantitative agreement with experimental responses. The absolute sound pressure level and mobility level are predicted to within a few decibels, and the equivalent piston area......The frequency response of sound pressure and top plate mobility is studied around the two first resonances of the guitar. These resonances are shown to result from a coupling between the fundamental top plate mode and the Helmholtz resonance of the cavity. A simple model is proposed for low...

Transposons As Tools for Functional Genomics in Vertebrate Models.

Science.gov (United States)

Kawakami, Koichi; Largaespada, David A; Ivics, Zoltán

2017-11-01

Genetic tools and mutagenesis strategies based on transposable elements are currently under development with a vision to link primary DNA sequence information to gene functions in vertebrate models. By virtue of their inherent capacity to insert into DNA, transposons can be developed into powerful tools for chromosomal manipulations. Transposon-based forward mutagenesis screens have numerous advantages including high throughput, easy identification of mutated alleles, and providing insight into genetic networks and pathways based on phenotypes. For example, the Sleeping Beauty transposon has become highly instrumental to induce tumors in experimental animals in a tissue-specific manner with the aim of uncovering the genetic basis of diverse cancers. Here, we describe a battery of mutagenic cassettes that can be applied in conjunction with transposon vectors to mutagenize genes, and highlight versatile experimental strategies for the generation of engineered chromosomes for loss-of-function as well as gain-of-function mutagenesis for functional gene annotation in vertebrate models, including zebrafish, mice, and rats. Copyright © 2017 Elsevier Ltd. All rights reserved.

Bayesian spatiotemporal model of fMRI data using transfer functions.

Science.gov (United States)

Quirós, Alicia; Diez, Raquel Montes; Wilson, Simon P

2010-09-01

This research describes a new Bayesian spatiotemporal model to analyse BOLD fMRI studies. In the temporal dimension, we describe the shape of the hemodynamic response function (HRF) with a transfer function model. The spatial continuity and local homogeneity of the evoked responses are modelled by a Gaussian Markov random field prior on the parameter indicating activations. The proposal constitutes an extension of the spatiotemporal model presented in a previous approach [Quirós, A., Montes Diez, R. and Gamerman, D., 2010. Bayesian spatiotemporal model of fMRI data, Neuroimage, 49: 442-456], offering more flexibility in the estimation of the HRF and computational advantages in the resulting MCMC algorithm. Simulations from the model are performed in order to ascertain the performance of the sampling scheme and the ability of the posterior to estimate model parameters, as well as to check the model sensitivity to signal to noise ratio. Results are shown on synthetic data and on a real data set from a block-design fMRI experiment. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Globally COnstrained Local Function Approximation via Hierarchical Modelling, a Framework for System Modelling under Partial Information

DEFF Research Database (Denmark)

Øjelund, Henrik; Sadegh, Payman

2000-01-01

be obtained. This paper presents a new approach for system modelling under partial (global) information (or the so called Gray-box modelling) that seeks to perserve the benefits of the global as well as local methodologies sithin a unified framework. While the proposed technique relies on local approximations......Local function approximations concern fitting low order models to weighted data in neighbourhoods of the points where the approximations are desired. Despite their generality and convenience of use, local models typically suffer, among others, from difficulties arising in physical interpretation...... simultaneously with the (local estimates of) function values. The approach is applied to modelling of a linear time variant dynamic system under prior linear time invariant structure where local regression fails as a result of high dimensionality....

Exploiting the functional and taxonomic structure of genomic data by probabilistic topic modeling.

Science.gov (United States)

Chen, Xin; Hu, Xiaohua; Lim, Tze Y; Shen, Xiajiong; Park, E K; Rosen, Gail L

2012-01-01

In this paper, we present a method that enable both homology-based approach and composition-based approach to further study the functional core (i.e., microbial core and gene core, correspondingly). In the proposed method, the identification of major functionality groups is achieved by generative topic modeling, which is able to extract useful information from unlabeled data. We first show that generative topic model can be used to model the taxon abundance information obtained by homology-based approach and study the microbial core. The model considers each sample as a “document,” which has a mixture of functional groups, while each functional group (also known as a “latent topic”) is a weight mixture of species. Therefore, estimating the generative topic model for taxon abundance data will uncover the distribution over latent functions (latent topic) in each sample. Second, we show that, generative topic model can also be used to study the genome-level composition of “N-mer” features (DNA subreads obtained by composition-based approaches). The model consider each genome as a mixture of latten genetic patterns (latent topics), while each functional pattern is a weighted mixture of the “N-mer” features, thus the existence of core genomes can be indicated by a set of common N-mer features. After studying the mutual information between latent topics and gene regions, we provide an explanation of the functional roles of uncovered latten genetic patterns. The experimental results demonstrate the effectiveness of proposed method.

Constructing rule-based models using the belief functions framework

NARCIS (Netherlands)

Almeida, R.J.; Denoeux, T.; Kaymak, U.; Greco, S.; Bouchon-Meunier, B.; Coletti, G.; Fedrizzi, M.; Matarazzo, B.; Yager, R.R.

2012-01-01

Abstract. We study a new approach to regression analysis. We propose a new rule-based regression model using the theoretical framework of belief functions. For this purpose we use the recently proposed Evidential c-means (ECM) to derive rule-based models solely from data. ECM allocates, for each

Gaussian copula as a likelihood function for environmental models

Science.gov (United States)

Wani, O.; Espadas, G.; Cecinati, F.; Rieckermann, J.

2017-12-01

Parameter estimation of environmental models always comes with uncertainty. To formally quantify this parametric uncertainty, a likelihood function needs to be formulated, which is defined as the probability of observations given fixed values of the parameter set. A likelihood function allows us to infer parameter values from observations using Bayes' theorem. The challenge is to formulate a likelihood function that reliably describes the error generating processes which lead to the observed monitoring data, such as rainfall and runoff. If the likelihood function is not representative of the error statistics, the parameter inference will give biased parameter values. Several uncertainty estimation methods that are currently being used employ Gaussian processes as a likelihood function, because of their favourable analytical properties. Box-Cox transformation is suggested to deal with non-symmetric and heteroscedastic errors e.g. for flow data which are typically more uncertain in high flows than in periods with low flows. Problem with transformations is that the results are conditional on hyper-parameters, for which it is difficult to formulate the analyst's belief a priori. In an attempt to address this problem, in this research work we suggest learning the nature of the error distribution from the errors made by the model in the "past" forecasts. We use a Gaussian copula to generate semiparametric error distributions . 1) We show that this copula can be then used as a likelihood function to infer parameters, breaking away from the practice of using multivariate normal distributions. Based on the results from a didactical example of predicting rainfall runoff, 2) we demonstrate that the copula captures the predictive uncertainty of the model. 3) Finally, we find that the properties of autocorrelation and heteroscedasticity of errors are captured well by the copula, eliminating the need to use transforms. In summary, our findings suggest that copulas are an

The Functional Segregation and Integration Model: Mixture Model Representations of Consistent and Variable Group-Level Connectivity in fMRI

DEFF Research Database (Denmark)

Churchill, Nathan William; Madsen, Kristoffer Hougaard; Mørup, Morten

2016-01-01

flexibility: they only estimate segregated structure and do not model interregional functional connectivity, nor do they account for network variability across voxels or between subjects. To address these issues, this letter develops the functional segregation and integration model (FSIM). This extension......The brain consists of specialized cortical regions that exchange information between each other, reflecting a combination of segregated (local) and integrated (distributed) processes that define brain function. Functional magnetic resonance imaging (fMRI) is widely used to characterize...... brain regions where network expression predicts subject age in the experimental data. Thus, the FSIM is effective at summarizing functional connectivity structure in group-level fMRI, with applications in modeling the relationships between network variability and behavioral/demographic variables....

Lyapunov functions for a dengue disease transmission model

International Nuclear Information System (INIS)

Tewa, Jean Jules; Dimi, Jean Luc; Bowong, Samuel

2009-01-01

In this paper, we study a model for the dynamics of dengue fever when only one type of virus is present. For this model, Lyapunov functions are used to show that when the basic reproduction ratio is less than or equal to one, the disease-free equilibrium is globally asymptotically stable, and when it is greater than one there is an endemic equilibrium which is also globally asymptotically stable.

Lyapunov functions for a dengue disease transmission model

Energy Technology Data Exchange (ETDEWEB)

Tewa, Jean Jules [Department of Mathematics, Faculty of Science, University of Yaounde I, P.O. Box 812, Yaounde (Cameroon)], E-mail: tewa@univ-metz.fr; Dimi, Jean Luc [Department of Mathematics, Faculty of Science, University Marien Ngouabi, P.O. Box 69, Brazzaville (Congo, The Democratic Republic of the)], E-mail: jldimi@yahoo.fr; Bowong, Samuel [Department of Mathematics and Computer Science, Faculty of Science, University of Douala, P.O. Box 24157, Douala (Cameroon)], E-mail: samuelbowong@yahoo.fr

2009-01-30

In this paper, we study a model for the dynamics of dengue fever when only one type of virus is present. For this model, Lyapunov functions are used to show that when the basic reproduction ratio is less than or equal to one, the disease-free equilibrium is globally asymptotically stable, and when it is greater than one there is an endemic equilibrium which is also globally asymptotically stable.

Partially linear varying coefficient models stratified by a functional covariate

KAUST Repository

Maity, Arnab; Huang, Jianhua Z.

2012-01-01

We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric

Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model

Directory of Open Access Journals (Sweden)

Yazid Edwar

2014-07-01

Full Text Available This paper proposes basis functions based time domain Volterra model for nonlinear system identification. The Volterra kernels are expanded by using complex exponential basis functions and estimated via genetic algorithm (GA. The accuracy and practicability of the proposed method are then assessed experimentally from a scaled 1:100 model of a prototype truss spar platform. Identification results in time and frequency domain are presented and coherent functions are performed to check the quality of the identification results. It is shown that results between experimental data and proposed method are in good agreement.

A systemic approach for modeling soil functions

Science.gov (United States)

Vogel, Hans-Jörg; Bartke, Stephan; Daedlow, Katrin; Helming, Katharina; Kögel-Knabner, Ingrid; Lang, Birgit; Rabot, Eva; Russell, David; Stößel, Bastian; Weller, Ulrich; Wiesmeier, Martin; Wollschläger, Ute

2018-03-01

The central importance of soil for the functioning of terrestrial systems is increasingly recognized. Critically relevant for water quality, climate control, nutrient cycling and biodiversity, soil provides more functions than just the basis for agricultural production. Nowadays, soil is increasingly under pressure as a limited resource for the production of food, energy and raw materials. This has led to an increasing demand for concepts assessing soil functions so that they can be adequately considered in decision-making aimed at sustainable soil management. The various soil science disciplines have progressively developed highly sophisticated methods to explore the multitude of physical, chemical and biological processes in soil. It is not obvious, however, how the steadily improving insight into soil processes may contribute to the evaluation of soil functions. Here, we present to a new systemic modeling framework that allows for a consistent coupling between reductionist yet observable indicators for soil functions with detailed process understanding. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. The non-linear character of these interactions produces stability and resilience of soil with respect to functional characteristics. We anticipate that this new conceptional framework will integrate the various soil science disciplines and help identify important future research questions at the interface between disciplines. It allows the overwhelming complexity of soil systems to be adequately coped with and paves the way for steadily improving our capability to assess soil functions based on scientific understanding.

Validation of a functional model for integration of safety into process system design

DEFF Research Database (Denmark)

Wu, J.; Lind, M.; Zhang, X.

2015-01-01

with the process system functionalities as required for the intended safety applications. To provide the scientific rigor and facilitate the acceptance of qualitative modelling, this contribution focuses on developing a scientifically based validation method for functional models. The Multilevel Flow Modeling (MFM...

Calculations of higher twist distribution functions in the MIT bag model

International Nuclear Information System (INIS)

Signal, A.I.

1997-01-01

We calculate all twist-2, -3 and -4 parton distribution functions involving two quark correlations using the wave function of the MIT bag model. The distributions are evolved up to experimental scales and combined to give the various nucleon structure functions. Comparisons with recent experimental data on higher twist structure functions at moderate values of Q 2 give good agreement with the calculated structure functions. (orig.)

Model parameters for representative wetland plant functional groups

Science.gov (United States)

Williams, Amber S.; Kiniry, James R.; Mushet, David M.; Smith, Loren M.; McMurry, Scott T.; Attebury, Kelly; Lang, Megan; McCarty, Gregory W.; Shaffer, Jill A.; Effland, William R.; Johnson, Mari-Vaughn V.

2017-01-01

Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and realistic simulation of the upland and wetland plant growth cycles. Objectives of this study were to quantify leaf area index (LAI), light extinction coefficient (k), and plant nitrogen (N), phosphorus (P), and potassium (K) concentrations in natural stands of representative plant species for some major plant functional groups in the United States. Functional groups in this study were based on these parameters and plant growth types to enable process-based modeling. We collected data at four locations representing some of the main wetland regions of the United States. At each site, we collected on-the-ground measurements of fraction of light intercepted, LAI, and dry matter within the 2013–2015 growing seasons. Maximum LAI and k variables showed noticeable variations among sites and years, while overall averages and functional group averages give useful estimates for multisite simulation modeling. Variation within each species gives an indication of what can be expected in such natural ecosystems. For P and K, the concentrations from highest to lowest were spikerush (Eleocharis macrostachya), reed canary grass (Phalaris arundinacea), smartweed (Polygonum spp.), cattail (Typha spp.), and hardstem bulrush (Schoenoplectus acutus). Spikerush had the highest N concentration, followed by smartweed, bulrush, reed canary grass, and then cattail. These parameters will be useful for the actual wetland species measured and for the wetland plant functional groups they represent. These parameters and the associated process-based models offer promise as valuable tools for evaluating environmental benefits of wetlands and for evaluating impacts of various agronomic practices in

Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

Science.gov (United States)

Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

2018-05-07

A Bayesian model for sparse, hierarchical inverse covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fmri, meg and eeg data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in meg beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.

Verifying the functional ability of microstructured surfaces by model-based testing

Science.gov (United States)

Hartmann, Wito; Weckenmann, Albert

2014-09-01

Micro- and nanotechnology enables the use of new product features such as improved light absorption, self-cleaning or protection, which are based, on the one hand, on the size of functional nanostructures and the other hand, on material-specific properties. With the need to reliably measure progressively smaller geometric features, coordinate and surface-measuring instruments have been refined and now allow high-resolution topography and structure measurements down to the sub-nanometre range. Nevertheless, in many cases it is not possible to make a clear statement about the functional ability of the workpiece or its topography because conventional concepts of dimensioning and tolerancing are solely geometry oriented and standardized surface parameters are not sufficient to consider interaction with non-geometric parameters, which are dominant for functions such as sliding, wetting, sealing and optical reflection. To verify the functional ability of microstructured surfaces, a method was developed based on a parameterized mathematical-physical model of the function. From this model, function-related properties can be identified and geometric parameters can be derived, which may be different for the manufacturing and verification processes. With this method it is possible to optimize the definition of the shape of the workpiece regarding the intended function by applying theoretical and experimental knowledge, as well as modelling and simulation. Advantages of this approach will be discussed and demonstrated by the example of a microstructured inking roll.

Colour-independent partition functions in coloured vertex models

Energy Technology Data Exchange (ETDEWEB)

Foda, O., E-mail: omar.foda@unimelb.edu.au [Dept. of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010 (Australia); Wheeler, M., E-mail: mwheeler@lpthe.jussieu.fr [Laboratoire de Physique Théorique et Hautes Energies, CNRS UMR 7589 (France); Université Pierre et Marie Curie – Paris 6, 4 place Jussieu, 75252 Paris cedex 05 (France)

2013-06-11

We study lattice configurations related to S{sub n}, the scalar product of an off-shell state and an on-shell state in rational A{sub n} integrable vertex models, n∈{1,2}. The lattice lines are colourless and oriented. The state variables are n conserved colours that flow along the line orientations, but do not necessarily cover every bond in the lattice. Choosing boundary conditions such that the positions where the colours flow into the lattice are fixed, and where they flow out are summed over, we show that the partition functions of these configurations, with these boundary conditions, are n-independent. Our results extend to trigonometric A{sub n} models, and to all n. This n-independence explains, in vertex-model terms, results from recent studies of S{sub 2} (Caetano and Vieira, 2012, [1], Wheeler, (arXiv:1204.2089), [2]). Namely, 1.S{sub 2}, which depends on two sets of Bethe roots, {b_1} and {b_2}, and cannot (as far as we know) be expressed in single determinant form, degenerates in the limit {b_1}→∞, and/or {b_2}→∞, into a product of determinants, 2. Each of the latter determinants is an A{sub 1} vertex-model partition function.

Colour-independent partition functions in coloured vertex models

International Nuclear Information System (INIS)

Foda, O.; Wheeler, M.

2013-01-01

We study lattice configurations related to S n , the scalar product of an off-shell state and an on-shell state in rational A n integrable vertex models, n∈{1,2}. The lattice lines are colourless and oriented. The state variables are n conserved colours that flow along the line orientations, but do not necessarily cover every bond in the lattice. Choosing boundary conditions such that the positions where the colours flow into the lattice are fixed, and where they flow out are summed over, we show that the partition functions of these configurations, with these boundary conditions, are n-independent. Our results extend to trigonometric A n models, and to all n. This n-independence explains, in vertex-model terms, results from recent studies of S 2 (Caetano and Vieira, 2012, [1], Wheeler, (arXiv:1204.2089), [2]). Namely, 1.S 2 , which depends on two sets of Bethe roots, {b 1 } and {b 2 }, and cannot (as far as we know) be expressed in single determinant form, degenerates in the limit {b 1 }→∞, and/or {b 2 }→∞, into a product of determinants, 2. Each of the latter determinants is an A 1 vertex-model partition function

Spin-density functional for exchange anisotropic Heisenberg model

International Nuclear Information System (INIS)

Prata, G.N.; Penteado, P.H.; Souza, F.C.; Libero, Valter L.

2009-01-01

Ground-state energies for antiferromagnetic Heisenberg models with exchange anisotropy are estimated by means of a local-spin approximation made in the context of the density functional theory. Correlation energy is obtained using the non-linear spin-wave theory for homogeneous systems from which the spin functional is built. Although applicable to chains of any size, the results are shown for small number of sites, to exhibit finite-size effects and allow comparison with exact-numerical data from direct diagonalization of small chains.

Improvement of a multi-stage model for the modeling of a functionalized nursing bed as support for the sensor-assisted function-alization of furniture in the hospital and care sector

Directory of Open Access Journals (Sweden)

Kitzig Andreas

2017-09-01

Full Text Available Development of preparation-free functionalized furniture based patient monitoring systems for use in the area of home- or stationary- care is often empirically driven. In particular, functionalization of furniture by means of different sensors is strongly affected by this development methodology. As a result, the systems are often not extensive-ly extendable or cannot be optimized because basic mechanisms are not comprehensible. In order to support development or optimization, a modelling approach is often useful. Thus, using a more comprehensive approach the required sensitivity of the sensors as well as their position in the system can be derived from a simulation model. In order to solve this problem, a multi-stage model was introduced at the BMT conference in 2014 by the authors, which allows the designer to model the entire system. The model has been extended and improved in the meantime and the achieved progress is presented in this work. The presented modelling approach can be divided into three main components. These are the person under supervision, the furniture (in our case a nursing bed and the sensors (force measuring cells which are modelled separately. In this work the main focus will be on improving the modelling of the human movement process and its implementation. Furthermore, the modelling of the sensor behavior in the nursing bed is described in detail with regard to their oscillation behavior and the influence on the model.

Mathematical modelling of enzyme synthesis during fermentations: the Q-functions

Energy Technology Data Exchange (ETDEWEB)

Nielsen, H K; Martiny, S C

1981-01-01

In modeling enzyme synthesis, the Q-function has been generalized to describe ordinary induction and repression as well as mixed induction-repression. The practical use of the Q-function as found in the literature was considered, especially the implications of applying fractional exponents.

Testing a Model of Functional Impairment in Telephone Crisis Support Workers.

Science.gov (United States)

Kitchingman, Taneile A; Wilson, Coralie J; Caputi, Peter; Wilson, Ian; Woodward, Alan

2017-11-01

It is well known that helping professionals experience functional impairment related to elevated symptoms of psychological distress as a result of frequent empathic engagement with distressed others. Whether telephone crisis support workers are impacted in a similar way is not currently reported in the literature. The purpose of this study was to test a hypothesized model of factors contributing to functional impairment in telephone crisis support workers. A national sample of 210 telephone crisis support workers completed an online survey including measures of emotion regulation, symptoms of general psychological distress and suicidal ideation, intentions to seek help for symptoms, and functional impairment. Structural equation modeling was used to test the fit of the data to the hypothesized model. Goodness-of-fit indices were adequate and supported the interactive effects of emotion regulation, general psychological distress, suicidal ideation, and intentions to seek help for ideation on functional impairment. These results warrant the deliberate management of telephone crisis support workers' impairment through service selection, training, supervision, and professional development strategies. Future research replicating and extending this model will further inform the modification and/or development of strategies to optimize telephone crisis support workers' well-being and delivery of support to callers.

Development of an Upper Extremity Function Measurement Model.

Science.gov (United States)

Hong, Ickpyo; Simpson, Annie N; Li, Chih-Ying; Velozo, Craig A

This study demonstrated the development of a measurement model for gross upper-extremity function (GUE). The dependent variable was the Rasch calibration of the 27 ICF-GUE test items. The predictors were object weight, lifting distance from floor, carrying, and lifting. Multiple regression was used to investigate the contribution that each independent variable makes to the model with 203 outpatients. Object weight and lifting distance were the only statistically and clinically significant independent variables in the model, accounting for 83% of the variance (p model indicates that, with each one pound increase in object weight, item challenge increases by 0.16 (p measurement model for the ICF-GUE can be explained by object weight and distance lifted from the floor.

Analysis of a Heroin Epidemic Model with Saturated Treatment Function

Directory of Open Access Journals (Sweden)

Isaac Mwangi Wangari

2017-01-01

Full Text Available A mathematical model is developed that examines how heroin addiction spreads in society. The model is formulated to take into account the treatment of heroin users by incorporating a realistic functional form that “saturates” representing the limited availability of treatment. Bifurcation analysis reveals that the model has an intrinsic backward bifurcation whenever the saturation parameter is larger than a fixed threshold. We are particularly interested in studying the model’s global stability. In the absence of backward bifurcations, Lyapunov functions can often be found and used to prove global stability. However, in the presence of backward bifurcations, such Lyapunov functions may not exist or may be difficult to construct. We make use of the geometric approach to global stability to derive a condition that ensures that the system is globally asymptotically stable. Numerical simulations are also presented to give a more complete representation of the model dynamics. Sensitivity analysis performed by Latin hypercube sampling (LHS suggests that the effective contact rate in the population, the relapse rate of heroin users undergoing treatment, and the extent of saturation of heroin users are mechanisms fuelling heroin epidemic proliferation.

A universal Model-R Coupler to facilitate the use of R functions for model calibration and analysis

Science.gov (United States)

Wu, Yiping; Liu, Shuguang; Yan, Wende

2014-01-01

Mathematical models are useful in various fields of science and engineering. However, it is a challenge to make a model utilize the open and growing functions (e.g., model inversion) on the R platform due to the requirement of accessing and revising the model's source code. To overcome this barrier, we developed a universal tool that aims to convert a model developed in any computer language to an R function using the template and instruction concept of the Parameter ESTimation program (PEST) and the operational structure of the R-Soil and Water Assessment Tool (R-SWAT). The developed tool (Model-R Coupler) is promising because users of any model can connect an external algorithm (written in R) with their model to implement various model behavior analyses (e.g., parameter optimization, sensitivity and uncertainty analysis, performance evaluation, and visualization) without accessing or modifying the model's source code.

Neutron strength functions: the link between resolved resonances and the optical model

International Nuclear Information System (INIS)

Moldauer, P.A.

1980-01-01

Neutron strength functions and scattering radii are useful as energy and channel radius independent parameters that characterize neutron scattering resonances and provide a connection between R-matrix resonance analysis and the optical model. The choice of R-matrix channel radii is discussed, as are limitations on the accuracies of strength functions. New definitions of the p-wave strength function and scattering radius are proposed. For light nuclei, where strength functions display optical model energy variations over the resolved resonances, a doubly reduced partial neutron width is introduced for more meaningful statistical analyses of widths. The systematic behavior of strength functions and scattering radii is discussed

Functional techniques in quantum field theory and two-dimensional models

International Nuclear Information System (INIS)

Souza, C. Farina de.

1985-03-01

Functional methods applied to Quantum Field Theory are studied. It is shown how to construct the Generating Functional using three of the most important methods existent in the literature, due to Feynman, Symanzik and Schwinger. The Axial Anomaly is discussed in the usual way, and a non perturbative method due to Fujikawa to obtain this anomaly in the path integral formalism is presented. The ''Roskies-Shaposnik-Fujikawa's method'', which makes use of Fujikawa's original idea to solve bidimensional models, is introduced in the Schwinger's model, which, in turn, is applied to obtain the exact solution of the axial model. It is discussed briefly how different regularization procedures can affect the theory in question. (author)

Modelling of multidimensional quantum systems by the numerical functional integration

International Nuclear Information System (INIS)

Lobanov, Yu.Yu.; Zhidkov, E.P.

1990-01-01

The employment of the numerical functional integration for the description of multidimensional systems in quantum and statistical physics is considered. For the multiple functional integrals with respect to Gaussian measures in the full separable metric spaces the new approximation formulas exact on a class of polynomial functionals of a given summary degree are constructed. The use of the formulas is demonstrated on example of computation of the Green function and the ground state energy in multidimensional Calogero model. 15 refs.; 2 tabs

Canine intrahepatic vasculature: is a functional anatomic model relevant to the dog?

Science.gov (United States)

Hall, Jon L; Mannion, Paddy; Ladlow, Jane F

2015-01-01

To clarify canine intrahepatic portal and hepatic venous system anatomy using corrosion casting and advanced imaging and to devise a novel functional anatomic model of the canine liver to investigate whether this could help guide the planning and surgical procedure of partial hepatic lobectomy and interventional radiological procedures. Prospective experimental study. Adult Greyhound cadavers (n = 8). Portal and hepatic vein corrosion casts of healthy livers were assessed using computed tomography (CT). The hepatic lobes have a consistent hilar hepatic and portal vein supply with some variation in the number of intrahepatic branches. For all specimens, 3 surgically resectable areas were identified in the left lateral lobe and 2 surgically resectable areas were identified in the right medial lobe as defined by a functional anatomic model. CT of detailed acrylic casts allowed complex intrahepatic vascular relationships to be investigated and compared with previous studies. Improving understanding of the intrahepatic vascular supply facilitates interpretation of advanced images in clinical patients, the planning and performance of surgical procedures, and may facilitate interventional vascular procedures, such as intravenous embolization of portosystemic shunts. Functional division of the canine liver similar to human models is possible. The left lateral and right medial lobes can be consistently divided into surgically resectable functional areas and partial lobectomies can be performed following a functional model; further study in clinically affected animals would be required to investigate the relevance of this functional model in the dog. © Copyright 2014 by The American College of Veterinary Surgeons.

A discrete stress-strength interference model based on universal generating function

International Nuclear Information System (INIS)

An Zongwen; Huang Hongzhong; Liu Yu

2008-01-01

Continuous stress-strength interference (SSI) model regards stress and strength as continuous random variables with known probability density function. This, to some extent, results in a limitation of its application. In this paper, stress and strength are treated as discrete random variables, and a discrete SSI model is presented by using the universal generating function (UGF) method. Finally, case studies demonstrate the validity of the discrete model in a variety of circumstances, in which stress and strength can be represented by continuous random variables, discrete random variables, or two groups of experimental data

Modeling and Circumventing the Effect of Sediments and Water Column on Receiver Functions

Science.gov (United States)

Audet, P.

2017-12-01

Teleseismic P-wave receiver functions are routinely used to resolve crust and mantle structure in various geologic settings. Receiver functions are approximations to the Earth's Green's functions and are composed of various scattered phase arrivals, depending on the complexity of the underlying Earth structure. For simple structure, the dominant arrivals (converted and back-scattered P-to-S phases) are well separated in time and can be reliably used in estimating crustal velocity structure. In the presence of sedimentary layers, strong reverberations typically produce high-amplitude oscillations that contaminate the early part of the wave train and receiver functions can be difficult to interpret in terms of underlying structure. The effect of a water column also limits the interpretability of under-water receiver functions due to the additional acoustic wave propagating within the water column that can contaminate structural arrivals. We perform numerical modeling of teleseismic Green's functions and receiver functions using a reflectivity technique for a range of Earth models that include thin sedimentary layers and overlying water column. These modeling results indicate that, as expected, receiver functions are difficult to interpret in the presence of sediments, but the contaminating effect of the water column is dependent on the thickness of the water layer. To circumvent these effects and recover source-side structure, we propose using an approach based on transfer function modeling that bypasses receiver functions altogether and estimates crustal properties directly from the waveforms (Frederiksen and Delayney, 2015). Using this approach, reasonable assumptions about the properties of the sedimentary layer can be included in forward calculations of the Green's functions that are convolved with radial waveforms to predict vertical waveforms. Exploration of model space using Monte Carlo-style search and least-square waveform misfits can be performed to

A Prototype Symbolic Model of Canonical Functional Neuroanatomy of the Motor System

Science.gov (United States)

Rubin, Daniel L.; Halle, Michael; Musen, Mark; Kikinis, Ron

2008-01-01

Recent advances in bioinformatics have opened entire new avenues for organizing, integrating and retrieving neuroscientific data, in a digital, machine-processable format, which can be at the same time understood by humans, using ontological, symbolic data representations. Declarative information stored in ontological format can be perused and maintained by domain experts, interpreted by machines, and serve as basis for a multitude of decision-support, computerized simulation, data mining, and teaching applications. We have developed a prototype symbolic model of canonical neuroanatomy of the motor system. Our symbolic model is intended to support symbolic lookup, logical inference and mathematical modeling by integrating descriptive, qualitative and quantitative functional neuroanatomical knowledge. Furthermore, we show how our approach can be extended to modeling impaired brain connectivity in disease states, such as common movement disorders. In developing our ontology, we adopted a disciplined modeling approach, relying on a set of declared principles, a high-level schema, Aristotelian definitions, and a frame-based authoring system. These features, along with the use of the Unified Medical Language System (UMLS) vocabulary, enable the alignment of our functional ontology with an existing comprehensive ontology of human anatomy, and thus allow for combining the structural and functional views of neuroanatomy for clinical decision support and neuroanatomy teaching applications. Although the scope of our current prototype ontology is limited to a particular functional system in the brain, it may be possible to adapt this approach for modeling other brain functional systems as well. PMID:18164666

One-loop correlation functions in the model of noncritical fermionic strings

International Nuclear Information System (INIS)

Belokurov, V.V.; Iofa, M.Z.

1996-01-01

In the model of noncritical fermionic strings, the David-Distler-Kawai ansatz is used to study one-loop n-point (n≤4) correlation functions for the vertex operators of massless bosonic states. The action functional of the model is the sum of super-Liouville action functional for the conformal mode and the action functional of d scalar supermultiplets. It is assumed that the total cosmological term is equal to zero. The amplitudes are calculated as the residues at the pole of the correlation function that corresponds to the conservation of Liouville momentum in the form Σβi=Q(1-h), where Q=√(9-d)/2 and h is the genus of the work sheet. In the one-loop approximation, the amplitudes can be obtained in the modular-invariant form, provided that the coefficients appearing in the sum over spin structures depend on moduli. In this case, the modular measure is defined up to a modular-invariant factor. This arbitrariness can be used to represent one-point correlation functions in the same functional form as for strings of critical dimension

Characteristic function-based semiparametric inference for skew-symmetric models

KAUST Repository

Potgieter, Cornelis J.

2012-12-26

Skew-symmetric models offer a very flexible class of distributions for modelling data. These distributions can also be viewed as selection models for the symmetric component of the specified skew-symmetric distribution. The estimation of the location and scale parameters corresponding to the symmetric component is considered here, with the symmetric component known. Emphasis is placed on using the empirical characteristic function to estimate these parameters. This is made possible by an invariance property of the skew-symmetric family of distributions, namely that even transformations of random variables that are skew-symmetric have a distribution only depending on the symmetric density. A distance metric between the real components of the empirical and true characteristic functions is minimized to obtain the estimators. The method is semiparametric, in that the symmetric component is specified, but the skewing function is assumed unknown. Furthermore, the methodology is extended to hypothesis testing. Two tests for a hypothesis of specific parameter values are considered, as well as a test for the hypothesis that the symmetric component has a specific parametric form. A resampling algorithm is described for practical implementation of these tests. The outcomes of various numerical experiments are presented. © 2012 Board of the Foundation of the Scandinavian Journal of Statistics.

A single model procedure for tank calibration function estimation

International Nuclear Information System (INIS)

York, J.C.; Liebetrau, A.M.

1995-01-01

Reliable tank calibrations are a vital component of any measurement control and accountability program for bulk materials in a nuclear reprocessing facility. Tank volume calibration functions used in nuclear materials safeguards and accountability programs are typically constructed from several segments, each of which is estimated independently. Ideally, the segments correspond to structural features in the tank. In this paper the authors use an extension of the Thomas-Liebetrau model to estimate the entire calibration function in a single step. This procedure automatically takes significant run-to-run differences into account and yields an estimate of the entire calibration function in one operation. As with other procedures, the first step is to define suitable calibration segments. Next, a polynomial of low degree is specified for each segment. In contrast with the conventional practice of constructing a separate model for each segment, this information is used to set up the design matrix for a single model that encompasses all of the calibration data. Estimation of the model parameters is then done using conventional statistical methods. The method described here has several advantages over traditional methods. First, modeled run-to-run differences can be taken into account automatically at the estimation step. Second, no interpolation is required between successive segments. Third, variance estimates are based on all the data, rather than that from a single segment, with the result that discontinuities in confidence intervals at segment boundaries are eliminated. Fourth, the restrictive assumption of the Thomas-Liebetrau method, that the measured volumes be the same for all runs, is not required. Finally, the proposed methods are readily implemented using standard statistical procedures and widely-used software packages

Nucleon deep-inelastic structure functions in a quark model with factorizability assumptions

International Nuclear Information System (INIS)

Linkevich, A.D.; Skachkov, N.B.

1979-01-01

Formula for structure functions of deep-inelastic electron scattering on nucleon is derived. For this purpose the dynamic model of factorizing quark amplitudes is used. It has been found that with increase of Q 2 transferred pulse square at great values of x kinemastic variable the decrease of structure function values is observed. At x single values the increase of structure function values is found. The comparison With experimental data shows a good agreement of the model with experiment

Function and Innervation of the Locus Ceruleus in a Macaque Model of Functional Hypothalamic Amenorrhea

OpenAIRE

Bethea, Cynthia L; Kim, Aaron; Cameron, Judy L

2012-01-01

A body of knowledge implicates an increase in output from the locus ceruleus (LC) during stress. We questioned the innervation and function of the LC in our macaque model of Functional Hypothalamic Amenorrhea, also known as Stress-Induced Amenorrhea. Cohorts of macaques were initially characterized as highly stress resilient (HSR) or stress-sensitive (SS) based upon the presence or absence of ovulation during a protocol involving 2 menstrual cycles with psychosocial and metabolic stress. Afte...

Goal-Function Tree Modeling for Systems Engineering and Fault Management

Science.gov (United States)

Johnson, Stephen B.; Breckenridge, Jonathan T.

2013-01-01

The draft NASA Fault Management (FM) Handbook (2012) states that Fault Management (FM) is a "part of systems engineering", and that it "demands a system-level perspective" (NASAHDBK- 1002, 7). What, exactly, is the relationship between systems engineering and FM? To NASA, systems engineering (SE) is "the art and science of developing an operable system capable of meeting requirements within often opposed constraints" (NASA/SP-2007-6105, 3). Systems engineering starts with the elucidation and development of requirements, which set the goals that the system is to achieve. To achieve these goals, the systems engineer typically defines functions, and the functions in turn are the basis for design trades to determine the best means to perform the functions. System Health Management (SHM), by contrast, defines "the capabilities of a system that preserve the system's ability to function as intended" (Johnson et al., 2011, 3). Fault Management, in turn, is the operational subset of SHM, which detects current or future failures, and takes operational measures to prevent or respond to these failures. Failure, in turn, is the "unacceptable performance of intended function." (Johnson 2011, 605) Thus the relationship of SE to FM is that SE defines the functions and the design to perform those functions to meet system goals and requirements, while FM detects the inability to perform those functions and takes action. SHM and FM are in essence "the dark side" of SE. For every function to be performed (SE), there is the possibility that it is not successfully performed (SHM); FM defines the means to operationally detect and respond to this lack of success. We can also describe this in terms of goals: for every goal to be achieved, there is the possibility that it is not achieved; FM defines the means to operationally detect and respond to this inability to achieve the goal. This brief description of relationships between SE, SHM, and FM provide hints to a modeling approach to

Functional Somatic Syndromes: Emerging Biomedical Models and Traditional Chinese Medicine

Directory of Open Access Journals (Sweden)

Steven Tan

2004-01-01

Full Text Available The so-called functional somatic syndromes comprise a group of disorders that are primarily symptom-based, multisystemic in presentation and probably involve alterations in mind-brain-body interactions. The emerging neurobiological models of allostasis/allostatic load and of the emotional motor system show striking similarities with concepts used by Traditional Chinese Medicine (TCM to understand the functional somatic disorders and their underlying pathogenesis. These models incorporate a macroscopic perspective, accounting for the toll of acute and chronic traumas, physical and emotional stressors and the complex interactions between the mind, brain and body. The convergence of these biomedical models with the ancient paradigm of TCM may provide a new insight into scientifically verifiable diagnostic and therapeutic approaches for these common disorders.

Importance of predictor variables for models of chemical function

Data.gov (United States)

U.S. Environmental Protection Agency — Importance of random forest predictors for all classification models of chemical function. This dataset is associated with the following publication: Isaacs , K., M....

Stability of cylindrical plasma in the Bessel function model

International Nuclear Information System (INIS)

Yamagishi, T.; Gimblett, C.G.

1988-01-01

The stability of free boundary ideal and tearing modes in a cylindrical plasma is studied by examining the discontinuity (Δ') of the helical flux function given by the force free Bessel function model at the singular surface. The m = O and m = 1 free boundary tearing modes become strongly unstable when the singular surface is just inside the plasma boundary for a wide range of longitudinal wave numbers. (author)

Functional Security Model: Managers Engineers Working Together

Science.gov (United States)

Guillen, Edward Paul; Quintero, Rulfo

2008-05-01

Information security has a wide variety of solutions including security policies, network architectures and technological applications, they are usually designed and implemented by security architects, but in its own complexity this solutions are difficult to understand by company managers and they are who finally fund the security project. The main goal of the functional security model is to achieve a solid security platform reliable and understandable in the whole company without leaving of side the rigor of the recommendations and the laws compliance in a single frame. This paper shows a general scheme of the model with the use of important standards and tries to give an integrated solution.

The Goodwin model: behind the Hill function.

Directory of Open Access Journals (Sweden)

Didier Gonze

Full Text Available The Goodwin model is a 3-variable model demonstrating the emergence of oscillations in a delayed negative feedback-based system at the molecular level. This prototypical model and its variants have been commonly used to model circadian and other genetic oscillators in biology. The only source of non-linearity in this model is a Hill function, characterizing the repression process. It was mathematically shown that to obtain limit-cycle oscillations, the Hill coefficient must be larger than 8, a value often considered unrealistic. It is indeed difficult to explain such a high coefficient with simple cooperative dynamics. We present here molecular models of the standard Goodwin model, based on single or multisite phosphorylation/dephosphorylation processes of a transcription factor, which have been previously shown to generate switch-like responses. We show that when the phosphorylation/dephosphorylation processes are fast enough, the limit-cycle obtained with a multisite phosphorylation-based mechanism is in very good quantitative agreement with the oscillations observed in the Goodwin model. Conditions in which the detailed mechanism is well approximated by the Goodwin model are given. A variant of the Goodwin model which displays sharp thresholds and relaxation oscillations is also explained by a double phosphorylation/dephosphorylation-based mechanism through a bistable behavior. These results not only provide rational support for the Goodwin model but also highlight the crucial role of the speed of post-translational processes, whose response curve are usually established at a steady state, in biochemical oscillators.

Phase advance and β function measurements using model-independent analysis

OpenAIRE

Chun-xi Wang; Vadim Sajaev; Chih-Yuan Yao

2003-01-01

Phase advance and β function are basic lattice functions characterizing the linear properties of an accelerator lattice. Accurate and efficient measurements of these quantities are important for commissioning and operating a machine. For rings with little coupling, we report a new method to measure these lattice functions based on the model-independent analysis technique, which uses beam histories of excited betatron oscillations measured simultaneously at a large number of beam position moni...

Hepatobiliary system functional analysis by blood flow and clearance delay model

International Nuclear Information System (INIS)

Aboltins, A.; Reinholds, E.

2002-01-01

A mathematical model for describing liver uptake-excretion is developed and approved. Model is based on different timing delays in hepatobiliary and blood flow system elements. Series of scintigraphic images with 99m Tc-mebrofenins or 99m Tc-HIDA taken with standard nuclear medicine gamma camera are used as the real data for calculations. The time-activity curves are obtained from many regions of human body - heart, liver, gallbladder, spleen, aorta, vein, etc. Both first pass and dynamic acquisition data are used. Results are calculated using real system parameters and compared to real scintigraphy data. Mathematical simulations are made to show difference of hepatobiliary system function at three main points: normal function, good blood flow with bad hepatic function and bad blood flow with good hepatic function. (authors)

A Classroom Note on: Modeling Functions with the TI-83/84 Calculator

Science.gov (United States)

Lubowsky, Jack

2011-01-01

In Pre-Calculus courses, students are taught the composition and combination of functions to model physical applications. However, when combining two or more functions into a single more complicated one, students may lose sight of the physical picture which they are attempting to model. A block diagram, or flow chart, in which each block…

Generalized neurofuzzy network modeling algorithms using Bézier-Bernstein polynomial functions and additive decomposition.

Science.gov (United States)

Hong, X; Harris, C J

2000-01-01

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bézier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bézier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bézier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bézier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Comparison of optical methods for surface roughness characterization

International Nuclear Information System (INIS)

Feidenhans’l, Nikolaj A; Hansen, Poul-Erik; Madsen, Morten H; Petersen, Jan C; Pilný, Lukáš; Bissacco, Giuliano; Taboryski, Rafael

2015-01-01

We report a study of the correlation between three optical methods for characterizing surface roughness: a laboratory scatterometer measuring the bi-directional reflection distribution function (BRDF instrument), a simple commercial scatterometer (rBRDF instrument), and a confocal optical profiler. For each instrument, the effective range of spatial surface wavelengths is determined, and the common bandwidth used when comparing the evaluated roughness parameters. The compared roughness parameters are: the root-mean-square (RMS) profile deviation (Rq), the RMS profile slope (Rdq), and the variance of the scattering angle distribution (Aq). The twenty-two investigated samples were manufactured with several methods in order to obtain a suitable diversity of roughness patterns.Our study shows a one-to-one correlation of both the Rq and the Rdq roughness values when obtained with the BRDF and the confocal instruments, if the common bandwidth is applied. Likewise, a correlation is observed when determining the Aq value with the BRDF and the rBRDF instruments.Furthermore, we show that it is possible to determine the Rq value from the Aq value, by applying a simple transfer function derived from the instrument comparisons. The presented method is validated for surfaces with predominantly 1D roughness, i.e. consisting of parallel grooves of various periods, and a reflectance similar to stainless steel. The Rq values are predicted with an accuracy of 38% at the 95% confidence interval. (paper)

A Model for Microcontroller Functionality Upset Induced by External Pulsed Electromagnetic Irradiation

Science.gov (United States)

2016-11-21

AFRL-RD-PS- AFRL-RD-PS- TN-2016-0003 TN-2016-0003 A Model for Microcontroller Functionality Upset Induced by External Pulsed Electromagnetic...TYPE Technical Note 3. DATES COVERED (From - To) 22-11-2015 – 21-11-2016 4. TITLE AND SUBTITLE A Model for Microcontroller Functionality Upset Induced by... microcontroller (µC) subjected to external irradiation by a narrowband electromagnetic (EM) pulse. In our model, the state of a µC is completely specified by

Signed distance function implicit geologic modeling

Directory of Open Access Journals (Sweden)

Roberto Mentzingen Rolo

Full Text Available Abstract Prior to every geostatistical estimation or simulation study there is a need for delimiting the geologic domains of the deposit, which is traditionally done manually by a geomodeler in a laborious, time consuming and subjective process. For this reason, novel techniques referred to as implicit modelling have appeared. These techniques provide algorithms that replace the manual digitization process of the traditional methods by some form of automatic procedure. This paper covers a few well established implicit methods currently available with special attention to the signed distance function methodology. A case study based on a real dataset was performed and its applicability discussed. Although it did not replace an experienced geomodeler, the method proved to be capable in creating semi-automatic geological models from the sampling data, especially in the early stages of exploration.

A review of function modeling : Approaches and applications

NARCIS (Netherlands)

Erden, M.S.; Komoto, H.; Van Beek, T.J.; D'Amelio, V.; Echavarria, E.; Tomiyama, T.

2008-01-01

This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research

Secure and Resilient Functional Modeling for Navy Cyber-Physical Systems

Science.gov (United States)

2017-05-24

control systems, it was determined that this project will employ the model of a Ship Chilled Water Distribution System as a central use case. This model...Siemens Corporation Corporate Technology Unrestricted. Distribution Statement A. Approved for public...release; distribution is unlimited. Page 1 of 4 Secure & Resilient Functional Modeling for Navy Cyber-Physical Systems FY17 Quarter 1 Technical Progress

Modeling the NPE with finite sources and empirical Green`s functions

Energy Technology Data Exchange (ETDEWEB)

Hutchings, L.; Kasameyer, P.; Goldstein, P. [Lawrence Livermore National Lab., CA (United States)] [and others

1994-12-31

In order to better understand the source characteristics of both nuclear and chemical explosions for purposes of discrimination, we have modeled the NPE chemical explosion as a finite source and with empirical Green`s functions. Seismograms are synthesized at four sties to test the validity of source models. We use a smaller chemical explosion detonated in the vicinity of the working point to obtain empirical Green`s functions. Empirical Green`s functions contain all the linear information of the geology along the propagation path and recording site, which are identical for chemical or nuclear explosions, and therefore reduce the variability in modeling the source of the larger event. We further constrain the solution to have the overall source duration obtained from point-source deconvolution results. In modeling the source, we consider both an elastic source on a spherical surface and an inelastic expanding spherical volume source. We found that the spherical volume solution provides better fits to observed seismograms. The potential to identify secondary sources was examined, but the resolution is too poor to be definitive.

The distance-decay function of geographical gravity model: Power law or exponential law?

International Nuclear Information System (INIS)

Chen, Yanguang

2015-01-01

Highlights: •The distance-decay exponent of the gravity model is a fractal dimension. •Entropy maximization accounts for the gravity model based on power law decay. •Allometric scaling relations relate gravity models with spatial interaction models. •The four-parameter gravity models have dual mathematical expressions. •The inverse power law is the most probable distance-decay function. -- Abstract: The distance-decay function of the geographical gravity model is originally an inverse power law, which suggests a scaling process in spatial interaction. However, the distance exponent of the model cannot be reasonably explained with the ideas from Euclidean geometry. This results in a dimension dilemma in geographical analysis. Consequently, a negative exponential function was used to replace the inverse power function to serve for a distance-decay function. But a new puzzle arose that the exponential-based gravity model goes against the first law of geography. This paper is devoted for solving these kinds of problems by mathematical reasoning and empirical analysis. New findings are as follows. First, the distance exponent of the gravity model is demonstrated to be a fractal dimension using the geometric measure relation. Second, the similarities and differences between the gravity models and spatial interaction models are revealed using allometric relations. Third, a four-parameter gravity model possesses a symmetrical expression, and we need dual gravity models to describe spatial flows. The observational data of China's cities and regions (29 elements indicative of 841 data points) in 2010 are employed to verify the theoretical inferences. A conclusion can be reached that the geographical gravity model based on power-law decay is more suitable for analyzing large, complex, and scale-free regional and urban systems. This study lends further support to the suggestion that the underlying rationale of fractal structure is entropy maximization. Moreover

Modeling of nanoscale liquid mixture transport by density functional hydrodynamics

Science.gov (United States)

Dinariev, Oleg Yu.; Evseev, Nikolay V.

2017-06-01

Modeling of multiphase compositional hydrodynamics at nanoscale is performed by means of density functional hydrodynamics (DFH). DFH is the method based on density functional theory and continuum mechanics. This method has been developed by the authors over 20 years and used for modeling in various multiphase hydrodynamic applications. In this paper, DFH was further extended to encompass phenomena inherent in liquids at nanoscale. The new DFH extension is based on the introduction of external potentials for chemical components. These potentials are localized in the vicinity of solid surfaces and take account of the van der Waals forces. A set of numerical examples, including disjoining pressure, film precursors, anomalous rheology, liquid in contact with heterogeneous surface, capillary condensation, and forward and reverse osmosis, is presented to demonstrate modeling capabilities.

Preequilibrium decay models and the quantum Green function method

International Nuclear Information System (INIS)

Zhivopistsev, F.A.; Rzhevskij, E.S.; Gosudarstvennyj Komitet po Ispol'zovaniyu Atomnoj Ehnergii SSSR, Moscow. Inst. Teoreticheskoj i Ehksperimental'noj Fiziki)

1977-01-01

The nuclear process mechanism and preequilibrium decay involving complex particles are expounded on the basis of the Green function formalism without the weak interaction assumptions. The Green function method is generalized to a general nuclear reaction: A+α → B+β+γ+...rho, where A is the target nucleus, α is a complex particle in the initial state, B is the final nucleus, and β, γ, ... rho are nuclear fragments in the final state. The relationship between the generalized Green function and Ssub(fi)-matrix is established. The resultant equations account for: 1) direct and quasi-direct processes responsible for the angular distribution asymmetry of the preequilibrium component; 2) the appearance of addends corresponding to the excitation of complex states of final nucleus; and 3) the relationship between the preequilibrium decay model and the general models of nuclear reaction theories (Lippman-Schwinger formalism). The formulation of preequilibrium emission via the S(T) matrix allows to account for all the differential terms in succession important to an investigation of the angular distribution assymetry of emitted particles

An Entropy-Assisted Shielding Function in DDES Formulation for the SST Turbulence Model

Directory of Open Access Journals (Sweden)

Ling Zhou

2017-02-01

Full Text Available The intent of shielding functions in delayed detached-eddy simulation methods (DDES is to preserve the wall boundary layers as Reynolds-averaged Navier–Strokes (RANS mode, avoiding possible modeled stress depletion (MSD or even unphysical separation due to grid refinement. An entropy function fs is introduced to construct a DDES formulation for the k-ω shear stress transport (SST model, whose performance is extensively examined on a range of attached and separated flows (flat-plate flow, circular cylinder flow, and supersonic cavity-ramp flow. Two more forms of shielding functions are also included for comparison: one that uses the blending function F2 of SST, the other which adopts the recalibrated shielding function fd_cor of the DDES version based on the Spalart-Allmaras (SA model. In general, all of the shielding functions do not impair the vortex in fully separated flows. However, for flows including attached boundary layer, both F2 and the recalibrated fd_cor are found to be too conservative to resolve the unsteady flow content. On the other side, fs is proposed on the theory of energy dissipation and independent on from any particular turbulence model, showing the generic priority by properly balancing the need of reserving the RANS modeled regions for wall boundary layers and generating the unsteady turbulent structures in detached areas.

Conceptual model of consumer’s willingness to eat functional foods

Science.gov (United States)

Babicz-Zielinska, Ewa; Jezewska-Zychowicz, Maria

The functional foods constitute the important segment of the food market. Among factors that determine the intentions to eat functional foods, the psychological factors play very important roles. Motives, attitudes and personality are key factors. The relationships between socio-demographic characteristics, attitudes and willingness to purchase functional foods were not fully confirmed. Consumers’ beliefs about health benefits from eaten foods seem to be a strong determinant of a choice of functional foods. The objective of this study was to determine relations between familiarity, attitudes, and beliefs in benefits and risks about functional foods and develop some conceptual models of willingness to eat. The sample of Polish consumers counted 1002 subjects at age 15+. The foods enriched with vitamins or minerals, and cholesterol-lowering margarine or drinks were considered. The questionnaire focused on familiarity with foods, attitudes, beliefs about benefits and risks of their consumption was constructed. The Pearson’s correlations and linear regression equations were calculated. The strongest relations appeared between attitudes, high health value and high benefits, (r = 0.722 and 0.712 for enriched foods, and 0.664 and 0.693 for cholesterol-lowering foods), and between high health value and high benefits (0.814 for enriched foods and 0.758 for cholesterol-lowering foods). The conceptual models based on linear regression of relations between attitudes and all other variables, considering or not the familiarity with the foods, were developed. The positive attitudes and declared consumption are more important for enriched foods. The beliefs on high health value and high benefits play the most important role in the purchase. The interrelations between different variables may be described by new linear regression models, with the beliefs in high benefits, positive attitudes and familiarity being most significant predictors. Health expectations and trust to

Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments.

Directory of Open Access Journals (Sweden)

Hahnbeom Park

Full Text Available Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.

Commonsense Psychology and the Functional Requirements of Cognitive Models

National Research Council Canada - National Science Library

Gordon, Andrew S

2005-01-01

In this paper we argue that previous models of cognitive abilities (e.g. memory, analogy) have been constructed to satisfy functional requirements of implicit commonsense psychological theories held by researchers and nonresearchers alike...

Assessment of nutritional status in the elderly: a proposed function-driven model.

Science.gov (United States)

Engelheart, Stina; Brummer, Robert

2018-01-01

There is no accepted or standardized definition of 'malnutrition'. Hence, there is also no definition of what constitutes an adequate nutritional status. In elderly people, assessment of nutritional status is complex and is complicated by multi-morbidity and disabilities combined with nutrition-related problems, such as dysphagia, decreased appetite, fatigue, and muscle weakness. We propose a nutritional status model that presents nutritional status from a comprehensive functional perspective. This model visualizes the complexity of the nutritional status in elderly people. The presented model could be interpreted as the nutritional status is conditional to a person's optimal function or situation. Another way of looking at it might be that a person's nutritional status affects his or her optimal situation. The proposed model includes four domains: (1) physical function and capacity; (2) health and somatic disorders; (3) food and nutrition; and (4) cognitive, affective, and sensory function. Each domain has a major impact on nutritional status, which in turn has a major impact on the outcome of each domain. Nutritional status is a multifaceted concept and there exist several knowledge gaps in the diagnosis, prevention, and optimization of treatment of inadequate nutritional status in elderly people. The nutritional status model may be useful in nutritional assessment research, as well as in the clinical setting.

Linking density functional and mode coupling models for supercooled liquids.

Science.gov (United States)

Premkumar, Leishangthem; Bidhoodi, Neeta; Das, Shankar P

2016-03-28

We compare predictions from two familiar models of the metastable supercooled liquid, respectively, constructed with thermodynamic and dynamic approaches. In the so called density functional theory the free energy F[ρ] of the liquid is a functional of the inhomogeneous density ρ(r). The metastable state is identified as a local minimum of F[ρ]. The sharp density profile characterizing ρ(r) is identified as a single particle oscillator, whose frequency is obtained from the parameters of the optimum density function. On the other hand, a dynamic approach to supercooled liquids is taken in the mode coupling theory (MCT) which predict a sharp ergodicity-non-ergodicity transition at a critical density. The single particle dynamics in the non-ergodic state, treated approximately, represents a propagating mode whose characteristic frequency is computed from the corresponding memory function of the MCT. The mass localization parameters in the above two models (treated in their simplest forms) are obtained, respectively, in terms of the corresponding natural frequencies depicted and are shown to have comparable magnitudes.

Modeling Belt-Servomechanism by Chebyshev Functional Recurrent Neuro-Fuzzy Network

Science.gov (United States)

Huang, Yuan-Ruey; Kang, Yuan; Chu, Ming-Hui; Chang, Yeon-Pun

A novel Chebyshev functional recurrent neuro-fuzzy (CFRNF) network is developed from a combination of the Takagi-Sugeno-Kang (TSK) fuzzy model and the Chebyshev recurrent neural network (CRNN). The CFRNF network can emulate the nonlinear dynamics of a servomechanism system. The system nonlinearity is addressed by enhancing the input dimensions of the consequent parts in the fuzzy rules due to functional expansion of a Chebyshev polynomial. The back propagation algorithm is used to adjust the parameters of the antecedent membership functions as well as those of consequent functions. To verify the performance of the proposed CFRNF, the experiment of the belt servomechanism is presented in this paper. Both of identification methods of adaptive neural fuzzy inference system (ANFIS) and recurrent neural network (RNN) are also studied for modeling of the belt servomechanism. The analysis and comparison results indicate that CFRNF makes identification of complex nonlinear dynamic systems easier. It is verified that the accuracy and convergence of the CFRNF are superior to those of ANFIS and RNN by the identification results of a belt servomechanism.

Linking density functional and mode coupling models for supercooled liquids

Energy Technology Data Exchange (ETDEWEB)

Premkumar, Leishangthem; Bidhoodi, Neeta; Das, Shankar P. [School of Physical Sciences, Jawaharlal Nehru University, New Delhi 110067 (India)

2016-03-28

We compare predictions from two familiar models of the metastable supercooled liquid, respectively, constructed with thermodynamic and dynamic approaches. In the so called density functional theory the free energy F[ρ] of the liquid is a functional of the inhomogeneous density ρ(r). The metastable state is identified as a local minimum of F[ρ]. The sharp density profile characterizing ρ(r) is identified as a single particle oscillator, whose frequency is obtained from the parameters of the optimum density function. On the other hand, a dynamic approach to supercooled liquids is taken in the mode coupling theory (MCT) which predict a sharp ergodicity-non-ergodicity transition at a critical density. The single particle dynamics in the non-ergodic state, treated approximately, represents a propagating mode whose characteristic frequency is computed from the corresponding memory function of the MCT. The mass localization parameters in the above two models (treated in their simplest forms) are obtained, respectively, in terms of the corresponding natural frequencies depicted and are shown to have comparable magnitudes.

Functional outcome measures in a surgical model of hip osteoarthritis in dogs.

Science.gov (United States)

Little, Dianne; Johnson, Stephen; Hash, Jonathan; Olson, Steven A; Estes, Bradley T; Moutos, Franklin T; Lascelles, B Duncan X; Guilak, Farshid

2016-12-01

The hip is one of the most common sites of osteoarthritis in the body, second only to the knee in prevalence. However, current animal models of hip osteoarthritis have not been assessed using many of the functional outcome measures used in orthopaedics, a characteristic that could increase their utility in the evaluation of therapeutic interventions. The canine hip shares similarities with the human hip, and functional outcome measures are well documented in veterinary medicine, providing a baseline for pre-clinical evaluation of therapeutic strategies for the treatment of hip osteoarthritis. The purpose of this study was to evaluate a surgical model of hip osteoarthritis in a large laboratory animal model and to evaluate functional and end-point outcome measures. Seven dogs were subjected to partial surgical debridement of cartilage from one femoral head. Pre- and postoperative pain and functional scores, gait analysis, radiographs, accelerometry, goniometry and limb circumference were evaluated through a 20-week recovery period, followed by histological evaluation of cartilage and synovium. Animals developed histological and radiographic evidence of osteoarthritis, which was correlated with measurable functional impairment. For example, Mankin scores in operated limbs were positively correlated to radiographic scores but negatively correlated to range of motion, limb circumference and 20-week peak vertical force. This study demonstrates that multiple relevant functional outcome measures can be used successfully in a large laboratory animal model of hip osteoarthritis. These measures could be used to evaluate relative efficacy of therapeutic interventions relevant to human clinical care.

The negotiated equilibrium model of spinal cord function.

Science.gov (United States)

Wolpaw, Jonathan R

2018-04-16

The belief that the spinal cord is hardwired is no longer tenable. Like the rest of the CNS, the spinal cord changes during growth and aging, when new motor behaviours are acquired, and in response to trauma and disease. This paper describes a new model of spinal cord function that reconciles its recently appreciated plasticity with its long recognized reliability as the final common pathway for behaviour. According to this model, the substrate of each motor behaviour comprises brain and spinal plasticity: the plasticity in the brain induces and maintains the plasticity in the spinal cord. Each time a behaviour occurs, the spinal cord provides the brain with performance information that guides changes in the substrate of the behaviour. All the behaviours in the repertoire undergo this process concurrently; each repeatedly induces plasticity to preserve its key features despite the plasticity induced by other behaviours. The aggregate process is a negotiation among the behaviours: they negotiate the properties of the spinal neurons and synapses that they all use. The ongoing negotiation maintains the spinal cord in an equilibrium - a negotiated equilibrium - that serves all the behaviours. This new model of spinal cord function is supported by laboratory and clinical data, makes predictions borne out by experiment, and underlies a new approach to restoring function to people with neuromuscular disorders. Further studies are needed to test its generality, to determine whether it may apply to other CNS areas such as the cerebral cortex, and to develop its therapeutic implications. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

STRUCTURAL AND FUNCTIONAL MODEL OF CLOUD ORIENTED LEARNING ENVIRONMENT FOR BACHELORS OF INFORMATICS TRAINING

Directory of Open Access Journals (Sweden)

Tetiana A. Vakaliuk

2017-06-01

Full Text Available The article summarizes the essence of the category "model". There are presented the main types of models used in educational research: structural, functional, structural and functional model as well as basic requirements for building these types of models. The national experience in building models and designing cloud-based learning environment of educational institutions (both higher and secondary is analyzed. It is presented structural and functional model of cloud-based learning environment for Bachelor of Informatics. Also we describe each component of cloud-based learning environment model for bachelors of informatics training: target, managerial, organizational, content and methodical, communication, technological and productive. It is summarized, that COLE should solve all major tasks that relate to higher education institutions.

Functional networks inference from rule-based machine learning models.

Science.gov (United States)

Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume

2016-01-01

Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The

Some aspects of wave-functions in disordered and incommensurate models

International Nuclear Information System (INIS)

Roman, E.; Wiecko, C.

1984-09-01

We study the localization length and fractal dimensionality of wave functions in the random diagonal and off-diagonal Anderson model. This preliminary study is intended to establish how much connection between these two magnitudes exists and how they behave at the transition from the localized to extended regimes both in these random models as well as in the incommensurate models such as Aubry's. (author)

Field Experiments on SAR Detection of Film Slicks

Science.gov (United States)

Ermakov, S.; da Silva, J. C. B.; Kapustin, I.; Sergievskaya, I.

2013-03-01

Field experiments on radar detection of film slicks using satellite synthetic aperture radar TerraSAR-X and X-band scatterometer on board a research vessel are described. The experiments were carried out with surfactant films with known physical parameters, the surface tension and the film elasticity, at low to moderate wind conditions and at different radar incidence angles. It is shown that the depression of radar backscatter (contrast) in films slicks for X-band SAR weakly depends on wind velocity/direction, film elasticity and incidence angles within the range of 200-400. Scatterometer contrasts obtained at incidence angles of about 600 are larger than SAR contrasts. Theoretical analysis of radar contrasts for low-to-moderate incidence angles has been carried out based on a hydrodynamic model of wind wave damping due to films and on a composite radar imaging model. The hydrodynamic model takes into account wave damping due to viscoelastic films, wind wave generation and a phenomenological term describing nonlinear limitation of the wind wave spectrum. The radar model takes into account Bragg scattering and specular scattering mechanisms, the latter is usually negligible compared to the Bragg mechanism at moderate incidence angles (larger than 30-35 degrees), but gives noticeable contribution to radar backscattering at smaller incidence angles particularly for slick areas when cm-scale ripples are strongly depressed by films. Calculated radar contrasts in slicks are compared with experiments and it is concluded that development of the model is needed to predict quantitatively observations.

Confronting species distribution model predictions with species functional traits.

Science.gov (United States)

Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

2016-02-01

Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

Quantitative and Functional Requirements for Bioluminescent Cancer Models.

Science.gov (United States)

Feys, Lynn; Descamps, Benedicte; Vanhove, Christian; Vermeulen, Stefan; Vandesompele, J O; Vanderheyden, Katrien; Messens, Kathy; Bracke, Marc; De Wever, Olivier

2016-01-01

Bioluminescent cancer models are widely used but detailed quantification of the luciferase signal and functional comparison with a non-transfected control cell line are generally lacking. In the present study, we provide quantitative and functional tests for luciferase-transfected cells. We quantified the luciferase expression in BLM and HCT8/E11 transfected cancer cells, and examined the effect of long-term luciferin exposure. The present study also investigated functional differences between parental and transfected cancer cells. Our results showed that quantification of different single-cell-derived populations are superior with droplet digital polymerase chain reaction. Quantification of luciferase protein level and luciferase bioluminescent activity is only useful when there is a significant difference in copy number. Continuous exposure of cell cultures to luciferin leads to inhibitory effects on mitochondrial activity, cell growth and bioluminescence. These inhibitory effects correlate with luciferase copy number. Cell culture and mouse xenograft assays showed no significant functional differences between luciferase-transfected and parental cells. Luciferase-transfected cells should be validated by quantitative and functional assays before starting large-scale experiments. Copyright © 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Implementation and identification of Preisach type hysteresis models with Everett Function in closed form

Energy Technology Data Exchange (ETDEWEB)

Szabó, Zsolt, E-mail: szabo@evt.bme.hu [Department of Broadband Infocommunications and Electromagnetic Theory, Budapest University of Technology and Economics, Budapest (Hungary); Füzi, János [Neutron Spectroscopy Department, Wigner Research Centre for Physics, Budapest (Hungary); Faculty of Engineering and Information Technology, University of Pécs (Hungary)

2016-05-15

The Preisach function is considered as a product of two special one dimensional functions, which allows the closed form evaluation of the Everett integral. The deduced closed form expressions are included in Preisach models, in particular in the static model, moving model and a rate dependent hysteresis model, which can simulate the frequency dependence of the magnetization process. The details of the freely available implementations, which are available online are presented. The identification of the model parameters and the accuracy to describe the magnetization process are discussed and demonstrated by fitting measured data. Transient electric circuit simulation with hysteresis demonstrates the applicability of the developed models. - Highlights: • Formulation of the Preisach model with Everett function in closed form. • Identification of the parameters: when the shape of the analytical Preisach function does not matches the ferromagnetic material the moving model can be applied to increase the accuracy. • Novel algorithm with Fixed Point iteration, which utilizes the closed formulation to simulate the frequency dependence of the magnetization process. • The developed hysteresis models are utilized in circuit simulation algorithm to determine the transient behavior of the current, which flows through a toroidal coil with ferromagnetic core.

Green function simulation of Hamiltonian lattice models with stochastic reconfiguration

International Nuclear Information System (INIS)

Beccaria, M.

2000-01-01

We apply a recently proposed Green function Monte Carlo procedure to the study of Hamiltonian lattice gauge theories. This class of algorithms computes quantum vacuum expectation values by averaging over a set of suitable weighted random walkers. By means of a procedure called stochastic reconfiguration the long standing problem of keeping fixed the walker population without a priori knowledge of the ground state is completely solved. In the U(1) 2 model, which we choose as our theoretical laboratory, we evaluate the mean plaquette and the vacuum energy per plaquette. We find good agreement with previous works using model-dependent guiding functions for the random walkers. (orig.)

The transfer function model for dynamic response of wet cooling coils

International Nuclear Information System (INIS)

Yao Ye; Liu Shiqing

2008-01-01

This paper mainly concerned about the dynamic response model of wet cooling coils that is developed by the Laplace transform method. The theoretic equations are firstly established based on the theory of energy conservation. Then, the transfer functions on the transient responses of wet cooling coils have been deduced using the method of Laplace transform. The transfer functions reveal the dynamic relationships between the inlet variables and the outlet ones of the cooling coils. Partial-fraction method and Newton-Raphson method are both used in the inversion of the transfer functions from the s-domain to τ-domain. To make the dynamic model of wet cooling coils more adaptive, RBFNN method is employed to determine the coefficients of heat and mass transfer. Experiments have been done and manifested that the coefficients of heat and mass transfer by RBFNN will be of great value to the validity of the transient response model of wet cooling coils in this study

Green's function method and its application to verification of diffusion models of GASFLOW code

International Nuclear Information System (INIS)

Xu, Z.; Travis, J.R.; Breitung, W.

2007-07-01

To validate the diffusion model and the aerosol particle model of the GASFLOW computer code, theoretical solutions of advection diffusion problems are developed by using the Green's function method. The work consists of a theory part and an application part. In the first part, the Green's functions of one-dimensional advection diffusion problems are solved in infinite, semi-infinite and finite domains with the Dirichlet, the Neumann and/or the Robin boundary conditions. Novel and effective image systems especially for the advection diffusion problems are made to find the Green's functions in a semi-infinite domain. Eigenfunction method is utilized to find the Green's functions in a bounded domain. In the case, key steps of a coordinate transform based on a concept of reversed time scale, a Laplace transform and an exponential transform are proposed to solve the Green's functions. Then the product rule of the multi-dimensional Green's functions is discussed in a Cartesian coordinate system. Based on the building blocks of one-dimensional Green's functions, the multi-dimensional Green's function solution can be constructed by applying the product rule. Green's function tables are summarized to facilitate the application of the Green's function. In the second part, the obtained Green's function solutions benchmark a series of validations to the diffusion model of gas species in continuous phase and the diffusion model of discrete aerosol particles in the GASFLOW code. Perfect agreements are obtained between the GASFLOW simulations and the Green's function solutions in case of the gas diffusion. Very good consistencies are found between the theoretical solutions of the advection diffusion equations and the numerical particle distributions in advective flows, when the drag force between the micron-sized particles and the conveying gas flow meets the Stokes' law about resistance. This situation is corresponding to a very small Reynolds number based on the particle

General atomistic approach for modeling metal-semiconductor interfaces using density functional theory and nonequilibrium Green's function

DEFF Research Database (Denmark)

Stradi, Daniele; Martinez, Umberto; Blom, Anders

2016-01-01

Metal-semiconductor contacts are a pillar of modern semiconductor technology. Historically, their microscopic understanding has been hampered by the inability of traditional analytical and numerical methods to fully capture the complex physics governing their operating principles. Here we introduce...... an atomistic approach based on density functional theory and nonequilibrium Green's function, which includes all the relevant ingredients required to model realistic metal-semiconductor interfaces and allows for a direct comparison between theory and experiments via I-Vbias curve simulations. We apply...... interfaces as it neglects electron tunneling, and that finite-size atomistic models have problems in describing these interfaces in the presence of doping due to a poor representation of space-charge effects. Conversely, the present method deals effectively with both issues, thus representing a valid...

Identification of hidden failures in control systems: a functional modelling approach

International Nuclear Information System (INIS)

Jalashgar, A.; Modarres, M.

1996-01-01

This paper presents a model which encompasses knowledge about a process control system's functionalities in a function-oriented failure analysis task. The technique called Hybrid MFM-GTST, mainly utilizes two different function - oriented methods (MFM and GTST) to identify all functions of the system components, and hence possible sources of hidden failures in process control systems. Hidden failures are referred to incipient failures within the system that in long term may lead to loss of major functions. The features of the method are described and demonstrated by using an example of a process control system

A Study on the Impact of Observation Assimilation on the Numerical Simulation of Tropical Cyclones JAL and THANE Using 3DVAR

KAUST Repository

Viswanadhapalli, Yesubabu

2013-12-08

In this work, the impact of assimilation of conventional and satellite remote sensing observations (Oceansat-2 winds, MODIS temperature/humidity profiles) is studied on the simulation of two tropical cyclones in the Bay of Bengal region of the Indian Ocean using a three-dimensional variational data assimilation (3DVAR) technique. The Weather Research and Forecasting (WRF)-Advanced Research WRF (ARW) mesoscale model is used to simulate the severe cyclone JAL: 5–8 November 2010 and the very severe cyclone THANE: 27–30 December 2011 with a double nested domain configuration and with a horizontal resolution of 27 × 9 km. Five numerical experiments are conducted for each cyclone. In the control run (CTL) the National Centers for Environmental Prediction global forecast system analysis and forecasts available at 50 km resolution were used for the initial and boundary conditions. In the second (VARAWS), third (VARSCAT), fourth (VARMODIS) and fifth (VARALL) experiments, the conventional surface observations, Oceansat-2 ocean surface wind vectors, temperature and humidity profiles of MODIS, and all observations were respectively used for assimilation. Results indicate meager impact with surface observations, and relatively higher impact with scatterometer wind data in the case of the JAL cyclone, and with MODIS temperature and humidity profiles in the case of THANE for the simulation of intensity and track parameters. These relative impacts are related to the area coverage of scatterometer winds and MODIS profiles in the respective storms, and are confirmed by the overall better results obtained with assimilation of all observations in both the cases. The improvements in track prediction are mainly contributed by the assimilation of scatterometer wind vector data, which reduced errors in the initial position and size of the cyclone vortices. The errors are reduced by 25, 21, 38 % in vector track position, and by 57, 36, 39 % in intensity, at 24, 48, 72�

Two-point functions in a holographic Kondo model

Science.gov (United States)

Erdmenger, Johanna; Hoyos, Carlos; O'Bannon, Andy; Papadimitriou, Ioannis; Probst, Jonas; Wu, Jackson M. S.

2017-03-01

We develop the formalism of holographic renormalization to compute two-point functions in a holographic Kondo model. The model describes a (0 + 1)-dimensional impurity spin of a gauged SU( N ) interacting with a (1 + 1)-dimensional, large- N , strongly-coupled Conformal Field Theory (CFT). We describe the impurity using Abrikosov pseudo-fermions, and define an SU( N )-invariant scalar operator O built from a pseudo-fermion and a CFT fermion. At large N the Kondo interaction is of the form O^{\\dagger}O, which is marginally relevant, and generates a Renormalization Group (RG) flow at the impurity. A second-order mean-field phase transition occurs in which O condenses below a critical temperature, leading to the Kondo effect, including screening of the impurity. Via holography, the phase transition is dual to holographic superconductivity in (1 + 1)-dimensional Anti-de Sitter space. At all temperatures, spectral functions of O exhibit a Fano resonance, characteristic of a continuum of states interacting with an isolated resonance. In contrast to Fano resonances observed for example in quantum dots, our continuum and resonance arise from a (0 + 1)-dimensional UV fixed point and RG flow, respectively. In the low-temperature phase, the resonance comes from a pole in the Green's function of the form - i2, which is characteristic of a Kondo resonance.

Two-point functions in a holographic Kondo model

Energy Technology Data Exchange (ETDEWEB)

Erdmenger, Johanna [Institut für Theoretische Physik und Astrophysik, Julius-Maximilians-Universität Würzburg,Am Hubland, D-97074 Würzburg (Germany); Max-Planck-Institut für Physik (Werner-Heisenberg-Institut),Föhringer Ring 6, D-80805 Munich (Germany); Hoyos, Carlos [Department of Physics, Universidad de Oviedo, Avda. Calvo Sotelo 18, 33007, Oviedo (Spain); O’Bannon, Andy [STAG Research Centre, Physics and Astronomy, University of Southampton,Highfield, Southampton SO17 1BJ (United Kingdom); Papadimitriou, Ioannis [SISSA and INFN - Sezione di Trieste, Via Bonomea 265, I 34136 Trieste (Italy); Probst, Jonas [Rudolf Peierls Centre for Theoretical Physics, University of Oxford,1 Keble Road, Oxford OX1 3NP (United Kingdom); Wu, Jackson M.S. [Department of Physics and Astronomy, University of Alabama, Tuscaloosa, AL 35487 (United States)

2017-03-07

We develop the formalism of holographic renormalization to compute two-point functions in a holographic Kondo model. The model describes a (0+1)-dimensional impurity spin of a gauged SU(N) interacting with a (1+1)-dimensional, large-N, strongly-coupled Conformal Field Theory (CFT). We describe the impurity using Abrikosov pseudo-fermions, and define an SU(N)-invariant scalar operator O built from a pseudo-fermion and a CFT fermion. At large N the Kondo interaction is of the form O{sup †}O, which is marginally relevant, and generates a Renormalization Group (RG) flow at the impurity. A second-order mean-field phase transition occurs in which O condenses below a critical temperature, leading to the Kondo effect, including screening of the impurity. Via holography, the phase transition is dual to holographic superconductivity in (1+1)-dimensional Anti-de Sitter space. At all temperatures, spectral functions of O exhibit a Fano resonance, characteristic of a continuum of states interacting with an isolated resonance. In contrast to Fano resonances observed for example in quantum dots, our continuum and resonance arise from a (0+1)-dimensional UV fixed point and RG flow, respectively. In the low-temperature phase, the resonance comes from a pole in the Green’s function of the form −i〈O〉{sup 2}, which is characteristic of a Kondo resonance.

Combining computer modelling and cardiac imaging to understand right ventricular pump function.

Science.gov (United States)

Walmsley, John; van Everdingen, Wouter; Cramer, Maarten J; Prinzen, Frits W; Delhaas, Tammo; Lumens, Joost

2017-10-01

Right ventricular (RV) dysfunction is a strong predictor of outcome in heart failure and is a key determinant of exercise capacity. Despite these crucial findings, the RV remains understudied in the clinical, experimental, and computer modelling literature. This review outlines how recent advances in using computer modelling and cardiac imaging synergistically help to understand RV function in health and disease. We begin by highlighting the complexity of interactions that make modelling the RV both challenging and necessary, and then summarize the multiscale modelling approaches used to date to simulate RV pump function in the context of these interactions. We go on to demonstrate how these modelling approaches in combination with cardiac imaging have improved understanding of RV pump function in pulmonary arterial hypertension, arrhythmogenic right ventricular cardiomyopathy, dyssynchronous heart failure and cardiac resynchronization therapy, hypoplastic left heart syndrome, and repaired tetralogy of Fallot. We conclude with a perspective on key issues to be addressed by computational models of the RV in the near future. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com.

A Radar/Radiometer Instrument for Mapping Soil Moisture and Ocean Salinity

Science.gov (United States)

Hildebrand, Peter H.; Hilliard, Laurence; Rincon, Rafael; LeVine, David; Mead, James

2003-01-01

The RadSTAR instrument combines an L-band, digital beam-forming radar with an L-band synthetic aperture, thinned array (STAR) radiometer. The RadSTAR development will support NASA Earth science goals by developing a novel, L-band scatterometer/ radiometer that measures Earth surface bulk material properties (surface emissions and backscatter) as well as surface characteristics (backscatter). Present, real aperture airborne L-Band active/passive measurement systems such as the JPUPALS (Wilson, et al, 2000) provide excellent sampling characteristics, but have no scanning capabilities, and are extremely large; the huge JPUPALS horn requires a the C-130 airborne platform, operated with the aft loading door open during flight operation. The approach used for the upcoming Aquarius ocean salinity mission or the proposed Hydros soil mission use real apertures with multiple fixed beams or scanning beams. For real aperture instruments, there is no upgrade path to scanning over a broad swath, except rotation of the whole aperture, which is an approach with obvious difficulties as aperture size increases. RadSTAR will provide polarimetric scatterometer and radiometer measurements over a wide swath, in a highly space-efficient configuration. The electronic scanning approaches provided through STAR technology and digital beam forming will enable the large L-band aperture to scan efficiently over a very wide swath. RadSTAR technology development, which merges an interferometric radiometer with a digital beam forming scatterometer, is an important step in the path to space for an L-band scatterometer/radiometer. RadSTAR couples a patch array antenna with a 1.26 GHz digital beam forming radar scatterometer and a 1.4 GHz STAR radiometer to provide Earth surface backscatter and emission measurements in a compact, cross-track scanning instrument with no moving parts. This technology will provide the first L-band, emission and backscatter measurements in a compact aircraft instrument

Zebrafish models for the functional genomics of neurogenetic disorders.

Science.gov (United States)

Kabashi, Edor; Brustein, Edna; Champagne, Nathalie; Drapeau, Pierre

2011-03-01

In this review, we consider recent work using zebrafish to validate and study the functional consequences of mutations of human genes implicated in a broad range of degenerative and developmental disorders of the brain and spinal cord. Also we present technical considerations for those wishing to study their own genes of interest by taking advantage of this easily manipulated and clinically relevant model organism. Zebrafish permit mutational analyses of genetic function (gain or loss of function) and the rapid validation of human variants as pathological mutations. In particular, neural degeneration can be characterized at genetic, cellular, functional, and behavioral levels. Zebrafish have been used to knock down or express mutations in zebrafish homologs of human genes and to directly express human genes bearing mutations related to neurodegenerative disorders such as spinal muscular atrophy, ataxia, hereditary spastic paraplegia, amyotrophic lateral sclerosis (ALS), epilepsy, Huntington's disease, Parkinson's disease, fronto-temporal dementia, and Alzheimer's disease. More recently, we have been using zebrafish to validate mutations of synaptic genes discovered by large-scale genomic approaches in developmental disorders such as autism, schizophrenia, and non-syndromic mental retardation. Advances in zebrafish genetics such as multigenic analyses and chemical genetics now offer a unique potential for disease research. Thus, zebrafish hold much promise for advancing the functional genomics of human diseases, the understanding of the genetics and cell biology of degenerative and developmental disorders, and the discovery of therapeutics. This article is part of a Special Issue entitled Zebrafish Models of Neurological Diseases. Copyright © 2010 Elsevier B.V. All rights reserved.

Modeling DPOAE input/output function compression: comparisons with hearing thresholds.

Science.gov (United States)

Bhagat, Shaum P

2014-09-01

Basilar membrane input/output (I/O) functions in mammalian animal models are characterized by linear and compressed segments when measured near the location corresponding to the characteristic frequency. A method of studying basilar membrane compression indirectly in humans involves measuring distortion-product otoacoustic emission (DPOAE) I/O functions. Previous research has linked compression estimates from behavioral growth-of-masking functions to hearing thresholds. The aim of this study was to compare compression estimates from DPOAE I/O functions and hearing thresholds at 1 and 2 kHz. A prospective correlational research design was performed. The relationship between DPOAE I/O function compression estimates and hearing thresholds was evaluated with Pearson product-moment correlations. Normal-hearing adults (n = 16) aged 22-42 yr were recruited. DPOAE I/O functions (L₂ = 45-70 dB SPL) and two-interval forced-choice hearing thresholds were measured in normal-hearing adults. A three-segment linear regression model applied to DPOAE I/O functions supplied estimates of compression thresholds, defined as breakpoints between linear and compressed segments and the slopes of the compressed segments. Pearson product-moment correlations between DPOAE compression estimates and hearing thresholds were evaluated. A high correlation between DPOAE compression thresholds and hearing thresholds was observed at 2 kHz, but not at 1 kHz. Compression slopes also correlated highly with hearing thresholds only at 2 kHz. The derivation of cochlear compression estimates from DPOAE I/O functions provides a means to characterize basilar membrane mechanics in humans and elucidates the role of compression in tone detection in the 1-2 kHz frequency range. American Academy of Audiology.

The Einstein action for algebras of matrix valued functions - Toy models

International Nuclear Information System (INIS)

Hajac, P.M.

1995-10-01

Two toy models are considered within the framework of noncommutative differential geometry. In the first one, the Einstein action of the Levi-Civita connection is computed for the algebra of matrix valued functions on a torus. It is shown that, assuming some constraints on the metric, this action splits into a classical-like, a quantum-like and a mixed term. In the second model, an analogue of the Palatini method of variation is applied to obtain critical points of the Einstein action functional for M 4 (R). It is pointed out that a solution to the Palatini variational problem is not necessarily a Levi-Civita connection. In this model, no additional assumptions regarding metrics are made. (author). 14 refs

Novel Methodology for Functional Modeling and Simulation of Wireless Embedded Systems

Directory of Open Access Journals (Sweden)

Sosa Morales Emma

2008-01-01

Full Text Available Abstract A novel methodology is presented for the modeling and the simulation of wireless embedded systems. Tight interaction between the analog and the digital functionality makes the design and verification of such systems a real challenge. The applied methodology brings together the functional models of the baseband algorithms written in C language with the circuit descriptions at behavioral level in Verilog or Verilog-AMS for the system simulations in a single kernel environment. The physical layer of an ultrawideband system has been successfully modeled and simulated. The results confirm that this methodology provides a standardized framework in order to efficiently and accurately simulate complex mixed signal applications for embedded systems.

X-band COSMO-SkyMed wind field retrieval, with application to coastal circulation modeling

Directory of Open Access Journals (Sweden)

A. Montuori

2013-02-01

Full Text Available In this paper, X-band COSMO-SkyMed^© synthetic aperture radar (SAR wind field retrieval is investigated, and the obtained data are used to force a coastal ocean circulation model. The SAR data set consists of 60 X-band Level 1B Multi-Look Ground Detected ScanSAR Huge Region COSMO-SkyMed^© SAR data, gathered in the southern Tyrrhenian Sea during the summer and winter seasons of 2010. The SAR-based wind vector field estimation is accomplished by resolving both the SAR-based wind speed and wind direction retrieval problems independently. The sea surface wind speed is retrieved by means of a SAR wind speed algorithm based on the azimuth cut-off procedure, while the sea surface wind direction is provided by means of a SAR wind direction algorithm based on the discrete wavelet transform multi-resolution analysis. The obtained wind fields are compared with ground truth data provided by both ASCAT scatterometer and ECMWF model wind fields. SAR-derived wind vector fields and ECMWF model wind data are used to construct a blended wind product regularly sampled in both space and time, which is then used to force a coastal circulation model of a southern Tyrrhenian coastal area to simulate wind-driven circulation processes. The modeling results show that X-band COSMO-SkyMed^© SAR data can be valuable in providing effective wind fields for coastal circulation modeling.

Grid refinement model in lattice Boltzmann method for stream function-vorticity formulations

Energy Technology Data Exchange (ETDEWEB)

Shin, Myung Seob [Dept. of Mechanical Engineering, Dongyang Mirae University, Seoul (Korea, Republic of)

2015-03-15

In this study, we present a grid refinement model in the lattice Boltzmann method (LBM) for two-dimensional incompressible fluid flow. That is, the model combines the desirable features of the lattice Boltzmann method and stream function-vorticity formulations. In order to obtain an accurate result, very fine grid (or lattice) is required near the solid boundary. Therefore, the grid refinement model is used in the lattice Boltzmann method for stream function-vorticity formulation. This approach is more efficient in that it can obtain the same accurate solution as that in single-block approach even if few lattices are used for computation. In order to validate the grid refinement approach for the stream function-vorticity formulation, the numerical simulations of lid-driven cavity flows were performed and good results were obtained.

Modeling Marine Electromagnetic Survey with Radial Basis Function Networks

Directory of Open Access Journals (Sweden)

Agus Arif

2014-11-01

Full Text Available A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP network. By comparing their validation and training performances (mean-squared errors and correlation coefficients, it is concluded that, in this case, the MLP network is comparatively better than the RBF network[1].[1] This manuscript is an extended version of our previous paper, entitled Radial Basis Function Networks for Modeling Marine Electromagnetic Survey, which had been presented on 2011 International Conference on Electrical Engineering and Informatics, 17-19 July 2011, Bandung, Indonesia.

Computation of piecewise affine terminal cost functions for model predictive control

NARCIS (Netherlands)

Brunner, F.D.; Lazar, M.; Allgöwer, F.; Fränzle, Martin; Lygeros, John

2014-01-01

This paper proposes a method for the construction of piecewise affine terminal cost functions for model predictive control (MPC). The terminal cost function is constructed on a predefined partition by solving a linear program for a given piecewise affine system, a stabilizing piecewise affine

Assimilation of the ESA CCI Soil Moisture ACTIVE and PASSIVE Product into the SURFEX Land Surface Model using the Ensemble Transform Kalman Filter

Science.gov (United States)

Blyverket, J.; Hamer, P.; Bertino, L.; Lahoz, W. A.

2017-12-01

The European Space Agency Climate Change Initiative for soil moisture (ESA CCI SM) was initiated in 2012 for a period of six years, the objective for this period was to produce the most complete and consistent global soil moisture data record based on both active and passive sensors. The ESA CCI SM products consist of three surface soil moisture datasets: The ACTIVE product and the PASSIVE product were created by fusing scatterometer and radiometer soil moisture data, respectively. The COMBINED product is a blended product based on the former two datasets. In this study we assimilate globally both the ACTIVE and PASSIVE product at a 25 km spatial resolution. The different satellite platforms have different overpass times, an observation is mapped to the hours 00.00, 06.00, 12.00 or 18.00 if it falls within a 3 hour window centred at these times. We use the SURFEX land surface model with the ISBA diffusion scheme for the soil hydrology. For the assimilation routine we apply the Ensemble Transform Kalman Filter (ETKF). The land surface model is driven by perturbed MERRA-2 atmospheric forcing data, which has a temporal resolution of one hour and is mapped to the SURFEX model grid. Bias between the land surface model and the ESA CCI product is removed by cumulative distribution function (CDF) matching. This work is a step towards creating a global root zone soil moisture product from the most comprehensive satellite surface soil moisture product available. As a first step we consider the period from 2010 - 2016. This allows for comparison against other global root zone soil moisture products (SMAP Level 4, which is independent of the ESA CCI SM product).

The Use of Modeling Approach for Teaching Exponential Functions

Science.gov (United States)

Nunes, L. F.; Prates, D. B.; da Silva, J. M.

2017-12-01

This work presents a discussion related to the teaching and learning of mathematical contents related to the study of exponential functions in a freshman students group enrolled in the first semester of the Science and Technology Bachelor’s (STB of the Federal University of Jequitinhonha and Mucuri Valleys (UFVJM). As a contextualization tool strongly mentioned in the literature, the modelling approach was used as an educational teaching tool to produce contextualization in the teaching-learning process of exponential functions to these students. In this sense, were used some simple models elaborated with the GeoGebra software and, to have a qualitative evaluation of the investigation and the results, was used Didactic Engineering as a methodology research. As a consequence of this detailed research, some interesting details about the teaching and learning process were observed, discussed and described.

Modeling of edge effect in subaperture tool influence functions of computer controlled optical surfacing.

Science.gov (United States)

Wan, Songlin; Zhang, Xiangchao; He, Xiaoying; Xu, Min

2016-12-20

Computer controlled optical surfacing requires an accurate tool influence function (TIF) for reliable path planning and deterministic fabrication. Near the edge of the workpieces, the TIF has a nonlinear removal behavior, which will cause a severe edge-roll phenomenon. In the present paper, a new edge pressure model is developed based on the finite element analysis results. The model is represented as the product of a basic pressure function and a correcting function. The basic pressure distribution is calculated according to the surface shape of the polishing pad, and the correcting function is used to compensate the errors caused by the edge effect. Practical experimental results demonstrate that the new model can accurately predict the edge TIFs with different overhang ratios. The relative error of the new edge model can be reduced to 15%.

A perturbative approach to the redshift space correlation function: beyond the Standard Model

Science.gov (United States)

Bose, Benjamin; Koyama, Kazuya

2017-08-01

We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model which is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with <= 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 50Mpch <= s <= 180Mpc/h. Excellent agreement is found in the differences between the modified gravity and GR multipole predictions for both approaches to the redshift space correlation function, highlighting their matched ability in picking up deviations from GR. We elucidate the timeliness of such non-standard templates at the dawn of stage-IV surveys and discuss necessary preparations and extensions needed for upcoming high quality data.

Electricity price forecasting through transfer function models

International Nuclear Information System (INIS)

Nogales, F.J.; Conejo, A.J.

2006-01-01

Forecasting electricity prices in present day competitive electricity markets is a must for both producers and consumers because both need price estimates to develop their respective market bidding strategies. This paper proposes a transfer function model to predict electricity prices based on both past electricity prices and demands, and discuss the rationale to build it. The importance of electricity demand information is assessed. Appropriate metrics to appraise prediction quality are identified and used. Realistic and extensive simulations based on data from the PJM Interconnection for year 2003 are conducted. The proposed model is compared with naive and other techniques. Journal of the Operational Research Society (2006) 57, 350-356.doi:10.1057/palgrave.jors.2601995; published online 18 May 2005. (author)

Structure-based Markov random field model for representing evolutionary constraints on functional sites.

Science.gov (United States)

Jeong, Chan-Seok; Kim, Dongsup

2016-02-24

Elucidating the cooperative mechanism of interconnected residues is an important component toward understanding the biological function of a protein. Coevolution analysis has been developed to model the coevolutionary information reflecting structural and functional constraints. Recently, several methods have been developed based on a probabilistic graphical model called the Markov random field (MRF), which have led to significant improvements for coevolution analysis; however, thus far, the performance of these models has mainly been assessed by focusing on the aspect of protein structure. In this study, we built an MRF model whose graphical topology is determined by the residue proximity in the protein structure, and derived a novel positional coevolution estimate utilizing the node weight of the MRF model. This structure-based MRF method was evaluated for three data sets, each of which annotates catalytic site, allosteric site, and comprehensively determined functional site information. We demonstrate that the structure-based MRF architecture can encode the evolutionary information associated with biological function. Furthermore, we show that the node weight can more accurately represent positional coevolution information compared to the edge weight. Lastly, we demonstrate that the structure-based MRF model can be reliably built with only a few aligned sequences in linear time. The results show that adoption of a structure-based architecture could be an acceptable approximation for coevolution modeling with efficient computation complexity.

Correlation Functions in Holographic Minimal Models

CERN Document Server

Papadodimas, Kyriakos

2012-01-01

We compute exact three and four point functions in the W_N minimal models that were recently conjectured to be dual to a higher spin theory in AdS_3. The boundary theory has a large number of light operators that are not only invisible in the bulk but grow exponentially with N even at small conformal dimensions. Nevertheless, we provide evidence that this theory can be understood in a 1/N expansion since our correlators look like free-field correlators corrected by a power series in 1/N . However, on examining these corrections we find that the four point function of the two bulk scalar fields is corrected at leading order in 1/N through the contribution of one of the additional light operators in an OPE channel. This suggests that, to correctly reproduce even tree-level correlators on the boundary, the bulk theory needs to be modified by the inclusion of additional fields. As a technical by-product of our analysis, we describe two separate methods -- including a Coulomb gas type free-field formalism -- that ...

Developing the multi-level functioning interface framework for DER models

DEFF Research Database (Denmark)

Han, Xue; Bindner, Henrik W.; You, Shi

2013-01-01

The paper summarises several modelling applications of distributed energy resources (DERs) for various purposes, and describes the related operational issues regarding the complexity of the future distribution grid. Furthermore, a multi-level functioning interface framework is proposed for DER mo....... The information mapping for photovoltaic panel (PV) modelling is also provided as an example....

Plant lessons: exploring ABCB functionality through structural modeling

Directory of Open Access Journals (Sweden)

Aurélien eBailly

2012-01-01

Full Text Available In contrast to mammalian ABCB1 proteins, narrow substrate specificity has been extensively documented for plant orthologs shown to catalyze the transport of the plant hormone, auxin. Using the crystal structures of the multidrug exporters Sav1866 and MmABCB1 as templates, we have developed structural models of plant ABCB proteins with a common architecture. Comparisons of these structures identified kingdom-specific candidate substrate-binding regions within the translocation chamber formed by the transmembrane domains of ABCBs from the model plant Arabidopsis. These results suggest an early evolutionary divergence of plant and mammalian ABCBs. Validation of these models becomes a priority for efforts to elucidate ABCB function and manipulate this class of transporters to enhance plant productivity and quality.

Modeling of sintering of functionally gradated materials

International Nuclear Information System (INIS)

Gasik, M.; Zhang, B.

2001-01-01

The functionally gradated materials (FGMs) are distinguished from isotropic materials by gradients of composition, phase distribution, porosity, and related properties. For FGMs made by powder metallurgy, sintering control is one of the most important factors. In this study sintering process of FGMs is modeled and simulated with a computer. A new modeling approach was used to formulate equation systems and the model for sintering of gradated hard metals, coupled with heat transfer and grain growth. A FEM module was developed to simulate FGM sintering in conventional, microwave and hybrid conditions, to calculate density, stress and temperature distribution. Behavior of gradated WC-Co hardmetal plate and cone specimens was simulated for various conditions, such as mean particle size, green density distribution and cobalt gradation parameter. The results show that the deformation behavior and stress history of graded powder compacts during heating, sintering and cooling could be predicted for optimization of sintering process. (author)

Describing a Strongly Correlated Model System with Density Functional Theory.

Science.gov (United States)

Kong, Jing; Proynov, Emil; Yu, Jianguo; Pachter, Ruth

2017-07-06

The linear chain of hydrogen atoms, a basic prototype for the transition from a metal to Mott insulator, is studied with a recent density functional theory model functional for nondynamic and strong correlation. The computed cohesive energy curve for the transition agrees well with accurate literature results. The variation of the electronic structure in this transition is characterized with a density functional descriptor that yields the atomic population of effectively localized electrons. These new methods are also applied to the study of the Peierls dimerization of the stretched even-spaced Mott insulator to a chain of H 2 molecules, a different insulator. The transitions among the two insulating states and the metallic state of the hydrogen chain system are depicted in a semiquantitative phase diagram. Overall, we demonstrate the capability of studying strongly correlated materials with a mean-field model at the fundamental level, in contrast to the general pessimistic view on such a feasibility.

Parton distribution functions with QED corrections in the valon model

Science.gov (United States)

Mottaghizadeh, Marzieh; Taghavi Shahri, Fatemeh; Eslami, Parvin

2017-10-01

The parton distribution functions (PDFs) with QED corrections are obtained by solving the QCD ⊗QED DGLAP evolution equations in the framework of the "valon" model at the next-to-leading-order QCD and the leading-order QED approximations. Our results for the PDFs with QED corrections in this phenomenological model are in good agreement with the newly related CT14QED global fits code [Phys. Rev. D 93, 114015 (2016), 10.1103/PhysRevD.93.114015] and APFEL (NNPDF2.3QED) program [Comput. Phys. Commun. 185, 1647 (2014), 10.1016/j.cpc.2014.03.007] in a wide range of x =[10-5,1 ] and Q2=[0.283 ,108] GeV2 . The model calculations agree rather well with those codes. In the latter, we proposed a new method for studying the symmetry breaking of the sea quark distribution functions inside the proton.

Binary pseudo-random patterned structures for modulation transfer function calibration and resolution characterization of a full-field transmission soft x-ray microscope

Energy Technology Data Exchange (ETDEWEB)

Yashchuk, V. V., E-mail: VVYashchuk@lbl.gov; Chan, E. R.; Lacey, I. [Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Fischer, P. J. [Center for X-Ray Optics, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Physics Department, University of California Santa Cruz, Santa Cruz, California 94056 (United States); Conley, R. [Advance Photon Source, Argonne National Laboratory, Argonne, Illinois 60439 (United States); National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, New York 11973 (United States); McKinney, W. R. [Diablo Valley College, 321 Golf Club Road, Pleasant Hill, California 94523 (United States); Artemiev, N. A. [KLA-Tencor Corp., 1 Technology Drive, Milpitas, California 95035 (United States); Bouet, N. [National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, New York 11973 (United States); Cabrini, S. [Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Calafiore, G.; Peroz, C.; Babin, S. [aBeam Technologies, Inc., Hayward, California 94541 (United States)

2015-12-15

We present a modulation transfer function (MTF) calibration method based on binary pseudo-random (BPR) one-dimensional sequences and two-dimensional arrays as an effective method for spectral characterization in the spatial frequency domain of a broad variety of metrology instrumentation, including interferometric microscopes, scatterometers, phase shifting Fizeau interferometers, scanning and transmission electron microscopes, and at this time, x-ray microscopes. The inherent power spectral density of BPR gratings and arrays, which has a deterministic white-noise-like character, allows a direct determination of the MTF with a uniform sensitivity over the entire spatial frequency range and field of view of an instrument. We demonstrate the MTF calibration and resolution characterization over the full field of a transmission soft x-ray microscope using a BPR multilayer (ML) test sample with 2.8 nm fundamental layer thickness. We show that beyond providing a direct measurement of the microscope’s MTF, tests with the BPRML sample can be used to fine tune the instrument’s focal distance. Our results confirm the universality of the method that makes it applicable to a large variety of metrology instrumentation with spatial wavelength bandwidths from a few nanometers to hundreds of millimeters.

Binary pseudo-random patterned structures for modulation transfer function calibration and resolution characterization of a full-field transmission soft x-ray microscope

International Nuclear Information System (INIS)

Yashchuk, V. V.; Chan, E. R.; Lacey, I.; Fischer, P. J.; Conley, R.; McKinney, W. R.; Artemiev, N. A.; Bouet, N.; Cabrini, S.; Calafiore, G.; Peroz, C.; Babin, S.

2015-01-01

We present a modulation transfer function (MTF) calibration method based on binary pseudo-random (BPR) one-dimensional sequences and two-dimensional arrays as an effective method for spectral characterization in the spatial frequency domain of a broad variety of metrology instrumentation, including interferometric microscopes, scatterometers, phase shifting Fizeau interferometers, scanning and transmission electron microscopes, and at this time, x-ray microscopes. The inherent power spectral density of BPR gratings and arrays, which has a deterministic white-noise-like character, allows a direct determination of the MTF with a uniform sensitivity over the entire spatial frequency range and field of view of an instrument. We demonstrate the MTF calibration and resolution characterization over the full field of a transmission soft x-ray microscope using a BPR multilayer (ML) test sample with 2.8 nm fundamental layer thickness. We show that beyond providing a direct measurement of the microscope’s MTF, tests with the BPRML sample can be used to fine tune the instrument’s focal distance. Our results confirm the universality of the method that makes it applicable to a large variety of metrology instrumentation with spatial wavelength bandwidths from a few nanometers to hundreds of millimeters

A Multi-Level Model of Moral Functioning Revisited

Science.gov (United States)

Reed, Don Collins

2009-01-01

The model of moral functioning scaffolded in the 2008 "JME" Special Issue is here revisited in response to three papers criticising that volume. As guest editor of that Special Issue I have formulated the main body of this response, concerning the dynamic systems approach to moral development, the problem of moral relativism and the role of…

Three-level models solvable in terms of the Clausen function

International Nuclear Information System (INIS)

Ishkhanyan, Artur; Suominen, Kalle-Antti

2003-01-01

The problem of analytical integrability of the three-level problem by reduction of the time-dependent Schroedinger equations to the third-order linear differential equation satisfied by the generalized hypergeometric functions 3 F 2 is considered. A total of 12 infinite classes of models solvable in terms of these functions is found, most of which are new and others are generalizations of the previously known families

Hydrological-niche models predict water plant functional group distributions in diverse wetland types.

Science.gov (United States)

Deane, David C; Nicol, Jason M; Gehrig, Susan L; Harding, Claire; Aldridge, Kane T; Goodman, Abigail M; Brookes, Justin D

2017-06-01

Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalize community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water plant functional group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 687 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed that models achieved acceptable predictive performance, with correct classification rates in the range 0.68-0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. © 2017 by the Ecological Society of America.

Model of bidirectional reflectance distribution function for metallic materials

International Nuclear Information System (INIS)

Wang Kai; Zhu Jing-Ping; Liu Hong; Hou Xun

2016-01-01

Based on the three-component assumption that the reflection is divided into specular reflection, directional diffuse reflection, and ideal diffuse reflection, a bidirectional reflectance distribution function (BRDF) model of metallic materials is presented. Compared with the two-component assumption that the reflection is composed of specular reflection and diffuse reflection, the three-component assumption divides the diffuse reflection into directional diffuse and ideal diffuse reflection. This model effectively resolves the problem that constant diffuse reflection leads to considerable error for metallic materials. Simulation and measurement results validate that this three-component BRDF model can improve the modeling accuracy significantly and describe the reflection properties in the hemisphere space precisely for the metallic materials. (paper)

Model of bidirectional reflectance distribution function for metallic materials

Science.gov (United States)

Wang, Kai; Zhu, Jing-Ping; Liu, Hong; Hou, Xun

2016-09-01

Based on the three-component assumption that the reflection is divided into specular reflection, directional diffuse reflection, and ideal diffuse reflection, a bidirectional reflectance distribution function (BRDF) model of metallic materials is presented. Compared with the two-component assumption that the reflection is composed of specular reflection and diffuse reflection, the three-component assumption divides the diffuse reflection into directional diffuse and ideal diffuse reflection. This model effectively resolves the problem that constant diffuse reflection leads to considerable error for metallic materials. Simulation and measurement results validate that this three-component BRDF model can improve the modeling accuracy significantly and describe the reflection properties in the hemisphere space precisely for the metallic materials.

Rapid formation of a sea ice barrier east of Svalbard

Science.gov (United States)

Nghiem, S. V.; van Woert, M. L.; Neumann, G.

2005-11-01

Daily SeaWinds scatterometer images acquired by the QuikSCAT satellite show an elongated sea ice feature that formed very rapidly (˜1-2 days) in November 2001 east of Svalbard over the Barents Sea. This sea ice structure, called "the Svalbard sea ice barrier," spanning approximately 10° in longitude and 2° in latitude, restricts the sea route and poses a significant navigation hazard. The secret of its formation appears to lie in the bottom of the sea: A comparison between bathymetry from the International Bathymetric Chart of the Arctic Ocean data and the pattern of sea ice formation from scatterometer data reveals that the sea ice barrier conforms well with and stretches above a deep elongated channel connecting the Franz Josef-Victoria Trough to the Hinlopen Basin between Svalbard and Franz Josef Land. Historic hydrographic data from this area indicate that this sea channel contains cold Arctic water less than 50 m below the surface. Strong and persistent cold northerly winds force strong heat loss from this shallow surface layer, leading to the rapid formation of the sea ice barrier. Heat transfer rates estimated from European Centre for Medium-Range Weather Forecasts temperature and wind data over this region suggest that the surface water along the deep channel can be rapidly cooled to the freezing point. Scatterometer results in 1999-2003 show that sea ice forms in this area between October and December. Understanding the ice formation mechanisms helps to select appropriate locations for deployment of buoys measuring wind and air-sea temperature profile and to facilitate ice monitoring, modeling, and forecasting.

Plasmon point spread functions: How do we model plasmon-mediated emission processes?

Science.gov (United States)

Willets, Katherine A.

2014-02-01

A major challenge with studying plasmon-mediated emission events is the small size of plasmonic nanoparticles relative to the wavelength of light. Objects smaller than roughly half the wavelength of light will appear as diffraction-limited spots in far-field optical images, presenting a significant experimental challenge for studying plasmonic processes on the nanoscale. Super-resolution imaging has recently been applied to plasmonic nanosystems and allows plasmon-mediated emission to be resolved on the order of ˜5 nm. In super-resolution imaging, a diffraction-limited spot is fit to some model function in order to calculate the position of the emission centroid, which represents the location of the emitter. However, the accuracy of the centroid position strongly depends on how well the fitting function describes the data. This Perspective discusses the commonly used two-dimensional Gaussian fitting function applied to super-resolution imaging of plasmon-mediated emission, then introduces an alternative model based on dipole point spread functions. The two fitting models are compared and contrasted for super-resolution imaging of nanoparticle scattering/luminescence, surface-enhanced Raman scattering, and surface-enhanced fluorescence.

Applying Functional Modeling for Accident Management of Nuclear Power Plant

Energy Technology Data Exchange (ETDEWEB)

Lind, Morten; Zhang Xinxin [Harbin Engineering University, Harbin (China)

2014-08-15

The paper investigate applications of functional modeling for accident management in complex industrial plant with special reference to nuclear power production. Main applications for information sharing among decision makers and decision support are identified. An overview of Multilevel Flow Modeling is given and a detailed presentation of the foundational means-end concepts is presented and the conditions for proper use in modelling accidents are identified. It is shown that Multilevel Flow Modeling can be used for modelling and reasoning about design basis accidents. Its possible role for information sharing and decision support in accidents beyond design basis is also indicated. A modelling example demonstrating the application of Multilevel Flow Modelling and reasoning for a PWR LOCA is presented.

Adaptive filters and internal models: multilevel description of cerebellar function.

Science.gov (United States)

Porrill, John; Dean, Paul; Anderson, Sean R

2013-11-01

Cerebellar function is increasingly discussed in terms of engineering schemes for motor control and signal processing that involve internal models. To address the relation between the cerebellum and internal models, we adopt the chip metaphor that has been used to represent the combination of a homogeneous cerebellar cortical microcircuit with individual microzones having unique external connections. This metaphor indicates that identifying the function of a particular cerebellar chip requires knowledge of both the general microcircuit algorithm and the chip's individual connections. Here we use a popular candidate algorithm as embodied in the adaptive filter, which learns to decorrelate its inputs from a reference ('teaching', 'error') signal. This algorithm is computationally powerful enough to be used in a very wide variety of engineering applications. However, the crucial issue is whether the external connectivity required by such applications can be implemented biologically. We argue that some applications appear to be in principle biologically implausible: these include the Smith predictor and Kalman filter (for state estimation), and the feedback-error-learning scheme for adaptive inverse control. However, even for plausible schemes, such as forward models for noise cancellation and novelty-detection, and the recurrent architecture for adaptive inverse control, there is unlikely to be a simple mapping between microzone function and internal model structure. This initial analysis suggests that cerebellar involvement in particular behaviours is therefore unlikely to have a neat classification into categories such as 'forward model'. It is more likely that cerebellar microzones learn a task-specific adaptive-filter operation which combines a number of signal-processing roles. Copyright © 2012 Elsevier Ltd. All rights reserved.

Predicting cognitive function of the Malaysian elderly: a structural equation modelling approach.

Science.gov (United States)

Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah; Shahar, Suzana

2018-01-01

The aim of this study was to identify the predictors of elderly's cognitive function based on biopsychosocial and cognitive reserve perspectives. The study included 2322 community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, biomarkers, psychosocial status, disability, and cognitive function. A biopsychosocial model of cognitive function was developed to test variables' predictive power on cognitive function. Statistical analyses were performed using SPSS (version 15.0) in conjunction with Analysis of Moment Structures Graphics (AMOS 7.0). The estimated theoretical model fitted the data well. Psychosocial stress and metabolic syndrome (MetS) negatively predicted cognitive function and psychosocial stress appeared as a main predictor. Socio-demographic characteristics, except gender, also had significant effects on cognitive function. However, disability failed to predict cognitive function. Several factors together may predict cognitive function in the Malaysian elderly population, and the variance accounted for it is large enough to be considered substantial. Key factor associated with the elderly's cognitive function seems to be psychosocial well-being. Thus, psychosocial well-being should be included in the elderly assessment, apart from medical conditions, both in clinical and community setting.

Non-local energy density functionals: models plus some exact general results

International Nuclear Information System (INIS)

March, N.H.

2001-02-01

Holas and March (Phys. Rev. A51, 2040, 1995) gave a formally exact expression for the force - δV xc (r-tilde)/δr-tilde associated with the exchange-correlation potential V xc (r-tilde) of density functional theory. This forged a precise link between first- and second-order density matrices and V xc (r-tilde). Here models are presented in which these low-order matrices can be related to the ground-state electron density. This allows non-local energy density functionals to be constructed within the framework of such models. Finally, results emerging from these models have led to the derivation of some exact 'nuclear cusp' relations for exchange and correlation energy densities in molecules, clusters and condensed phases. (author)

The Einstein action for algebras of matrix valued functions - Toy models

Energy Technology Data Exchange (ETDEWEB)

Hajac, P M

1995-10-01

Two toy models are considered within the framework of noncommutative differential geometry. In the first one, the Einstein action of the Levi-Civita connection is computed for the algebra of matrix valued functions on a torus. It is shown that, assuming some constraints on the metric, this action splits into a classical-like, a quantum-like and a mixed term. In the second model, an analogue of the Palatini method of variation is applied to obtain critical points of the Einstein action functional for M{sub 4}(R). It is pointed out that a solution to the Palatini variational problem is not necessarily a Levi-Civita connection. In this model, no additional assumptions regarding metrics are made. (author). 14 refs.

Functional Decomposition of Modeling and Simulation Terrain Database Generation Process

National Research Council Canada - National Science Library

Yakich, Valerie R; Lashlee, J. D

2008-01-01

.... This report documents the conceptual procedure as implemented by Lockheed Martin Simulation, Training, and Support and decomposes terrain database construction using the Integration Definition for Function Modeling (IDEF...

Bridging the gap between measurements and modelling: a cardiovascular functional avatar.

Science.gov (United States)

Casas, Belén; Lantz, Jonas; Viola, Federica; Cedersund, Gunnar; Bolger, Ann F; Carlhäll, Carl-Johan; Karlsson, Matts; Ebbers, Tino

2017-07-24

Lumped parameter models of the cardiovascular system have the potential to assist researchers and clinicians to better understand cardiovascular function. The value of such models increases when they are subject specific. However, most approaches to personalize lumped parameter models have thus far required invasive measurements or fall short of being subject specific due to a lack of the necessary clinical data. Here, we propose an approach to personalize parameters in a model of the heart and the systemic circulation using exclusively non-invasive measurements. The personalized model is created using flow data from four-dimensional magnetic resonance imaging and cuff pressure measurements in the brachial artery. We term this personalized model the cardiovascular avatar. In our proof-of-concept study, we evaluated the capability of the avatar to reproduce pressures and flows in a group of eight healthy subjects. Both quantitatively and qualitatively, the model-based results agreed well with the pressure and flow measurements obtained in vivo for each subject. This non-invasive and personalized approach can synthesize medical data into clinically relevant indicators of cardiovascular function, and estimate hemodynamic variables that cannot be assessed directly from clinical measurements.