The vanishing limit of the square-well fluid: The adhesive hard-sphere model as a reference system

NASA Astrophysics Data System (ADS)

Largo, J.; Miller, M. A.; Sciortino, F.

2008-04-01

We report a simulation study of the gas-liquid critical point for the square-well potential, for values of well width δ as small as 0.005 times the particle diameter σ. For small δ, the reduced second virial coefficient at the critical point B2*c is found to depend linearly on δ. The observed weak linear dependence is not sufficient to produce any significant observable effect if the critical temperature Tc is estimated via a constant B2*c assumption, due to the highly nonlinear transformation between B2*c and Tc. This explains the previously observed validity of the law of corresponding states. The critical density ρc is also found to be constant when measured in units of the cube of the average distance between two bonded particles (1+0.5δ)σ. The possibility of describing the δ →0 dependence with precise functional forms provides improved accurate estimates of the critical parameters of the adhesive hard-sphere model.

The vanishing limit of the square-well fluid: the adhesive hard-sphere model as a reference system.

PubMed

Largo, J; Miller, M A; Sciortino, F

2008-04-07

We report a simulation study of the gas-liquid critical point for the square-well potential, for values of well width delta as small as 0.005 times the particle diameter sigma. For small delta, the reduced second virial coefficient at the critical point B2*c is found to depend linearly on delta. The observed weak linear dependence is not sufficient to produce any significant observable effect if the critical temperature Tc is estimated via a constant B2*c assumption, due to the highly nonlinear transformation between B2*c and Tc. This explains the previously observed validity of the law of corresponding states. The critical density rho c is also found to be constant when measured in units of the cube of the average distance between two bonded particles (1+0.5 delta)sigma. The possibility of describing the delta-->0 dependence with precise functional forms provides improved accurate estimates of the critical parameters of the adhesive hard-sphere model.

Hydrogeology and simulation of ground-water flow at US Marine Corps Air Station, Cherry Point, North Carolina, 1987-90

USGS Publications Warehouse

Eimers, J.L.; Daniel, C. C.; Coble, R.W.

1994-01-01

Geophysical and lithologic well-log data from 30 wells and chloride data, and water-level data from oil-test wells, supply wells, and observation wells were evaluated to define the hydrogeologic framework at the U.S. Marine Corps Air Station, Cherry Point, North Carolina. Elements of the hydrogeologic framework important to this study include six aquifers and their respective confining units. In descending order, these aquifers are the surficial, Yorktown, Pungo River, upper and lower Castle Hayne, and Beaufort. The upper and lower Castle Hayne and Beaufort aquifers and related confining units are relatively continuous throughout the study area. The surficial, Yorktown, Pungo River, and upper and lower Castle Hayne aquifers contain freshwater. The upper and lower Castle Hayne aquifers serve as the Air Station?s principal supply of freshwater. However, the lower Castle Hayne aquifer contains brackish water near its base and there is potential for upward movement of this water to supply wells completed in this aquifer. The potential for brackish-water encroachment is greatest if wells are screened too deep in the lower Castle Hayne aquifer or if pumping rates are too high. Lateral movement of brackish water into aquifers incised by estuarine streams is also possible if ground-water flow gradients toward these bodies are reversed by pumping. The potential for the reversed movement of water from the surficial aquifer downward to the water-supply aquifer is greatest in areas where clay confining units are missing. These missing clay units could indicate the presence of a paleochannel of the Neuse River. A quasi three-dimensional finite-difference ground-water flow model was constructed and calibrated to simulate conditions at and in the vicinity of the Air Station for the period of 1987-90. Comparisons of 94 observed and computed heads were made, and the average difference between them is -0.2 feet with a root mean square error of 5.7 feet. An analysis was made to evaluate the sensitivity of the model to the absence of the Yorktown and Pungo River confining units in a 1-square-mile area in the southern part of the Air Station. This analysis resulted in a maximum simulated head increase of 2 feet in one 0.11-square-mile model cell in the Pungo River aquifer.

Structure, thermodynamic properties, and phase diagrams of few colloids confined in a spherical pore.

PubMed

Paganini, Iván E; Pastorino, Claudio; Urrutia, Ignacio

2015-06-28

We study a system of few colloids confined in a small spherical cavity with event driven molecular dynamics simulations in the canonical ensemble. The colloidal particles interact through a short range square-well potential that takes into account the basic elements of attraction and excluded-volume repulsion of the interaction among colloids. We analyze the structural and thermodynamic properties of this few-body confined system in the framework of inhomogeneous fluids theory. Pair correlation function and density profile are used to determine the structure and the spatial characteristics of the system. Pressure on the walls, internal energy, and surface quantities such as surface tension and adsorption are also analyzed for a wide range of densities and temperatures. We have characterized systems from 2 to 6 confined particles, identifying distinctive qualitative behavior over the thermodynamic plane T - ρ, in a few-particle equivalent to phase diagrams of macroscopic systems. Applying the extended law of corresponding states, the square well interaction is mapped to the Asakura-Oosawa model for colloid-polymer mixtures. We link explicitly the temperature of the confined square-well fluid to the equivalent packing fraction of polymers in the Asakura-Oosawa model. Using this approach, we study the confined system of few colloids in a colloid-polymer mixture.

Structure, thermodynamic properties, and phase diagrams of few colloids confined in a spherical pore

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

Paganini, Iván E.; Pastorino, Claudio, E-mail: pastor@cnea.gov.ar; Urrutia, Ignacio, E-mail: iurrutia@cnea.gov.ar

2015-06-28

We study a system of few colloids confined in a small spherical cavity with event driven molecular dynamics simulations in the canonical ensemble. The colloidal particles interact through a short range square-well potential that takes into account the basic elements of attraction and excluded-volume repulsion of the interaction among colloids. We analyze the structural and thermodynamic properties of this few-body confined system in the framework of inhomogeneous fluids theory. Pair correlation function and density profile are used to determine the structure and the spatial characteristics of the system. Pressure on the walls, internal energy, and surface quantities such as surfacemore » tension and adsorption are also analyzed for a wide range of densities and temperatures. We have characterized systems from 2 to 6 confined particles, identifying distinctive qualitative behavior over the thermodynamic plane T − ρ, in a few-particle equivalent to phase diagrams of macroscopic systems. Applying the extended law of corresponding states, the square well interaction is mapped to the Asakura-Oosawa model for colloid-polymer mixtures. We link explicitly the temperature of the confined square-well fluid to the equivalent packing fraction of polymers in the Asakura-Oosawa model. Using this approach, we study the confined system of few colloids in a colloid-polymer mixture.« less

Potential effects of deep-well waste disposal in western New York

USGS Publications Warehouse

Waller, Roger Milton; Turk, John T.; Dingman, Robert James

1978-01-01

Mathematical and laboratory models were used to observe, respectively, the hydraulic and chemical reactions that may take place during proposed injection of a highly acidic, iron-rich waste pickle liquor into a deep waste-disposal well in western New York. Field temperature and pressure conditions were simulated in the tests. Hydraulic pressure in the middle stages of the initial (1968) injection test had probably hydraulically fractured the Cambrian sandstone-dolomite formation adjacent to the borehole. Transmissivity of the formation is 13 feet squared per day. The proposed rate of injection (72,000 gallons per day) of waste pickle liquor would approach a wellhead pressure of 600 pounds per square inch in about a year. Hydraulic fracturing would reoccur at about 580 pounds per square inch. The measurable cone of influence would extend about 22 miles after injection for 1 year. Chemical reactions between acidic wastes and brine-saturated dolomite would create precipitates that would drastically reduce the permeability of the unfractured part of the dolomite. Nondolomitic sandstone permeability would not be affected by chemical reactions, but the pores might be plugged by the iron-bearing waste. The digital model can be used for qualitative predictions on a regional scale. (Woodard-USGS)

Aerodynamic parameter estimation via Fourier modulating function techniques

NASA Technical Reports Server (NTRS)

Pearson, A. E.

1995-01-01

Parameter estimation algorithms are developed in the frequency domain for systems modeled by input/output ordinary differential equations. The approach is based on Shinbrot's method of moment functionals utilizing Fourier based modulating functions. Assuming white measurement noises for linear multivariable system models, an adaptive weighted least squares algorithm is developed which approximates a maximum likelihood estimate and cannot be biased by unknown initial or boundary conditions in the data owing to a special property attending Shinbrot-type modulating functions. Application is made to perturbation equation modeling of the longitudinal and lateral dynamics of a high performance aircraft using flight-test data. Comparative studies are included which demonstrate potential advantages of the algorithm relative to some well established techniques for parameter identification. Deterministic least squares extensions of the approach are made to the frequency transfer function identification problem for linear systems and to the parameter identification problem for a class of nonlinear-time-varying differential system models.

The paradoxical zero reflection at zero energy

NASA Astrophysics Data System (ADS)

Ahmed, Zafar; Sharma, Vibhu; Sharma, Mayank; Singhal, Ankush; Kaiwart, Rahul; Priyadarshini, Pallavi

2017-03-01

Usually, the reflection probability R(E) of a particle of zero energy incident on a potential which converges to zero asymptotically is found to be 1: R(0)=1. But earlier, a paradoxical phenomenon of zero reflection at zero energy (R(0)=0) has been revealed as a threshold anomaly. Extending the concept of half-bound state (HBS) of 3D, here we show that in 1D when a symmetric (asymmetric) attractive potential well possesses a zero-energy HBS, R(0)=0 (R(0)\\ll 1). This can happen only at some critical values q c of an effective parameter q of the potential well in the limit E\\to {0}+. We demonstrate this critical phenomenon in two simple analytically solvable models: square and exponential wells. However, in numerical calculations, even for these two models R(0)=0 is observed only as extrapolation to zero energy from low energies, close to a precise critical value q c. By numerical investigation of a variety of potential wells, we conclude that for a given potential well (symmetric or asymmetric), we can adjust the effective parameter q to have a low reflection at a low energy.

Modeling Hurricane Katrina's merchantable timber and wood damage in south Mississippi using remotely sensed and field-measured data

NASA Astrophysics Data System (ADS)

Collins, Curtis Andrew

Ordinary and weighted least squares multiple linear regression techniques were used to derive 720 models predicting Katrina-induced storm damage in cubic foot volume (outside bark) and green weight tons (outside bark). The large number of models was dictated by the use of three damage classes, three product types, and four forest type model strata. These 36 models were then fit and reported across 10 variable sets and variable set combinations for volume and ton units. Along with large model counts, potential independent variables were created using power transforms and interactions. The basis of these variables was field measured plot data, satellite (Landsat TM and ETM+) imagery, and NOAA HWIND wind data variable types. As part of the modeling process, lone variable types as well as two-type and three-type combinations were examined. By deriving models with these varying inputs, model utility is flexible as all independent variable data are not needed in future applications. The large number of potential variables led to the use of forward, sequential, and exhaustive independent variable selection techniques. After variable selection, weighted least squares techniques were often employed using weights of one over the square root of the pre-storm volume or weight of interest. This was generally successful in improving residual variance homogeneity. Finished model fits, as represented by coefficient of determination (R2), surpassed 0.5 in numerous models with values over 0.6 noted in a few cases. Given these models, an analyst is provided with a toolset to aid in risk assessment and disaster recovery should Katrina-like weather events reoccur.

Nuclear matter parameters and optical model analysis of proton elastic scattering on the doubly magic nucleus 40Ca

NASA Astrophysics Data System (ADS)

Khalaf, A. M.; Khalifa, M. M.; Solieman, A. H. M.; Comsan, M. N. H.

2018-01-01

Owing to its doubly magic nature having equal numbers of protons and neutrons, the 40Ca nuclear scattering can be successfully described by the optical model that assumes a spherical nuclear potential. Therefore, optical model analysis was employed to calculate the elastic scattering cross section for p +40Ca interaction at energies from 9 to 22 MeV as well as the polarization at energies from 10 to 18.2 MeV. New optical model parameters (OMPs) were proposed based on the best fitting to experimental data. It is found that the best fit OMPs depend on the energy by smooth relationships. The results were compared with other OMPs sets regarding their chi square values (χ2). The obtained OMP's set was used to calculate the volume integral of the potentials and the root mean square (rms) value of nuclear matter radius of 40Ca. In addition, 40Ca bulk nuclear matter properties were discussed utilizing both the obtained rms radius and the Thomas-Fermi rms radius calculated using spherical Hartree-Fock formalism employing Skyrme type nucleon-nucleon force. The nuclear scattering SCAT2000 FORTRAN code was used for the optical model analysis.

Development of molecular closures for the reference interaction site model theory with application to square-well and Lennard-Jones homonuclear diatomics.

PubMed

Munaò, Gianmarco; Costa, Dino; Caccamo, Carlo

2016-10-19

Inspired by significant improvements obtained for the performances of the polymer reference interaction site model (PRISM) theory of the fluid phase when coupled with 'molecular closures' (Schweizer and Yethiraj 1993 J. Chem. Phys. 98 9053), we exploit a matrix generalization of this concept, suitable for the more general RISM framework. We report a preliminary test of the formalism, as applied to prototype square-well homonuclear diatomics. As for the structure, comparison with Monte Carlo shows that molecular closures are slightly more predictive than their 'atomic' counterparts, and thermodynamic properties are equally accurate. We also devise an application of molecular closures to models interacting via continuous, soft-core potentials, by using well established prescriptions in liquid state perturbation theories. In the case of Lennard-Jones dimers, our scheme definitely improves over the atomic one, providing semi-quantitative structural results, and quite good estimates of internal energy, pressure and phase coexistence. Our finding paves the way to a systematic employment of molecular closures within the RISM framework to be applied to more complex systems, such as molecules constituted by several non-equivalent interaction sites.

Geohydrology and water quality of stratified-drift aquifers in the Saco and Ossipee River basins, east-central New Hampshire

USGS Publications Warehouse

Moore, R.B.; Medalie, Laura

1995-01-01

Stratified-drift aquifers discontinuously underlie 152.5 square miles of the Saco and Ossipee River Basins, which have a total drainage area of 869.4 square miles. Saturated thicknesses of stratified drift in the study area are locally greater than 280 feet, but generally are less. Transmissivity locally exceeds 8,000 feet squared per day but are generally less. About 93.6 square miles, or 10.8 percent of the study area, are identified as having transmissivity greater than 1,000 feet squared per day. The stratified-drift aquifer in Ossipee, Freedom, Effingham, Madison, and Tamworth was analyzed for the availability of ground water by use of transient simulations and a two-dimensional, finite-difference ground-water-flow model. The numerical -model results indicate that potential available water amounts in this aquifer are 7.72 million gallons per day. Sample results of water- quality analyses obtained from 25 test wells and 4 springs indicated that water was generally suitable for drinking and other domestic purposes. Concen- trations of dissolved constituents in ground-water samples are less than or meet U.S. Environmental Protection Agency (USEPA)primary and secondary drinking-water regulations. Concentrations of inorganic constituents that exceeded the USEPA's secondary regulations were chloride and sodium, iron manganese, and fluoride.

Simulation of groundwater flow to assess future withdrawals associated with Base Realignment and Closure (BRAC) at Fort George G. Meade, Maryland

USGS Publications Warehouse

Raffensperger, Jeff P.; Fleming, Brandon J.; Banks, William S.L.; Horn, Marilee A.; Nardi, Mark R.; Andreasen, David C.

2010-01-01

Increased groundwater withdrawals from confined aquifers in the Maryland Coastal Plain to supply anticipated growth at Fort George G. Meade (Fort Meade) and surrounding areas resulting from the Department of Defense Base Realignment and Closure Program may have adverse effects in the outcrop or near-outcrop areas. Specifically, increased pumping from the Potomac Group aquifers (principally the Patuxent aquifer) could potentially reduce base flow in small streams below rates necessary for healthy biological functioning. Additionally, water levels may be lowered near, or possibly below, the top of the aquifer within the confined-unconfined transition zone near the outcrop area. A three-dimensional groundwater flow model was created to incorporate and analyze data on water withdrawals, streamflow, and hydraulic head in the region. The model is based on an earlier model developed to assess the effects of future withdrawals from well fields in Anne Arundel County, Maryland and surrounding areas, and includes some of the same features, including model extent, boundary conditions, and vertical discretization (layering). The resolution (horizontal grid discretization) of the earlier model limited its ability to simulate the effects of withdrawals on the outcrop and near-outcrop areas. The model developed for this study included a block-shaped higher-resolution local grid, referred to as the child model, centered on Fort Meade, which was coupled to the coarser-grid parent model using the shared node Local Grid Refinement capability of MODFLOW-LGR. A more detailed stream network was incorporated into the child model. In addition, for part of the transient simulation period, stress periods were reduced in length from 1 year to 3 months, to allow for simulation of the effects of seasonally varying withdrawals and recharge on the groundwater-flow system and simulated streamflow. This required revision of the database on withdrawals and estimation of seasonal variations in recharge represented in the earlier model. The calibrated model provides a tool for future forecasts of changes in the system under different management scenarios, and for simulating potential effects of withdrawals at Fort Meade and the surrounding area on water levels in the near-outcrop area and base flow in the outcrop area. Model error was assessed by comparing observed and simulated water levels from 62 wells (55 in the parent model and 7 in the child model). The root-mean-square error values for the parent and child model were 8.72 and 11.91 feet, respectively. Root-mean-square error values for the 55 parent model observation wells range from 0.95 to 30.31 feet; the range for the 7 child model observation wells is 5.00 to 24.17 feet. Many of the wells with higher root-mean-square error values occur at the perimeter of the child model and near large pumping centers, as well as updip in the confined aquifers. Root-mean-square error values decrease downdip and away from the large pumping centers. Both the parent and child models are sensitive to increasing withdrawal rates. The parent model is more sensitive than the child model to decreasing transmissivity of layers 3, 4, 5, and 6. The parent model is relatively insensitive to riverbed vertical conductance, however, the child model does exhibit some sensitivity to decreasing riverbed conductance. The overall water budget for the model included sources and sinks of water including recharge, surface-water bodies and rivers and streams, general-head boundaries, and withdrawals from permitted wells. Withdrawal from wells in 2005 was estimated to be equivalent to 8.5 percent of the total recharge rate.

Motoneuron membrane potentials follow a time inhomogeneous jump diffusion process.

PubMed

Jahn, Patrick; Berg, Rune W; Hounsgaard, Jørn; Ditlevsen, Susanne

2011-11-01

Stochastic leaky integrate-and-fire models are popular due to their simplicity and statistical tractability. They have been widely applied to gain understanding of the underlying mechanisms for spike timing in neurons, and have served as building blocks for more elaborate models. Especially the Ornstein-Uhlenbeck process is popular to describe the stochastic fluctuations in the membrane potential of a neuron, but also other models like the square-root model or models with a non-linear drift are sometimes applied. Data that can be described by such models have to be stationary and thus, the simple models can only be applied over short time windows. However, experimental data show varying time constants, state dependent noise, a graded firing threshold and time-inhomogeneous input. In the present study we build a jump diffusion model that incorporates these features, and introduce a firing mechanism with a state dependent intensity. In addition, we suggest statistical methods to estimate all unknown quantities and apply these to analyze turtle motoneuron membrane potentials. Finally, simulated and real data are compared and discussed. We find that a square-root diffusion describes the data much better than an Ornstein-Uhlenbeck process with constant diffusion coefficient. Further, the membrane time constant decreases with increasing depolarization, as expected from the increase in synaptic conductance. The network activity, which the neuron is exposed to, can be reasonably estimated to be a threshold version of the nerve output from the network. Moreover, the spiking characteristics are well described by a Poisson spike train with an intensity depending exponentially on the membrane potential.

Comparison of linear and square superposition hardening models for the surface nanoindentation of ion-irradiated materials

NASA Astrophysics Data System (ADS)

Xiao, Xiazi; Yu, Long

2018-05-01

Linear and square superposition hardening models are compared for the surface nanoindentation of ion-irradiated materials. Hardening mechanisms of both dislocations and defects within the plasticity affected region (PAR) are considered. Four sets of experimental data for ion-irradiated materials are adopted to compare with theoretical results of the two hardening models. It is indicated that both models describe experimental data equally well when the PAR is within the irradiated layer; whereas, when the PAR is beyond the irradiated region, the square superposition hardening model performs better. Therefore, the square superposition model is recommended to characterize the hardening behavior of ion-irradiated materials.

Algebraic perturbation theory for dense liquids with discrete potentials

NASA Astrophysics Data System (ADS)

Adib, Artur B.

2007-06-01

A simple theory for the leading-order correction g1(r) to the structure of a hard-sphere liquid with discrete (e.g., square-well) potential perturbations is proposed. The theory makes use of a general approximation that effectively eliminates four-particle correlations from g1(r) with good accuracy at high densities. For the particular case of discrete perturbations, the remaining three-particle correlations can be modeled with a simple volume-exclusion argument, resulting in an algebraic and surprisingly accurate expression for g1(r) . The structure of a discrete “core-softened” model for liquids with anomalous thermodynamic properties is reproduced as an application.

Room temperature ionic liquids: A simple model. Effect of chain length and size of intermolecular potential on critical temperature.

PubMed

Chapela, Gustavo A; Guzmán, Orlando; Díaz-Herrera, Enrique; del Río, Fernando

2015-04-21

A model of a room temperature ionic liquid can be represented as an ion attached to an aliphatic chain mixed with a counter ion. The simple model used in this work is based on a short rigid tangent square well chain with an ion, represented by a hard sphere interacting with a Yukawa potential at the head of the chain, mixed with a counter ion represented as well by a hard sphere interacting with a Yukawa potential of the opposite sign. The length of the chain and the depth of the intermolecular forces are investigated in order to understand which of these factors are responsible for the lowering of the critical temperature. It is the large difference between the ionic and the dispersion potentials which explains this lowering of the critical temperature. Calculation of liquid-vapor equilibrium orthobaric curves is used to estimate the critical points of the model. Vapor pressures are used to obtain an estimate of the triple point of the different models in order to calculate the span of temperatures where they remain a liquid. Surface tensions and interfacial thicknesses are also reported.

Delineation of areas contributing recharge to selected public-supply wells in Glacial Valley-Fill and Wetland Settings, Rhode Island

USGS Publications Warehouse

Friesz, Paul J.

2004-01-01

Areas contributing recharge and sources of water to one proposed and seven present public-supply wells, screened in sand and gravel deposits and clustered in three study areas, were determined on the basis of calibrated, steady-state ground-water-flow models representing average hydrologic conditions. The area contributing recharge to a well is defined as the surface area where water recharges the ground water and then flows toward and discharges to the well. In Cumberland and Lincoln, public-supply well fields on opposite sides of the Blackstone River are in a narrow valley bordered by steep hillslopes. Ground-water-level and river-stage measurements indicated that river water was infiltrating the aquifer and flowing toward the wells during pumping conditions. Simulated areas contributing recharge to the Cumberland well field operating alone for both average (324 gallons per minute) and maximum (1,000 gallons per minute) pumping rates extend on both sides of the river to the lateral model boundaries, which is the contact between the valley and uplands. The area contributing recharge at the average pumping rate is about 0.05 square mile and the well field derives 72 percent of pumped water from upland runoff. At the maximum pumping rate, the area contributing recharge extends farther up and down the valley to 0.12 square mile and the primary source of water to the well field was infiltrated river water (53 percent). Upland areas draining toward the areas contributing recharge encompass 0.58 and 0.66 square mile for the average and maximum rates, respectively. By incorporating the backup Lincoln well-field withdrawals (2,083 gallons per minute) into the model, the area contributing recharge to the Cumberland well field operating at its maximum rate is reduced to 0.08 square mile; part of the simulated area which contributes recharge to the Cumberland well field when it is operating alone contributes instead to the Lincoln well field when both well fields are pumped. The Cumberland well field compensates by increasing the percentage of water it withdraws from the river by 11 percent. The upland area draining toward the Cumberland contributing area is 0.55 square mile. The area contributing recharge to the Lincoln well field is 0.08 square mile and infiltrated river water contributes 88 percent of the total water; the upland area draining toward the contributing area is 0.34 square mile. In North Smithfield, a public-supply well in a valley-fill setting is close to Trout Brook Pond, which is an extension of the Lower Slatersville Reservoir. A comparison of water levels from the pond and underlying sediments indicates that water is not infiltrated from Trout Brook Pond when the supply well is pumped at its maximum rate of 200 gallons per minute. Simulated areas contributing recharge for the maximum pumping rate and for the estimated maximum yield, 500 gallons per minute, of a proposed replacement well extend to the ground-water divides on both sides of Trout Brook Pond. For the 200 gallons-per-minute rate, the area contributing recharge is 0.23 square mile; the well derives almost all of its water from intercepted ground water that normally discharges to surface-water bodies. For the pumping rate of 500 gallons per minute, the area contributing recharge is 0.45 square mile. The increased pumping rate is balanced by additional intercepted ground water and by inducing 25 percent of the total withdrawn water from surface water. In Westerly, one public-supply well is in a watershed where the primarily hydrologic feature is a wetland. Water levels in piezometers surrounding the well site indicated a downward vertical gradient and the potential for water in the wetland to infiltrate the underlying aquifer. The simulated area contributing recharge for the average pumping rate (240 gallons per minute) and for the maximum pumping rate (700 gallons per minute) extends to the surrounding uplands (surficial materials not covered by t

A methodology for least-squares local quasi-geoid modelling using a noisy satellite-only gravity field model

NASA Astrophysics Data System (ADS)

Klees, R.; Slobbe, D. C.; Farahani, H. H.

2018-04-01

The paper is about a methodology to combine a noisy satellite-only global gravity field model (GGM) with other noisy datasets to estimate a local quasi-geoid model using weighted least-squares techniques. In this way, we attempt to improve the quality of the estimated quasi-geoid model and to complement it with a full noise covariance matrix for quality control and further data processing. The methodology goes beyond the classical remove-compute-restore approach, which does not account for the noise in the satellite-only GGM. We suggest and analyse three different approaches of data combination. Two of them are based on a local single-scale spherical radial basis function (SRBF) model of the disturbing potential, and one is based on a two-scale SRBF model. Using numerical experiments, we show that a single-scale SRBF model does not fully exploit the information in the satellite-only GGM. We explain this by a lack of flexibility of a single-scale SRBF model to deal with datasets of significantly different bandwidths. The two-scale SRBF model performs well in this respect, provided that the model coefficients representing the two scales are estimated separately. The corresponding methodology is developed in this paper. Using the statistics of the least-squares residuals and the statistics of the errors in the estimated two-scale quasi-geoid model, we demonstrate that the developed methodology provides a two-scale quasi-geoid model, which exploits the information in all datasets.

Estimation of inlet flow rates for image-based aneurysm CFD models: where and how to begin?

PubMed

Valen-Sendstad, Kristian; Piccinelli, Marina; KrishnankuttyRema, Resmi; Steinman, David A

2015-06-01

Patient-specific flow rates are rarely available for image-based computational fluid dynamics models. Instead, flow rates are often assumed to scale according to the diameters of the arteries of interest. Our goal was to determine how choice of inlet location and scaling law affect such model-based estimation of inflow rates. We focused on 37 internal carotid artery (ICA) aneurysm cases from the Aneurisk cohort. An average ICA flow rate of 245 mL min(-1) was assumed from the literature, and then rescaled for each case according to its inlet diameter squared (assuming a fixed velocity) or cubed (assuming a fixed wall shear stress). Scaling was based on diameters measured at various consistent anatomical locations along the models. Choice of location introduced a modest 17% average uncertainty in model-based flow rate, but within individual cases estimated flow rates could vary by >100 mL min(-1). A square law was found to be more consistent with physiological flow rates than a cube law. Although impact of parent artery truncation on downstream flow patterns is well studied, our study highlights a more insidious and potentially equal impact of truncation site and scaling law on the uncertainty of assumed inlet flow rates and thus, potentially, downstream flow patterns.

Quantum dynamics of relativistic bosons through nonminimal vector square potentials

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

Oliveira, Luiz P. de, E-mail: oliveira.phys@gmail.com

The dynamics of relativistic bosons (scalar and vectorial) through nonminimal vector square (well and barrier) potentials is studied in the Duffin–Kemmer–Petiau (DKP) formalism. We show that the problem can be mapped in effective Schrödinger equations for a component of the DKP spinor. An oscillatory transmission coefficient is found and there is total reflection. Additionally, the energy spectrum of bound states is obtained and reveals the Schiff–Snyder–Weinberg effect, for specific conditions the potential lodges bound states of particles and antiparticles. - Highlights: • DKP bosons in a nonminimal vector square potential are studied. • Spin zero and spin one bosons havemore » the same results. • The Schiff–Snyder–Weinberg effect is observed.« less

Hypoglycemia early alarm systems based on recursive autoregressive partial least squares models.

PubMed

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. © 2012 Diabetes Technology Society.

Hypoglycemia Early Alarm Systems Based on Recursive Autoregressive Partial Least Squares Models

PubMed Central

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Background Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. Methods A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Results Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. Conclusions The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. PMID:23439179

Quantum dynamics of relativistic bosons through nonminimal vector square potentials

NASA Astrophysics Data System (ADS)

de Oliveira, Luiz P.

2016-09-01

The dynamics of relativistic bosons (scalar and vectorial) through nonminimal vector square (well and barrier) potentials is studied in the Duffin-Kemmer-Petiau (DKP) formalism. We show that the problem can be mapped in effective Schrödinger equations for a component of the DKP spinor. An oscillatory transmission coefficient is found and there is total reflection. Additionally, the energy spectrum of bound states is obtained and reveals the Schiff-Snyder-Weinberg effect, for specific conditions the potential lodges bound states of particles and antiparticles.

Performance of the S - [chi][squared] Statistic for Full-Information Bifactor Models

ERIC Educational Resources Information Center

Li, Ying; Rupp, Andre A.

2011-01-01

This study investigated the Type I error rate and power of the multivariate extension of the S - [chi][squared] statistic using unidimensional and multidimensional item response theory (UIRT and MIRT, respectively) models as well as full-information bifactor (FI-bifactor) models through simulation. Manipulated factors included test length, sample…

Hofstadter butterfly evolution in the space of two-dimensional Bravais lattices

NASA Astrophysics Data System (ADS)

Yılmaz, F.; Oktel, M. Ö.

2017-06-01

The self-similar energy spectrum of a particle in a periodic potential under a magnetic field, known as the Hofstadter butterfly, is determined by the lattice geometry as well as the external field. Recent realizations of artificial gauge fields and adjustable optical lattices in cold-atom experiments necessitate the consideration of these self-similar spectra for the most general two-dimensional lattice. In a previous work [F. Yılmaz et al., Phys. Rev. A 91, 063628 (2015), 10.1103/PhysRevA.91.063628], we investigated the evolution of the spectrum for an experimentally realized lattice which was tuned by changing the unit-cell structure but keeping the square Bravais lattice fixed. We now consider all possible Bravais lattices in two dimensions and investigate the structure of the Hofstadter butterfly as the lattice is deformed between lattices with different point-symmetry groups. We model the optical lattice with a sinusoidal real-space potential and obtain the tight-binding model for any lattice geometry by calculating the Wannier functions. We introduce the magnetic field via Peierls substitution and numerically calculate the energy spectrum. The transition between the two most symmetric lattices, i.e., the triangular and the square lattices, displays the importance of bipartite symmetry featuring deformation as well as closing of some of the major energy gaps. The transitions from the square to rectangular lattice and from the triangular to centered rectangular lattices are analyzed in terms of coupling of one-dimensional chains. We calculate the Chern numbers of the major gaps and Chern number transfer between bands during the transitions. We use gap Chern numbers to identify distinct topological regions in the space of Bravais lattices.

Investigation into solar drying of potato: effect of sample geometry on drying kinetics and CO2 emissions mitigation.

PubMed

Tripathy, P P

2015-03-01

Drying experiments have been performed with potato cylinders and slices using a laboratory scale designed natural convection mixed-mode solar dryer. The drying data were fitted to eight different mathematical models to predict the drying kinetics, and the validity of these models were evaluated statistically through coefficient of determination (R(2)), root mean square error (RMSE) and reduced chi-square (χ (2)). The present investigation showed that amongst all the mathematical models studied, the Modified Page model was in good agreement with the experimental drying data for both potato cylinders and slices. A mathematical framework has been proposed to estimate the performance of the food dryer in terms of net CO2 emissions mitigation potential along with unit cost of CO2 mitigation arising because of replacement of different fossil fuels by renewable solar energy. For each fossil fuel replaced, the gross annual amount of CO2 as well as net amount of annual CO2 emissions mitigation potential considering CO2 emissions embodied in the manufacture of mixed-mode solar dryer has been estimated. The CO2 mitigation potential and amount of fossil fuels saved while drying potato samples were found to be the maximum for coal followed by light diesel oil and natural gas. It was inferred from the present study that by the year 2020, 23 % of CO2 emissions can be mitigated by the use of mixed-mode solar dryer for drying of agricultural products.

Explicit least squares system parameter identification for exact differential input/output models

NASA Technical Reports Server (NTRS)

Pearson, A. E.

1993-01-01

The equation error for a class of systems modeled by input/output differential operator equations has the potential to be integrated exactly, given the input/output data on a finite time interval, thereby opening up the possibility of using an explicit least squares estimation technique for system parameter identification. The paper delineates the class of models for which this is possible and shows how the explicit least squares cost function can be obtained in a way that obviates dealing with unknown initial and boundary conditions. The approach is illustrated by two examples: a second order chemical kinetics model and a third order system of Lorenz equations.

Nutritional Status of Rural Older Adults Is Linked to Physical and Emotional Health.

PubMed

Jung, Seung Eun; Bishop, Alex J; Kim, Minjung; Hermann, Janice; Kim, Giyeon; Lawrence, Jeannine

2017-06-01

Although nutritional status is influenced by multidimensional aspects encompassing physical and emotional well-being, there is limited research on this complex relationship. The purpose of this study was to examine the interplay between indicators of physical health (perceived health status and self-care capacity) and emotional well-being (depressive affect and loneliness) on rural older adults' nutritional status. The cross-sectional study was conducted from June 1, 2007, to June 1, 2008. A total of 171 community-dwelling older adults, aged 65 years and older, residing within nonmetro rural communities in the United States participated in this study. Participants completed validated instruments measuring self-care capacity, perceived health status, loneliness, depressive affect, and nutritional status. Structural equation modeling was employed to investigate the complex interplay of physical and emotional health status with nutritional status among rural older adults. The χ 2 test, comparative fit index, root mean square error of approximation, and standardized root mean square residual were used to assess model fit. The χ 2 test and the other model fit indexes showed the hypothesized structural equation model provided a good fit to the data (χ 2 (2)=2.15; P=0.34; comparative fit index=1.00; root mean square error of approximation=0.02; and standardized root mean square residual=0.03). Self-care capacity was significantly related with depressive affect (γ=-0.11; P=0.03), whereas self-care capacity was not significantly related with loneliness. Perceived health status had a significant negative relationship with both loneliness (γ=-0.16; P=0.03) and depressive affect (γ=-0.22; P=0.03). Although loneliness showed no significant direct relationship with nutritional status, it showed a significant direct relationship with depressive affect (β=.4; P<0.01). Finally, the results demonstrated that depressive affect had a significant negative relationship with nutritional status (β=-.30; P<0.01). The results indicated physical health and emotional indicators have significant multidimensional associations with nutritional status among rural older adults. The present study provides insights into the importance of addressing both physical and emotional well-being together to reduce potential effects of poor emotional well-being on nutritional status, particularly among rural older adults with impaired physical health and self-care capacity. Copyright © 2017 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

New Holographic Chaplygin Gas Model of Dark Energy

NASA Astrophysics Data System (ADS)

Malekjani, M.; Khodam-Mohammadi, A.

In this work, we investigate the holographic dark energy model with a new infrared cutoff (new HDE model), proposed by Granda and Oliveros. Using this new definition for the infrared cutoff, we establish the correspondence between the new HDE model and the standard Chaplygin gas (SCG), generalized Chaplygin gas (GCG) and modified Chaplygin gas (MCG) scalar field models in a nonflat universe. The potential and dynamics for these scalar field models, which describe the accelerated expansion of the universe, are reconstructed. According to the evolutionary behavior of the new HDE model, we derive the same form of dynamics and potential for the different SCG, GCG and MCG models. We also calculate the squared sound speed of the new HDE model as well as the SCG, GCG and MCG models, and investigate the new HDE Chaplygin gas models from the viewpoint of linear perturbation theory. In addition, all results in the nonflat universe are discussed in the limiting case of the flat universe, i.e. k = 0.

Sound field simulation and acoustic animation in urban squares

NASA Astrophysics Data System (ADS)

Kang, Jian; Meng, Yan

2005-04-01

Urban squares are important components of cities, and the acoustic environment is important for their usability. While models and formulae for predicting the sound field in urban squares are important for their soundscape design and improvement, acoustic animation tools would be of great importance for designers as well as for public participation process, given that below a certain sound level, the soundscape evaluation depends mainly on the type of sounds rather than the loudness. This paper first briefly introduces acoustic simulation models developed for urban squares, as well as empirical formulae derived from a series of simulation. It then presents an acoustic animation tool currently being developed. In urban squares there are multiple dynamic sound sources, so that the computation time becomes a main concern. Nevertheless, the requirements for acoustic animation in urban squares are relatively low compared to auditoria. As a result, it is important to simplify the simulation process and algorithms. Based on a series of subjective tests in a virtual reality environment with various simulation parameters, a fast simulation method with acceptable accuracy has been explored. [Work supported by the European Commission.

Equilibrium Phase Behavior of the Square-Well Linear Microphase-Forming Model.

PubMed

Zhuang, Yuan; Charbonneau, Patrick

2016-07-07

We have recently developed a simulation approach to calculate the equilibrium phase diagram of particle-based microphase formers. Here, this approach is used to calculate the phase behavior of the square-well linear model for different strengths and ranges of the linear long-range repulsive component. The results are compared with various theoretical predictions for microphase formation. The analysis further allows us to better understand the mechanism for microphase formation in colloidal suspensions.

Extended law of corresponding states for protein solutions

NASA Astrophysics Data System (ADS)

Platten, Florian; Valadez-Pérez, Néstor E.; Castañeda-Priego, Ramón; Egelhaaf, Stefan U.

2015-05-01

The so-called extended law of corresponding states, as proposed by Noro and Frenkel [J. Chem. Phys. 113, 2941 (2000)], involves a mapping of the phase behaviors of systems with short-range attractive interactions. While it has already extensively been applied to various model potentials, here we test its applicability to protein solutions with their complex interactions. We successfully map their experimentally determined metastable gas-liquid binodals, as available in the literature, to the binodals of short-range square-well fluids, as determined by previous as well as new Monte Carlo simulations. This is achieved by representing the binodals as a function of the temperature scaled with the critical temperature (or as a function of the reduced second virial coefficient) and the concentration scaled by the cube of an effective particle diameter, where the scalings take into account the attractive and repulsive contributions to the interaction potential, respectively. The scaled binodals of the protein solutions coincide with simulation data of the adhesive hard-sphere fluid. Furthermore, once the repulsive contributions are taken into account by the effective particle diameter, the temperature dependence of the reduced second virial coefficients follows a master curve that corresponds to a linear temperature dependence of the depth of the square-well potential. We moreover demonstrate that, based on this approach and cloud-point measurements only, second virial coefficients can be estimated, which we show to agree with values determined by light scattering or by Derjaguin-Landau-Verwey-Overbeek (DLVO)-based calculations.

Extended law of corresponding states for protein solutions.

PubMed

Platten, Florian; Valadez-Pérez, Néstor E; Castañeda-Priego, Ramón; Egelhaaf, Stefan U

2015-05-07

The so-called extended law of corresponding states, as proposed by Noro and Frenkel [J. Chem. Phys. 113, 2941 (2000)], involves a mapping of the phase behaviors of systems with short-range attractive interactions. While it has already extensively been applied to various model potentials, here we test its applicability to protein solutions with their complex interactions. We successfully map their experimentally determined metastable gas-liquid binodals, as available in the literature, to the binodals of short-range square-well fluids, as determined by previous as well as new Monte Carlo simulations. This is achieved by representing the binodals as a function of the temperature scaled with the critical temperature (or as a function of the reduced second virial coefficient) and the concentration scaled by the cube of an effective particle diameter, where the scalings take into account the attractive and repulsive contributions to the interaction potential, respectively. The scaled binodals of the protein solutions coincide with simulation data of the adhesive hard-sphere fluid. Furthermore, once the repulsive contributions are taken into account by the effective particle diameter, the temperature dependence of the reduced second virial coefficients follows a master curve that corresponds to a linear temperature dependence of the depth of the square-well potential. We moreover demonstrate that, based on this approach and cloud-point measurements only, second virial coefficients can be estimated, which we show to agree with values determined by light scattering or by Derjaguin-Landau-Verwey-Overbeek (DLVO)-based calculations.

Applications of neural networks to the studies of phase transitions of two-dimensional Potts models

NASA Astrophysics Data System (ADS)

Li, C.-D.; Tan, D.-R.; Jiang, F.-J.

2018-04-01

We study the phase transitions of two-dimensional (2D) Q-states Potts models on the square lattice, using the first principles Monte Carlo (MC) simulations as well as the techniques of neural networks (NN). We demonstrate that the ideas from NN can be adopted to study these considered phase transitions efficiently. In particular, even with a simple NN constructed in this investigation, we are able to obtain the relevant information of the nature of these phase transitions, namely whether they are first order or second order. Our results strengthen the potential applicability of machine learning in studying various states of matters. Subtlety of applying NN techniques to investigate many-body systems is briefly discussed as well.

SWMF Global Magnetosphere Simulations of January 2005: Geomagnetic Indices and Cross-Polar Cap Potential

NASA Astrophysics Data System (ADS)

Haiducek, John D.; Welling, Daniel T.; Ganushkina, Natalia Y.; Morley, Steven K.; Ozturk, Dogacan Su

2017-12-01

We simulated the entire month of January 2005 using the Space Weather Modeling Framework (SWMF) with observed solar wind data as input. We conducted this simulation with and without an inner magnetosphere model and tested two different grid resolutions. We evaluated the model's accuracy in predicting Kp, SYM-H, AL, and cross-polar cap potential (CPCP). We find that the model does an excellent job of predicting the SYM-H index, with a root-mean-square error (RMSE) of 17-18 nT. Kp is predicted well during storm time conditions but overpredicted during quiet times by a margin of 1 to 1.7 Kp units. AL is predicted reasonably well on average, with an RMSE of 230-270 nT. However, the model reaches the largest negative AL values significantly less often than the observations. The model tended to overpredict CPCP, with RMSE values on the order of 46-48 kV. We found the results to be insensitive to grid resolution, with the exception of the rate of occurrence for strongly negative AL values. The use of the inner magnetosphere component, however, affected results significantly, with all quantities except CPCP improved notably when the inner magnetosphere model was on.

Mapping the economic benefits to livestock keepers from intervening against bovine trypanosomosis in Eastern Africa.

PubMed

Shaw, A P M; Cecchi, G; Wint, G R W; Mattioli, R C; Robinson, T P

2014-02-01

Endemic animal diseases such as tsetse-transmitted trypanosomosis are a constant drain on the financial resources of African livestock keepers and on the productivity of their livestock. Knowing where the potential benefits of removing animal trypanosomosis are distributed geographically would provide crucial evidence for prioritising and targeting cost-effective interventions as well as a powerful tool for advocacy. To this end, a study was conducted on six tsetse-infested countries in Eastern Africa: Ethiopia, Kenya, Somalia, South Sudan, Sudan and Uganda. First, a map of cattle production systems was generated, with particular attention to the presence of draught and dairy animals. Second, herd models for each production system were developed for two scenarios: with or without trypanosomosis. The herd models were based on publications and reports on cattle productivity (fertility, mortality, yields, sales), from which the income from, and growth of cattle populations were estimated over a twenty-year period. Third, a step-wise spatial expansion model was used to estimate how cattle populations might migrate to new areas when maximum stocking rates are exceeded. Last, differences in income between the two scenarios were mapped, thus providing a measure of the maximum benefits that could be obtained from intervening against tsetse and trypanosomosis. For this information to be readily mappable, benefits were calculated per bovine and converted to US$ per square kilometre. Results indicate that the potential benefits from dealing with trypanosomosis in Eastern Africa are both very high and geographically highly variable. The estimated total maximum benefit to livestock keepers for the whole of the study area amounts to nearly US$ 2.5 billion, discounted at 10% over twenty years--an average of approximately US$ 3300 per square kilometre of tsetse-infested area--but with great regional variation from less than US$ 500 per square kilometre to well over US$ 10,000. The greatest potential benefits accrue to Ethiopia, because of its very high livestock densities and the importance of animal traction, but also to parts of Kenya and Uganda. In general, the highest benefit levels occur on the fringes of the tsetse infestations. The implications of the models' assumptions and generalisations are discussed. Copyright © 2013 Food and Agriculture Organization of the United Nations. Published by Elsevier B.V. All rights reserved.

Kinetics of Methane Production from Swine Manure and Buffalo Manure.

PubMed

Sun, Chen; Cao, Weixing; Liu, Ronghou

2015-10-01

The degradation kinetics of swine and buffalo manure for methane production was investigated. Six kinetic models were employed to describe the corresponding experimental data. These models were evaluated by two statistical measurements, which were root mean square prediction error (RMSPE) and Akaike's information criterion (AIC). The results showed that the logistic and Fitzhugh models could predict the experimental data very well for the digestion of swine and buffalo manure, respectively. The predicted methane yield potential for swine and buffalo manure was 487.9 and 340.4 mL CH4/g volatile solid (VS), respectively, which was close to experimental values, when the digestion temperature was 36 ± 1 °C in the biochemical methane potential assays. Besides, the rate constant revealed that swine manure had a much faster methane production rate than buffalo manure.

Spatial Bose-Einstein Condensation.

ERIC Educational Resources Information Center

Masut, Remo; Mullin, William J.

1979-01-01

Analyzes three examples of spatial Bose-Einstein condensations in which the particles macroscopically occupy the lowest localized state of an inhomogeneous external potential. The three cases are (1) a box with a small square potential well inside, (2) a harmonic oscillator potential, and (3) randomly sized trapping potentials caused by…

Theoretical study of solvent effects on the coil-globule transition

NASA Astrophysics Data System (ADS)

Polson, James M.; Opps, Sheldon B.; Abou Risk, Nicholas

2009-06-01

The coil-globule transition of a polymer in a solvent has been studied using Monte Carlo simulations of a single chain subject to intramolecular interactions as well as a solvent-mediated effective potential. This solvation potential was calculated using several different theoretical approaches for two simple polymer/solvent models, each employing hard-sphere chains and hard-sphere solvent particles as well as attractive square-well potentials between some interaction sites. For each model, collapse is driven by variation in a parameter which changes the energy mismatch between monomers and solvent particles. The solvation potentials were calculated using two fundamentally different methodologies, each designed to predict the conformational behavior of polymers in solution: (1) the polymer reference interaction site model (PRISM) theory and (2) a many-body solvation potential (MBSP) based on scaled particle theory introduced by Grayce [J. Chem. Phys. 106, 5171 (1997)]. For the PRISM calculations, two well-studied solvation monomer-monomer pair potentials were employed, each distinguished by the closure relation used in its derivation: (i) a hypernetted-chain (HNC)-type potential and (ii) a Percus-Yevick (PY)-type potential. The theoretical predictions were each compared to results obtained from explicit-solvent discontinuous molecular dynamics simulations on the same polymer/solvent model systems [J. Chem. Phys. 125, 194904 (2006)]. In each case, the variation in the coil-globule transition properties with solvent density is mostly qualitatively correct, though the quantitative agreement between the theory and prediction is typically poor. The HNC-type potential yields results that are more qualitatively consistent with simulation. The conformational behavior of the polymer upon collapse predicted by the MBSP approach is quantitatively correct for low and moderate solvent densities but is increasingly less accurate for higher densities. At high solvent densities, the PRISM-HNC and MBSP approaches tend to overestimate, while the PRISM-PY approach underestimates the tendency of the solvent to drive polymer collapse.

Theoretical and material studies on thin-film electroluminescent devices

NASA Technical Reports Server (NTRS)

Summers, C. J.; Brennan, K. F.

1986-01-01

A theoretical study of resonant tunneling in multilayered heterostructures is presented based on an exact solution of the Schroedinger equation under the application of a constant electric field. By use of the transfer matrix approach, the transmissivity of the structure is determined as a function of the incident electron energy. The approach presented is easily extended to many layer structures where it is more accurate than other existing transfer matrix or WKB models. The transmission resonances are compared to the bound state energies calculated for a finite square well under bias using either an asymmetric square well model or the exact solution of an infinite square well under the application of an electric field. The results show good agreement with other existing models as well as with the bound state energies. The calculations were then applied to a new superlattice structure, the variablly spaced superlattice energy filter, (VSSEP) which is designed such that under bias the spatial quantization levels fully align. Based on these calculations, a new class of resonant tunneling superlattice devices can be designed.

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

ERIC Educational Resources Information Center

Henseler, Jorg; Chin, Wynne W.

2010-01-01

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

Elastic and inelastic collisions of swarms

NASA Astrophysics Data System (ADS)

Armbruster, Dieter; Martin, Stephan; Thatcher, Andrea

2017-04-01

Scattering interactions of swarms in potentials that are generated by an attraction-repulsion model are studied. In free space, swarms in this model form a well-defined steady state describing the translation of a stable formation of the particles whose shape depends on the interaction potential. Thus, the collision between a swarm and a boundary or between two swarms can be treated as (quasi)-particle scattering. Such scattering experiments result in internal excitations of the swarm or in bound states, respectively. In addition, varying a parameter linked to the relative importance of damping and potential forces drives transitions between elastic and inelastic scattering of the particles. By tracking the swarm's center of mass, a refraction rule is derived via simulations relating the incoming and outgoing directions of a swarm hitting the wall. Iterating the map derived from the refraction law allows us to predict and understand the dynamics and bifurcations of swarms in square boxes and in channels.

Summary of hydrologic testing of the Floridan aquifer system at Fort Stewart, coastal Georgia, 2009-2010

USGS Publications Warehouse

Gonthier, Gerald J.

2011-01-01

Two test wells were completed at Fort Stewart, coastal Georgia, to investigate the potential for using the Lower Floridan aquifer as a source of water to satisfy anticipated, increased water needs. The U.S. Geological Survey, in cooperation with the U.S. Department of the Army, completed hydrologic testing of the Floridan aquifer system at the study site, including flowmeter surveys, slug tests, and 24- and 72-hour aquifer tests by mid-March 2010. Analytical approaches and model simulation were applied to aquifer-test results to provide estimates of transmissivity and hydraulic conductivity of the multilayered Floridan aquifer system. Data from a 24-hour aquifer test of the Upper Floridan aquifer were evaluated by using the straight-line Cooper-Jacob analytical method. Data from a 72-hour aquifer test of the Lower Floridan aquifer were simulated by using axisymmetric model simulations. Results of aquifer testing indicated that the Upper Floridan aquifer has a transmissivity of 100,000 feet-squared per day, and the Lower Floridan aquifer has a transmissivity of 7,000 feet-squared per day. A specific storage for the Floridan aquifer system as a result of model calibration was 3E-06 ft–1. Additionally, during a 72-hour aquifer test of the Lower Floridan aquifer, a drawdown response was observed in two Upper Floridan aquifer wells, one of which was more than 1 mile away from the pumped well.

The wall traction induced by flowing red blood cells in model microvessels and its potential mechanotransduction

NASA Astrophysics Data System (ADS)

Freund, Jonathan; Vermot, Julien

2013-11-01

There is evidence in early embryonic development, even well before advective oxygen transport is important, that the presence of red bloods cells per se trigger essential steps of normal vascular development. For example, showed that sequestration of blood cells early in the development of a mouse, such that the hematocrit is reduced, suppresses normal vascular network development. Vascular development also provides a model for remodeling and angiogenesis. We consider the transient stresses associated with blood cells flowing in model microvessels of comparable diameter to those at early stages of development (6 μm to 12 μm). A detailed simulation tool is used to show that passing blood cells present a significant fluctuating traction signature on the vessel wall, well above the mean stresses. This is particularly pronounced for slow flows (<= 50 μm/s) or small diameters (<= 7 μm), for which root-mean-square wall traction fluctuations can exceed their mean. These events potentially present mechanotranduction triggers that direct development or remodeling. Attenuation of such fluctuating tractions by a viscoelastic endothelial glycocalyx layer is also considered. NSF supported.

Extended law of corresponding states in short-range square wells: a potential energy landscape study.

PubMed

Foffi, Giuseppe; Sciortino, Francesco

2006-11-01

We study the statistical properties of the potential energy landscape of a system of particles interacting via a very short-range square-well potential (of depth -u0) as a function of the range of attraction Delta to provide thermodynamic insights of the Noro and Frenkel [M. G. Noro and D. Frenkel, J. Chem. Phys. 113, 2941 (2000)] scaling. We exactly evaluate the basin free energy and show that it can be separated into a vibrational (Delta dependent) and a floppy (Delta independent) component. We also show that the partition function is a function of Deltaebetauo, explaining the equivalence of the thermodynamics for systems characterized by the same second virial coefficient. An outcome of our approach is the possibility of counting the number of floppy modes (and their entropy).

Microcanonical ensemble simulation method applied to discrete potential fluids

NASA Astrophysics Data System (ADS)

Sastre, Francisco; Benavides, Ana Laura; Torres-Arenas, José; Gil-Villegas, Alejandro

2015-09-01

In this work we extend the applicability of the microcanonical ensemble simulation method, originally proposed to study the Ising model [A. Hüller and M. Pleimling, Int. J. Mod. Phys. C 13, 947 (2002), 10.1142/S0129183102003693], to the case of simple fluids. An algorithm is developed by measuring the transition rates probabilities between macroscopic states, that has as advantage with respect to conventional Monte Carlo NVT (MC-NVT) simulations that a continuous range of temperatures are covered in a single run. For a given density, this new algorithm provides the inverse temperature, that can be parametrized as a function of the internal energy, and the isochoric heat capacity is then evaluated through a numerical derivative. As an illustrative example we consider a fluid composed of particles interacting via a square-well (SW) pair potential of variable range. Equilibrium internal energies and isochoric heat capacities are obtained with very high accuracy compared with data obtained from MC-NVT simulations. These results are important in the context of the application of the Hüller-Pleimling method to discrete-potential systems, that are based on a generalization of the SW and square-shoulder fluids properties.

A reaction-diffusion model for market fluctuations - A relation between price change and traded volumes

NASA Astrophysics Data System (ADS)

Yuvan, Steven; Bier, Martin

2018-02-01

Two decades ago Bak et al. (1997) [3] proposed a reaction-diffusion model to describe market fluctuations. In the model buyers and sellers diffuse from opposite ends of a 1D interval that represents a price range. Trades occur when buyers and sellers meet. We show analytically and numerically that the model well reproduces the square-root relation between traded volumes and price changes that is observed in real-life markets. The result is remarkable as this relation has commonly been explained in terms of more elaborate trader strategies. We furthermore explain why the square-root relation is robust under model modifications and we show how real-life bond market data exhibit the square-root relation.

Determination of formal redox potentials in aqueous solution of copper(II) complexes with ligands having nitrogen and oxygen donor atoms and comparison with their EPR and UV-Vis spectral features.

PubMed

Tabbì, Giovanni; Giuffrida, Alessandro; Bonomo, Raffaele P

2013-11-01

Formal redox potentials in aqueous solution were determined for copper(II) complexes with ligands having oxygen and nitrogen as donor atoms. All the chosen copper(II) complexes have well-known stereochemistries (pseudo-octahedral, square planar, square-based pyramidal, trigonal bipyramidal or tetrahedral) as witnessed by their reported spectroscopic, EPR and UV-visible (UV-Vis) features, so that a rough correlation between the measured redox potential and the typical geometrical arrangement of the copper(II) complex could be established. Negative values have been obtained for copper(II) complexes in tetragonally elongated pseudo-octahedral geometries, when measured against Ag/AgCl reference electrode. Copper(II) complexes in tetrahedral environments (or flattened tetrahedral geometries) show positive redox potential values. There is a region, always in the field of negative redox potentials which groups the copper(II) complexes exhibiting square-based pyramidal arrangements. Therefore, it is suggested that a measurement of the formal redox potential could be of great help, when some ambiguities might appear in the interpretation of spectroscopic (EPR and UV-Vis) data. Unfortunately, when the comparison is made between copper(II) complexes in square-based pyramidal geometries and those in square planar environments (or a pseudo-octahedral) a little perturbed by an equatorial tetrahedral distortion, their redox potentials could fall in the same intermediate region. In this case spectroscopic data have to be handled with great care in order to have an answer about a copper complex geometrical characteristics. © 2013.

Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics.

PubMed

Beattie, Kylie A; Hill, Adam P; Bardenet, Rémi; Cui, Yi; Vandenberg, Jamie I; Gavaghan, David J; de Boer, Teun P; Mirams, Gary R

2018-03-24

Ion current kinetics are commonly represented by current-voltage relationships, time constant-voltage relationships and subsequently mathematical models fitted to these. These experiments take substantial time, which means they are rarely performed in the same cell. Rather than traditional square-wave voltage clamps, we fitted a model to the current evoked by a novel sum-of-sinusoids voltage clamp that was only 8 s long. Short protocols that can be performed multiple times within a single cell will offer many new opportunities to measure how ion current kinetics are affected by changing conditions. The new model predicts the current under traditional square-wave protocols well, with better predictions of underlying currents than literature models. The current under a novel physiologically relevant series of action potential clamps is predicted extremely well. The short sinusoidal protocols allow a model to be fully fitted to individual cells, allowing us to examine cell-cell variability in current kinetics for the first time. Understanding the roles of ion currents is crucial to predict the action of pharmaceuticals and mutations in different scenarios, and thereby to guide clinical interventions in the heart, brain and other electrophysiological systems. Our ability to predict how ion currents contribute to cellular electrophysiology is in turn critically dependent on our characterisation of ion channel kinetics - the voltage-dependent rates of transition between open, closed and inactivated channel states. We present a new method for rapidly exploring and characterising ion channel kinetics, applying it to the hERG potassium channel as an example, with the aim of generating a quantitatively predictive representation of the ion current. We fitted a mathematical model to currents evoked by a novel 8 second sinusoidal voltage clamp in CHO cells overexpressing hERG1a. The model was then used to predict over 5 minutes of recordings in the same cell in response to further protocols: a series of traditional square step voltage clamps, and also a novel voltage clamp comprising a collection of physiologically relevant action potentials. We demonstrate that we can make predictive cell-specific models that outperform the use of averaged data from a number of different cells, and thereby examine which changes in gating are responsible for cell-cell variability in current kinetics. Our technique allows rapid collection of consistent and high quality data, from single cells, and produces more predictive mathematical ion channel models than traditional approaches. © 2018 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.

Bayesian evidences for dark energy models in light of current observational data

NASA Astrophysics Data System (ADS)

Lonappan, Anto. I.; Kumar, Sumit; Ruchika; Dinda, Bikash R.; Sen, Anjan A.

2018-02-01

We do a comprehensive study of the Bayesian evidences for a large number of dark energy models using a combination of latest cosmological data from SNIa, CMB, BAO, strong lensing time delay, growth measurements, measurements of Hubble parameter at different redshifts and measurements of angular diameter distance by Megamaser Cosmology Project. We consider a variety of scalar field models with different potentials as well as different parametrizations for the dark energy equation of state. Among 21 models that we consider in our study, we do not find strong evidences in favor of any evolving dark energy model compared to Λ CDM . For the evolving dark energy models, we show that purely nonphantom models have much better evidences compared to those models that allow both phantom and nonphantom behaviors. Canonical scalar field with exponential and tachyon field with square potential have highest evidences among all the models considered in this work. We also show that a combination of low redshift measurements decisively favors an accelerating Λ CDM model compared to a nonaccelerating power law model.

Two-body potential model based on cosine series expansion for ionic materials

DOE PAGES

Oda, Takuji; Weber, William J.; Tanigawa, Hisashi

2015-09-23

There is a method to construct a two-body potential model for ionic materials with a Fourier series basis and we examine it. For this method, the coefficients of cosine basis functions are uniquely determined by solving simultaneous linear equations to minimize the sum of weighted mean square errors in energy, force and stress, where first-principles calculation results are used as the reference data. As a validation test of the method, potential models for magnesium oxide are constructed. The mean square errors appropriately converge with respect to the truncation of the cosine series. This result mathematically indicates that the constructed potentialmore » model is sufficiently close to the one that is achieved with the non-truncated Fourier series and demonstrates that this potential virtually provides minimum error from the reference data within the two-body representation. The constructed potential models work appropriately in both molecular statics and dynamics simulations, especially if a two-step correction to revise errors expected in the reference data is performed, and the models clearly outperform two existing Buckingham potential models that were tested. Moreover, the good agreement over a broad range of energies and forces with first-principles calculations should enable the prediction of materials behavior away from equilibrium conditions, such as a system under irradiation.« less

A suggestion for computing objective function in model calibration

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang

2014-01-01

A parameter-optimization process (model calibration) is usually required for numerical model applications, which involves the use of an objective function to determine the model cost (model-data errors). The sum of square errors (SSR) has been widely adopted as the objective function in various optimization procedures. However, ‘square error’ calculation was found to be more sensitive to extreme or high values. Thus, we proposed that the sum of absolute errors (SAR) may be a better option than SSR for model calibration. To test this hypothesis, we used two case studies—a hydrological model calibration and a biogeochemical model calibration—to investigate the behavior of a group of potential objective functions: SSR, SAR, sum of squared relative deviation (SSRD), and sum of absolute relative deviation (SARD). Mathematical evaluation of model performance demonstrates that ‘absolute error’ (SAR and SARD) are superior to ‘square error’ (SSR and SSRD) in calculating objective function for model calibration, and SAR behaved the best (with the least error and highest efficiency). This study suggests that SSR might be overly used in real applications, and SAR may be a reasonable choice in common optimization implementations without emphasizing either high or low values (e.g., modeling for supporting resources management).

Microcanonical-ensemble computer simulation of the high-temperature expansion coefficients of the Helmholtz free energy of a square-well fluid

NASA Astrophysics Data System (ADS)

Sastre, Francisco; Moreno-Hilario, Elizabeth; Sotelo-Serna, Maria Guadalupe; Gil-Villegas, Alejandro

2018-02-01

The microcanonical-ensemble computer simulation method (MCE) is used to evaluate the perturbation terms Ai of the Helmholtz free energy of a square-well (SW) fluid. The MCE method offers a very efficient and accurate procedure for the determination of perturbation terms of discrete-potential systems such as the SW fluid and surpass the standard NVT canonical ensemble Monte Carlo method, allowing the calculation of the first six expansion terms. Results are presented for the case of a SW potential with attractive ranges 1.1 ≤ λ ≤ 1.8. Using semi-empirical representation of the MCE values for Ai, we also discuss the accuracy in the determination of the phase diagram of this system.

From direct-space discrepancy functions to crystallographic least squares.

PubMed

Giacovazzo, Carmelo

2015-01-01

Crystallographic least squares are a fundamental tool for crystal structure analysis. In this paper their properties are derived from functions estimating the degree of similarity between two electron-density maps. The new approach leads also to modifications of the standard least-squares procedures, potentially able to improve their efficiency. The role of the scaling factor between observed and model amplitudes is analysed: the concept of unlocated model is discussed and its scattering contribution is combined with that arising from the located model. Also, the possible use of an ancillary parameter, to be associated with the classical weight related to the variance of the observed amplitudes, is studied. The crystallographic discrepancy factors, basic tools often combined with least-squares procedures in phasing approaches, are analysed. The mathematical approach here described includes, as a special case, the so-called vector refinement, used when accurate estimates of the target phases are available.

Fractional Dynamics of Single File Diffusion in Dusty Plasma Ring

NASA Astrophysics Data System (ADS)

Muniandy, S. V.; Chew, W. X.; Asgari, H.; Wong, C. S.; Lim, S. C.

2011-11-01

Single file diffusion (SFD) refers to the constrained motion of particles in quasi-one-dimensional channel such that the particles are unable to pass each other. Possible SFD of charged dust confined in biharmonic annular potential well with screened Coulomb interaction is investigated. Transition from normal diffusion to anomalous sub-diffusion behaviors is observed. Deviation from SFD's mean square displacement scaling behavior of 1/2-exponent may occur in strongly interacting systems. A phenomenological model based on fractional Langevin equation is proposed to account for the anomalous SFD behavior in dusty plasma ring.

Generalized Structured Component Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Takane, Yoshio

2004-01-01

We propose an alternative method to partial least squares for path analysis with components, called generalized structured component analysis. The proposed method replaces factors by exact linear combinations of observed variables. It employs a well-defined least squares criterion to estimate model parameters. As a result, the proposed method…

Causal modeling in international migration research: a methodological prolegomenon.

PubMed

Papademetriou, D G; Hopple, G W

1982-10-01

The authors examine the value of using models to study the migration process. In particular, they demonstrate the potential utility of a partial least squares modeling approach to the causal analysis of international migration.

Vapour-liquid interfacial properties of square-well chains from density functional theory and Monte Carlo simulation.

PubMed

Martínez-Ruiz, Francisco José; Blas, Felipe J; Moreno-Ventas Bravo, A Ignacio; Míguez, José Manuel; MacDowell, Luis G

2017-05-17

The statistical associating fluid theory for attractive potentials of variable range (SAFT-VR) density functional theory (DFT) developed by [Gloor et al., J. Chem. Phys., 2004, 121, 12740-12759] is used to predict the interfacial behaviour of molecules modelled as fully-flexible square-well chains formed from tangentially-bonded monomers of diameter σ and potential range λ = 1.5σ. Four different model systems, comprising 4, 8, 12, and 16 monomers per molecule, are considered. In addition to that, we also compute a number of interfacial properties of molecular chains from direct simulation of the vapour-liquid interface. The simulations are performed in the canonical ensemble, and the vapour-liquid interfacial tension is evaluated using the wandering interface (WIM) method, a technique based on the thermodynamic definition of surface tension. Apart from surface tension, we also obtain density profiles, coexistence densities, vapour pressures, and critical temperature and density, paying particular attention to the effect of the chain length on these properties. According to our results, the main effect of increasing the chain length (at fixed temperature) is to sharpen the vapour-liquid interface and to increase the width of the biphasic coexistence region. As a result, the interfacial thickness decreases and the surface tension increases as the molecular chains get longer. The interfacial thickness and surface tension appear to exhibit an asymptotic limiting behaviour for long chains. A similar behaviour is also observed for the coexistence densities and critical properties. Agreement between theory and simulation results indicates that SAFT-VR DFT is only able to predict qualitatively the interfacial properties of the model. Our results are also compared with simulation data taken from the literature, including the vapour-liquid coexistence densities, vapour pressures, and surface tension.

Least-squares model-based halftoning

NASA Astrophysics Data System (ADS)

Pappas, Thrasyvoulos N.; Neuhoff, David L.

1992-08-01

A least-squares model-based approach to digital halftoning is proposed. It exploits both a printer model and a model for visual perception. It attempts to produce an 'optimal' halftoned reproduction, by minimizing the squared error between the response of the cascade of the printer and visual models to the binary image and the response of the visual model to the original gray-scale image. Conventional methods, such as clustered ordered dither, use the properties of the eye only implicitly, and resist printer distortions at the expense of spatial and gray-scale resolution. In previous work we showed that our printer model can be used to modify error diffusion to account for printer distortions. The modified error diffusion algorithm has better spatial and gray-scale resolution than conventional techniques, but produces some well known artifacts and asymmetries because it does not make use of an explicit eye model. Least-squares model-based halftoning uses explicit eye models and relies on printer models that predict distortions and exploit them to increase, rather than decrease, both spatial and gray-scale resolution. We have shown that the one-dimensional least-squares problem, in which each row or column of the image is halftoned independently, can be implemented with the Viterbi's algorithm. Unfortunately, no closed form solution can be found in two dimensions. The two-dimensional least squares solution is obtained by iterative techniques. Experiments show that least-squares model-based halftoning produces more gray levels and better spatial resolution than conventional techniques. We also show that the least- squares approach eliminates the problems associated with error diffusion. Model-based halftoning can be especially useful in transmission of high quality documents using high fidelity gray-scale image encoders. As we have shown, in such cases halftoning can be performed at the receiver, just before printing. Apart from coding efficiency, this approach permits the halftoner to be tuned to the individual printer, whose characteristics may vary considerably from those of other printers, for example, write-black vs. write-white laser printers.

Prediction of thermodynamic properties of coal derivatives. Progress report, September 1, 1981-August 31, 1982

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

Donohue, M.D.

It is the purpose of this research program to develop a model to predict the thermodynamic properties of coal derivatives. Unlike natural gas and petroleum, coal and its gasification and liquefaction products are predominantly aromatic and have substantial quadrupole moments. Because of these quadrupole forces, the numerous correlational techniques that have been developed for petroleum products cannot be used to predict the thermodynamic properties of coal derivatives. We are presently developing a correlation that will be useful in predicting the thermodynamic properties of coal derivatives. This theory is based on the Perturbed-Hard-Chain theory, but is different from PHCT in twomore » respects. First, PHCT uses a square-well to describe the intermolecular potential energy between two molecules. In our new theory, the Lennard-Jones potential energy function is used. The second difference is that we take into account the effect of quadrupole forces on the intermolecular potential energy. In PHCT these forces were ignored. In PHCT the contributions to the partition function (or equation of state) that arise from the attractive forces between molecules (regardless of whether these forces are treated as a square-well or by Lennard-Jones) are calculated by assuming that they are perturbations on a hard sphere. In calculating the contributions to the partition function that arise from the quadrupole-quadrupole interactions, we use a second order perturbation about the Lennard-Jones. For aromatic molecules, the effect of this additional perturbation is significant.« less

Global minimum profile error (GMPE) - a least-squares-based approach for extracting macroscopic rate coefficients for complex gas-phase chemical reactions.

PubMed

Duong, Minh V; Nguyen, Hieu T; Mai, Tam V-T; Huynh, Lam K

2018-01-03

Master equation/Rice-Ramsperger-Kassel-Marcus (ME/RRKM) has shown to be a powerful framework for modeling kinetic and dynamic behaviors of a complex gas-phase chemical system on a complicated multiple-species and multiple-channel potential energy surface (PES) for a wide range of temperatures and pressures. Derived from the ME time-resolved species profiles, the macroscopic or phenomenological rate coefficients are essential for many reaction engineering applications including those in combustion and atmospheric chemistry. Therefore, in this study, a least-squares-based approach named Global Minimum Profile Error (GMPE) was proposed and implemented in the MultiSpecies-MultiChannel (MSMC) code (Int. J. Chem. Kinet., 2015, 47, 564) to extract macroscopic rate coefficients for such a complicated system. The capability and limitations of the new approach were discussed in several well-defined test cases.

Correcting bias in the rational polynomial coefficients of satellite imagery using thin-plate smoothing splines

NASA Astrophysics Data System (ADS)

Shen, Xiang; Liu, Bin; Li, Qing-Quan

2017-03-01

The Rational Function Model (RFM) has proven to be a viable alternative to the rigorous sensor models used for geo-processing of high-resolution satellite imagery. Because of various errors in the satellite ephemeris and instrument calibration, the Rational Polynomial Coefficients (RPCs) supplied by image vendors are often not sufficiently accurate, and there is therefore a clear need to correct the systematic biases in order to meet the requirements of high-precision topographic mapping. In this paper, we propose a new RPC bias-correction method using the thin-plate spline modeling technique. Benefiting from its excellent performance and high flexibility in data fitting, the thin-plate spline model has the potential to remove complex distortions in vendor-provided RPCs, such as the errors caused by short-period orbital perturbations. The performance of the new method was evaluated by using Ziyuan-3 satellite images and was compared against the recently developed least-squares collocation approach, as well as the classical affine-transformation and quadratic-polynomial based methods. The results show that the accuracies of the thin-plate spline and the least-squares collocation approaches were better than the other two methods, which indicates that strong non-rigid deformations exist in the test data because they cannot be adequately modeled by simple polynomial-based methods. The performance of the thin-plate spline method was close to that of the least-squares collocation approach when only a few Ground Control Points (GCPs) were used, and it improved more rapidly with an increase in the number of redundant observations. In the test scenario using 21 GCPs (some of them located at the four corners of the scene), the correction residuals of the thin-plate spline method were about 36%, 37%, and 19% smaller than those of the affine transformation method, the quadratic polynomial method, and the least-squares collocation algorithm, respectively, which demonstrates that the new method can be more effective at removing systematic biases in vendor-supplied RPCs.

Least-Squares Self-Calibration of Imaging Array Data

NASA Technical Reports Server (NTRS)

Arendt, R. G.; Moseley, S. H.; Fixsen, D. J.

2004-01-01

When arrays are used to collect multiple appropriately-dithered images of the same region of sky, the resulting data set can be calibrated using a least-squares minimization procedure that determines the optimal fit between the data and a model of that data. The model parameters include the desired sky intensities as well as instrument parameters such as pixel-to-pixel gains and offsets. The least-squares solution simultaneously provides the formal error estimates for the model parameters. With a suitable observing strategy, the need for separate calibration observations is reduced or eliminated. We show examples of this calibration technique applied to HST NICMOS observations of the Hubble Deep Fields and simulated SIRTF IRAC observations.

Comb model for the anomalous diffusion with dual-phase-lag constitutive relation

NASA Astrophysics Data System (ADS)

Liu, Lin; Zheng, Liancun; Fan, Yu; Chen, Yanping; Liu, Fawang

2018-10-01

As a development of the Fick's model, the dual-phase-lag constitutive relationship with macroscopic and microscopic relaxation characteristics is introduced to describe the anomalous diffusion in comb model. The Dirac delta function in the formulated governing equation represents the special spatial structure of comb model that the horizontal current only exists on the x axis. Solutions are obtained by analytical method with Laplace transform and Fourier transform. The dependence of concentration field and mean square displacement on different parameters are presented and discussed. Results show that the macroscopic and microscopic relaxation parameters have opposite effects on the particle distribution and mean square displacement. Furthermore, four significant results with constant 1/2 are concluded, namely the product of the particle number and the mean square displacement on the x axis equals to 1/2, the exponent of mean square displacement is 1/2 at the special case τq= τP, an asymptotic form of mean square displacement (MSD∼t1/2 as t→0, ∞) is obtained as well at the short time behavior and the long time behavior.

Quantum tunneling and scattering of a composite object

NASA Astrophysics Data System (ADS)

Ahsan, Naureen

Reaction physics involving composite objects with internal degrees of freedom is an important subject since it is encountered in the context of nuclear processes like fusion, fission, particle decay, as well as many other branches of science. Quantum tunneling and scattering of a composite object are explored in this work. A few model Hamiltonians are chosen as examples where a two-particle system interacts, in one dimension, with a target that poses a delta-potential or an infinite wall potential. It is assumed that only one of the two components interacts with the target. The study includes the harmonic oscillator and the infinite square well as examples of intrinsic Hamiltonians that do not allow the projectile to break up, and a finite square well and a delta-well as examples of Hamiltonians that do. The Projection Method and the Variable Phase Method are applied with the aim of an exact solution to the relevant scattering problems. These methods are discussed in the context of the pertinent convergence issues related thereto, and of their applicability. Virtual excitations of the projectile into the classically forbidden energy-domain are found to play a dominant and non-perturbative role in shaping reaction observables, giving rise to enhanced or reduced tunneling in various situations. Cusps and discontinuities are found to appear in observables as manifestations of unitarity and redistribution of flux at the thresholds. The intrinsic structure gives rise to resonancelike behavior in tunneling probabilities. It is also shown that there is charge asymmetry in the scattering of a composite object, unlike in the case of a structureless particle.

Robust scoring functions for protein-ligand interactions with quantum chemical charge models.

PubMed

Wang, Jui-Chih; Lin, Jung-Hsin; Chen, Chung-Ming; Perryman, Alex L; Olson, Arthur J

2011-10-24

Ordinary least-squares (OLS) regression has been used widely for constructing the scoring functions for protein-ligand interactions. However, OLS is very sensitive to the existence of outliers, and models constructed using it are easily affected by the outliers or even the choice of the data set. On the other hand, determination of atomic charges is regarded as of central importance, because the electrostatic interaction is known to be a key contributing factor for biomolecular association. In the development of the AutoDock4 scoring function, only OLS was conducted, and the simple Gasteiger method was adopted. It is therefore of considerable interest to see whether more rigorous charge models could improve the statistical performance of the AutoDock4 scoring function. In this study, we have employed two well-established quantum chemical approaches, namely the restrained electrostatic potential (RESP) and the Austin-model 1-bond charge correction (AM1-BCC) methods, to obtain atomic partial charges, and we have compared how different charge models affect the performance of AutoDock4 scoring functions. In combination with robust regression analysis and outlier exclusion, our new protein-ligand free energy regression model with AM1-BCC charges for ligands and Amber99SB charges for proteins achieve lowest root-mean-squared error of 1.637 kcal/mol for the training set of 147 complexes and 2.176 kcal/mol for the external test set of 1427 complexes. The assessment for binding pose prediction with the 100 external decoy sets indicates very high success rate of 87% with the criteria of predicted root-mean-squared deviation of less than 2 Å. The success rates and statistical performance of our robust scoring functions are only weakly class-dependent (hydrophobic, hydrophilic, or mixed).

Magneto-optical properties of semi-parabolic plus semi-inverse squared quantum wells

NASA Astrophysics Data System (ADS)

Tung, Luong V.; Vinh, Pham T.; Phuc, Huynh V.

2018-06-01

We theoretically study the optical absorption in a quantum well with the semi-parabolic potential plus the semi-inverse squared potential (SPSIS) in the presence of a static magnetic field in which both one- and two-photon absorption processes have been taken into account. The expression of the magneto-optical absorption coefficient (MOAC) is expressed by the second-order golden rule approximation including the electron-LO phonon interaction. We also use the profile method to obtain the full width at half maximum (FWHM) of the absorption peaks. Our numerical results show that either MOAC or FWHM strongly depends on the confinement frequency, temperature, and magnetic field but their dependence on the parameter β is very weak. The temperature dependence of FWHM is consistent with the previous theoretical and experimental works.

New Theoretical Model of Nerve Conduction in Unmyelinated Nerves

PubMed Central

Akaishi, Tetsuya

2017-01-01

Nerve conduction in unmyelinated fibers has long been described based on the equivalent circuit model and cable theory. However, without the change in ionic concentration gradient across the membrane, there would be no generation or propagation of the action potential. Based on this concept, we employ a new conductive model focusing on the distribution of voltage-gated sodium ion channels and Coulomb force between electrolytes. Based on this new model, the propagation of the nerve conduction was suggested to take place far before the generation of action potential at each channel. We theoretically showed that propagation of action potential, which is enabled by the increasing Coulomb force produced by inflowing sodium ions, from one sodium ion channel to the next sodium channel would be inversely proportionate to the density of sodium channels on the axon membrane. Because the longitudinal number of sodium ion channel would be proportionate to the square root of channel density, the conduction velocity of unmyelinated nerves is theoretically shown to be proportionate to the square root of channel density. Also, from a viewpoint of equilibrium state of channel importation and degeneration, channel density was suggested to be proportionate to axonal diameter. Based on these simple basis, conduction velocity in unmyelinated nerves was theoretically shown to be proportionate to the square root of axonal diameter. This new model would also enable us to acquire more accurate and understandable vision on the phenomena in unmyelinated nerves in addition to the conventional electric circuit model and cable theory. PMID:29081751

Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

NASA Technical Reports Server (NTRS)

Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

2016-01-01

Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

Quality of clinical supervision and counselor emotional exhaustion: the potential mediating roles of organizational and occupational commitment.

PubMed

Knudsen, Hannah K; Roman, Paul M; Abraham, Amanda J

2013-01-01

Counselor emotional exhaustion has negative implications for treatment organizations as well as the health of counselors. Quality clinical supervision is protective against emotional exhaustion, but research on the mediating mechanisms between supervision and exhaustion is limited. Drawing upon data from 934 counselors affiliated with treatment programs in the National Institute on Drug Abuse's Clinical Trials Network (CTN), this study examined commitment to the treatment organization and commitment to the counseling occupation as potential mediators of the relationship between quality clinical supervision and emotional exhaustion. The final ordinary least squares (OLS) regression model, which accounted for the nesting of counselors within treatment organizations, indicated that these two types of commitment were plausible mediators of the association between clinical supervision and exhaustion. Higher quality clinical supervision was strongly correlated with commitment to the treatment organization as well as commitment to the occupation of SUD counseling. These findings suggest that quality clinical supervision has the potential to yield important benefits for counselor well-being by strengthening ties to both their employing organization as well the larger treatment field, but longitudinal research is needed to establish these causal relationships. Copyright © 2013 Elsevier Inc. All rights reserved.

Quality of clinical supervision and counselor emotional exhaustion: The potential mediating roles of organizational and occupational commitment

PubMed Central

Knudsen, Hannah K.; Roman, Paul M.; Abraham, Amanda J.

2013-01-01

Counselor emotional exhaustion has negative implications for treatment organizations as well as the health of counselors. Quality clinical supervision is protective against emotional exhaustion, but research on the mediating mechanisms between supervision and exhaustion is limited. Drawing upon data from 934 counselors affiliated with treatment programs in the National Institute on Drug Abuse’s Clinical Trials Network (CTN), this study examined commitment to the treatment organization and commitment to the counseling occupation as potential mediators of the relationship between quality clinical supervision and emotional exhaustion. The final ordinary least squares (OLS) regression model, which accounted for the nesting of counselors within treatment organizations, indicated that these two types of commitment were plausible mediators of the association between clinical supervision and exhaustion. Higher quality clinical supervision was strongly correlated with commitment to the treatment organization as well as commitment to the occupation of SUD counseling. These findings suggest that quality clinical supervision has the potential to yield important benefits for counselor well-being by strengthening ties to both their employing organization as well the larger treatment field, but longitudinal research is needed to establish these causal relationships. PMID:23312873

Does active ageing contribute to life satisfaction for older people? Testing a new model of active ageing.

PubMed

Marsillas, Sara; De Donder, Liesbeth; Kardol, Tinie; van Regenmortel, Sofie; Dury, Sarah; Brosens, Dorien; Smetcoren, An-Sofie; Braña, Teresa; Varela, Jesús

2017-09-01

Several debates have emerged across the literature about the conceptualisation of active ageing. The aim of this study is to develop a model of the construct that is focused on the individual, including different elements of people's lives that have the potential to be modified by intervention programs. Moreover, the paper examines the contributions of active ageing to life satisfaction, as well as the possible predictive role of coping styles on active ageing. For this purpose, a representative sample of 404 Galician (Spain) community-dwelling older adults (aged ≥60 years) were interviewed using a structured survey. The results demonstrate that the proposed model composed of two broad categories is valid. The model comprises status variables (related to physical, psychological, and social health) as well as different types of activities, called processual variables. This model is tested using partial least squares (PLS) regression. The findings show that active ageing is a fourth-order, formative construct. In addition, PLS analyses indicate that active ageing has a moderate and positive path on life satisfaction and that coping styles may predict active ageing. The discussion highlights the potential of active ageing as a relevant concept for people's lives, drawing out policy implications and suggestions for further research.

Simple model for molecular scattering

NASA Astrophysics Data System (ADS)

Mehta, Nirav; Ticknor, Christopher; Hazzard, Kaden

2017-04-01

The collisions of ultracold molecules are qualitatively different from the collisions of ultracold atoms due to the high density of bimolecular resonances near the collision energy. We present results from a simple N-channel scattering model with square-well channel potentials and constant channel couplings (inside the well) designed to reproduce essential features of chaotic molecular scattering. The potential depths and channel splittings are tuned to reproduce the appropriate density of states for the short-range bimolecular collision complex (BCC), which affords a direct comparison of the resulting level-spacing distribution to that expected from random matrix theory (RMT), namely the so-called Wigner surmise. The density of states also sets the scale for the rate of dissociation from the BCC to free molecules, as approximated by transition state theory (TST). Our model affords a semi-analytic solution for the scattering amplitude in the open channel, and a determinantal equation for the eigenenergies of the short-ranged BCC. It is likely the simplest finite-ranged scattering model that can be compared to expectations from the approximations of RMT, and TST. The validity of these approximations has implications for the many-channel Hubbard model recently developed. This research was funded in part by the National Science Foundation under Grant No. NSF PHY-1125915.

Real-Time Adaptive Least-Squares Drag Minimization for Performance Adaptive Aeroelastic Wing

NASA Technical Reports Server (NTRS)

Ferrier, Yvonne L.; Nguyen, Nhan T.; Ting, Eric

2016-01-01

This paper contains a simulation study of a real-time adaptive least-squares drag minimization algorithm for an aeroelastic model of a flexible wing aircraft. The aircraft model is based on the NASA Generic Transport Model (GTM). The wing structures incorporate a novel aerodynamic control surface known as the Variable Camber Continuous Trailing Edge Flap (VCCTEF). The drag minimization algorithm uses the Newton-Raphson method to find the optimal VCCTEF deflections for minimum drag in the context of an altitude-hold flight control mode at cruise conditions. The aerodynamic coefficient parameters used in this optimization method are identified in real-time using Recursive Least Squares (RLS). The results demonstrate the potential of the VCCTEF to improve aerodynamic efficiency for drag minimization for transport aircraft.

Certification in Structural Health Monitoring Systems

DTIC Science & Technology

2011-09-01

validation [3,8]. This may be accomplished by computing the sum of squares of pure error ( SSPE ) and its associated squared correlation [3,8]. To compute...these values, a cross- validation sample must be established. In general, if the SSPE is high, the model does not predict well on independent data...plethora of cross- validation methods, some of which are more useful for certain models than others [3,8]. When possible, a disclosure of the SSPE

Identification of multivariable nonlinear systems in the presence of colored noises using iterative hierarchical least squares algorithm.

PubMed

Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam

2014-07-01

This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Orthogonal Regression: A Teaching Perspective

ERIC Educational Resources Information Center

Carr, James R.

2012-01-01

A well-known approach to linear least squares regression is that which involves minimizing the sum of squared orthogonal projections of data points onto the best fit line. This form of regression is known as orthogonal regression, and the linear model that it yields is known as the major axis. A similar method, reduced major axis regression, is…

Geohydrology and simulated ground-water flow in northwestern Elkhart County, Indiana

USGS Publications Warehouse

Arihood, L.D.; Cohen, D.A.

1998-01-01

In 1994, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency and the City of Elkhart, developed a ground-water model of the Elkhart, Indiana, area to determine the avail-ability and source of water at potential new well fields. The modeled area covered 190 square miles of northwestern Elkhart County and a small part of southern Michigan. Three Superfund sites and several other sites in this area are undergoing environmental cleanup. The model would be used to guide the location of well fields so that Superfund sites and environmental cleanup areas would not be within recharge areas for the well fields. The City of Elkhart obtains its water supply from two aquifers separated by a generally continuous confining unit. The upper aquifer is composed primarily of sand and gravel of glacial origin. Thickness of the upper aquifer ranges from 0 to 116 feet and averages 47 feet. The lower aquifer is composed of sand and gravel with interbedded lenses of silt and clay. Thickness of the lower aquifer ranges from 1 to 335 feet and averages 35 feet. The intervening confining unit is composed of silt and clay with interbedded sand and gravel; the confining unit ranges from 0 to 177 feet, with an average thickness of 27 feet. Flow through the aquifers is generally horizontal vertically downward from the upper aquifer, through the confining unit, and into the lower aquifer, except where flow is vertically upward at the St. Joseph River and other large streams. The hydraulic characteristics of the aquifers and confining unit were estimated by analyzing aquifer-test data from well drillers? logs and by calibration of the model. The horizontal hydraulic conductivity of the upper aquifer is 170 feet per day within about 1 mile of the St. Joseph and Elkhart Rivers and 370 feet per day at distances greater than about 1 mile. The horizontal hydraulic conductivity of the lower aquifer is 370 feet per day throughout the modeled area, with the exception of an area near the center of the modeled area where the horizontal hydraulic conductivity is 170 feet per day. Transmissivity of the lower aquifer increases generally from southwest to northeast; transmissivity values range from near 0 where the lower aquifer is absent to 57,000 square feet per day and average about 8,100 square feet per day. The vertical hydraulic conductivity of the confining unit is 0.07 feet per day; the vertical conductivity of the streambeds commonly is 1.0 foot per day and ranges from 0.05 foot per day to 50 feet per day. The areal recharge rate to the outwash deposits was determined by a base-flow separation technique to be 16 inches per year, and the areal recharge rate to the till was assumed to be 4 inches per year. A two-layer digital model was used to simulate flow in the ground-water system. The model was calibrated on the basis of historical water-use data, water-level records, and gain/loss data for streams during May and June 1979. The model was recalibrated with water-use data and water-level records from 1988. For 1979 data, 49 percent of the inflow to the model area is from precipitation and 46 percent is ground-water inflow across the model boundaries. Most of the ground-water inflow across the model boundary is from the north and east, which corresponds to high values of transmissivity?as high as 57,000 feet squared per day?in the model layers in the northern and eastern areas. Eighty-two percent of the ground-water discharge is to the streams; 5 percent of the ground-water discharge is to wells. Source areas and flow paths to the City of Elkhart public well fields are affected by the location of streams and the geology in the area. Flow to the North Well Field originates north-west of the well field, forms relatively straight flow paths, and moves southeast toward the well field and the St. Joseph River. Flow to the South Well Field begins mostly in the out-wash along Yellow Creek south of the well field, moves northward, and t

Brownian Dynamics simulations of model colloids in channel geometries and external fields

NASA Astrophysics Data System (ADS)

Siems, Ullrich; Nielaba, Peter

2018-04-01

We review the results of Brownian Dynamics simulations of colloidal particles in external fields confined in channels. Super-paramagnetic Brownian particles are well suited two- dimensional model systems for a variety of problems on different length scales, ranging from pedestrian walking through a bottleneck to ions passing ion-channels in living cells. In such systems confinement into channels can have a great influence on the diffusion and transport properties. Especially we will discuss the crossover from single file diffusion in a narrow channel to the diffusion in the extended two-dimensional system. Therefore a new algorithm for computing the mean square displacement (MSD) on logarithmic time scales is presented. In a different study interacting colloidal particles were dragged over a washboard potential and are additionally confined in a two-dimensional micro-channel. In this system kink and anti-kink solitons determine the depinning process of the particles from the periodic potential.

Modeling groundwater nitrate concentrations in private wells in Iowa

USGS Publications Warehouse

Wheeler, David C.; Nolan, Bernard T.; Flory, Abigail R.; DellaValle, Curt T.; Ward, Mary H.

2015-01-01

Contamination of drinking water by nitrate is a growing problem in many agricultural areas of the country. Ingested nitrate can lead to the endogenous formation of N-nitroso compounds, potent carcinogens. We developed a predictive model for nitrate concentrations in private wells in Iowa. Using 34,084 measurements of nitrate in private wells, we trained and tested random forest models to predict log nitrate levels by systematically assessing the predictive performance of 179 variables in 36 thematic groups (well depth, distance to sinkholes, location, land use, soil characteristics, nitrogen inputs, meteorology, and other factors). The final model contained 66 variables in 17 groups. Some of the most important variables were well depth, slope length within 1 km of the well, year of sample, and distance to nearest animal feeding operation. The correlation between observed and estimated nitrate concentrations was excellent in the training set (r-square = 0.77) and was acceptable in the testing set (r-square = 0.38). The random forest model had substantially better predictive performance than a traditional linear regression model or a regression tree. Our model will be used to investigate the association between nitrate levels in drinking water and cancer risk in the Iowa participants of the Agricultural Health Study cohort.

Modeling groundwater nitrate concentrations in private wells in Iowa.

PubMed

Wheeler, David C; Nolan, Bernard T; Flory, Abigail R; DellaValle, Curt T; Ward, Mary H

2015-12-01

Contamination of drinking water by nitrate is a growing problem in many agricultural areas of the country. Ingested nitrate can lead to the endogenous formation of N-nitroso compounds, potent carcinogens. We developed a predictive model for nitrate concentrations in private wells in Iowa. Using 34,084 measurements of nitrate in private wells, we trained and tested random forest models to predict log nitrate levels by systematically assessing the predictive performance of 179 variables in 36 thematic groups (well depth, distance to sinkholes, location, land use, soil characteristics, nitrogen inputs, meteorology, and other factors). The final model contained 66 variables in 17 groups. Some of the most important variables were well depth, slope length within 1 km of the well, year of sample, and distance to nearest animal feeding operation. The correlation between observed and estimated nitrate concentrations was excellent in the training set (r-square=0.77) and was acceptable in the testing set (r-square=0.38). The random forest model had substantially better predictive performance than a traditional linear regression model or a regression tree. Our model will be used to investigate the association between nitrate levels in drinking water and cancer risk in the Iowa participants of the Agricultural Health Study cohort. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluation of the Bitterness of Traditional Chinese Medicines using an E-Tongue Coupled with a Robust Partial Least Squares Regression Method.

PubMed

Lin, Zhaozhou; Zhang, Qiao; Liu, Ruixin; Gao, Xiaojie; Zhang, Lu; Kang, Bingya; Shi, Junhan; Wu, Zidan; Gui, Xinjing; Li, Xuelin

2016-01-25

To accurately, safely, and efficiently evaluate the bitterness of Traditional Chinese Medicines (TCMs), a robust predictor was developed using robust partial least squares (RPLS) regression method based on data obtained from an electronic tongue (e-tongue) system. The data quality was verified by the Grubb's test. Moreover, potential outliers were detected based on both the standardized residual and score distance calculated for each sample. The performance of RPLS on the dataset before and after outlier detection was compared to other state-of-the-art methods including multivariate linear regression, least squares support vector machine, and the plain partial least squares regression. Both R² and root-mean-squares error (RMSE) of cross-validation (CV) were recorded for each model. With four latent variables, a robust RMSECV value of 0.3916 with bitterness values ranging from 0.63 to 4.78 were obtained for the RPLS model that was constructed based on the dataset including outliers. Meanwhile, the RMSECV, which was calculated using the models constructed by other methods, was larger than that of the RPLS model. After six outliers were excluded, the performance of all benchmark methods markedly improved, but the difference between the RPLS model constructed before and after outlier exclusion was negligible. In conclusion, the bitterness of TCM decoctions can be accurately evaluated with the RPLS model constructed using e-tongue data.

Study of Aggregation of Janus Ellipsoids

NASA Astrophysics Data System (ADS)

Ruth, Donovan; Li, Wei; Khadka, Shreeya; Rickman, Jeffrey; Gunton, James

2013-03-01

We perform numerical simulations of a quasi-square well potential model of one-patch colloidal particles to investigate the collective structure of a system of Janus ellipsoids. We show that for Janus ellipsoids such that one half is an attractive patch, while the entire ellipsoid has a hardcore repulsion, the system organizes into a distribution of orientationally ordered micelles and vesicles. We analyze the cluster distribution at several temperatures and low densities and show that below certain temperatures the system is populated by stable clusters and depending on temperature and density the system is populated by either vesicles or micelle structures.

Diffuse-flow conceptualization and simulation of the Edwards aquifer, San Antonio region, Texas

USGS Publications Warehouse

Lindgren, R.J.

2006-01-01

A numerical ground-water-flow model (hereinafter, the conduit-flow Edwards aquifer model) of the karstic Edwards aquifer in south-central Texas was developed for a previous study on the basis of a conceptualization emphasizing conduit development and conduit flow, and included simulating conduits as one-cell-wide, continuously connected features. Uncertainties regarding the degree to which conduits pervade the Edwards aquifer and influence ground-water flow, as well as other uncertainties inherent in simulating conduits, raised the question of whether a model based on the conduit-flow conceptualization was the optimum model for the Edwards aquifer. Accordingly, a model with an alternative hydraulic conductivity distribution without conduits was developed in a study conducted during 2004-05 by the U.S. Geological Survey, in cooperation with the San Antonio Water System. The hydraulic conductivity distribution for the modified Edwards aquifer model (hereinafter, the diffuse-flow Edwards aquifer model), based primarily on a conceptualization in which flow in the aquifer predominantly is through a network of numerous small fractures and openings, includes 38 zones, with hydraulic conductivities ranging from 3 to 50,000 feet per day. Revision of model input data for the diffuse-flow Edwards aquifer model was limited to changes in the simulated hydraulic conductivity distribution. The root-mean-square error for 144 target wells for the calibrated steady-state simulation for the diffuse-flow Edwards aquifer model is 20.9 feet. This error represents about 3 percent of the total head difference across the model area. The simulated springflows for Comal and San Marcos Springs for the calibrated steady-state simulation were within 2.4 and 15 percent of the median springflows for the two springs, respectively. The transient calibration period for the diffuse-flow Edwards aquifer model was 1947-2000, with 648 monthly stress periods, the same as for the conduit-flow Edwards aquifer model. The root-mean-square error for a period of drought (May-November 1956) for the calibrated transient simulation for 171 target wells is 33.4 feet, which represents about 5 percent of the total head difference across the model area. The root-mean-square error for a period of above-normal rainfall (November 1974-July 1975) for the calibrated transient simulation for 169 target wells is 25.8 feet, which represents about 4 percent of the total head difference across the model area. The root-mean-square error ranged from 6.3 to 30.4 feet in 12 target wells with long-term water-level measurements for varying periods during 1947-2000 for the calibrated transient simulation for the diffuse-flow Edwards aquifer model, and these errors represent 5.0 to 31.3 percent of the range in water-level fluctuations of each of those wells. The root-mean-square errors for the five major springs in the San Antonio segment of the aquifer for the calibrated transient simulation, as a percentage of the range of discharge fluctuations measured at the springs, varied from 7.2 percent for San Marcos Springs and 8.1 percent for Comal Springs to 28.8 percent for Leona Springs. The root-mean-square errors for hydraulic heads for the conduit-flow Edwards aquifer model are 27, 76, and 30 percent greater than those for the diffuse-flow Edwards aquifer model for the steady-state, drought, and above-normal rainfall synoptic time periods, respectively. The goodness-of-fit between measured and simulated springflows is similar for Comal, San Marcos, and Leona Springs for the diffuse-flow Edwards aquifer model and the conduit-flow Edwards aquifer model. The root-mean-square errors for Comal and Leona Springs were 15.6 and 21.3 percent less, respectively, whereas the root-mean-square error for San Marcos Springs was 3.3 percent greater for the diffuse-flow Edwards aquifer model compared to the conduit-flow Edwards aquifer model. The root-mean-square errors for San Antonio and San Pedro Springs were appreciably greater, 80.2 and 51.0 percent, respectively, for the diffuse-flow Edwards aquifer model. The simulated water budgets for the diffuse-flow Edwards aquifer model are similar to those for the conduit-flow Edwards aquifer model. Differences in percentage of total sources or discharges for a budget component are 2.0 percent or less for all budget components for the steady-state and transient simulations. The largest difference in terms of the magnitude of water budget components for the transient simulation for 1956 was a decrease of about 10,730 acre-feet per year (about 2 per-cent) in springflow for the diffuse-flow Edwards aquifer model compared to the conduit-flow Edwards aquifer model. This decrease in springflow (a water budget discharge) was largely offset by the decreased net loss of water from storage (a water budget source) of about 10,500 acre-feet per year.

1D momentum-conserving systems: the conundrum of anomalous versus normal heat transport

NASA Astrophysics Data System (ADS)

Li, Yunyun; Liu, Sha; Li, Nianbei; Hänggi, Peter; Li, Baowen

2015-04-01

Transport and the spread of heat in Hamiltonian one dimensional momentum conserving nonlinear systems is commonly thought to proceed anomalously. Notable exceptions, however, do exist of which the coupled rotator model is a prominent case. Therefore, the quest arises to identify the origin of manifest anomalous energy and momentum transport in those low dimensional systems. We develop the theory for both, the statistical densities for momentum- and energy-spread and particularly its momentum-/heat-diffusion behavior, as well as its corresponding momentum/heat transport features. We demonstrate that the second temporal derivative of the mean squared deviation of the momentum spread is proportional to the equilibrium correlation of the total momentum flux. Subtracting the part which corresponds to a ballistic momentum spread relates (via this integrated, subleading momentum flux correlation) to an effective viscosity, or equivalently, to the underlying momentum diffusivity. We next put forward the intriguing hypothesis: normal spread of this so adjusted excess momentum density causes normal energy spread and alike normal heat transport (Fourier Law). Its corollary being that an anomalous, superdiffusive broadening of this adjusted excess momentum density in turn implies an anomalous energy spread and correspondingly anomalous, superdiffusive heat transport. This hypothesis is successfully corroborated within extensive molecular dynamics simulations over large extended time scales. Our numerical validation of the hypothesis involves four distinct archetype classes of nonlinear pair-interaction potentials: (i) a globally bounded pair interaction (the noted coupled rotator model), (ii) unbounded interactions acting at large distances (the coupled rotator model amended with harmonic pair interactions), (iii) the case of a hard point gas with unbounded square-well interactions and (iv) a pair interaction potential being unbounded at short distances while displaying an asymptotic free part (Lennard-Jones model). We compare our findings with recent predictions obtained from nonlinear fluctuating hydrodynamics theory.

Double folding analysis of 3He elastic and inelastic scattering to low lying states on 90Zr, 116Sn and 208Pb at 270 MeV

NASA Astrophysics Data System (ADS)

Marwa, N. El-Hammamy

2015-03-01

The experimental data on elastic and inelastic scattering of 270 MeV 3He particles to several low lying states in 90Zr, 116Sn and 208Pb are analyzed within the double folding model (DFM). Fermi density distribution (FDD) of target nuclei is used to obtain real potentials with different powers. DF results are introduced into a modified DWUCK4 code to calculate the elastic and inelastic scattering cross sections. Two choices of potentials form factors are used; Woods Saxon (WS) and Woods Saxon Squared (WS2) for real potential, while the imaginary part is taken as phenomenological Woods Saxon (PWS) and phenomenological Woods Saxon Squared (PWS2). This comparison provides information about the similarities and differences of the models used in calculations.

Phase diagram of heteronuclear Janus dumbbells

NASA Astrophysics Data System (ADS)

O'Toole, Patrick; Giacometti, Achille; Hudson, Toby

Using Aggregation-Volume-Bias Monte Carlo simulations along with Successive Umbrella Sampling and Histogram Re-weighting, we study the phase diagram of a system of dumbbells formed by two touching spheres having variable sizes, as well as different interaction properties. The first sphere ($h$) interacts with all other spheres belonging to different dumbbells with a hard-sphere potential. The second sphere ($s$) interacts via a square-well interaction with other $s$ spheres belonging to different dumbbells and with a hard-sphere potential with all remaining $h$ spheres. We focus on the region where the $s$ sphere is larger than the $h$ sphere, as measured by a parameter $1\\le \\alpha\\le 2 $ controlling the relative size of the two spheres. As $\\alpha \\to 2$ a simple fluid of square-well spheres is recovered, whereas $\\alpha \\to 1$ corresponds to the Janus dumbbell limit, where the $h$ and $s$ spheres have equal sizes. Many phase diagrams falling into three classes are observed, depending on the value of $\\alpha$. The $1.8 \\le \\alpha \\le 2$ is dominated by a gas-liquid phase separation very similar to that of a pure square-well fluid with varied critical temperature and density. When $1.3 \\le \\alpha \\le 1.8$ we find a progressive destabilization of the gas-liquid phase diagram by the onset of self-assembled structures, that eventually lead to a metastability of the gas-liquid transition below $\\alpha=1.2$.

Facies Modeling Using 3D Pre-Stack Simultaneous Seismic Inversion and Multi-Attribute Probability Neural Network Transform in the Wattenberg Field, Colorado

NASA Astrophysics Data System (ADS)

Harryandi, Sheila

The Niobrara/Codell unconventional tight reservoir play at Wattenberg Field, Colorado has potentially two billion barrels of oil equivalent requiring hundreds of wells to access this resource. The Reservoir Characterization Project (RCP), in conjunction with Anadarko Petroleum Corporation (APC), began reservoir characterization research to determine how to increase reservoir recovery while maximizing operational efficiency. Past research results indicate that targeting the highest rock quality within the reservoir section for hydraulic fracturing is optimal for improving horizontal well stimulation through multi-stage hydraulic fracturing. The reservoir is highly heterogeneous, consisting of alternating chalks and marls. Modeling the facies within the reservoir is very important to be able to capture the heterogeneity at the well-bore scale; this heterogeneity is then upscaled from the borehole scale to the seismic scale to distribute the heterogeneity in the inter-well space. I performed facies clustering analysis to create several facies defining the reservoir interval in the RCP Wattenberg Field study area. Each facies can be expressed in terms of a range of rock property values from wells obtained by cluster analysis. I used the facies classification from the wells to guide the pre-stack seismic inversion and multi-attribute transform. The seismic data extended the facies information and rock quality information from the wells. By obtaining this information from the 3D facies model, I generated a facies volume capturing the reservoir heterogeneity throughout a ten square mile study-area within the field area. Recommendations are made based on the facies modeling, which include the location for future hydraulic fracturing/re-fracturing treatments to improve recovery from the reservoir, and potential deeper intervals for future exploration drilling targets.

Design of model experiments for melt flow and solidification in a square container under time-dependent magnetic fields

NASA Astrophysics Data System (ADS)

Meier, D.; Lukin, G.; Thieme, N.; Bönisch, P.; Dadzis, K.; Büttner, L.; Pätzold, O.; Czarske, J.; Stelter, M.

2017-03-01

This paper describes novel equipment for model experiments designed for detailed studies on electromagnetically driven flows as well as solidification and melting processes with low-melting metals in a square-based container. Such model experiments are relevant for a validation of numerical flow simulation, in particular in the field of directional solidification of multi-crystalline photovoltaic silicon ingots. The equipment includes two square-shaped electromagnetic coils and a melt container with a base of 220×220 mm2 and thermostat-controlled heat exchangers at top and bottom. A system for dual-plane, spatial- and time-resolved flow measurements as well as for in-situ tracking of the solid-liquid interface is developed on the basis of the ultrasound Doppler velocimetry. The parameters of the model experiment are chosen to meet the scaling laws for a transfer of experimental results to real silicon growth processes. The eutectic GaInSn alloy and elemental gallium with melting points of 10.5 °C and 29.8 °C, respectively, are used as model substances. Results of experiments for testing the equipment are presented and discussed.

BCS Theory of Time-Reversal-Symmetric Hofstadter-Hubbard Model

NASA Astrophysics Data System (ADS)

Umucalılar, R. O.; Iskin, M.

2017-08-01

The competition between the length scales associated with the periodicity of a lattice potential and the cyclotron radius of a uniform magnetic field is known to have dramatic effects on the single-particle properties of a quantum particle, e.g., the fractal spectrum is known as the Hofstadter butterfly. Having this intricate competition in mind, we consider a two-component Fermi gas on a square optical lattice with opposite synthetic magnetic fields for the components, and study its effects on the many-body BCS-pairing phenomenon. By a careful addressing of the distinct superfluid transitions from the semimetal, quantum spin-Hall insulator, or normal phases, we explore the low-temperature phase diagrams of the model, displaying lobe structures that are reminiscent of the well-known Mott-insulator transitions of the Bose-Hubbard model.

An individual-based model of rabbit viral haemorrhagic disease on European wild rabbits (Oryctolagus cuniculus)

USGS Publications Warehouse

Fa, John E.; Sharples, Colin M.; Bell, Diana J.; DeAngelis, Donald L.

2001-01-01

We developed an individual-based model of Rabbit Viral Hemorrhagic Disease (RVHD) for European wild rabbits (Oryctolagus cuniculus L.), representing up to 1000 rabbits in four hectares. Model output for productivity and recruitment matched published values. The disease was density-dependent and virulence affected outcome. Strains that caused death after several days produced greater overall mortality than strains in which rabbits either died or recovered very quickly. Disease effect also depended on time of year. We also elaborated a larger scale model representing 25 km2 and 100,000+ rabbits, split into a number of grid-squares. This was a more traditional model that did not represent individual rabbits, but employed a system of dynamic equations for each grid-square. Disease spread depended on probability of transmission between neighboring grid-squares. Potential recovery from a major population crash caused by the disease relied on disease virulence and frequency of recurrence. The model's dependence on probability of disease transmission between grid-squares suggests the way that the model represents the spatial distribution of the population affects simulation. Although data on RVHD in Europe are lacking, our models provide a basis for describing the disease in realistic detail and for assessing influence of various social and spatial factors on spread.

Nonlinear Reynolds stress model for turbulent shear flows

NASA Technical Reports Server (NTRS)

Barton, J. Michael; Rubinstein, R.; Kirtley, K. R.

1991-01-01

A nonlinear algebraic Reynolds stress model, derived using the renormalization group, is applied to equilibrium homogeneous shear flow and fully developed flow in a square duct. The model, which is quadratically nonlinear in the velocity gradients, successfully captures the large-scale inhomogeneity and anisotropy of the flows studied. The ratios of normal stresses, as well as the actual magnitudes of the stresses are correctly predicted for equilibrium homogeneous shear flow. Reynolds normal stress anisotropy and attendant turbulence driven secondary flow are predicted for a square duct. Profiles of mean velocity and normal stresses are in good agreement with measurements. Very close to walls, agreement with measurements diminishes. The model has the benefit of containing no arbitrary constants; all values are determined directly from the theory. It seems that near wall behavior is influenced by more than the large scale anisotropy accommodated in the current model. More accurate near wall calculations may well require a model for anisotropic dissipation.

Reference interaction site model and optimized perturbation theories of colloidal dumbbells with increasing anisotropy

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

Munaò, Gianmarco, E-mail: gmunao@unime.it; Costa, Dino; Caccamo, Carlo

We investigate thermodynamic properties of anisotropic colloidal dumbbells in the frameworks provided by the Reference Interaction Site Model (RISM) theory and an Optimized Perturbation Theory (OPT), this latter based on a fourth-order high-temperature perturbative expansion of the free energy, recently generalized to molecular fluids. Our model is constituted by two identical tangent hard spheres surrounded by square-well attractions with same widths and progressively different depths. Gas-liquid coexistence curves are obtained by predicting pressures, free energies, and chemical potentials. In comparison with previous simulation results, RISM and OPT agree in reproducing the progressive reduction of the gas-liquid phase separation as themore » anisotropy of the interaction potential becomes more pronounced; in particular, the RISM theory provides reasonable predictions for all coexistence curves, bar the strong anisotropy regime, whereas OPT performs generally less well. Both theories predict a linear dependence of the critical temperature on the interaction strength, reproducing in this way the mean-field behavior observed in simulations; the critical density—that drastically drops as the anisotropy increases—turns to be less accurate. Our results appear as a robust benchmark for further theoretical studies, in support to the simulation approach, of self-assembly in model colloidal systems.« less

Extension of the Haseman-Elston regression model to longitudinal data.

PubMed

Won, Sungho; Elston, Robert C; Park, Taesung

2006-01-01

We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene x time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well. Copyright 2006 S. Karger AG, Basel.

[Application of near infrared spectroscopy combined with particle swarm optimization based least square support vactor machine to rapid quantitative analysis of Corni Fructus].

PubMed

Liu, Xue-song; Sun, Fen-fang; Jin, Ye; Wu, Yong-jiang; Gu, Zhi-xin; Zhu, Li; Yan, Dong-lan

2015-12-01

A novel method was developed for the rapid determination of multi-indicators in corni fructus by means of near infrared (NIR) spectroscopy. Particle swarm optimization (PSO) based least squares support vector machine was investigated to increase the levels of quality control. The calibration models of moisture, extractum, morroniside and loganin were established using the PSO-LS-SVM algorithm. The performance of PSO-LS-SVM models was compared with partial least squares regression (PLSR) and back propagation artificial neural network (BP-ANN). The calibration and validation results of PSO-LS-SVM were superior to both PLS and BP-ANN. For PSO-LS-SVM models, the correlation coefficients (r) of calibrations were all above 0.942. The optimal prediction results were also achieved by PSO-LS-SVM models with the RMSEP (root mean square error of prediction) and RSEP (relative standard errors of prediction) less than 1.176 and 15.5% respectively. The results suggest that PSO-LS-SVM algorithm has a good model performance and high prediction accuracy. NIR has a potential value for rapid determination of multi-indicators in Corni Fructus.

The Square Kilometre Array

NASA Technical Reports Server (NTRS)

Huynh, Minh; Lazio, Joseph

2011-01-01

The Square Kilometre Array (SKA) will be the premier instrument to study radiation at centimetre and metre wavelengths from the cosmos, and in particular neutral hydrogen, the most abundant element in the universe. The SKA will probe the dawn of galaxy formation as well as allow advances in many other areas of astronomy, such as fundamental physics, astro-biology and cosmology. The SKA will have a collecting area of up to one million square metres spread over at least 3000 km, providing a collecting area more than twenty times greater than the current largest radio telescope. Its field of view on the sky will be several tens of square degrees with potentially several large (100 square degrees) independent beams at the lower frequencies, providing a survey speed many thousands of times greater than current facilities. This paper summarises the key science drivers of the SKA and provides an update on the international project.

Quantitative Modelling of Trace Elements in Hard Coal.

PubMed

Smoliński, Adam; Howaniec, Natalia

2016-01-01

The significance of coal in the world economy remains unquestionable for decades. It is also expected to be the dominant fossil fuel in the foreseeable future. The increased awareness of sustainable development reflected in the relevant regulations implies, however, the need for the development and implementation of clean coal technologies on the one hand, and adequate analytical tools on the other. The paper presents the application of the quantitative Partial Least Squares method in modeling the concentrations of trace elements (As, Ba, Cd, Co, Cr, Cu, Mn, Ni, Pb, Rb, Sr, V and Zn) in hard coal based on the physical and chemical parameters of coal, and coal ash components. The study was focused on trace elements potentially hazardous to the environment when emitted from coal processing systems. The studied data included 24 parameters determined for 132 coal samples provided by 17 coal mines of the Upper Silesian Coal Basin, Poland. Since the data set contained outliers, the construction of robust Partial Least Squares models for contaminated data set and the correct identification of outlying objects based on the robust scales were required. These enabled the development of the correct Partial Least Squares models, characterized by good fit and prediction abilities. The root mean square error was below 10% for all except for one the final Partial Least Squares models constructed, and the prediction error (root mean square error of cross-validation) exceeded 10% only for three models constructed. The study is of both cognitive and applicative importance. It presents the unique application of the chemometric methods of data exploration in modeling the content of trace elements in coal. In this way it contributes to the development of useful tools of coal quality assessment.

Quantitative Modelling of Trace Elements in Hard Coal

PubMed Central

Smoliński, Adam; Howaniec, Natalia

2016-01-01

The significance of coal in the world economy remains unquestionable for decades. It is also expected to be the dominant fossil fuel in the foreseeable future. The increased awareness of sustainable development reflected in the relevant regulations implies, however, the need for the development and implementation of clean coal technologies on the one hand, and adequate analytical tools on the other. The paper presents the application of the quantitative Partial Least Squares method in modeling the concentrations of trace elements (As, Ba, Cd, Co, Cr, Cu, Mn, Ni, Pb, Rb, Sr, V and Zn) in hard coal based on the physical and chemical parameters of coal, and coal ash components. The study was focused on trace elements potentially hazardous to the environment when emitted from coal processing systems. The studied data included 24 parameters determined for 132 coal samples provided by 17 coal mines of the Upper Silesian Coal Basin, Poland. Since the data set contained outliers, the construction of robust Partial Least Squares models for contaminated data set and the correct identification of outlying objects based on the robust scales were required. These enabled the development of the correct Partial Least Squares models, characterized by good fit and prediction abilities. The root mean square error was below 10% for all except for one the final Partial Least Squares models constructed, and the prediction error (root mean square error of cross–validation) exceeded 10% only for three models constructed. The study is of both cognitive and applicative importance. It presents the unique application of the chemometric methods of data exploration in modeling the content of trace elements in coal. In this way it contributes to the development of useful tools of coal quality assessment. PMID:27438794

From square-well to Janus: Improved algorithm for integral equation theory and comparison with thermodynamic perturbation theory within the Kern-Frenkel model

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

Giacometti, Achille, E-mail: achille.giacometti@unive.it; Gögelein, Christoph, E-mail: christoph.goegelein@ds.mpg.de; Lado, Fred, E-mail: lado@ncsu.edu

2014-03-07

Building upon past work on the phase diagram of Janus fluids [F. Sciortino, A. Giacometti, and G. Pastore, Phys. Rev. Lett. 103, 237801 (2009)], we perform a detailed study of integral equation theory of the Kern-Frenkel potential with coverage that is tuned from the isotropic square-well fluid to the Janus limit. An improved algorithm for the reference hypernetted-chain (RHNC) equation for this problem is implemented that significantly extends the range of applicability of RHNC. Results for both structure and thermodynamics are presented and compared with numerical simulations. Unlike previous attempts, this algorithm is shown to be stable down to themore » Janus limit, thus paving the way for analyzing the frustration mechanism characteristic of the gas-liquid transition in the Janus system. The results are also compared with Barker-Henderson thermodynamic perturbation theory on the same model. We then discuss the pros and cons of both approaches within a unified treatment. On balance, RHNC integral equation theory, even with an isotropic hard-sphere reference system, is found to be a good compromise between accuracy of the results, computational effort, and uniform quality to tackle self-assembly processes in patchy colloids of complex nature. Further improvement in RHNC however clearly requires an anisotropic reference bridge function.« less

Free energy landscape of protein-like chains with discontinuous potentials

NASA Astrophysics Data System (ADS)

Movahed, Hanif Bayat; van Zon, Ramses; Schofield, Jeremy

2012-06-01

In this article the configurational space of two simple protein models consisting of polymers composed of a periodic sequence of four different kinds of monomers is studied as a function of temperature. In the protein models, hydrogen bond interactions, electrostatic repulsion, and covalent bond vibrations are modeled by discontinuous step, shoulder, and square-well potentials, respectively. The protein-like chains exhibit a secondary alpha helix structure in their folded states at low temperatures, and allow a natural definition of a configuration by considering which beads are bonded. Free energies and entropies of configurations are computed using the parallel tempering method in combination with hybrid Monte Carlo sampling of the canonical ensemble of the discontinuous potential system. The probability of observing the most common configuration is used to analyze the nature of the free energy landscape, and it is found that the model with the least number of possible bonds exhibits a funnel-like free energy landscape at low enough temperature for chains with fewer than 30 beads. For longer proteins, the free landscape consists of several minima, where the configuration with the lowest free energy changes significantly by lowering the temperature and the probability of observing the most common configuration never approaches one due to the degeneracy of the lowest accessible potential energy.

Growth kinetics of borided layers: Artificial neural network and least square approaches

NASA Astrophysics Data System (ADS)

Campos, I.; Islas, M.; Ramírez, G.; VillaVelázquez, C.; Mota, C.

2007-05-01

The present study evaluates the growth kinetics of the boride layer Fe 2B in AISI 1045 steel, by means of neural networks and the least square techniques. The Fe 2B phase was formed at the material surface using the paste boriding process. The surface boron potential was modified considering different boron paste thicknesses, with exposure times of 2, 4 and 6 h, and treatment temperatures of 1193, 1223 and 1273 K. The neural network and the least square models were set by the layer thickness of Fe 2B phase, and assuming that the growth of the boride layer follows a parabolic law. The reliability of the techniques used is compared with a set of experiments at a temperature of 1223 K with 5 h of treatment time and boron potentials of 2, 3, 4 and 5 mm. The results of the Fe 2B layer thicknesses show a mean error of 5.31% for the neural network and 3.42% for the least square method.

Modified QCD ghost f(T,TG) gravity

NASA Astrophysics Data System (ADS)

Jawad, Abdul; Rani, Shamaila; Chattopadhyay, Surajit

2015-12-01

In this paper, we explore the reconstruction scenario of modified QCD ghost dark energy model and newly proposed f(T,TG) gravity in flat FRW universe. We consider the well-known assumption of scale factor, i.e., power law form. We construct the f(T,TG) model and discuss its cosmological consequences through various cosmological parameters such as equation of state parameter, squared speed of sound and ω_{DE}-ω '_{DE}. The equation of state parameter provides the quintom-like behavior of the universe. The squared speed of sound exhibits the stability of model in the later time. Also, ω_{DE}- ω '_{DE} corresponds to freezing as well as thawing regions. It is also interesting to remark here that the results of equation of state parameter and w_{DE}-w'_{DE} coincide with the observational data.

Evaluation of the Bitterness of Traditional Chinese Medicines using an E-Tongue Coupled with a Robust Partial Least Squares Regression Method

PubMed Central

Lin, Zhaozhou; Zhang, Qiao; Liu, Ruixin; Gao, Xiaojie; Zhang, Lu; Kang, Bingya; Shi, Junhan; Wu, Zidan; Gui, Xinjing; Li, Xuelin

2016-01-01

To accurately, safely, and efficiently evaluate the bitterness of Traditional Chinese Medicines (TCMs), a robust predictor was developed using robust partial least squares (RPLS) regression method based on data obtained from an electronic tongue (e-tongue) system. The data quality was verified by the Grubb’s test. Moreover, potential outliers were detected based on both the standardized residual and score distance calculated for each sample. The performance of RPLS on the dataset before and after outlier detection was compared to other state-of-the-art methods including multivariate linear regression, least squares support vector machine, and the plain partial least squares regression. Both R2 and root-mean-squares error (RMSE) of cross-validation (CV) were recorded for each model. With four latent variables, a robust RMSECV value of 0.3916 with bitterness values ranging from 0.63 to 4.78 were obtained for the RPLS model that was constructed based on the dataset including outliers. Meanwhile, the RMSECV, which was calculated using the models constructed by other methods, was larger than that of the RPLS model. After six outliers were excluded, the performance of all benchmark methods markedly improved, but the difference between the RPLS model constructed before and after outlier exclusion was negligible. In conclusion, the bitterness of TCM decoctions can be accurately evaluated with the RPLS model constructed using e-tongue data. PMID:26821026

Potential energy surface fitting by a statistically localized, permutationally invariant, local interpolating moving least squares method for the many-body potential: Method and application to N{sub 4}

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

Bender, Jason D.; Doraiswamy, Sriram; Candler, Graham V., E-mail: truhlar@umn.edu, E-mail: candler@aem.umn.edu

2014-02-07

Fitting potential energy surfaces to analytic forms is an important first step for efficient molecular dynamics simulations. Here, we present an improved version of the local interpolating moving least squares method (L-IMLS) for such fitting. Our method has three key improvements. First, pairwise interactions are modeled separately from many-body interactions. Second, permutational invariance is incorporated in the basis functions, using permutationally invariant polynomials in Morse variables, and in the weight functions. Third, computational cost is reduced by statistical localization, in which we statistically correlate the cutoff radius with data point density. We motivate our discussion in this paper with amore » review of global and local least-squares-based fitting methods in one dimension. Then, we develop our method in six dimensions, and we note that it allows the analytic evaluation of gradients, a feature that is important for molecular dynamics. The approach, which we call statistically localized, permutationally invariant, local interpolating moving least squares fitting of the many-body potential (SL-PI-L-IMLS-MP, or, more simply, L-IMLS-G2), is used to fit a potential energy surface to an electronic structure dataset for N{sub 4}. We discuss its performance on the dataset and give directions for further research, including applications to trajectory calculations.« less

A Study on Grid-Square Statistics Based Estimation of Regional Electricity Demand and Regional Potential Capacity of Distributed Generators

NASA Astrophysics Data System (ADS)

Kato, Takeyoshi; Sugimoto, Hiroyuki; Suzuoki, Yasuo

We established a procedure for estimating regional electricity demand and regional potential capacity of distributed generators (DGs) by using a grid square statistics data set. A photovoltaic power system (PV system) for residential use and a co-generation system (CGS) for both residential and commercial use were taken into account. As an example, the result regarding Aichi prefecture was presented in this paper. The statistical data of the number of households by family-type and the number of employees by business category for about 4000 grid-square with 1km × 1km area was used to estimate the floor space or the electricity demand distribution. The rooftop area available for installing PV systems was also estimated with the grid-square statistics data set. Considering the relation between a capacity of existing CGS and a scale-index of building where CGS is installed, the potential capacity of CGS was estimated for three business categories, i.e. hotel, hospital, store. In some regions, the potential capacity of PV systems was estimated to be about 10,000kW/km2, which corresponds to the density of the existing area with intensive installation of PV systems. Finally, we discussed the ratio of regional potential capacity of DGs to regional maximum electricity demand for deducing the appropriate capacity of DGs in the model of future electricity distribution system.

Investigating the mechanism of aggregation of colloidal particles during electrophoretic deposition

NASA Astrophysics Data System (ADS)

Guelcher, Scott Arthur

Charged particles deposited near an electrode aggregate to form ordered clusters in the presence of both dc and ac applied electric fields. The aggregation process could have important applications in areas such as coatings technology and ceramics processing. This thesis has sought to identify the phenomena driving the aggregation process. According to the electroosmotic flow developed by Solomentsev et al. (1997), aggregation in dc electric fields is caused by convection in the electroosmotic flow about deposited particles, and it is therefore an electrokinetic phenomenon which scales linearly with the electric field and the zeta-potential of the particles. Trajectories of pairs of particles aggregating to form doublets have been shown to scale linearly with the electric field and the zeta-potential of the particles, as predicted by the electroosmotic flow model. Furthermore, quantitative agreement has been demonstrated between the experimental and calculated trajectories for surface-to-surface separation distances between the particles ranging from one to two radii. The trajectories were calculated from the electroosmotic flow model with no fitting parameters; the only inputs to the model were the mobility of the deposited particles, the zeta- potential of the particles, and the applied electric field, all of which were measured independently. Clustering of colloidal particles deposited near an electrode in ac fields has also been observed, but a suitable model for the aggregation process has not been proposed and quantitative data in the literature are scarce. Trajectories of pairs of particles aggregating to form doublets in an ac field have been shown to scale with the root-mean-square (rms) electric field raised to the power 1.4 over the range of electric fields 10-35 V/cm (100-Hz sine and square waves). The aggregation is also frequency dependent; the doublets aggregate fastest at 30 Hz (square wave) and slowest at 500 Hz (square wave), while the interaction is repulsive at 1 kHz (square wave). The advantage of ac fields is that the process can operated at frequencies sufficiently high to avoid the negative effects of electrochemical reactions.

Application of least square support vector machine and multivariate adaptive regression spline models in long term prediction of river water pollution

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Parmar, Kulwinder Singh

2016-03-01

This study investigates the accuracy of least square support vector machine (LSSVM), multivariate adaptive regression splines (MARS) and M5 model tree (M5Tree) in modeling river water pollution. Various combinations of water quality parameters, Free Ammonia (AMM), Total Kjeldahl Nitrogen (TKN), Water Temperature (WT), Total Coliform (TC), Fecal Coliform (FC) and Potential of Hydrogen (pH) monitored at Nizamuddin, Delhi Yamuna River in India were used as inputs to the applied models. Results indicated that the LSSVM and MARS models had almost same accuracy and they performed better than the M5Tree model in modeling monthly chemical oxygen demand (COD). The average root mean square error (RMSE) of the LSSVM and M5Tree models was decreased by 1.47% and 19.1% using MARS model, respectively. Adding TC input to the models did not increase their accuracy in modeling COD while adding FC and pH inputs to the models generally decreased the accuracy. The overall results indicated that the MARS and LSSVM models could be successfully used in estimating monthly river water pollution level by using AMM, TKN and WT parameters as inputs.

Contrast improvement of continuous wave diffuse optical tomography reconstruction by hybrid approach using least square and genetic algorithm

NASA Astrophysics Data System (ADS)

Patra, Rusha; Dutta, Pranab K.

2015-07-01

Reconstruction of the absorption coefficient of tissue with good contrast is of key importance in functional diffuse optical imaging. A hybrid approach using model-based iterative image reconstruction and a genetic algorithm is proposed to enhance the contrast of the reconstructed image. The proposed method yields an observed contrast of 98.4%, mean square error of 0.638×10-3, and object centroid error of (0.001 to 0.22) mm. Experimental validation of the proposed method has also been provided with tissue-like phantoms which shows a significant improvement in image quality and thus establishes the potential of the method for functional diffuse optical tomography reconstruction with continuous wave setup. A case study of finger joint imaging is illustrated as well to show the prospect of the proposed method in clinical diagnosis. The method can also be applied to the concentration measurement of a region of interest in a turbid medium.

New strategy to identify radicals in a time evolving EPR data set by multivariate curve resolution-alternating least squares.

PubMed

Fadel, Maya Abou; de Juan, Anna; Vezin, Hervé; Duponchel, Ludovic

2016-12-01

Electron paramagnetic resonance (EPR) spectroscopy is a powerful technique that is able to characterize radicals formed in kinetic reactions. However, spectral characterization of individual chemical species is often limited or even unmanageable due to the severe kinetic and spectral overlap among species in kinetic processes. Therefore, we applied, for the first time, multivariate curve resolution-alternating least squares (MCR-ALS) method to EPR time evolving data sets to model and characterize the different constituents in a kinetic reaction. Here we demonstrate the advantage of multivariate analysis in the investigation of radicals formed along the kinetic process of hydroxycoumarin in alkaline medium. Multiset analysis of several EPR-monitored kinetic experiments performed in different conditions revealed the individual paramagnetic centres as well as their kinetic profiles. The results obtained by MCR-ALS method demonstrate its prominent potential in analysis of EPR time evolved spectra. Copyright © 2016 Elsevier B.V. All rights reserved.

Detecting Unobserved Heterogeneity in the Relationship between Subjective Well-Being and Satisfaction in Various Domains of Life Using the REBUS-PLS Path Modelling Approach: A Case Study

ERIC Educational Resources Information Center

Zanin, Luca

2013-01-01

In this article, we propose a model to estimate the direct and indirect effects of the relationship between subjective well-being and satisfaction in various domains of life using a partial least squares path modelling approach in a structural equation model framework. A drawback of these models is that they assume homogeneous behaviour over the…

978-nm square-wave in an all-fiber single-mode ytterbium-doped fiber laser

NASA Astrophysics Data System (ADS)

Li, Shujie; Xu, Lixin; Gu, Chun

2018-01-01

A 978 nm single mode passively mode-locked all-fiber laser delivering square-wave pulses was demonstrated using a figure-8 cavity and a 75 cm commercial double-clad ytterbium-doped fiber. We found the three-level system near 978 nm was able to operate efficiently under clad pumping, simultaneously oscillation around 1030 nm well inhibited. The optimized nonlinear amplifying loop mirror made the mode locking stable and performed the square-pulses shaping. To the best of our knowledge, it is the first time to report the square-wave pulse fiber laser operating at 980 nm. The spectral width of the 978 mode-locked square pulses was about 4 nm, far greater than that of the mode-locked square pulses around 1060 nm reported before, which would be helpful to deeply understand the various square-wave pulses' natures and forming mechanisms. Compared with modulated single-mode or multimode 980 nm LDs, this kind of 980 nm square-wave sources having higher brightness, more steeper rising and falling edge and shorter pulse width, might have potential applications in pumping nanosecond ytterbium or erbium fiber lasers and amplifiers.

Observed tidal braking in the earth/moon/sun system

NASA Technical Reports Server (NTRS)

Christodoulidis, D. C.; Smith, D. E.; Williamson, R. G.; Klosko, S. M.

1988-01-01

The low degree and order terms in the spherical harmonic model of the tidal potential were observed through the perturbations which are induced on near-earth satellite orbital motions. Evaluations of tracking observations from 17 satellites and a GEM-T1 geopotential model were used in the tidal recovery which was made in the presence of over 600 long-wavelength coefficients from 32 major and minor tides. Wahr's earth tidal model was used as a basis for the recovery of the ocean tidal terms. Using this tidal model, the secular change in the moon's mean motion due to tidal dissipation was found to be -25.27 + or - 0.61 arcsec/century-squared. The estimation of lunar acceleration agreed with that observed from lunar laser ranging techniques (-24.9 + or - 1.0 arcsec/century-squared), with the corresponding tidal braking of earth's rotation being -5.98 + or - 0.22 X 10 to the -22 rad/second-squared. If the nontidal braking of the earth due to the observed secular change in the earth's second zonal harmonic is considered, satellite techniques yield a total value of the secular change in the earth's rotation rate of -4.69 + or - 0.36 X 10 to the -22 rad/second-squared.

Modelling of the batch biosorption system: study on exchange of protons with cell wall-bound mineral ions.

PubMed

Mishra, Vishal

2015-01-01

The interchange of the protons with the cell wall-bound calcium and magnesium ions at the interface of solution/bacterial cell surface in the biosorption system at various concentrations of protons has been studied in the present work. A mathematical model for establishing the correlation between concentration of protons and active sites was developed and optimized. The sporadic limited residence time reactor was used to titrate the calcium and magnesium ions at the individual data point. The accuracy of the proposed mathematical model was estimated using error functions such as nonlinear regression, adjusted nonlinear regression coefficient, the chi-square test, P-test and F-test. The values of the chi-square test (0.042-0.017), P-test (<0.001-0.04), sum of square errors (0.061-0.016), root mean square error (0.01-0.04) and F-test (2.22-19.92) reported in the present research indicated the suitability of the model over a wide range of proton concentrations. The zeta potential of the bacterium surface at various concentrations of protons was observed to validate the denaturation of active sites.

Energy Levels in Quantum Wells.

NASA Astrophysics Data System (ADS)

Zang, Jan Xin

Normalized analytical equations for eigenstates of an arbitrary one-dimensional configuration of square potentials in a well have been derived. The general formulation is used to evaluate the energy levels of a particle in a very deep potential well containing seven internal barriers. The configuration can be considered as a finite superlattice sample or as a simplified model for a sample with only several atom layers. The results are shown in graphical forms as functions of the height and width of the potential barriers and as functions of the ratio of the effective mass in barrier to the mass in well. The formation of energy bands and surface eigenstates from eigenstates of a deep single well, the coming close of two energy bands and a surface state which are separate ordinarily, and mixing of the wave function of a surface state with the bulk energy bands are seen. Then the normalized derivation is extended to study the effect of a uniform electric field applied across a one-dimensional well containing an internal configuration of square potentials The general formulation is used to calculate the electric field dependence of the energy levels of a deep well with five internal barriers. Typical results are shown in graphical forms as functions of the barrier height, barrier width, barrier effective mass and the field strength. The formation of Stark ladders and surface states from the eigenstates of a single deep well in an electric field, the localization process of wave functions with changing barrier height, width, and field strength and their anticrossing behaviors are seen. The energy levels of a hydrogenic impurity in a uniform medium and in a uniform magnetic field are calculated with variational methods. The energy eigenvalues for the eigenstates with major quantum number less than or equal to 3 are obtained. The results are consistent with previous results. Furthermore, the energy levels of a hydrogenic impurity at the bottom of a one-dimensional parabolic quantum well with a magnetic field normal to the plane of the well are calculated with the finite-basis-set variational method. The limit of small radial distance and the limit of great radial distance are considered to choose a set of proper basis functions. It is found that the energy levels increase with increasing parabolic parameter alpha and increase with increasing normalized magnetic field strength gamma except those levels with magnetic quantum number m < 0 at small gamma.

Further Development of a Computational Vision Model for the Generation and Analysis of Photo-Realistic Scenes for Military and Civilian Virtual Reality Applications

DTIC Science & Technology

1996-02-01

rectangle in the center of the image straddling the boundary between the foreground grass and background treeline . The synthetic content of the target region...the square in the middle of the grass, the square in the middle of the tree leaves, and the square on the treeline are all synthetic textures. The...target rectangle on the treeline boundary. What was suprising was that the synthetic grass texture was not well matched in the rectangle in the grass

Truncated Calogero-Sutherland models

NASA Astrophysics Data System (ADS)

Pittman, S. M.; Beau, M.; Olshanii, M.; del Campo, A.

2017-05-01

A one-dimensional quantum many-body system consisting of particles confined in a harmonic potential and subject to finite-range two-body and three-body inverse-square interactions is introduced. The range of the interactions is set by truncation beyond a number of neighbors and can be tuned to interpolate between the Calogero-Sutherland model and a system with nearest and next-nearest neighbors interactions discussed by Jain and Khare. The model also includes the Tonks-Girardeau gas describing impenetrable bosons as well as an extension with truncated interactions. While the ground state wave function takes a truncated Bijl-Jastrow form, collective modes of the system are found in terms of multivariable symmetric polynomials. We numerically compute the density profile, one-body reduced density matrix, and momentum distribution of the ground state as a function of the range r and the interaction strength.

Delineation and Prediction Uncertainty of Areas Contributing Recharge to Selected Well Fields in Wetland and Coastal Settings, Southern Rhode Island

USGS Publications Warehouse

Friesz, Paul J.

2010-01-01

Areas contributing recharge to four well fields in two study sites in southern Rhode Island were delineated on the basis of steady-state groundwater-flow models representing average hydrologic conditions. The wells are screened in sand and gravel deposits in wetland and coastal settings. The groundwater-flow models were calibrated by inverse modeling using nonlinear regression. Summary statistics from nonlinear regression were used to evaluate the uncertainty associated with the predicted areas contributing recharge to the well fields. In South Kingstown, two United Water Rhode Island well fields are in Mink Brook watershed and near Worden Pond and extensive wetlands. Wetland deposits of peat near the well fields generally range in thickness from 5 to 8 feet. Analysis of water-level drawdowns in a piezometer screened beneath the peat during a 20-day pumping period indicated vertical leakage and a vertical hydraulic conductivity for the peat of roughly 0.01 ft/d. The simulated area contributing recharge for average withdrawals of 2,138 gallons per minute during 2003-07 extended to groundwater divides in mostly till and morainal deposits, and it encompassed 2.30 square miles. Most of a sand and gravel mining operation between the well fields was in the simulated contributing area. For the maximum pumping capacity (5,100 gallons per minute), the simulated area contributing recharge expanded to 5.54 square miles. The well fields intercepted most of the precipitation recharge in Mink Brook watershed and in an adjacent small watershed, and simulated streams ceased to flow. The simulated contributing area to the well fields included an area beneath Worden Pond and a remote, isolated area in upland till on the opposite side of Worden Pond from the well fields. About 12 percent of the pumped water was derived from Worden Pond. In Charlestown, the Central Beach Fire District and the East Beach Water Association well fields are on a small (0.85 square mile) peninsula in a coastal setting. The wells are screened in a coarse-grained, ice-proximal part of a morphosequence with saturated thicknesses generally less than 30 feet on the peninsula. The simulated area contributing recharge for the average withdrawal (16 gallons per minute) during 2003-07 was 0.018 square mile. The contributing area extended southwestward from the well fields to a simulated groundwater mound; it underlay part of a small nearby wetland, and it included isolated areas on the side of the wetland opposite the well fields. For the maximum pumping rate (230 gallons per minute), the simulated area contributing recharge (0.26 square mile) expanded in all directions; it included a till area on the peninsula, and it underlay part of a nearby pond. Because the well fields are screened in a thin aquifer, simulated groundwater traveltimes from recharge locations to the discharging wells were short: 94 percent of the traveltimes were 10 years or less, and the median traveltime was 1.3 years. Model-prediction uncertainty was evaluated using a Monte Carlo analysis; the parameter variance-covariance matrix from nonlinear regression was used to create parameter sets for the analysis. Important parameters for model prediction that could not be estimated by nonlinear regression were incorporated into the variance-covariance matrix. For the South Kingstown study site, observations provided enough information to constrain the uncertainty of these parameters within realistic ranges, but for the Charlestown study site, prior information on parameters was required. Thus, the uncertainty analysis for the South Kingstown study site was an outcome of calibrating the model to available observations, but the Charlestown study site was also dependent on information provided by the modeler. A water budget and model-fit statistical criteria were used to assess parameter sets so that prediction uncertainty was not overestimated. For the scenarios using maximum pumping rates at both study

Correlation Between Microstructure and Optical Properties of Cu (In0.7, Ga0.3) Se2 Grown by Electrodeposition Technique

NASA Astrophysics Data System (ADS)

Chihi, Adel; Bessais, Brahim

2017-01-01

Polycrystalline thin films Cu (In0.7, Ga0.3) Se2 (CIGSe) were grown on copper foils at various cathodic potentials by using an electrodeposition technique. Scanning electron microscopy showed that the average diameter of CIGSe grains increase from 0.1 μm to 1 μm when the cathodic potential decreases. The structure and surface morphology were investigated by x-ray diffraction and atomic force microscopy (AFM) techniques. This structure study shows that the thin films were well crystallized in a chalcopyrite structure without unwanted secondary phases with a preferred orientation along (112) plane. Energy-dispersive x-ray analyses confirms the existence of CIGSe single phase on a copper substrate. AFM analysis indicated that the root mean square roughness decreases from 64.28 to 27.42 when the potential deposition increases from -0.95 V to -0.77 V. Using Raman scattering spectroscopy, the A1 optical phonon mode was observed in 173 cm-1 and two other weak peaks were detected at 214 cm-1 and 225 cm-1 associated with the B2 and E modes of the CIGSe phase. Through spectroscopy ellipsometry analysis, a three-layer optical model was exploited to derive the optical properties and layer thickness of the CIGSe film by least-squares fitting the measured variation in polarization light versus the obtained microstructure.

Muscle contraction during electro-muscular incapacitation: A comparison between square-wave pulses and the TASER(®) X26 Electronic control device.

PubMed

Comeaux, James A; Jauchem, James R; Cox, D Duane; Crane, Carrie C; D'Andrea, John A

2011-01-01

Electronic control devices (including the Advanced TASER(®) X26 model produced by TASER International) incapacitate individuals by causing muscle contractions. To provide information relevant to development of future potential devices, effects of monophasic square waves with different parameters were compared with those of the X26 electronic control device, using two animal models (frogs and swine). Pulse power, electrical pulse charge, pulse duration, and pulse repetition frequency affected muscle contraction. There was no difference in the charge required, between the square waveform and the X26 waveform, to cause approximately the same muscle-contraction response (in terms of the strength-duration curve). Thus, on the basis of these initial studies, the detailed shape of a waveform may not be important in terms of generating electro-muscular incapacitation. More detailed studies, however, may be required to thoroughly test all potential waveforms to be considered for future use in ECDs. 2010 American Academy of Forensic Sciences. Published 2010. This article is a U.S. Government work and is in the public domain in the U.S.A.

Hydraulic characterization of volcanic rocks in Pahute Mesa using an integrated analysis of 16 multiple-well aquifer tests, Nevada National Security Site, 2009–14

USGS Publications Warehouse

Garcia, C. Amanda; Jackson, Tracie R.; Halford, Keith J.; Sweetkind, Donald S.; Damar, Nancy A.; Fenelon, Joseph M.; Reiner, Steven R.

2017-01-20

An improved understanding of groundwater flow and radionuclide migration downgradient from underground nuclear-testing areas at Pahute Mesa, Nevada National Security Site, requires accurate subsurface hydraulic characterization. To improve conceptual models of flow and transport in the complex hydrogeologic system beneath Pahute Mesa, the U.S. Geological Survey characterized bulk hydraulic properties of volcanic rocks using an integrated analysis of 16 multiple-well aquifer tests. Single-well aquifer-test analyses provided transmissivity estimates at pumped wells. Transmissivity estimates ranged from less than 1 to about 100,000 square feet per day in Pahute Mesa and the vicinity. Drawdown from multiple-well aquifer testing was estimated and distinguished from natural fluctuations in more than 200 pumping and observation wells using analytical water-level models. Drawdown was detected at distances greater than 3 miles from pumping wells and propagated across hydrostratigraphic units and major structures, indicating that neither faults nor structural blocks noticeably impede or divert groundwater flow in the study area.Consistent hydraulic properties were estimated by simultaneously interpreting drawdown from the 16 multiple-well aquifer tests with an integrated groundwater-flow model composed of 11 well-site models—1 for each aquifer test site. Hydraulic properties were distributed across volcanic rocks with the Phase II Pahute Mesa-Oasis Valley Hydrostratigraphic Framework Model. Estimated hydraulic-conductivity distributions spanned more than two orders of magnitude in hydrostratigraphic units. Overlapping hydraulic conductivity ranges among units indicated that most Phase II Hydrostratigraphic Framework Model units were not hydraulically distinct. Simulated total transmissivity ranged from 1,600 to 68,000 square feet per day for all pumping wells analyzed. High-transmissivity zones exceeding 10,000 square feet per day exist near caldera margins and extend along the northern and eastern Pahute Mesa study area and near the southwestern edge of the study area. The estimated hydraulic-property distributions and observed hydraulic connections among geologic structures improved the characterization and representation of groundwater flow at Pahute Mesa.

Mapping and Analysis of Forest and Land Fire Potential Using Geospatial Technology and Mathematical Modeling

NASA Astrophysics Data System (ADS)

Suliman, M. D. H.; Mahmud, M.; Reba, M. N. M.; S, L. W.

2014-02-01

Forest and land fire can cause negative implications for forest ecosystems, biodiversity, air quality and soil structure. However, the implications involved can be minimized through effective disaster management system. Effective disaster management mechanisms can be developed through appropriate early warning system as well as an efficient delivery system. This study tried to focus on two aspects, namely by mapping the potential of forest fire and land as well as the delivery of information to users through WebGIS application. Geospatial technology and mathematical modeling used in this study for identifying, classifying and mapping the potential area for burning. Mathematical models used is the Analytical Hierarchy Process (AHP), while Geospatial technologies involved include remote sensing, Geographic Information System (GIS) and digital field data collection. The entire Selangor state was chosen as our study area based on a number of cases have been reported over the last two decades. AHP modeling to assess the comparison between the three main criteria of fuel, topography and human factors design. Contributions of experts directly involved in forest fire fighting operations and land comprising officials from the Fire and Rescue Department Malaysia also evaluated in this model. The study found that about 32.83 square kilometers of the total area of Selangor state are the extreme potential for fire. Extreme potential areas identified are in Bestari Jaya and Kuala Langat High Ulu. Continuity of information and terrestrial forest fire potential was displayed in WebGIS applications on the internet. Display information through WebGIS applications is a better approach to help the decision-making process at a high level of confidence and approximate real conditions. Agencies involved in disaster management such as Jawatankuasa Pengurusan Dan Bantuan Bencana (JPBB) of District, State and the National under the National Security Division and the Fire and Rescue Department Malaysia can use the end result of this study in preparation for the land and forest fires in the future.

[Study on the detection of active ingredient contents of Paecilomyces hepiali mycelium via near infrared spectroscopy].

PubMed

Teng, Wei-Zhuo; Song, Jia; Meng, Fan-Xin; Meng, Qing-Fan; Lu, Jia-Hui; Hu, Shuang; Teng, Li-Rong; Wang, Di; Xie, Jing

2014-10-01

Partial least squares (PLS) and radial basis function neural network (RBFNN) combined with near infrared spectros- copy (NIR) were applied to develop models for cordycepic acid, polysaccharide and adenosine analysis in Paecilomyces hepialid fermentation mycelium. The developed models possess well generalization and predictive ability which can be applied for crude drugs and related productions determination. During the experiment, 214 Paecilomyces hepialid mycelium samples were obtained via chemical mutagenesis combined with submerged fermentation. The contents of cordycepic acid, polysaccharide and adenosine were determined via traditional methods and the near infrared spectroscopy data were collected. The outliers were removed and the numbers of calibration set were confirmed via Monte Carlo partial least square (MCPLS) method. Based on the values of degree of approach (Da), both moving window partial least squares (MWPLS) and moving window radial basis function neural network (MWRBFNN) were applied to optimize characteristic wavelength variables, optimum preprocessing methods and other important variables in the models. After comparison, the RBFNN, RBFNN and PLS models were developed successfully for cordycepic acid, polysaccharide and adenosine detection, and the correlation between reference values and predictive values in both calibration set (R2c) and validation set (R2p) of optimum models was 0.9417 and 0.9663, 0.9803 and 0.9850, and 0.9761 and 0.9728, respectively. All the data suggest that these models possess well fitness and predictive ability.

Numerical modelling of rapid, flow-like landslides across 3-D terrains: a Tsunami Squares approach to El Picacho landslide, El Salvador, September 19, 1982

NASA Astrophysics Data System (ADS)

Wang, Jiajia; Ward, Steven N.; Xiao, Lili

2015-06-01

Flow-like landslides are rapidly moving fluid-solid mixtures that can cause significant destruction along paths that run far from their original sources. Existing models for run out prediction and motion simulation of flow-like landslides have many limitations. In this paper, we develop a new method named `Tsunami Squares' to simulate the generation, propagation and stoppage of flow-like landslides based on conservation of volume and momentum. Landslide materials in the new method form divisible squares that are displaced, then further fractured. The squares move under the influence of gravity-driven acceleration and suffer decelerations due to basal and dynamic frictions. Distinctively, this method takes into account solid and fluid mechanics, particle interactions and flow regime transitions. We apply this approach to simulate the 1982 El Picacho landslide in San Salvador, capital city of El Salvador. Landslide products from Tsunami Squares such as run out distance, velocities, erosion and deposition depths and impacted area agree well with field investigated and eyewitness data.

An empirical test of Lanchester's square law: mortality during battles of the fire ant Solenopsis invicta

PubMed Central

Plowes, Nicola J.R; Adams, Eldridge S

2005-01-01

Lanchester's models of attrition describe casualty rates during battles between groups as functions of the numbers of individuals and their fighting abilities. Originally developed to describe human warfare, Lanchester's square law has been hypothesized to apply broadly to social animals as well, with important consequences for their aggressive behaviour and social structure. According to the square law, the fighting ability of a group is proportional to the square of the number of individuals, but rises only linearly with fighting ability of individuals within the group. By analyzing mortality rates of fire ants (Solenopsis invicta) fighting in different numerical ratios, we provide the first quantitative test of Lanchester's model for a non-human animal. Casualty rates of fire ants were not consistent with the square law; instead, group fighting ability was an approximately linear function of group size. This implies that the relative numbers of casualties incurred by two fighting groups are not strongly affected by relative group sizes and that battles do not disproportionately favour group size over individual prowess. PMID:16096093

Simulation-Based Approach to Determining Electron Transfer Rates Using Square-Wave Voltammetry.

PubMed

Dauphin-Ducharme, Philippe; Arroyo-Currás, Netzahualcóyotl; Kurnik, Martin; Ortega, Gabriel; Li, Hui; Plaxco, Kevin W

2017-05-09

The efficiency with which square-wave voltammetry differentiates faradic and charging currents makes it a particularly sensitive electroanalytical approach, as evidenced by its ability to measure nanomolar or even picomolar concentrations of electroactive analytes. Because of the relative complexity of the potential sweep it uses, however, the extraction of detailed kinetic and mechanistic information from square-wave data remains challenging. In response, we demonstrate here a numerical approach by which square-wave data can be used to determine electron transfer rates. Specifically, we have developed a numerical approach in which we model the height and the shape of voltammograms collected over a range of square-wave frequencies and amplitudes to simulated voltammograms as functions of the heterogeneous rate constant and the electron transfer coefficient. As validation of the approach, we have used it to determine electron transfer kinetics in both freely diffusing and diffusionless surface-tethered species, obtaining electron transfer kinetics in all cases in good agreement with values derived using non-square-wave methods.

Calibration and compensation method of three-axis geomagnetic sensor based on pre-processing total least square iteration

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhang, X.; Xiao, W.

2018-04-01

As the geomagnetic sensor is susceptible to interference, a pre-processing total least square iteration method is proposed for calibration compensation. Firstly, the error model of the geomagnetic sensor is analyzed and the correction model is proposed, then the characteristics of the model are analyzed and converted into nine parameters. The geomagnetic data is processed by Hilbert transform (HHT) to improve the signal-to-noise ratio, and the nine parameters are calculated by using the combination of Newton iteration method and the least squares estimation method. The sifter algorithm is used to filter the initial value of the iteration to ensure that the initial error is as small as possible. The experimental results show that this method does not need additional equipment and devices, can continuously update the calibration parameters, and better than the two-step estimation method, it can compensate geomagnetic sensor error well.

Assessing statistical differences between parameters estimates in Partial Least Squares path modeling.

PubMed

Rodríguez-Entrena, Macario; Schuberth, Florian; Gelhard, Carsten

2018-01-01

Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess differences between parameters that are estimated for different subpopulations, the study at hand introduces a technique that allows to also assess whether two parameter estimates that are derived from the same sample are statistically different. To illustrate this advancement to PLS-SEM, we particularly refer to a reduced version of the well-established technology acceptance model.

A Study on the Stream Cipher Embedded Magic Square of Random Access Files

NASA Astrophysics Data System (ADS)

Liu, Chenglian; Zhao, Jian-Ming; Rafsanjani, Marjan Kuchaki; Shen, Yijuan

2011-09-01

Magic square and stream cipher issues are both interesting and well-tried topics. In this paper, we are proposing a new scheme which streams cipher applications for random access files based on the magic square method. There are two thresholds required to secure our data, if using only decrypts by the stream cipher. It isn't to recovery original source. On other hand, we improve the model of cipher stream to strengthen and defend efficiently; it also was its own high speed and calculates to most parts of the key stream generator.

Filter Tuning Using the Chi-Squared Statistic

NASA Technical Reports Server (NTRS)

Lilly-Salkowski, Tyler B.

2017-01-01

This paper examines the use of the Chi-square statistic as a means of evaluating filter performance. The goal of the process is to characterize the filter performance in the metric of covariance realism. The Chi-squared statistic is the value calculated to determine the realism of a covariance based on the prediction accuracy and the covariance values at a given point in time. Once calculated, it is the distribution of this statistic that provides insight on the accuracy of the covariance. The process of tuning an Extended Kalman Filter (EKF) for Aqua and Aura support is described, including examination of the measurement errors of available observation types, and methods of dealing with potentially volatile atmospheric drag modeling. Predictive accuracy and the distribution of the Chi-squared statistic, calculated from EKF solutions, are assessed.

Anharmonic Normal Mode Analysis of Elastic Network Model Improves the Modeling of Atomic Fluctuations in Protein Crystal Structures

PubMed Central

Zheng, Wenjun

2010-01-01

Abstract Protein conformational dynamics, despite its significant anharmonicity, has been widely explored by normal mode analysis (NMA) based on atomic or coarse-grained potential functions. To account for the anharmonic aspects of protein dynamics, this study proposes, and has performed, an anharmonic NMA (ANMA) based on the Cα-only elastic network models, which assume elastic interactions between pairs of residues whose Cα atoms or heavy atoms are within a cutoff distance. The key step of ANMA is to sample an anharmonic potential function along the directions of eigenvectors of the lowest normal modes to determine the mean-squared fluctuations along these directions. ANMA was evaluated based on the modeling of anisotropic displacement parameters (ADPs) from a list of 83 high-resolution protein crystal structures. Significant improvement was found in the modeling of ADPs by ANMA compared with standard NMA. Further improvement in the modeling of ADPs is attained if the interactions between a protein and its crystalline environment are taken into account. In addition, this study has determined the optimal cutoff distances for ADP modeling based on elastic network models, and these agree well with the peaks of the statistical distributions of distances between Cα atoms or heavy atoms derived from a large set of protein crystal structures. PMID:20550915

A Conditionally Integrable Bi-confluent Heun Potential Involving Inverse Square Root and Centrifugal Barrier Terms

NASA Astrophysics Data System (ADS)

Ishkhanyan, Tigran A.; Krainov, Vladimir P.; Ishkhanyan, Artur M.

2018-05-01

We present a conditionally integrable potential, belonging to the bi-confluent Heun class, for which the Schrödinger equation is solved in terms of the confluent hypergeometric functions. The potential involves an attractive inverse square root term x-1/2 with arbitrary strength and a repulsive centrifugal barrier core x-2 with the strength fixed to a constant. This is a potential well defined on the half-axis. Each of the fundamental solutions composing the general solution of the Schrödinger equation is written as an irreducible linear combination, with non-constant coefficients, of two confluent hypergeometric functions. We present the explicit solution in terms of the non-integer order Hermite functions of scaled and shifted argument and discuss the bound states supported by the potential. We derive the exact equation for the energy spectrum and approximate that by a highly accurate transcendental equation involving trigonometric functions. Finally, we construct an accurate approximation for the bound-state energy levels.

Linking parasite populations in hosts to parasite populations in space through Taylor's law and the negative binomial distribution

PubMed Central

Poulin, Robert; Lagrue, Clément

2017-01-01

The spatial distribution of individuals of any species is a basic concern of ecology. The spatial distribution of parasites matters to control and conservation of parasites that affect human and nonhuman populations. This paper develops a quantitative theory to predict the spatial distribution of parasites based on the distribution of parasites in hosts and the spatial distribution of hosts. Four models are tested against observations of metazoan hosts and their parasites in littoral zones of four lakes in Otago, New Zealand. These models differ in two dichotomous assumptions, constituting a 2 × 2 theoretical design. One assumption specifies whether the variance function of the number of parasites per host individual is described by Taylor's law (TL) or the negative binomial distribution (NBD). The other assumption specifies whether the numbers of parasite individuals within each host in a square meter of habitat are independent or perfectly correlated among host individuals. We find empirically that the variance–mean relationship of the numbers of parasites per square meter is very well described by TL but is not well described by NBD. Two models that posit perfect correlation of the parasite loads of hosts in a square meter of habitat approximate observations much better than two models that posit independence of parasite loads of hosts in a square meter, regardless of whether the variance–mean relationship of parasites per host individual obeys TL or NBD. We infer that high local interhost correlations in parasite load strongly influence the spatial distribution of parasites. Local hotspots could influence control and conservation of parasites. PMID:27994156

Investigating bias in squared regression structure coefficients

PubMed Central

Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce

2015-01-01

The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients. PMID:26217273

Consistency Between Sun-Induced Chlorophyll Fluorescence and Gross Primary Production of Vegetation in North America

NASA Technical Reports Server (NTRS)

Zhang, Yao; Xiao, Xiangming; Jin, Cui; Dong, Jinwei; Zhou, Sha; Wagle, Pradeep; Joiner, Joanna; Guanter, Luis; Zhang, Yongguang; Zhang , Geli;

Observed tidal braking in the earth/moon/sun system

NASA Technical Reports Server (NTRS)

Christodoulidis, D. C.; Smith, D. E.; Williamson, R. G.; Klosko, S. M.

1987-01-01

The low degree and order terms in the spherical harmonic model of the tidal potential were observed through the perturbations which are induced on near-earth satellite orbital motions. Evaluations of tracking observations from 17 satellites and a GEM-T1 geopotential model were used in the tidal recovery which was made in the presence of over 600 long-wavelength coefficients from 32 major and minor tides. Wahr's earth tidal model was used as a basis for the recovery of the ocean tidal terms. Using this tidal model, the secular change in the moon's mean motion due to tidal dissipation was found to be -25.27 + or - 0.61 arcsec/century squared. The estimation of lunar acceleration agreed with that observed from lunar laser ranging techniques (-24.9 + or - 1.0 arcsec/century squared), with the corresponding tidal braking of earth's rotation being -5.98 + or - 0.22 x 10 to the minus 22 rad/second squared. If the nontidal braking of the earth due to the observed secular change in the earth's second zonal harmonic is considered, satellite techniques yield a total value of the secular change of the earth's rotation rate of -4.69 + or - 0.36 x 10 to the minus 22 rad/second squared.

Linear mixing model applied to coarse resolution satellite data

NASA Technical Reports Server (NTRS)

Holben, Brent N.; Shimabukuro, Yosio E.

1992-01-01

A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.

Annual updating of plantation inventory estimates using hybrid models

Treesearch

Peter Snowdon

2000-01-01

Data for Pinus radiata D. Don grown in the Australian Capital Territory (ACT) are used to show that annual indices of growth potential can be successfully incorporated into Schumacher projection models of stand basal area growth. Significant reductions in the error mean squares of the models can be obtained by including an annual growth index derived...

Impact of defects on percolation in random sequential adsorption of linear k-mers on square lattices.

PubMed

Tarasevich, Yuri Yu; Laptev, Valeri V; Vygornitskii, Nikolai V; Lebovka, Nikolai I

2015-01-01

The effect of defects on the percolation of linear k-mers (particles occupying k adjacent sites) on a square lattice is studied by means of Monte Carlo simulation. The k-mers are deposited using a random sequential adsorption mechanism. Two models L(d) and K(d) are analyzed. In the L(d) model it is assumed that the initial square lattice is nonideal and some fraction of sites d is occupied by nonconducting point defects (impurities). In the K(d) model the initial square lattice is perfect. However, it is assumed that some fraction of the sites in the k-mers d consists of defects, i.e., is nonconducting. The length of the k-mers k varies from 2 to 256. Periodic boundary conditions are applied to the square lattice. The dependences of the percolation threshold concentration of the conducting sites p(c) vs the concentration of defects d are analyzed for different values of k. Above some critical concentration of defects d(m), percolation is blocked in both models, even at the jamming concentration of k-mers. For long k-mers, the values of d(m) are well fitted by the functions d(m)∝k(m)(-α)-k(-α) (α=1.28±0.01 and k(m)=5900±500) and d(m)∝log(10)(k(m)/k) (k(m)=4700±1000) for the L(d) and K(d) models, respectively. Thus, our estimation indicates that the percolation of k-mers on a square lattice is impossible even for a lattice without any defects if k⪆6×10(3).

Study of cluster formation in a quasi-square well model of Janus ellipsoids

NASA Astrophysics Data System (ADS)

Ruth, Donovan; Rickman, Jeffrey; Gunton, James; Li, Wei

2014-03-01

We investigate the effect of geometry and range of attractive interaction on the self-assembly of Janus particles. In particular, we consider Janus spheroids with an aspect ratio of 0.6 and a quasi-square well model with a short range attractive interaction of 0.2 sigma where sigma is the characteristic length of the spheroid. We find that below a certain transition temperature the system forms orientationally ordered micelles and vesicles, with a cluster distribution qualitatively similar to that found in an earlier study of Janus spheres. (Phys. Chem. Chem. Phys. (2010) vol 12, 11869-11877, F. Sciortino, A. Giacometti and G. Pastore) Finally we discuss the implications of our work for encapsulation by self-assembly. Acknowledgement: This work was supported by a grant from the Mathers Foundation.

A fast least-squares algorithm for population inference

PubMed Central

2013-01-01

Background Population inference is an important problem in genetics used to remove population stratification in genome-wide association studies and to detect migration patterns or shared ancestry. An individual’s genotype can be modeled as a probabilistic function of ancestral population memberships, Q, and the allele frequencies in those populations, P. The parameters, P and Q, of this binomial likelihood model can be inferred using slow sampling methods such as Markov Chain Monte Carlo methods or faster gradient based approaches such as sequential quadratic programming. This paper proposes a least-squares simplification of the binomial likelihood model motivated by a Euclidean interpretation of the genotype feature space. This results in a faster algorithm that easily incorporates the degree of admixture within the sample of individuals and improves estimates without requiring trial-and-error tuning. Results We show that the expected value of the least-squares solution across all possible genotype datasets is equal to the true solution when part of the problem has been solved, and that the variance of the solution approaches zero as its size increases. The Least-squares algorithm performs nearly as well as Admixture for these theoretical scenarios. We compare least-squares, Admixture, and FRAPPE for a variety of problem sizes and difficulties. For particularly hard problems with a large number of populations, small number of samples, or greater degree of admixture, least-squares performs better than the other methods. On simulated mixtures of real population allele frequencies from the HapMap project, Admixture estimates sparsely mixed individuals better than Least-squares. The least-squares approach, however, performs within 1.5% of the Admixture error. On individual genotypes from the HapMap project, Admixture and least-squares perform qualitatively similarly and within 1.2% of each other. Significantly, the least-squares approach nearly always converges 1.5- to 6-times faster. Conclusions The computational advantage of the least-squares approach along with its good estimation performance warrants further research, especially for very large datasets. As problem sizes increase, the difference in estimation performance between all algorithms decreases. In addition, when prior information is known, the least-squares approach easily incorporates the expected degree of admixture to improve the estimate. PMID:23343408

A fast least-squares algorithm for population inference.

PubMed

Parry, R Mitchell; Wang, May D

2013-01-23

Population inference is an important problem in genetics used to remove population stratification in genome-wide association studies and to detect migration patterns or shared ancestry. An individual's genotype can be modeled as a probabilistic function of ancestral population memberships, Q, and the allele frequencies in those populations, P. The parameters, P and Q, of this binomial likelihood model can be inferred using slow sampling methods such as Markov Chain Monte Carlo methods or faster gradient based approaches such as sequential quadratic programming. This paper proposes a least-squares simplification of the binomial likelihood model motivated by a Euclidean interpretation of the genotype feature space. This results in a faster algorithm that easily incorporates the degree of admixture within the sample of individuals and improves estimates without requiring trial-and-error tuning. We show that the expected value of the least-squares solution across all possible genotype datasets is equal to the true solution when part of the problem has been solved, and that the variance of the solution approaches zero as its size increases. The Least-squares algorithm performs nearly as well as Admixture for these theoretical scenarios. We compare least-squares, Admixture, and FRAPPE for a variety of problem sizes and difficulties. For particularly hard problems with a large number of populations, small number of samples, or greater degree of admixture, least-squares performs better than the other methods. On simulated mixtures of real population allele frequencies from the HapMap project, Admixture estimates sparsely mixed individuals better than Least-squares. The least-squares approach, however, performs within 1.5% of the Admixture error. On individual genotypes from the HapMap project, Admixture and least-squares perform qualitatively similarly and within 1.2% of each other. Significantly, the least-squares approach nearly always converges 1.5- to 6-times faster. The computational advantage of the least-squares approach along with its good estimation performance warrants further research, especially for very large datasets. As problem sizes increase, the difference in estimation performance between all algorithms decreases. In addition, when prior information is known, the least-squares approach easily incorporates the expected degree of admixture to improve the estimate.

Geohydrology and water quality of stratified-drift aquifers in the lower Merrimack and coastal river basins, southeastern New Hampshire

USGS Publications Warehouse

Stekl, Peter J.; Flanagan, Sarah M.

1992-01-01

Communities in the lower Merrimack River basin and coastal river basins of southeastern New Hampshire are experiencing increased demands for water because of a rapid increase in population. The population in 1987 was 225,495 and is expected to increase by 30 percent during the next decade. As of 1987, five towns used the stratified-drift aquifers for municipal supply and withdrew an estimated 6 million gallons per day. Four towns used the bedrock aquifer for municipal supply and withdrew an average of 1 .6 million gallons per day. Stratified-drift deposits cover 78 of the 327 square miles of the study area. These deposits are generally less than 10 square miles in areal extent, and their saturated thickness ranges front less than 20 feet to as much as 100 feet . Transinissivity exceeds 4,000 square feet per day in several locations. Stratified-drift aquifers in the eastern part are predominantly small ice-contact deposits surrounded by marine sediments or till of low hydraulic conductivity. Stratified-drift aquifers in the western part consist of ice-contact and proglacial deposits that are large in areal extent and are commonly in contact with surface-water bodies. Five stratified-drift aquifers, in the towns of Derry, Windham, Kingston, North Hampton, and Greenland, have the greatest potential to supply additional amounts of water. Potential yields and contributing areas of hypothetical supply wells were estimated for an aquifer in Windham near Cobbetts Pond and for an aquifer in Kingston along the Powwow River by use of a method analogous to superposition in conjunction with a numerical ground-waterflow model. The potential yield is estimated to be 0 .6 million gallons per day for the Windham-Cobbetts Pond aquifer and 4 .0 million gallons per day for the Kingston-Powwow River aquifer. Contributing recharge area for supply wells is estimated to be 1.6 square miles in the Windham-Cobbetts Pond aquifer and 4.9 square miles in the Kingston-Powwow River aquifer. Analyses of water samples from 30 wells indicate that the water quality in the basins studied is generally suitable for drinking and other domestic purposes. Concentrations of iron and manganese exceeded the U.S . Environmental Protection Agency's (USEPA) and the New Hampshire Water Supply Engineering Bureau's secondary maximum contaminant levels for drinking water in 20 samples. With one exception, concentrations of volatile organic compounds at all wells sampled met New Hampshire Water Supply and Engineering Bureau's drinking-water standards. At one well, trichloroethylene was detected at a concentration of 5.7 micrograms per liter. Ground-water contamination has been detected at several hazardous-waste sites in the study area. Currently, 5 sites are on the USEPA's National Priority List of superfund sites, 10 sites are Resource Conservation and Recovery Act of 1976 sites, and 1 site is a Department of Defense hazardous-waste site of stratigraphic layers is a product of a material's density and the velocity at which sound travels through that material . The reflected signals return to the hydrophones at the water surface and are then filtered, amplified, and displayed graphically on the chart recorder to allow interpretation of aquifer stratigraphy and bedrock depths. Lithologic data from nearby wells and test holes were used as control points to check the interpretation of the reflection profiles. Test drilling was done at 66 locations (pls . 1-3) to determine sediment grain size, stratigraphy, depth to water table, depth to bedrock, and ground water quality . A 6-inch-diameter, hollow-stem auger was used for test drilling . Split-spoon samples of subsurface materials collected at specific depths were used to evaluate the grain-size characteristics and identify the stratigraphic sequence of materials comprising the aquifers . Thirty-eight test holes cased with a 2-inch-diameter polyvinyl-chloride (PVC) pipe and slotted screens were used to make ground-water-level measurements and collect ground-water-quality samples. Surface-water-discharge measurements were made at 16 sites during low flow when the surface water is primarily ground-water discharge . These low-flow measurements indicate quantities of ground water potentially available from aquifers. Hydraulic conductivities of aquifer materials were estimated from grain-size-distribution data from 61 samples of stratified drift . Transmissivity was estimated from well logs by assigning hydraulic conductivity to specific well-log intervals, multiplying by the saturated thickness of the interval, and summing the results . Additional transmissivity values were obtained from an analysis of specific capacity and aquifer-test data. Long-term aquifer yields and contributing areas to hypothetical supply wells were estimated by application of a method that is analogous to super position and incorporates a ground-water-flow model developed by McDonald and Harbaugh (1988) . This method was applied to two aquifers judged to have the best potential for providing additional ground-water supplies. Samples of ground water from 26 test wells and 4 municipal wells were collected in March and August 1987 for analysis of common inorganic, organic, and volatile organic constituents. Methods for collecting and analyzing the samples are described by Fishman and Freidman (1989) . The water-quality results from the well samples were used to characterize background water quality in the stratified-drift aquifers.

Connectivity percolation in suspensions of attractive square-well spherocylinders.

PubMed

Dixit, Mohit; Meyer, Hugues; Schilling, Tanja

2016-01-01

We have studied the connectivity percolation transition in suspensions of attractive square-well spherocylinders by means of Monte Carlo simulation and connectedness percolation theory. In the 1980s the percolation threshold of slender fibers has been predicted to scale as the fibers' inverse aspect ratio [Phys. Rev. B 30, 3933 (1984)PRBMDO1098-012110.1103/PhysRevB.30.3933]. The main finding of our study is that the attractive spherocylinder system reaches this inverse scaling regime at much lower aspect ratios than found in suspensions of hard spherocylinders. We explain this difference by showing that third virial corrections of the pair connectedness functions, which are responsible for the deviation from the scaling regime, are less important for attractive potentials than for hard particles.

Dimensional Analysis and Electric Potential Due to a Uniformly Charged Sheet

ERIC Educational Resources Information Center

Aghamohammadi, Amir

2011-01-01

Dimensional analysis, superposition principle, and continuity of electric potential are used to study the electric potential of a uniformly charged square sheet on its plane. It is shown that knowing the electric potential on the diagonal and inside the square sheet is equivalent to knowing it everywhere on the plane of the square sheet. The…

Physiologically grounded metrics of model skill: a case study estimating heat stress in intertidal populations

PubMed Central

Kish, Nicole E.; Helmuth, Brian; Wethey, David S.

2016-01-01

Models of ecological responses to climate change fundamentally assume that predictor variables, which are often measured at large scales, are to some degree diagnostic of the smaller-scale biological processes that ultimately drive patterns of abundance and distribution. Given that organisms respond physiologically to stressors, such as temperature, in highly non-linear ways, small modelling errors in predictor variables can potentially result in failures to predict mortality or severe stress, especially if an organism exists near its physiological limits. As a result, a central challenge facing ecologists, particularly those attempting to forecast future responses to environmental change, is how to develop metrics of forecast model skill (the ability of a model to predict defined events) that are biologically meaningful and reflective of underlying processes. We quantified the skill of four simple models of body temperature (a primary determinant of physiological stress) of an intertidal mussel, Mytilus californianus, using common metrics of model performance, such as root mean square error, as well as forecast verification skill scores developed by the meteorological community. We used a physiologically grounded framework to assess each model's ability to predict optimal, sub-optimal, sub-lethal and lethal physiological responses. Models diverged in their ability to predict different levels of physiological stress when evaluated using skill scores, even though common metrics, such as root mean square error, indicated similar accuracy overall. Results from this study emphasize the importance of grounding assessments of model skill in the context of an organism's physiology and, especially, of considering the implications of false-positive and false-negative errors when forecasting the ecological effects of environmental change. PMID:27729979

Single ion dynamics in molten sodium bromide

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

Alcaraz, O.; Trullas, J.; Demmel, F.

We present a study on the single ion dynamics in the molten alkali halide NaBr. Quasielastic neutron scattering was employed to extract the self-diffusion coefficient of the sodium ions at three temperatures. Molecular dynamics simulations using rigid and polarizable ion models have been performed in parallel to extract the sodium and bromide single dynamics and ionic conductivities. Two methods have been employed to derive the ion diffusion, calculating the mean squared displacements and the velocity autocorrelation functions, as well as analysing the increase of the line widths of the self-dynamic structure factors. The sodium diffusion coefficients show a remarkable goodmore » agreement between experiment and simulation utilising the polarisable potential.« less

Limitations of the method of complex basis functions

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

Baumel, R.T.; Crocker, M.C.; Nuttall, J.

1975-08-01

The method of complex basis functions proposed by Rescigno and Reinhardt is applied to the calculation of the amplitude in a model problem which can be treated analytically. It is found for an important class of potentials, including some of infinite range and also the square well, that the method does not provide a converging sequence of approximations. However, in some cases, approximations of relatively low order might be close to the correct result. The method is also applied to S-wave e-H elastic scattering above the ionization threshold, and spurious ''convergence'' to the wrong result is found. A procedure whichmore » might overcome the difficulties of the method is proposed.« less

Results of a strategic science study to inform policies targeting extreme thinness standards in the fashion industry.

PubMed

Rodgers, Rachel F; Ziff, Sara; Lowy, Alice S; Yu, Kimberly; Austin, S Bryn

2017-03-01

The appearance pressures experienced by fashion models have been criticized as harmful to their health, as well as increasing eating disorder risk among youth by promoting ideals of extreme thinness. Given recent legislation to protect models, we undertook a strategic science study to assess professional fashion models' perceptions of the potential impact and feasibility of seven policy proposals. A sample of 85 female fashion models, mean age = 22.7 years (SD 3.7) completed an online survey assessing unhealthy weight control behaviors (UWCB), perceived pressure from agencies to lose weight, as well as the perceived impact and feasibility of seven potential policy actions. Chi-squared analyses and multivariable logistic regressions compared UWCB among models who were asked to lose weight and those who were not. Friedman and Kendall's W tests were conducted to examine differences in impact and feasibility ratings across the seven policy proposals. Models reported high levels of pressure to lose weight, which was associated with higher odds of engaging in UWCB. The policy approaches rated as most impactful were those to increase worker protections, though they were rated as only moderately feasible. Requiring employers to provide food and a 30-min break for jobs longer than 6 h was rated as both impactful and feasible. Imposing restrictions on minimum BMI was rated as the least impactful. Approaches providing employment protections and healthier working conditions are most supported by professional models. These findings help to illuminate viable policy approaches from the perspective of key stakeholders. © 2017 Wiley Periodicals, Inc.

Proposal and application of a regional methodology of comparative risk assessment for potentially contaminated sites.

PubMed

Marzocchini, Manrico; Tatàno, Fabio; Moretti, Michela Simona; Antinori, Caterina; Orilisi, Stefano

2018-06-05

A possible approach for determining soil and groundwater quality criteria for contaminated sites is the comparative risk assessment. Originating from but not limited to Italian interest in a decentralised (regional) implementation of comparative risk assessment, this paper first addresses the proposal of an original methodology called CORIAN REG-M , which was created with initial attention to the context of potentially contaminated sites in the Marche Region (Central Italy). To deepen the technical-scientific knowledge and applicability of the comparative risk assessment, the following characteristics of the CORIAN REG-M methodology appear to be relevant: the simplified but logical assumption of three categories of factors (source and transfer/transport of potential contamination, and impacted receptors) within each exposure pathway; the adaptation to quality and quantity of data that are available or derivable at the given scale of concern; the attention to a reliable but unsophisticated modelling; the achievement of a conceptual linkage to the absolute risk assessment approach; and the potential for easy updating and/or refining of the methodology. Further, the application of the CORIAN REG-M methodology to some case-study sites located in the Marche Region indicated the following: a positive correlation can be expected between air and direct contact pathway scores, as well as between individual pathway scores and the overall site scores based on a root-mean-square algorithm; the exposure pathway, which presents the highest variability of scores, tends to be dominant at sites with the highest computed overall site scores; and the adoption of a root-mean-square algorithm can be expected to emphasise the overall site scoring.

Small-scale (flash) flood early warning in the light of operational requirements: opportunities and limits with regard to user demands, driving data, and hydrologic modeling techniques

NASA Astrophysics Data System (ADS)

Philipp, Andy; Kerl, Florian; Büttner, Uwe; Metzkes, Christine; Singer, Thomas; Wagner, Michael; Schütze, Niels

2016-05-01

In recent years, the Free State of Saxony (Eastern Germany) was repeatedly hit by both extensive riverine flooding, as well as flash flood events, emerging foremost from convective heavy rainfall. Especially after a couple of small-scale, yet disastrous events in 2010, preconditions, drivers, and methods for deriving flash flood related early warning products are investigated. This is to clarify the feasibility and the limits of envisaged early warning procedures for small catchments, hit by flashy heavy rain events. Early warning about potentially flash flood prone situations (i.e., with a suitable lead time with regard to required reaction-time needs of the stakeholders involved in flood risk management) needs to take into account not only hydrological, but also meteorological, as well as communication issues. Therefore, we propose a threefold methodology to identify potential benefits and limitations in a real-world warning/reaction context. First, the user demands (with respect to desired/required warning products, preparation times, etc.) are investigated. Second, focusing on small catchments of some hundred square kilometers, two quantitative precipitation forecasts are verified. Third, considering the user needs, as well as the input parameter uncertainty (i.e., foremost emerging from an uncertain QPF), a feasible, yet robust hydrological modeling approach is proposed on the basis of pilot studies, employing deterministic, data-driven, and simple scoring methods.

Visible and Near-Infrared Spectroscopy Analysis of a Polycyclic Aromatic Hydrocarbon in Soils

PubMed Central

Okparanma, Reuben N.; Mouazen, Abdul M.

2013-01-01

Visible and near-infrared (VisNIR) spectroscopy is becoming recognised by soil scientists as a rapid and cost-effective measurement method for hydrocarbons in petroleum-contaminated soils. This study investigated the potential application of VisNIR spectroscopy (350–2500 nm) for the prediction of phenanthrene, a polycyclic aromatic hydrocarbon (PAH), in soils. A total of 150 diesel-contaminated soil samples were used in the investigation. Partial least-squares (PLS) regression analysis with full cross-validation was used to develop models to predict the PAH compound. Results showed that the PAH compound was predicted well with residual prediction deviation of 2.0–2.32, root-mean-square error of prediction of 0.21–0.25 mg kg−1, and coefficient of determination (r 2) of 0.75–0.83. The mechanism of prediction was attributed to covariation of the PAH with clay and soil organic carbon. Overall, the results demonstrated that the methodology may be used for predicting phenanthrene in soils utilizing the interrelationship between clay and soil organic carbon. PMID:24453798

Near-infrared spectroscopy for the detection and quantification of bacterial contaminations in pharmaceutical products.

PubMed

Quintelas, Cristina; Mesquita, Daniela P; Lopes, João A; Ferreira, Eugénio C; Sousa, Clara

2015-08-15

Accurate detection and quantification of microbiological contaminations remains an issue mainly due the lack of rapid and precise analytical techniques. Standard methods are expensive and time-consuming being associated to high economic losses and public health threats. In the context of pharmaceutical industry, the development of fast analytical techniques able to overcome these limitations is crucial and spectroscopic techniques might constitute a reliable alternative. In this work we proved the ability of Fourier transform near infrared spectroscopy (FT-NIRS) to detect and quantify bacteria (Bacillus subtilis, Escherichia coli, Pseudomonas fluorescens, Salmonella enterica, Staphylococcus epidermidis) from 10 to 10(8) CFUs/mL in sterile saline solutions (NaCl 0.9%). Partial least squares discriminant analysis (PLSDA) models showed that FT-NIRS was able to discriminate between sterile and contaminated solutions for all bacteria as well as to identify the contaminant bacteria. Partial least squares (PLS) models allowed bacterial quantification with limits of detection ranging from 5.1 to 9 CFU/mL for E. coli and B. subtilis, respectively. This methodology was successfully validated in three pharmaceutical preparations (contact lens solution, cough syrup and topic anti-inflammatory solution) proving that this technique possess a high potential to be routinely used for the detection and quantification of bacterial contaminations. Copyright © 2015 Elsevier B.V. All rights reserved.

Monitoring-well network and sampling design for ground-water quality, Wind River Indian Reservation, Wyoming

USGS Publications Warehouse

Mason, Jon P.; Sebree, Sonja K.; Quinn, Thomas L.

2005-01-01

The Wind River Indian Reservation, located in parts of Fremont and Hot Springs Counties, Wyoming, has a total land area of more than 3,500 square miles. Ground water on the Wind River Indian Reservation is a valuable resource for Shoshone and Northern Arapahoe tribal members and others who live on the Reservation. There are many types of land uses on the Reservation that have the potential to affect the quality of ground-water resources. Urban areas, rural housing developments, agricultural lands, landfills, oil and natural gas fields, mining, and pipeline utility corridors all have the potential to affect ground-water quality. A cooperative study was developed between the U.S. Geological Survey and the Wind River Environmental Quality Commission to identify areas of the Reservation that have the highest potential for ground-water contamination and develop a comprehensive plan to monitor these areas. An arithmetic overlay model for the Wind River Indian Reservation was created using seven geographic information system data layers representing factors with varying potential to affect ground-water quality. The data layers used were: the National Land Cover Dataset, water well density, aquifer sensitivity, oil and natural gas fields and petroleum pipelines, sites with potential contaminant sources, sites that are known to have ground-water contamination, and National Pollutant Discharge Elimination System sites. A prioritization map for monitoring ground-water quality on the Reservation was created using the model. The prioritization map ranks the priority for monitoring ground-water quality in different areas of the Reservation as low, medium, or high. To help minimize bias in selecting sites for a monitoring well network, an automated stratified random site-selection approach was used to select 30 sites for ground-water quality monitoring within the high priority areas. In addition, the study also provided a sampling design for constituents to be monitored, sampling frequency, and a simple water-table level observation well network.

Effect of non-parabolicity and confinement potential on exciton binding energy in a quantum well

NASA Astrophysics Data System (ADS)

Vignesh, G.; Nithiananthi, P.

2018-04-01

The effect of non-parabolicity(NP) (both conduction and valance band) on the binding energy(EB) of a ground state exciton in GaAs/AlxGa1-xAs single Quantum Well(QW) has been calculated using variational method. Confinement of a light hole(LH-CB1-X) and heavy hole(HH-CB1-X) exciton have been numerically evaluated as a function of well width and barrier heights by imposing three different confinement potentials such as square(SQW), parabolic(PQW) and triangular(TQW). Due to NP effects, EB of exciton is increasedin the narrow well region irrespective of the type of exciton, barrier height and nature of the confinement potentials applied. Non-parabolicity effect is prominent in abrupt(SQW) and linearlyvarying(TQW) confinement potentials. All these effects are attributed to be an inter-play between the Coulombic interaction and NP effects among the subband structures.

Understanding the Phase Behavior of Tetrahydrofuran + Carbon Dioxide, + Methane, and + Water Binary Mixtures from the SAFT-VR Approach.

PubMed

Míguez, J M; Piñeiro, M M; Algaba, J; Mendiboure, B; Torré, J P; Blas, F J

2015-11-05

The high-pressure phase diagrams of the tetrahydrofuran(1) + carbon dioxide(2), + methane(2), and + water(2) mixtures are examined using the SAFT-VR approach. Carbon dioxide molecule is modeled as two spherical segments tangentially bonded, water is modeled as a spherical segment with four associating sites to represent the hydrogen bonding, methane is represented as an isolated sphere, and tetrahydrofuran is represented as a chain of m tangentially bonded spherical segments. Dispersive interactions are modeled using the square-well intermolecular potential. In addition, two different molecular model mixtures are developed to take into account the subtle balance between water-tetrahydrofuran hydrogen-bonding interactions. The polar and quadrupolar interactions present in water, tetrahydrofuran, and carbon dioxide are treated in an effective way via square-well potentials of variable range. The optimized intermolecular parameters are taken from the works of Giner et al. (Fluid Phase Equil. 2007, 255, 200), Galindo and Blas (J. Phys. Chem. B 2002, 106, 4503), Patel et al. (Ind. Eng. Chem. Res. 2003, 42, 3809), and Clark et al. (Mol. Phys. 2006, 104, 3561) for tetrahydrofuran, carbon dioxide, methane, and water, respectively. The phase diagrams of the binary mixtures exhibit different types of phase behavior according to the classification of van Konynenburg and Scott, ranging from types I, III, and VI phase behavior for the tetrahydrofuran(1) + carbon dioxide(2), + methane(2), and + water(2) binary mixtures, respectively. This last type is characterized by the presence of a Bancroft point, positive azeotropy, and the so-called closed-loop curves that represent regions of liquid-liquid immiscibility in the phase diagram. The system exhibits lower critical solution temperatures (LCSTs), which denote the lower limit of immiscibility together with upper critical solution temperatures (UCSTs). This behavior is explained in terms of competition between the incompatibility with the alkyl parts of the tetrahydrofuran ring chain and the hydrogen bonding between water and the ether group. A minimum number of unlike interaction parameters are fitted to give the optimal representation of the most representative features of the binary phase diagrams. In the particular case of tetrahydrofuran(1) + water(2), two sets of intermolecular potential model parameters are proposed to describe accurately either the hypercritical point associated with the closed-loop liquid-liquid immiscibility region or the location of the mixture lower- and upper-critical end-points. The theory is not only able to predict the type of phase behavior of each mixture, but also provides a reasonably good description of the global phase behavior whenever experimental data are available.

Van Hove singularities in the paramagnetic phase of the Hubbard model: DMFT study

NASA Astrophysics Data System (ADS)

Žitko, Rok; Bonča, Janez; Pruschke, Thomas

2009-12-01

Using the dynamical mean-field theory (DMFT) with the numerical renormalization-group impurity solver we study the paramagnetic phase of the Hubbard model with the density of states (DOS) corresponding to the three-dimensional (3D) cubic lattice and the two-dimensional (2D) square lattice, as well as a DOS with inverse square-root singularity. We show that the electron correlations rapidly smooth out the square-root van Hove singularities (kinks) in the spectral function for the 3D lattice and that the Mott metal-insulator transition (MIT) as well as the magnetic-field-induced MIT differ only little from the well-known results for the Bethe lattice. The consequences of the logarithmic singularity in the DOS for the 2D lattice are more dramatic. At half filling, the divergence pinned at the Fermi level is not washed out, only its integrated weight decreases as the interaction is increased. While the Mott transition is still of the usual kind, the magnetic-field-induced MIT falls into a different universality class as there is no field-induced localization of quasiparticles. In the case of a power-law singularity in the DOS at the Fermi level, the power-law singularity persists in the presence of interaction, albeit with a different exponent, and the effective impurity model in the DMFT turns out to be a pseudogap Anderson impurity model with a hybridization function which vanishes at the Fermi level. The system is then a generalized Fermi liquid. At finite doping, regular Fermi-liquid behavior is recovered.

Rasch fit statistics and sample size considerations for polytomous data.

PubMed

Smith, Adam B; Rush, Robert; Fallowfield, Lesley J; Velikova, Galina; Sharpe, Michael

2008-05-29

Previous research on educational data has demonstrated that Rasch fit statistics (mean squares and t-statistics) are highly susceptible to sample size variation for dichotomously scored rating data, although little is known about this relationship for polytomous data. These statistics help inform researchers about how well items fit to a unidimensional latent trait, and are an important adjunct to modern psychometrics. Given the increasing use of Rasch models in health research the purpose of this study was therefore to explore the relationship between fit statistics and sample size for polytomous data. Data were collated from a heterogeneous sample of cancer patients (n = 4072) who had completed both the Patient Health Questionnaire - 9 and the Hospital Anxiety and Depression Scale. Ten samples were drawn with replacement for each of eight sample sizes (n = 25 to n = 3200). The Rating and Partial Credit Models were applied and the mean square and t-fit statistics (infit/outfit) derived for each model. The results demonstrated that t-statistics were highly sensitive to sample size, whereas mean square statistics remained relatively stable for polytomous data. It was concluded that mean square statistics were relatively independent of sample size for polytomous data and that misfit to the model could be identified using published recommended ranges.

Rasch fit statistics and sample size considerations for polytomous data

PubMed Central

Smith, Adam B; Rush, Robert; Fallowfield, Lesley J; Velikova, Galina; Sharpe, Michael

2008-01-01

Background Previous research on educational data has demonstrated that Rasch fit statistics (mean squares and t-statistics) are highly susceptible to sample size variation for dichotomously scored rating data, although little is known about this relationship for polytomous data. These statistics help inform researchers about how well items fit to a unidimensional latent trait, and are an important adjunct to modern psychometrics. Given the increasing use of Rasch models in health research the purpose of this study was therefore to explore the relationship between fit statistics and sample size for polytomous data. Methods Data were collated from a heterogeneous sample of cancer patients (n = 4072) who had completed both the Patient Health Questionnaire – 9 and the Hospital Anxiety and Depression Scale. Ten samples were drawn with replacement for each of eight sample sizes (n = 25 to n = 3200). The Rating and Partial Credit Models were applied and the mean square and t-fit statistics (infit/outfit) derived for each model. Results The results demonstrated that t-statistics were highly sensitive to sample size, whereas mean square statistics remained relatively stable for polytomous data. Conclusion It was concluded that mean square statistics were relatively independent of sample size for polytomous data and that misfit to the model could be identified using published recommended ranges. PMID:18510722

Topologically Nontrivial Magnon Bands in Artificial Square Spin Ices with Dzyaloshinskii-Moriya Interaction

NASA Astrophysics Data System (ADS)

Iacocca, Ezio; Heinonen, Olle

2017-09-01

Systems that exhibit topologically protected edge states are interesting both from a fundamental point of view as well as for potential applications, the latter because of the absence of backscattering and robustness to perturbations. It is desirable to be able to control and manipulate such edge states. Here, we show that artificial square ices can incorporate both features: an interfacial Dzyaloshinskii-Moriya interaction gives rise to topologically nontrivial magnon bands, and the equilibrium state of the spin ice is reconfigurable with different configurations having different magnon dispersions and topology. The topology is found to develop as odd-symmetry bulk and edge magnon bands approach each other so that constructive band inversion occurs in reciprocal space. Our results show that topologically protected bands are supported in square spin ices.

A comprehensive comparison between thermodynamic perturbation theory and first-order mean spherical approximation: Based on discrete potentials with hard core

NASA Astrophysics Data System (ADS)

Zhou, Shiqi; Zhou, Run

2017-08-01

Using the TL (Tang and Lu, 1993) method, Ornstein-Zernike integral equation is solved perturbatively under the mean spherical approximation (MSA) for fluid with potential consisting of a hard sphere plus square-well plus square-shoulder (HS + SW + SS) to obtain first-order analytic expressions of radial distribution function (RDF), second-order direct correlation function, and semi-analytic expressions for common thermodynamic properties. A comprehensive comparison between the first-order MSA and high temperature series expansion (HTSE) to third-, fifth- and seventh-order is performed over a wide parameter range for both a HS + SW and the HS + SW + SS model fluids by using corresponding ;exact; Monte Carlo results as a reference; although the HTSE is carried out up to seventh-order, and not to the first order as the first-order MSA the comparison is considered fair from a calculation complexity perspective. It is found that the performance of the first-order MSA is dramatically model-dependent: as target potentials go from the HS + SW to the HS + SW + SS, (i) there is a dramatic dropping of performance of the first-order MSA expressions in calculating the thermodynamic properties, especially both the excess internal energy and constant volume excess heat capacity of the HS + SW + SS model cannot be predicted even qualitatively correctly. (ii) One tendency is noticed that the first-order MSA gets more reliable with increasing temperatures in dealing with the pressure, excess Helmholtz free energy, excess enthalpy and excess chemical potential. (iii) Concerning the RDF, the first-order MSA is not as disappointing as it displays in the cases of thermodynamics. (iv) In the case of the HS + SW model, the first-order MSA solution is shown to be quantitatively correct in calculating the pressure and excess chemical potential even if the reduced temperatures are as low as 0.8. On the other hand, the seventh-order HTSE is less model-dependent; in most cases of the HS + SW and the HS + SW + SS models, the seventh-order HTSE improves the fifth- and third-order HTSE in both thermodynamic properties and RDF, and the improvements are very demonstrable in both the excess internal energy and constant volume excess heat capacity; for very limited cases, the seventh-order HTSE improves the fifth-order HTSE only within lower density domain and even shows a bit of inadaptation over higher density domain.

Empirical Correction to the Likelihood Ratio Statistic for Structural Equation Modeling with Many Variables.

PubMed

Yuan, Ke-Hai; Tian, Yubin; Yanagihara, Hirokazu

2015-06-01

Survey data typically contain many variables. Structural equation modeling (SEM) is commonly used in analyzing such data. The most widely used statistic for evaluating the adequacy of a SEM model is T ML, a slight modification to the likelihood ratio statistic. Under normality assumption, T ML approximately follows a chi-square distribution when the number of observations (N) is large and the number of items or variables (p) is small. However, in practice, p can be rather large while N is always limited due to not having enough participants. Even with a relatively large N, empirical results show that T ML rejects the correct model too often when p is not too small. Various corrections to T ML have been proposed, but they are mostly heuristic. Following the principle of the Bartlett correction, this paper proposes an empirical approach to correct T ML so that the mean of the resulting statistic approximately equals the degrees of freedom of the nominal chi-square distribution. Results show that empirically corrected statistics follow the nominal chi-square distribution much more closely than previously proposed corrections to T ML, and they control type I errors reasonably well whenever N ≥ max(50,2p). The formulations of the empirically corrected statistics are further used to predict type I errors of T ML as reported in the literature, and they perform well.

Quantum square-well with logarithmic central spike

NASA Astrophysics Data System (ADS)

Znojil, Miloslav; Semorádová, Iveta

2018-01-01

Singular repulsive barrier V (x) = -gln(|x|) inside a square-well is interpreted and studied as a linear analog of the state-dependent interaction ℒeff(x) = -gln[ψ∗(x)ψ(x)] in nonlinear Schrödinger equation. In the linearized case, Rayleigh-Schrödinger perturbation theory is shown to provide a closed-form spectrum at sufficiently small g or after an amendment of the unperturbed Hamiltonian. At any spike strength g, the model remains solvable numerically, by the matching of wave functions. Analytically, the singularity is shown regularized via the change of variables x = expy which interchanges the roles of the asymptotic and central boundary conditions.

Penetrable square-well fluids: exact results in one dimension.

PubMed

Santos, Andrés; Fantoni, Riccardo; Giacometti, Achille

2008-05-01

We introduce a model of attractive penetrable spheres by adding a short-range attractive square well outside a penetrable core, and we provide a detailed analysis of structural and thermodynamical properties in one dimension using the exact impenetrable counterpart as a starting point. The model is expected to describe star polymers in regimes of good and moderate solvent under dilute conditions. We derive the exact coefficients of a low-density expansion up to second order for the radial distribution function and up to fourth order in the virial expansion. These exact results are used as a benchmark to test the reliability of approximate theories (Percus-Yevick and hypernetted chain). Notwithstanding the lack of an exact solution for arbitrary densities, our results are expected to be rather precise within a wide range of temperatures and densities. A detailed analysis of some limiting cases is carried out. In particular, we provide a complete solution of the sticky penetrable-sphere model in one dimension up to the same order in density. The issue of Ruelle's thermodynamics stability is analyzed and the region of a well-defined thermodynamic limit is identified.

Near Infrared Spectroscopy Detection and Quantification of Herbal Medicines Adulterated with Sibutramine.

PubMed

da Silva, Neirivaldo Cavalcante; Honorato, Ricardo Saldanha; Pimentel, Maria Fernanda; Garrigues, Salvador; Cervera, Maria Luisa; de la Guardia, Miguel

2015-09-01

There is an increasing demand for herbal medicines in weight loss treatment. Some synthetic chemicals, such as sibutramine (SB), have been detected as adulterants in herbal formulations. In this study, two strategies using near infrared (NIR) spectroscopy have been developed to evaluate potential adulteration of herbal medicines with SB: a qualitative screening approach and a quantitative methodology based on multivariate calibration. Samples were composed by products commercialized as herbal medicines, as well as by laboratory adulterated samples. Spectra were obtained in the range of 14,000-4000 per cm. Using PLS-DA, a correct classification of 100% was achieved for the external validation set. In the quantitative approach, the root mean squares error of prediction (RMSEP), for both PLS and MLR models, was 0.2% w/w. The results prove the potential of NIR spectroscopy and multivariate calibration in quantifying sibutramine in adulterated herbal medicines samples. © 2015 American Academy of Forensic Sciences.

Preprocessing Inconsistent Linear System for a Meaningful Least Squares Solution

NASA Technical Reports Server (NTRS)

Sen, Syamal K.; Shaykhian, Gholam Ali

2011-01-01

Mathematical models of many physical/statistical problems are systems of linear equations. Due to measurement and possible human errors/mistakes in modeling/data, as well as due to certain assumptions to reduce complexity, inconsistency (contradiction) is injected into the model, viz. the linear system. While any inconsistent system irrespective of the degree of inconsistency has always a least-squares solution, one needs to check whether an equation is too much inconsistent or, equivalently too much contradictory. Such an equation will affect/distort the least-squares solution to such an extent that renders it unacceptable/unfit to be used in a real-world application. We propose an algorithm which (i) prunes numerically redundant linear equations from the system as these do not add any new information to the model, (ii) detects contradictory linear equations along with their degree of contradiction (inconsistency index), (iii) removes those equations presumed to be too contradictory, and then (iv) obtain the minimum norm least-squares solution of the acceptably inconsistent reduced linear system. The algorithm presented in Matlab reduces the computational and storage complexities and also improves the accuracy of the solution. It also provides the necessary warning about the existence of too much contradiction in the model. In addition, we suggest a thorough relook into the mathematical modeling to determine the reason why unacceptable contradiction has occurred thus prompting us to make necessary corrections/modifications to the models - both mathematical and, if necessary, physical.

Preprocessing in Matlab Inconsistent Linear System for a Meaningful Least Squares Solution

NASA Technical Reports Server (NTRS)

Sen, Symal K.; Shaykhian, Gholam Ali

2011-01-01

Mathematical models of many physical/statistical problems are systems of linear equations Due to measurement and possible human errors/mistakes in modeling/data, as well as due to certain assumptions to reduce complexity, inconsistency (contradiction) is injected into the model, viz. the linear system. While any inconsistent system irrespective of the degree of inconsistency has always a least-squares solution, one needs to check whether an equation is too much inconsistent or, equivalently too much contradictory. Such an equation will affect/distort the least-squares solution to such an extent that renders it unacceptable/unfit to be used in a real-world application. We propose an algorithm which (i) prunes numerically redundant linear equations from the system as these do not add any new information to the model, (ii) detects contradictory linear equations along with their degree of contradiction (inconsistency index), (iii) removes those equations presumed to be too contradictory, and then (iv) obtain the . minimum norm least-squares solution of the acceptably inconsistent reduced linear system. The algorithm presented in Matlab reduces the computational and storage complexities and also improves the accuracy of the solution. It also provides the necessary warning about the existence of too much contradiction in the model. In addition, we suggest a thorough relook into the mathematical modeling to determine the reason why unacceptable contradiction has occurred thus prompting us to make necessary corrections/modifications to the models - both mathematical and, if necessary, physical.

A square root ensemble Kalman filter application to a motor-imagery brain-computer interface.

PubMed

Kamrunnahar, M; Schiff, S J

2011-01-01

We here investigated a non-linear ensemble Kalman filter (SPKF) application to a motor imagery brain computer interface (BCI). A square root central difference Kalman filter (SR-CDKF) was used as an approach for brain state estimation in motor imagery task performance, using scalp electroencephalography (EEG) signals. Healthy human subjects imagined left vs. right hand movements and tongue vs. bilateral toe movements while scalp EEG signals were recorded. Offline data analysis was conducted for training the model as well as for decoding the imagery movements. Preliminary results indicate the feasibility of this approach with a decoding accuracy of 78%-90% for the hand movements and 70%-90% for the tongue-toes movements. Ongoing research includes online BCI applications of this approach as well as combined state and parameter estimation using this algorithm with different system dynamic models.

View-Based Organization and Interplay of Spatial Working and Long-Term Memories

PubMed Central

Röhrich, Wolfgang G.; Hardiess, Gregor; Mallot, Hanspeter A.

2014-01-01

Space perception provides egocentric, oriented views of the environment from which working and long-term memories are constructed. “Allocentric” (i.e. position-independent) long-term memories may be organized as graphs of recognized places or views but the interaction of such cognitive graphs with egocentric working memories is unclear. Here we present a simple coherent model of view-based working and long-term memories, together with supporting evidence from behavioral experiments. The model predicts that within a given place, memories for some views may be more salient than others, that imagery of a target square should depend on the location where the recall takes place, and that recall favors views of the target square that would be obtained when approaching it from the current recall location. In two separate experiments in an outdoor urban environment, pedestrians were approached at various interview locations and asked to draw sketch maps of one of two well-known squares. Orientations of the sketch map productions depended significantly on distance and direction of the interview location from the target square, i.e. different views were recalled at different locations. Further analysis showed that location-dependent recall is related to the respective approach direction when imagining a walk from the interview location to the target square. The results are consistent with a view-based model of spatial long-term and working memories and their interplay. PMID:25409437

Methods for estimating annual exceedance probability discharges for streams in Arkansas, based on data through water year 2013

USGS Publications Warehouse

Wagner, Daniel M.; Krieger, Joshua D.; Veilleux, Andrea G.

2016-08-04

In 2013, the U.S. Geological Survey initiated a study to update regional skew, annual exceedance probability discharges, and regional regression equations used to estimate annual exceedance probability discharges for ungaged locations on streams in the study area with the use of recent geospatial data, new analytical methods, and available annual peak-discharge data through the 2013 water year. An analysis of regional skew using Bayesian weighted least-squares/Bayesian generalized-least squares regression was performed for Arkansas, Louisiana, and parts of Missouri and Oklahoma. The newly developed constant regional skew of -0.17 was used in the computation of annual exceedance probability discharges for 281 streamgages used in the regional regression analysis. Based on analysis of covariance, four flood regions were identified for use in the generation of regional regression models. Thirty-nine basin characteristics were considered as potential explanatory variables, and ordinary least-squares regression techniques were used to determine the optimum combinations of basin characteristics for each of the four regions. Basin characteristics in candidate models were evaluated based on multicollinearity with other basin characteristics (variance inflation factor < 2.5) and statistical significance at the 95-percent confidence level (p ≤ 0.05). Generalized least-squares regression was used to develop the final regression models for each flood region. Average standard errors of prediction of the generalized least-squares models ranged from 32.76 to 59.53 percent, with the largest range in flood region D. Pseudo coefficients of determination of the generalized least-squares models ranged from 90.29 to 97.28 percent, with the largest range also in flood region D. The regional regression equations apply only to locations on streams in Arkansas where annual peak discharges are not substantially affected by regulation, diversion, channelization, backwater, or urbanization. The applicability and accuracy of the regional regression equations depend on the basin characteristics measured for an ungaged location on a stream being within range of those used to develop the equations.

Divergence of activity expansions: Is it actually a problem?

NASA Astrophysics Data System (ADS)

Ushcats, M. V.; Bulavin, L. A.; Sysoev, V. M.; Ushcats, S. Yu.

2017-12-01

For realistic interaction models, which include both molecular attraction and repulsion (e.g., Lennard-Jones, modified Lennard-Jones, Morse, and square-well potentials), the asymptotic behavior of the virial expansions for pressure and density in powers of activity has been studied taking power terms of high orders into account on the basis of the known finite-order irreducible integrals as well as the recent approximations of infinite irreducible series. Even in the divergence region (at subcritical temperatures), this behavior stays thermodynamically adequate (in contrast to the behavior of the virial equation of state with the same set of irreducible integrals) and corresponds to the beginning of the first-order phase transition: the divergence yields the jump (discontinuity) in density at constant pressure and chemical potential. In general, it provides a statistical explanation of the condensation phenomenon, but for liquid or solid states, the physically proper description (which can turn the infinite discontinuity into a finite jump of density) still needs further study of high-order cluster integrals and, especially, their real dependence on the system volume (density).

Generalizability of dietary patterns of the inverse association between alcohol consumption and type 2 diabetes risk

USDA-ARS?s Scientific Manuscript database

Epidemiology of dietary components and disease risk limits interpretability due to potential residual confounding by correlated dietary components. Dietary pattern analyses by factor analysis or partial least squares may overcome this limitation. To examine confounding by dietary pattern as well as ...

Confounding by dietary pattern of the inverse association between alcohol consumption and type 2 diabetes risk

USDA-ARS?s Scientific Manuscript database

Epidemiology of dietary components and disease risk limits interpretability due to potential residual confounding by correlated dietary components. Dietary pattern analyses by factor analysis or partial least squares may overcome the limitation. To examine confounding by dietary pattern as well as ...

Confounding by dietary patterns of the inverse association between alcohol consumption and type 2 diabetes risk

USDA-ARS?s Scientific Manuscript database

Epidemiology of dietary components and disease risk limits interpretability due to potential residual confounding by correlated dietary components. Dietary pattern analyses by factor analysis or partial least squares may overcome this limitation. To examine confounding by dietary pattern as well as ...

Impurity in a Bose-Einstein condensate: Study of the attractive and repulsive branch using quantum Monte Carlo methods

NASA Astrophysics Data System (ADS)

Ardila, L. A. Peña; Giorgini, S.

2015-09-01

We investigate the properties of an impurity immersed in a dilute Bose gas at zero temperature using quantum Monte Carlo methods. The interactions between bosons are modeled by a hard-sphere potential with scattering length a , whereas the interactions between the impurity and the bosons are modeled by a short-range, square-well potential where both the sign and the strength of the scattering length b can be varied by adjusting the well depth. We characterize the attractive and the repulsive polaron branch by calculating the binding energy and the effective mass of the impurity. Furthermore, we investigate the structural properties of the bath, such as the impurity-boson contact parameter and the change of the density profile around the impurity. At the unitary limit of the impurity-boson interaction, we find that the effective mass of the impurity remains smaller than twice its bare mass, while the binding energy scales with ℏ2n2 /3/m , where n is the density of the bath and m is the common mass of the impurity and the bosons in the bath. The implications for the phase diagram of binary Bose-Bose mixtures at low concentrations are also discussed.

Potential use of multispectral imaging technology to identify moisture content and water-holding capacity in cooked pork sausages.

PubMed

Ma, Fei; Zhang, Bin; Wang, Wu; Li, Peijun; Niu, Xiangli; Chen, Conggui; Zheng, Lei

2018-03-01

The traditional detection methods for moisture content (MC) and water-holding capacity (WHC) in cooked pork sausages (CPS) are destructive, time consuming, require skilled personnel and are not suitable for online industry applications. The goal of this work was to explore the potential of multispectral imaging (MSI) in combination with multivariate analysis for the identification of MC and WHC in CPS. Spectra and textures of 156 CPS treated by six salt concentrations (0-2.5%) were analyzed using different calibration models to find the most optimal results of predicting MC and WHC in CPS. By using the fused data of spectra and textures, partial least squares regression models performed well for determining the MC and WHC, with a correlation coefficient (r) of 0.949 and 0.832, respectively. Additionally, their spatial distribution in CPS could be visualized via applying prediction equations to transfer each pixel in the image. Results of satisfactory detection and visualization of the MC and WHC showed that MSI has the potential to serve as a rapid and non-destructive method for use in sausage industry. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Electrospray ionization mass spectrometry and partial least squares discriminant analysis applied to the quality control of olive oil.

PubMed

Alves, Junia O; Botelho, Bruno G; Sena, Marcelo M; Augusti, Rodinei

2013-10-01

Direct infusion electrospray ionization mass spectrometry in the positive ion mode [ESI(+)-MS] is used to obtain fingerprints of aqueous-methanolic extracts of two types of olive oils, extra virgin (EV) and ordinary (OR), as well as of samples of EV olive oil adulterated by the addition of OR olive oil and other edible oils: corn (CO), sunflower (SF), soybean (SO) and canola (CA). The MS data is treated by the partial least squares discriminant analysis (PLS-DA) protocol aiming at discriminating the above-mentioned classes formed by the genuine olive oils, EV (1) and OR (2), as well as the EV adulterated samples, i.e. EV/SO (3), EV/CO (4), EV/SF (5), EV/CA (6) and EV/OR (7). The PLS-DA model employed is built with 190 and 70 samples for the training and test sets, respectively. For all classes (1-7), EV and OR olive oils as well as the adulterated samples (in a proportion varying from 0.5 to 20.0% w/w) are properly classified. The developed methodology required no ions identification and demonstrated to be fast, as each measurement lasted about 3 min including the extraction step and MS analysis, and reliable, because high sensitivities (rate of true positives) and specificities (rate of true negatives) were achieved. Finally, it can be envisaged that this approach has potential to be applied in quality control of EV olive oils. Copyright © 2013 John Wiley & Sons, Ltd.

Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm

NASA Astrophysics Data System (ADS)

Jiang, Hui; Liu, Guohai; Mei, Congli; Yu, Shuang; Xiao, Xiahong; Ding, Yuhan

2012-11-01

The feasibility of rapid determination of the process variables (i.e. pH and moisture content) in solid-state fermentation (SSF) of wheat straw using Fourier transform near infrared (FT-NIR) spectroscopy was studied. Synergy interval partial least squares (siPLS) algorithm was implemented to calibrate regression model. The number of PLS factors and the number of subintervals were optimized simultaneously by cross-validation. The performance of the prediction model was evaluated according to the root mean square error of cross-validation (RMSECV), the root mean square error of prediction (RMSEP) and the correlation coefficient (R). The measurement results of the optimal model were obtained as follows: RMSECV = 0.0776, Rc = 0.9777, RMSEP = 0.0963, and Rp = 0.9686 for pH model; RMSECV = 1.3544% w/w, Rc = 0.8871, RMSEP = 1.4946% w/w, and Rp = 0.8684 for moisture content model. Finally, compared with classic PLS and iPLS models, the siPLS model revealed its superior performance. The overall results demonstrate that FT-NIR spectroscopy combined with siPLS algorithm can be used to measure process variables in solid-state fermentation of wheat straw, and NIR spectroscopy technique has a potential to be utilized in SSF industry.

An initial model for estimating soybean development stages from spectral data

NASA Technical Reports Server (NTRS)

Henderson, K. E.; Badhwar, G. D.

1982-01-01

A model, utilizing a direct relationship between remotely sensed spectral data and soybean development stage, has been proposed. The model is based upon transforming the spectral data in Landsat bands to greenness values over time and relating the area of this curve to soybean development stage. Soybean development stages were estimated from data acquired in 1978 from research plots at the Purdue University Agronomy Farm as well as Landsat data acquired over sample areas of the U.S. Corn Belt in 1978 and 1979. Analysis of spectral data from research plots revealed that the model works well with reasonable variation in planting date, row spacing, and soil background. The R-squared of calculated U.S. observed development stage exceeded 0.91 for all treatment variables. Using Landsat data the calculated U.S. observed development stage gave an R-squared of 0.89 in 1978 and 0.87 in 1979. No difference in the models performance could be detected between early and late planted fields, small and large fields, or high and low yielding fields.

New limb-darkening coefficients for modeling binary star light curves

NASA Technical Reports Server (NTRS)

Van Hamme, W.

1993-01-01

We present monochromatic, passband-specific, and bolometric limb-darkening coefficients for a linear as well as nonlinear logarithmic and square root limb-darkening laws. These coefficients, including the bolometric ones, are needed when modeling binary star light curves with the latest version of the Wilson-Devinney light curve progam. We base our calculations on the most recent ATLAS stellar atmosphere models for solar chemical composition stars with a wide range of effective temperatures and surface gravitites. We examine how well various limb-darkening approximations represent the variation of the emerging specific intensity across a stellar surface as computed according to the model. For binary star light curve modeling purposes, we propose the use of a logarithmic or a square root law. We design our tables in such a manner that the relative quality of either law with respect to another can be easily compared. Since the computation of bolometric limb-darkening coefficients first requires monochromatic coefficients, we also offer tables of these coefficients (at 1221 wavelength values between 9.09 nm and 160 micrometer) and tables of passband-specific coefficients for commonly used photometric filters.

Coupling-parameter expansion in thermodynamic perturbation theory.

PubMed

Ramana, A Sai Venkata; Menon, S V G

2013-02-01

An approach to the coupling-parameter expansion in the liquid state theory of simple fluids is presented by combining the ideas of thermodynamic perturbation theory and integral equation theories. This hybrid scheme avoids the problems of the latter in the two phase region. A method to compute the perturbation series to any arbitrary order is developed and applied to square well fluids. Apart from the Helmholtz free energy, the method also gives the radial distribution function and the direct correlation function of the perturbed system. The theory is applied for square well fluids of variable ranges and compared with simulation data. While the convergence of perturbation series and the overall performance of the theory is good, improvements are needed for potentials with shorter ranges. Possible directions for further developments in the coupling-parameter expansion are indicated.

Effect of confinement potential on exciton diamagnetism in the perspective of constituent carriers in a Quantum Well

NASA Astrophysics Data System (ADS)

Vignesh, G.; Nithiananthi, P.

2018-03-01

Diamagnetic susceptibility of excitons is investigated in the perspective of the electron and hole separation along the lateral (ρ) and normal direction (z) of a GaAs/AlxGa1-xAs quantum well. Using a variational technique, the spatial extensions of these carriers has been observed. The coulomb interaction of the carriers is investigated by subjecting the carriers to three confinement potentials, Square (SQW), Parabolic (PQW) and Triangular Quantum Wells (TQW). The stability of the exciton has been estimated by observing the diamagnetic susceptibility. The hole is very sensitive to confinement potential and has tremendous variations in spatial extension. Among the three confinements, TQW offers more localization and high stability to excitons. The anisotropy of band parameters and the dielectric constants of the well and barrier materials are taken into consideration.

Evaluating effects of potential changes in streamflow regime on fish and aquatic-invertebrate assemblages in the New Jersey Pinelands

USGS Publications Warehouse

Kennen, Jonathan G.; Riskin, Melissa L.

2010-01-01

Changes in water demand associated with population growth and changes in land-use practices in the Pinelands region of southern New Jersey will have a direct effect on stream hydrology. The most pronounced and measurable hydrologic effect is likely to be flow reductions associated with increasing water extraction. Because water-supply needs will continue to grow along with population in the Pinelands area, the goal of maintaining a sustainable balance between the availability of water to protect existing aquatic assemblages while conserving the surficial aquifer for long-term support of human water use needs to be addressed. Although many aquatic fauna have shown resilience and resistance to short-term changes in flows associated with water withdrawals, sustained effects associated with ongoing water-development processes are not well understood. In this study, the U.S. Geological Survey sampled forty-three 100-meter-long stream reaches during high- and low-flow periods across a designed hydrologic gradient ranging from small- (4.1 square kilometers (1.6 square miles)) to medium- (66.3 square kilometers (25.6 square miles)) sized Pinelands stream basins. This design, which uses basin size as a surrogate for water availability, provided an opportunity to evaluate the possible effects of potential variation in stream hydrology on fish and aquatic-invertebrate assemblage response in New Jersey Pinelands streams where future water extraction is expected based on known build-out scenarios. Multiple-regression models derived from extracted non-metric multidimensional scaling axis scores of fish and aquatic invertebrates indicate that some variability in aquatic-assemblage composition across the hydrologic gradient is associated with anthropogenic disturbance, such as urbanization, changes in stream chemistry, and concomitant changes in high-flow runoff patterns. To account for such underlying effects in the study models, any flow parameter or assemblage attribute that was found to be significantly correlated (|rho| = 0.5000) to known anthropogenic drivers (for example, the amount of urbanization in the basin) was eliminated from analysis. A reduced set of low- and annual-flow hydrologic variables, found to be unrelated to anthropogenic influences, was used to develop assemblage-response models. Many linear (monotonic) and curvilinear bivariate flow-ecology response models were developed for fish and invertebrate assemblages. For example, the duration and magnitude of low-flow events were significant predictors of invertebrate-assemblage complexity (for example, invertebrate-species richness, Plecoptera richness, and Ephemeroptera abundance); however, response models between flow attributes and fish-assemblage structure were, in all cases, more poorly fit. Annual flow variability also was important, especially variability across mean minimum monthly flows and annual mean streamflow. In general, all response models followed upward or downward trends that would be expected given hydrologic changes in Pinelands streams. This study demonstrates that the structural and functional response of aquatic assemblages of the Pinelands ecosystem resulting from changes in water-use practices associated with population growth and increased water extraction may be predictable.

Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 2. Applications

USGS Publications Warehouse

Cooley, Richard L.

1983-01-01

This paper investigates factors influencing the degree of improvement in estimates of parameters of a nonlinear regression groundwater flow model by incorporating prior information of unknown reliability. Consideration of expected behavior of the regression solutions and results of a hypothetical modeling problem lead to several general conclusions. First, if the parameters are properly scaled, linearized expressions for the mean square error (MSE) in parameter estimates of a nonlinear model will often behave very nearly as if the model were linear. Second, by using prior information, the MSE in properly scaled parameters can be reduced greatly over the MSE of ordinary least squares estimates of parameters. Third, plots of estimated MSE and the estimated standard deviation of MSE versus an auxiliary parameter (the ridge parameter) specifying the degree of influence of the prior information on regression results can help determine the potential for improvement of parameter estimates. Fourth, proposed criteria can be used to make appropriate choices for the ridge parameter and another parameter expressing degree of overall bias in the prior information. Results of a case study of Truckee Meadows, Reno-Sparks area, Washoe County, Nevada, conform closely to the results of the hypothetical problem. In the Truckee Meadows case, incorporation of prior information did not greatly change the parameter estimates from those obtained by ordinary least squares. However, the analysis showed that both sets of estimates are more reliable than suggested by the standard errors from ordinary least squares.

On-line Model Structure Selection for Estimation of Plasma Boundary in a Tokamak

NASA Astrophysics Data System (ADS)

Škvára, Vít; Šmídl, Václav; Urban, Jakub

2015-11-01

Control of the plasma field in the tokamak requires reliable estimation of the plasma boundary. The plasma boundary is given by a complex mathematical model and the only available measurements are responses of induction coils around the plasma. For the purpose of boundary estimation the model can be reduced to simple linear regression with potentially infinitely many elements. The number of elements must be selected manually and this choice significantly influences the resulting shape. In this paper, we investigate the use of formal model structure estimation techniques for the problem. Specifically, we formulate a sparse least squares estimator using the automatic relevance principle. The resulting algorithm is a repetitive evaluation of the least squares problem which could be computed in real time. Performance of the resulting algorithm is illustrated on simulated data and evaluated with respect to a more detailed and computationally costly model FREEBIE.

Relationship between X(5) models and the interacting boson model

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

Barea, Jose; Departamento de Fisica Atomica, Molecular y Nuclear, Facultad de Fisica, Universidad de Sevilla, Apartado 1065, E-41080 Sevilla; Arias, Jose M.

2010-08-15

The connections between the X(5) models [the original X(5) using an infinite square well, X(5)-{beta}{sup 8}, X(5)-{beta}{sup 6}, X(5)-{beta}{sup 4}, and X(5)-{beta}{sup 2}], based on particular solutions of the geometrical Bohr Hamiltonian with harmonic potential in the {gamma} degree of freedom, and the interacting boson model (IBM) are explored. This work is the natural extension of the work presented in Garcia-Ramos and Arias, Phys. Rev. C 77, 054307 (2008) for the E(5) models. For that purpose, a quite general one- and two-body IBM Hamiltonian is used and a numerical fit to the different X(5) model energies is performed; then themore » obtained wave functions are used to calculate B(E2) transition rates. It is shown that within the IBM one can reproduce well the results for energies and B(E2) transition rates obtained with all these X(5) models, although the agreement is not so impressive as for the E(5) models. From the fitted IBM parameters the corresponding energy surface can be extracted and, surprisingly, only the X(5) case corresponds in the moderately large N limit to an energy surface very close to the one expected for a critical point, whereas the rest of models are situated a little further away.« less

Self-organization of a self-assembled supramolecular rectangle, square, and three-dimensional cage on Au111 surfaces.

PubMed

Yuan, Qun-Hui; Wan, Li-Jun; Jude, Hershel; Stang, Peter J

2005-11-23

The structure and conformation of three self-assembled supramolecular species, a rectangle, a square, and a three-dimensional cage, on Au111 surfaces were investigated by scanning tunneling microscopy. These supramolecular assemblies adsorb on Au111 surfaces and self-organize to form highly ordered adlayers with distinct conformations that are consistent with their chemical structures. The faces of the supramolecular rectangle and square lie flat on the surface, preserving their rectangle and square conformations, respectively. The three-dimensional cage also forms well-ordered adlayers on the gold surface, forming regular molecular rows of assemblies. When the rectangle and cage were mixed together, the assemblies separated into individual domains, and no mixed adlayers were observed. These results provide direct evidence of the noncrystalline solid-state structures of these assemblies and information about how they self-organize on Au111 surfaces, which is of importance in the potential manufacturing of functional nanostructures and devices.

Simulation of a long-term aquifer test conducted near the Rio Grande, Albuquerque, New Mexico

USGS Publications Warehouse

McAda, Douglas P.

2001-01-01

A long-term aquifer test was conducted near the Rio Grande in Albuquerque during January and February 1995 using 22 wells and piezometers at nine sites, with the City of Albuquerque Griegos 1 production well as the pumped well. Griegos 1 discharge averaged about 2,330 gallons per minute for 54.4 days. A three-dimensional finite-difference ground-water-flow model was used to estimate aquifer properties in the vicinity of the Griegos well field and the amount of infiltration induced into the aquifer system from the Rio Grande and riverside drains as a result of pumping during the test. The model was initially calibrated by trial-and-error adjustments of the aquifer properties. The model was recalibrated using a nonlinear least-squares regression technique. The aquifer system in the area includes the middle Tertiary to Quaternary Santa Fe Group and post-Santa Fe Group valley- and basin-fill deposits of the Albuquerque Basin. The Rio Grande and adjacent riverside drains are in hydraulic connection with the aquifer system. The hydraulic-conductivity values of the upper part of the Santa Fe Group resulting from the model calibrated by trial and error varied by zone in the model and ranged from 12 to 33 feet per day. The hydraulic conductivity of the inner-valley alluvium was 45 feet per day. The vertical to horizontal anisotropy ratio was 1:140. Specific storage was 4 x 10-6 per foot of aquifer thickness, and specific yield was 0.15 (dimensionless). The sum of squared errors between the observed and simulated drawdowns was 130 feet squared. Not all aquifer properties could be estimated using nonlinear regression because of model insensitivity to some aquifer properties at observation locations. Hydraulic conductivity of the inner-valley alluvium, middle part of the Santa Fe Group, and riverbed and riverside-drain bed and specific yield had low sensitivity values and therefore could not be estimated. Of the properties estimated, hydraulic conductivity of the upper part of the Santa Fe Group was estimated to be 12 feet per day, the vertical to horizontal anisotropy ratio was estimated to be 1:82, and specific storage was estimated to be 1.2 x 10-6 per foot of aquifer thickness. The overall sum of squared errors between the observed and simulated drawdowns was 87 feet squared, a significant improvement over the model calibrated by trial and error. At the end of aquifer-test pumping, induced infiltration from the Rio Grande and riverside drains was simulated to be 13 percent of the total amount of water pumped. The remainder was water removed from aquifer storage. After pumping stopped, induced infiltration continued to replenish aquifer storage. Simulations estimated that 5 years after pumping began (about 4.85 years after pumping stopped), 58 to 72 percent of the total amount of water pumped was replenished by induced infiltration from the Rio Grande surface-water system.

Tunable magnetic vortex resonance in a potential well

NASA Astrophysics Data System (ADS)

Warnicke, P.; Wohlhüter, P.; Suszka, A. K.; Stevenson, S. E.; Heyderman, L. J.; Raabe, J.

2017-11-01

We use frequency-resolved x-ray microscopy to fully characterize the potential well of a magnetic vortex in a soft ferromagnetic permalloy square. The vortex core is excited with magnetic broadband pulses and simultaneously displaced with a static magnetic field. We observe a frequency increase (blueshift) in the gyrotropic mode of the vortex core with increasing bias field. Supported by micromagnetic simulations, we show that this frequency increase is accompanied by internal deformation of the vortex core. The ability to modify the inner structure of the vortex core provides a mechanism to control the dynamics of magnetic vortices.

Constructive methods for the ground-state energy of fully interacting fermion gases

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

Aguilera Navarro, V.C.; Baker G.A. Jr.; Benofy, L.P.

1987-11-01

A perturbation scheme based not on the ideal gas but on a system of purely repulsive cores is applied to a typical fully interacting fermion gas. This is ''neutron matter'' interacting via (a) the repulsive ''Bethe homework-problem'' potential, (b) a hard-core--plus--square-well potential, and (c) the Baker-Hind-Kahane modification of the latter, suitable for describing a more accurate two-nucleon potential. Pade extrapolation techniques and generalizations thereof are employed to represent both the density dependence as well as the attractive coupling dependence of the perturbation expansion. Equations of state are constructed and compared with Jastrow--Monte Carlo calculations as well as expectations based onmore » semiempirical mass formulas. Excellent agreement is found with the latter.« less

The Copenhagen problem with a quasi-homogeneous potential

NASA Astrophysics Data System (ADS)

Fakis, Demetrios; Kalvouridis, Tilemahos

2017-05-01

The Copenhagen problem is a well-known case of the famous restricted three-body problem. In this work instead of considering Newtonian potentials and forces we assume that the two primaries create a quasi-homogeneous potential, which means that we insert to the inverse square law of gravitation an inverse cube corrective term in order to approximate various phenomena as the radiation pressure of the primaries or the non-sphericity of them. Based on this new consideration we investigate the equilibrium locations of the small body and their parametric dependence, as well as the zero-velocity curves and surfaces for the planar motion, and the evolution of the regions where this motion is permitted when the Jacobian constant varies.

Self-avoiding walks that cross a square

NASA Astrophysics Data System (ADS)

Burkhardt, T. W.; Guim, I.

1991-10-01

The authors consider self-avoiding walks that traverse an L*L square lattice. Whittington and Guttmann (1990) have proved the existence of a phase transition in the infinite-L limit at a critical value of the step fugacity. They make several finite-size scaling predictions for the critical region, using the relation between self-avoiding walks and the N-vector model of magnetism. Adsorbing as well as nonadsorbing boundaries are considered. The predictions are in good agreement with numerical data for L

BCS-Bose model of exotic superconductors: Generalized coherence length

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

Casas, M.; Getino, J.M.; de Llano, M.

1994-12-01

Analytic expressions are derived for the root-mean-square (rms) radius of a pair of fermions in a BCS many-fermion state in one, two, and three dimensions, in terms of the BCS gap energy and the associated chemical potential. These expressions are valid for any coupling strength of [ital any] pair interaction model implying a momentum-independent gap energy. The latter holds, e.g., for an attractive [delta] pair potential examined in the one-dimensional (1D) case (whose [ital N]-fermion ground state can be determined exactly) or for the BCS (electron-phonon) model interaction in any dimension. Weak-coupling and/or high-density limits for the rms radius aremore » identical in 1D, 2D, and 3D, and reduce to the familiar well-known Pippard result to within a factor of order unity. In contrast, strong-coupling and/or low-density limits coincide in 1D and 3D, but differ by a factor of order unity in the 2D limit, and in each case are essentially the size of a single, isolated pair. The 1D [delta] interaction McGuire-Yang-Gaudin many-fermion model is studied in detail. The interaction renormalization scheme of Miyake and of Randeria, Duan, and Shieh, and the BCS interaction model, both in 2D, are employed to analyze cuprate superconductor empirical results. Reasonable agreement between theoretical rms radii with experimental coherence lengths suggests that cuprates can be described moderately well as [ital weakly] [ital coupled] superconductors within the BCS-Bose formalism.« less

Size dependent bandgap of molecular beam epitaxy grown InN quantum dots measured by scanning tunneling spectroscopy

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

Kumar, Mahesh; Roul, Basanta; Central Research Laboratory, Bharat Electronics, Bangalore-560013

InN quantum dots (QDs) were grown on Si (111) by epitaxial Stranski-Krastanow growth mode using plasma-assisted molecular beam epitaxy. Single-crystalline wurtzite structure of InN QDs was verified by the x-ray diffraction and transmission electron microscopy. Scanning tunneling microscopy has been used to probe the structural aspects of QDs. A surface bandgap of InN QDs was estimated from scanning tunneling spectroscopy (STS) I-V curves and found that it is strongly dependent on the size of QDs. The observed size-dependent STS bandgap energy shifts with diameter and height were theoretical explained based on an effective mass approximation with finite-depth square-well potential model.

Nonlinear Dynamical Model of a Soft Viscoelastic Dielectric Elastomer

NASA Astrophysics Data System (ADS)

Zhang, Junshi; Chen, Hualing; Li, Dichen

2017-12-01

Actuated by alternating stimulation, dielectric elastomers (DEs) show a behavior of complicated nonlinear vibration, implying a potential application as dynamic electromechanical actuators. As is well known, for a vibrational system, including the DE system, the dynamic properties are significantly affected by the geometrical sizes. In this article, a nonlinear dynamical model is deduced to investigate the geometrical effects on dynamic properties of viscoelastic DEs. The DEs with square and arbitrary rectangular geometries are considered, respectively. Besides, the effects of tensile forces on dynamic performances of rectangular DEs with comparably small and large geometrical sizes are explored. Phase paths and Poincaré maps are utilized to detect the periodicity of the nonlinear vibrations of DEs. The resonance characteristics of DEs incorporating geometrical effects are also investigated. The results indicate that the dynamic properties of DEs, including deformation response, vibrational periodicity, and resonance, are tuned when the geometrical sizes vary.

Numerical Models of Pore Pressure and Stress Changes along Basement Faults due to Wastewater Injection: Applications to Potentially Induced Seismicity in Southern Kansas

NASA Astrophysics Data System (ADS)

Koltermann, C.; Hearn, E. H.

2015-12-01

As hydrocarbon extraction techniques that generate large volumes of wastewater have come into widespread use in the central United States, increased volumes have been injected into deep disposal wells, with a corresponding dramatic increase in seismicity rates. South-central Kansas is of particular scientific interest because fluid injection rates have recently increased due to renewed gas and oil production from the Mississippi Lime Play, and the local seismicity is being monitored with a seismometer network deployed by the USGS. In addition, since only a small percentage of injection wells seem to induce seismicity, it is important to characterize contributing factors. We have developed groundwater flow models using MODFLOW-USG to (1) assess hydrogeologic conditions under which seismicity may be triggered, for cases in which wastewater is injected into sedimentary strata overlying fractured crystalline basement rock and to (2) explore the possible relationship between wastewater injection and the November 2014 M 4.8 Milan, Kansas earthquake. The USG version of MODFLOW allows us to use unstructured meshes, which vastly reduces computation time while allowing dense meshing near injection wells and faults. Our single-well test model has been benchmarked to published models (Zhang et al., 2013) and will be used to evaluate sensitivity pore pressures and stresses to model parameters. Our south Kansas model represents high-rate injection wells, as well as oil and gas wells producing from the Arbuckle and overlying Mississippian formations in a 40-km square region. Based on modeled pore pressure and stress changes along the target fault, we will identify conditions that would be consistent with inducing an earthquake at the Milan hypocenter. Parameters to be varied include hydraulic properties of sedimentary rock units, crystalline basement and the fault zone, as well as the (poorly resolved) Milan earthquake hypocenter depth.

Inventory of drainage wells and potential sources of contaminants to drainage-well inflow in Southwest Orlando, Orange County, Florida

USGS Publications Warehouse

Taylor, George Fred

1993-01-01

Potential sources of contaminants that could pose a threat to drainage-well inflow and to water in the Floridan aquifer system in southwest Orlando, Florida, were studied between October and December 1990. Drainage wells and public-supply wells were inventoried in a 14-square-mile area, and available data on land use and activities within each drainage well basin were tabulated. Three public-supply wells (tapping the Lower Floridan aquifer) and 38 drainage wells (open to the Upper Floridan aquifer) were located in 17 drainage basins within the study area. The primary sources of drainage-well inflow are lake overflow, street runoff, seepage from the surficial aquifer system, and process-wastewater disposal. Drainage-well inflow from a variety of ares, including resi- dential, commercial, undeveloped, paved, and industrial areas, are potential sources of con- taminants. The four general types of possible contaminants to drainage-well inflow are inorganic chemicals, organic compounds, turbidity, and microbiological contaminants. Potential contami- nant sources include plant nurseries, citrus groves, parking lots, plating companies, auto- motive repair shops, and most commonly, lake- overflow water. Drainage wells provide a pathway for contaminants to enter the Upper Floridan aquifer and there is a potential for contaminants to move downward from the Upper Floridan to the Lower Floridan aquifer.

Gene expression programming approach for the estimation of moisture ratio in herbal plants drying with vacuum heat pump dryer

NASA Astrophysics Data System (ADS)

Dikmen, Erkan; Ayaz, Mahir; Gül, Doğan; Şahin, Arzu Şencan

2017-07-01

The determination of drying behavior of herbal plants is a complex process. In this study, gene expression programming (GEP) model was used to determine drying behavior of herbal plants as fresh sweet basil, parsley and dill leaves. Time and drying temperatures are input parameters for the estimation of moisture ratio of herbal plants. The results of the GEP model are compared with experimental drying data. The statistical values as mean absolute percentage error, root-mean-squared error and R-square are used to calculate the difference between values predicted by the GEP model and the values actually observed from the experimental study. It was found that the results of the GEP model and experimental study are in moderately well agreement. The results have shown that the GEP model can be considered as an efficient modelling technique for the prediction of moisture ratio of herbal plants.

An analytical drain current model for symmetric double-gate MOSFETs

NASA Astrophysics Data System (ADS)

Yu, Fei; Huang, Gongyi; Lin, Wei; Xu, Chuanzhong

2018-04-01

An analytical surface-potential-based drain current model of symmetric double-gate (sDG) MOSFETs is described as a SPICE compatible model in this paper. The continuous surface and central potentials from the accumulation to the strong inversion regions are solved from the 1-D Poisson's equation in sDG MOSFETs. Furthermore, the drain current is derived from the charge sheet model as a function of the surface potential. Over a wide range of terminal voltages, doping concentrations, and device geometries, the surface potential calculation scheme and drain current model are verified by solving the 1-D Poisson's equation based on the least square method and using the Silvaco Atlas simulation results and experimental data, respectively. Such a model can be adopted as a useful platform to develop the circuit simulator and provide the clear understanding of sDG MOSFET device physics.

A square root ensemble Kalman filter application to a motor-imagery brain-computer interface

PubMed Central

Kamrunnahar, M.; Schiff, S. J.

2017-01-01

We here investigated a non-linear ensemble Kalman filter (SPKF) application to a motor imagery brain computer interface (BCI). A square root central difference Kalman filter (SR-CDKF) was used as an approach for brain state estimation in motor imagery task performance, using scalp electroencephalography (EEG) signals. Healthy human subjects imagined left vs. right hand movements and tongue vs. bilateral toe movements while scalp EEG signals were recorded. Offline data analysis was conducted for training the model as well as for decoding the imagery movements. Preliminary results indicate the feasibility of this approach with a decoding accuracy of 78%–90% for the hand movements and 70%–90% for the tongue-toes movements. Ongoing research includes online BCI applications of this approach as well as combined state and parameter estimation using this algorithm with different system dynamic models. PMID:22255799

[Temperature compensation for portable Vis/NIR spectrometer measurement of apple fruit soluble solids contents].

PubMed

Wang, Jia-hua; Qi, Shu-ye; Tang, Zhi-hui; Jia, Shou-xing; Li, Yong-yu

2012-05-01

Visible (Vis)/near infrared (NIR) spectroscopy has been used successfully to measure soluble solids content (SSC) in fruit. However, for practical implementation, the NIR technique needs to be able to compensate for fruit temperature fluctuations, as it was observed that the sample temperature affects the NIR spectrum. A portable Vis/NIR spectrometer was used to collect diffused transmittance spectra of apples at different temperatures (0-30 degrees C). The spectral data of apple at 20 degrees C was used to develop a norm partial least squares (PLS) model. Slope/bias technique was found to well suits to control the accuracy of the calibration model for SSC concerning temperature fluctuations. The correctional PLS models were used to predict the SSC of apple at 0, 10 and 30 degrees C, respectively. The correctional method was found to perform well with Q values of 0.810, 0.822 and 0.802, respectively. When no precautions are taken, the Q value on the SSC may be as small as 0.525-0.680. The results obtained highlight the potential of portable Vis/NIR instruments for assessing internal quality of fruits on site under varying weather conditions.

A multidimensional stability model for predicting shallow landslide size and shape across landscapes.

PubMed

Milledge, David G; Bellugi, Dino; McKean, Jim A; Densmore, Alexander L; Dietrich, William E

2014-11-01

The size of a shallow landslide is a fundamental control on both its hazard and geomorphic importance. Existing models are either unable to predict landslide size or are computationally intensive such that they cannot practically be applied across landscapes. We derive a model appropriate for natural slopes that is capable of predicting shallow landslide size but simple enough to be applied over entire watersheds. It accounts for lateral resistance by representing the forces acting on each margin of potential landslides using earth pressure theory and by representing root reinforcement as an exponential function of soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are well constrained by field data. The model predicts failure for the observed scar geometry and finds that larger or smaller conformal shapes are more stable. Numerical experiments demonstrate that friction on the boundaries of a potential landslide increases considerably the magnitude of lateral reinforcement, relative to that due to root cohesion alone. We find that there is a critical depth in both cohesive and cohesionless soils, resulting in a minimum size for failure, which is consistent with observed size-frequency distributions. Furthermore, the differential resistance on the boundaries of a potential landslide is responsible for a critical landslide shape which is longer than it is wide, consistent with observed aspect ratios. Finally, our results show that minimum size increases as approximately the square of failure surface depth, consistent with observed landslide depth-area data.

Using Small Unmanned Aerial Systems to Advance Hydrological Models in Coastal Watersheds

NASA Astrophysics Data System (ADS)

Moorhead, R.; Hathcock, L.; Coffey, J. J.; Hood, R. E.; van Cooten, S.; Choate, K.; Rawson, H.; Kosturock, A.

2014-12-01

Small unmanned aerial systems (sUASs) have the potential to provide highly useful information for models of earth systems that vary over time intervals of days and for which sub-meter resolution is crucial. In particular, the state of coastal watershed plains are highly dependent on vegetation type and cover, soil type, weather, river flooding, and coastal inundation. The vegetation type and cover affect the drying potential, as well as the watershed's resistance to flood water movement. The soil type, soil moisture, and pond depths affect the ability of the watershed to absorb river flood waters and inundation from the sea. In this presentation we will describe a data collection campaign and model modification effort for hydrological models in a coastal watershed. The data collection campaign is obtaining data bimonthly using multiple UASs to capture the state of the watershed quicker. In particular, the vegetation cover and the extent of the water surface expression are captured at approximately a 1 inch spatial resolution over a few days with sUASs that can image 1-2 square miles per hour. The vegetation data provides a time-varying input to improve the estimation of the roughness coefficient and the dry potential from the traditionally static datasets. By correlating the high spatio-temporal resolution surface water expression with data from approximately ten river gauges, models can be improved and validated under more conditions. The presentation will also discuss the requisite sUAS capabilities and our experience in using them.

A multidimensional stability model for predicting shallow landslide size and shape across landscapes

PubMed Central

Milledge, David G; Bellugi, Dino; McKean, Jim A; Densmore, Alexander L; Dietrich, William E

2014-01-01

The size of a shallow landslide is a fundamental control on both its hazard and geomorphic importance. Existing models are either unable to predict landslide size or are computationally intensive such that they cannot practically be applied across landscapes. We derive a model appropriate for natural slopes that is capable of predicting shallow landslide size but simple enough to be applied over entire watersheds. It accounts for lateral resistance by representing the forces acting on each margin of potential landslides using earth pressure theory and by representing root reinforcement as an exponential function of soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are well constrained by field data. The model predicts failure for the observed scar geometry and finds that larger or smaller conformal shapes are more stable. Numerical experiments demonstrate that friction on the boundaries of a potential landslide increases considerably the magnitude of lateral reinforcement, relative to that due to root cohesion alone. We find that there is a critical depth in both cohesive and cohesionless soils, resulting in a minimum size for failure, which is consistent with observed size-frequency distributions. Furthermore, the differential resistance on the boundaries of a potential landslide is responsible for a critical landslide shape which is longer than it is wide, consistent with observed aspect ratios. Finally, our results show that minimum size increases as approximately the square of failure surface depth, consistent with observed landslide depth-area data. PMID:26213663

Closed form solution for a double quantum well using Gröbner basis

NASA Astrophysics Data System (ADS)

Acus, A.; Dargys, A.

2011-07-01

Analytical expressions for the spectrum, eigenfunctions and dipole matrix elements of a square double quantum well (DQW) are presented for a general case when the potential in different regions of the DQW has different heights and the effective masses are different. This was achieved by using a Gröbner basis algorithm that allowed us to disentangle the resulting coupled polynomials without explicitly solving the transcendental eigenvalue equation.

The hypoxia model in human psychopharmacology: neurophysiological and psychometric studies with aniracetam i.v.

PubMed

Saletu, B; Grünberger, J

1984-01-01

Changes in human brain function and mental performance under hypoxic hypoxidosis as well as after intravenous injection of aniracetam - a new potentially nootropic 2-pyrrolidinone derivative - were investigated in a double-blind placebo-controlled study utilizing computer-assisted spectral analysis of the EEG and psychometric tests. Hypoxic hypoxidosis was induced by a fixed gas combination of 11.2% O2 and 88.8% N2, which was inhaled under normobaric conditions by 10 male healthy volunteers. The following substances were injected intravenously at weekly intervals according to a latin square design: placebo, 10 mg and 100 mg aniracetam and the solvent under hypoxic conditions as well as placebo under normoxic conditions. Spectral analysis of the EEG recorded under hypoxia demonstrated neurophysiological alterations indicative of a deterioration in vigilance, which was also reflected by a deterioration in psychomotor activity and mnestic performance in the psychometric tests. Aniracetam i.v. attenuated the hypoxia-induced deterioration of brain function and mental performance, thus exhibiting protective properties against hypoxia in man. The usefulness of the hypoxia model in the screening of antihypoxidotic compounds is discussed.

Two ultraviolet radiation datasets that cover China

NASA Astrophysics Data System (ADS)

Liu, Hui; Hu, Bo; Wang, Yuesi; Liu, Guangren; Tang, Liqin; Ji, Dongsheng; Bai, Yongfei; Bao, Weikai; Chen, Xin; Chen, Yunming; Ding, Weixin; Han, Xiaozeng; He, Fei; Huang, Hui; Huang, Zhenying; Li, Xinrong; Li, Yan; Liu, Wenzhao; Lin, Luxiang; Ouyang, Zhu; Qin, Boqiang; Shen, Weijun; Shen, Yanjun; Su, Hongxin; Song, Changchun; Sun, Bo; Sun, Song; Wang, Anzhi; Wang, Genxu; Wang, Huimin; Wang, Silong; Wang, Youshao; Wei, Wenxue; Xie, Ping; Xie, Zongqiang; Yan, Xiaoyuan; Zeng, Fanjiang; Zhang, Fawei; Zhang, Yangjian; Zhang, Yiping; Zhao, Chengyi; Zhao, Wenzhi; Zhao, Xueyong; Zhou, Guoyi; Zhu, Bo

2017-07-01

Ultraviolet (UV) radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization's measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes.

Body shape helps legged robots climb and turn in complex 3-D terrains

NASA Astrophysics Data System (ADS)

Han, Yuanfeng; Wang, Zheliang; Li, Chen

Analogous to streamlined shapes that reduce drag in fluids, insects' ellipsoid-like rounded body shapes were recently discovered to be ``terradynamically streamlined'' and enhance locomotion in cluttered terrain by facilitating body rolling. Here, we hypothesize that there exist more terradynamic shapes that facilitate other modes of locomotion like climbing and turning in complex 3-D terrains by facilitating body pitching and yawing. To test our hypothesis, we modified the body shape of a legged robot by adding an elliptical and a rectangular shell and tested how it negotiated with circular and square vertical pillars. With a rectangular shell the robot always pitched against square pillars in an attempt to climb, whereas with an elliptical shell it always yawed and turned away from circular pillars given a small initial lateral displacement. Square / circular pillars facilitated pitching / yawing, respectively. To begin to reveal the contact physics, we developed a locomotion energy landscape model. Our model revealed that potential energy barriers to transition from pitching to yawing are high for angular locomotor and obstacle shapes (rectangular / square) but vanish for rounded shapes (elliptical / circular). Our study supports the plausibility of locomotion energy landscapes for understanding the rich locomotor transitions in complex 3-D terrains.

An efficient method for model refinement in diffuse optical tomography

NASA Astrophysics Data System (ADS)

Zirak, A. R.; Khademi, M.

2007-11-01

Diffuse optical tomography (DOT) is a non-linear, ill-posed, boundary value and optimization problem which necessitates regularization. Also, Bayesian methods are suitable owing to measurements data are sparse and correlated. In such problems which are solved with iterative methods, for stabilization and better convergence, the solution space must be small. These constraints subject to extensive and overdetermined system of equations which model retrieving criteria specially total least squares (TLS) must to refine model error. Using TLS is limited to linear systems which is not achievable when applying traditional Bayesian methods. This paper presents an efficient method for model refinement using regularized total least squares (RTLS) for treating on linearized DOT problem, having maximum a posteriori (MAP) estimator and Tikhonov regulator. This is done with combination Bayesian and regularization tools as preconditioner matrices, applying them to equations and then using RTLS to the resulting linear equations. The preconditioning matrixes are guided by patient specific information as well as a priori knowledge gained from the training set. Simulation results illustrate that proposed method improves the image reconstruction performance and localize the abnormally well.

The contribution of China’s emissions to global climate forcing

NASA Astrophysics Data System (ADS)

Li, Bengang; Gasser, Thomas; Ciais, Philippe; Piao, Shilong; Tao, Shu; Balkanski, Yves; Hauglustaine, Didier; Boisier, Juan-Pablo; Chen, Zhuo; Huang, Mengtian; Li, Laurent Zhaoxin; Li, Yue; Liu, Hongyan; Liu, Junfeng; Peng, Shushi; Shen, Zehao; Sun, Zhenzhong; Wang, Rong; Wang, Tao; Yin, Guodong; Yin, Yi; Zeng, Hui; Zeng, Zhenzhong; Zhou, Feng

2016-03-01

Knowledge of the contribution that individual countries have made to global radiative forcing is important to the implementation of the agreement on “common but differentiated responsibilities” reached by the United Nations Framework Convention on Climate Change. Over the past three decades, China has experienced rapid economic development, accompanied by increased emission of greenhouse gases, ozone precursors and aerosols, but the magnitude of the associated radiative forcing has remained unclear. Here we use a global coupled biogeochemistry-climate model and a chemistry and transport model to quantify China’s present-day contribution to global radiative forcing due to well-mixed greenhouse gases, short-lived atmospheric climate forcers and land-use-induced regional surface albedo changes. We find that China contributes 10% ± 4% of the current global radiative forcing. China’s relative contribution to the positive (warming) component of global radiative forcing, mainly induced by well-mixed greenhouse gases and black carbon aerosols, is 12% ± 2%. Its relative contribution to the negative (cooling) component is 15% ± 6%, dominated by the effect of sulfate and nitrate aerosols. China’s strongest contributions are 0.16 ± 0.02 watts per square metre for CO2 from fossil fuel burning, 0.13 ± 0.05 watts per square metre for CH4, -0.11 ± 0.05 watts per square metre for sulfate aerosols, and 0.09 ± 0.06 watts per square metre for black carbon aerosols. China’s eventual goal of improving air quality will result in changes in radiative forcing in the coming years: a reduction of sulfur dioxide emissions would drive a faster future warming, unless offset by larger reductions of radiative forcing from well-mixed greenhouse gases and black carbon.

The contribution of China's emissions to global climate forcing.

PubMed

Li, Bengang; Gasser, Thomas; Ciais, Philippe; Piao, Shilong; Tao, Shu; Balkanski, Yves; Hauglustaine, Didier; Boisier, Juan-Pablo; Chen, Zhuo; Huang, Mengtian; Li, Laurent Zhaoxin; Li, Yue; Liu, Hongyan; Liu, Junfeng; Peng, Shushi; Shen, Zehao; Sun, Zhenzhong; Wang, Rong; Wang, Tao; Yin, Guodong; Yin, Yi; Zeng, Hui; Zeng, Zhenzhong; Zhou, Feng

2016-03-17

Knowledge of the contribution that individual countries have made to global radiative forcing is important to the implementation of the agreement on "common but differentiated responsibilities" reached by the United Nations Framework Convention on Climate Change. Over the past three decades, China has experienced rapid economic development, accompanied by increased emission of greenhouse gases, ozone precursors and aerosols, but the magnitude of the associated radiative forcing has remained unclear. Here we use a global coupled biogeochemistry-climate model and a chemistry and transport model to quantify China's present-day contribution to global radiative forcing due to well-mixed greenhouse gases, short-lived atmospheric climate forcers and land-use-induced regional surface albedo changes. We find that China contributes 10% ± 4% of the current global radiative forcing. China's relative contribution to the positive (warming) component of global radiative forcing, mainly induced by well-mixed greenhouse gases and black carbon aerosols, is 12% ± 2%. Its relative contribution to the negative (cooling) component is 15% ± 6%, dominated by the effect of sulfate and nitrate aerosols. China's strongest contributions are 0.16 ± 0.02 watts per square metre for CO2 from fossil fuel burning, 0.13 ± 0.05 watts per square metre for CH4, -0.11 ± 0.05 watts per square metre for sulfate aerosols, and 0.09 ± 0.06 watts per square metre for black carbon aerosols. China's eventual goal of improving air quality will result in changes in radiative forcing in the coming years: a reduction of sulfur dioxide emissions would drive a faster future warming, unless offset by larger reductions of radiative forcing from well-mixed greenhouse gases and black carbon.

Non-perturbative reheating and Nnaturalness

NASA Astrophysics Data System (ADS)

Hardy, Edward

2017-11-01

We study models in which reheating happens only through non-perturbative processes. The energy transferred can be exponentially suppressed unless the inflaton is coupled to a particle with a parametrically small mass. Additionally, in some models a light scalar with a negative mass squared parameter leads to much more efficient reheating than one with a positive mass squared of the same magnitude. If a theory contains many sectors similar to the Standard Model coupled to the inflaton via their Higgses, such dynamics can realise the Nnaturalness solution to the hierarchy problem. A sector containing a light Higgs with a non-zero vacuum expectation value is dominantly reheated and there is little energy transferred to the other sectors, consistent with cosmological constraints. The inflaton must decouple from other particles and have a flat potential at large field values, in which case the visible sector UV cutoff can be raised to 10 TeV in a simple model.

Parameter estimation of Monod model by the Least-Squares method for microalgae Botryococcus Braunii sp

NASA Astrophysics Data System (ADS)

See, J. J.; Jamaian, S. S.; Salleh, R. M.; Nor, M. E.; Aman, F.

2018-04-01

This research aims to estimate the parameters of Monod model of microalgae Botryococcus Braunii sp growth by the Least-Squares method. Monod equation is a non-linear equation which can be transformed into a linear equation form and it is solved by implementing the Least-Squares linear regression method. Meanwhile, Gauss-Newton method is an alternative method to solve the non-linear Least-Squares problem with the aim to obtain the parameters value of Monod model by minimizing the sum of square error ( SSE). As the result, the parameters of the Monod model for microalgae Botryococcus Braunii sp can be estimated by the Least-Squares method. However, the estimated parameters value obtained by the non-linear Least-Squares method are more accurate compared to the linear Least-Squares method since the SSE of the non-linear Least-Squares method is less than the linear Least-Squares method.

A non-linear data mining parameter selection algorithm for continuous variables

PubMed Central

Razavi, Marianne; Brady, Sean

2017-01-01

In this article, we propose a new data mining algorithm, by which one can both capture the non-linearity in data and also find the best subset model. To produce an enhanced subset of the original variables, a preferred selection method should have the potential of adding a supplementary level of regression analysis that would capture complex relationships in the data via mathematical transformation of the predictors and exploration of synergistic effects of combined variables. The method that we present here has the potential to produce an optimal subset of variables, rendering the overall process of model selection more efficient. This algorithm introduces interpretable parameters by transforming the original inputs and also a faithful fit to the data. The core objective of this paper is to introduce a new estimation technique for the classical least square regression framework. This new automatic variable transformation and model selection method could offer an optimal and stable model that minimizes the mean square error and variability, while combining all possible subset selection methodology with the inclusion variable transformations and interactions. Moreover, this method controls multicollinearity, leading to an optimal set of explanatory variables. PMID:29131829

Simulation of ground-water flow in the Saginaw Aquifer, Clinton, Eaton, and Ingham counties, Michigan

USGS Publications Warehouse

Holtschlag, David J.; Luukkonen, Carol L.; Nicholas, J.R.

1996-01-01

A numerical model was developed to simulate ground-water flow in the Tri-County region, which consists of Clinton, Eaton, and Ingham Counties, Michigan. This region includes a nine-township area surrounding Lansing, Michigan. The model simulates the regional response of the Saginaw aquifer to major groundwater withdrawals associated with public-supply wells. The Saginaw aquifer, which is in the Grand River and Saginaw Formations of Pennsylvanian age, is the primary source of ground water for Tri-County residents. The Saginaw aquifer is overlain by glacial deposits, which also are important ground-water sources in some locations. Flow in the Saginaw aquifer and the glacial deposits is simulated by discretizing the flow system into model cells arranged in two layers. Each cell, which corresponds to a land area of 0.0625 square mile, represents the locally averaged properties of the system. The spatial variation of hydraulic properties controlling ground-water flow was estimated by geostatistical analysis of 4,947 well logs. Parameter estimation, a form of nonlinear regression, was used to calibrate the flow model. Results of steady-state ground-water-flow simulations show close agreement between water flowing into and out of the model area for 1992 pumping conditions; standard error of the difference between simulated and measured heads is 14.7 feet. Simulation results for three alternative pumping scenarios for the year 2020 show that the glacial aquifer could be dewatered in places if hypothetical increases in pumping are not distributed throughout the Tri-County region. Contributing areas to public-supply wells in the nine-township area were delineated by a particle-tracking analysis. These areas cover about 121 square miles. Contributing areas for particles having travel times of 40 years or less cover about 42 square miles. Results of tritium sampling support results of model simulations to delineate contributing areas.

The square lattice Ising model on the rectangle II: finite-size scaling limit

NASA Astrophysics Data System (ADS)

Hucht, Alfred

2017-06-01

Based on the results published recently (Hucht 2017 J. Phys. A: Math. Theor. 50 065201), the universal finite-size contributions to the free energy of the square lattice Ising model on the L× M rectangle, with open boundary conditions in both directions, are calculated exactly in the finite-size scaling limit L, M\\to∞ , T\\to Tc , with fixed temperature scaling variable x\\propto(T/Tc-1)M and fixed aspect ratio ρ\\propto L/M . We derive exponentially fast converging series for the related Casimir potential and Casimir force scaling functions. At the critical point T=Tc we confirm predictions from conformal field theory (Cardy and Peschel 1988 Nucl. Phys. B 300 377, Kleban and Vassileva 1991 J. Phys. A: Math. Gen. 24 3407). The presence of corners and the related corner free energy has dramatic impact on the Casimir scaling functions and leads to a logarithmic divergence of the Casimir potential scaling function at criticality.

Characterizing ISI and sub-threshold membrane potential distributions: Ensemble of IF neurons with random squared-noise intensity.

PubMed

Kumar, Sanjeev; Karmeshu

2018-04-01

A theoretical investigation is presented that characterizes the emerging sub-threshold membrane potential and inter-spike interval (ISI) distributions of an ensemble of IF neurons that group together and fire together. The squared-noise intensity σ 2 of the ensemble of neurons is treated as a random variable to account for the electrophysiological variations across population of nearly identical neurons. Employing superstatistical framework, both ISI distribution and sub-threshold membrane potential distribution of neuronal ensemble are obtained in terms of generalized K-distribution. The resulting distributions exhibit asymptotic behavior akin to stretched exponential family. Extensive simulations of the underlying SDE with random σ 2 are carried out. The results are found to be in excellent agreement with the analytical results. The analysis has been extended to cover the case corresponding to independent random fluctuations in drift in addition to random squared-noise intensity. The novelty of the proposed analytical investigation for the ensemble of IF neurons is that it yields closed form expressions of probability distributions in terms of generalized K-distribution. Based on a record of spiking activity of thousands of neurons, the findings of the proposed model are validated. The squared-noise intensity σ 2 of identified neurons from the data is found to follow gamma distribution. The proposed generalized K-distribution is found to be in excellent agreement with that of empirically obtained ISI distribution of neuronal ensemble. Copyright © 2018 Elsevier B.V. All rights reserved.

Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods.

PubMed

Durakli Velioglu, Serap; Ercioglu, Elif; Boyaci, Ismail Hakki

2017-05-01

This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

Prediction of Radical Scavenging Activities of Anthocyanins Applying Adaptive Neuro-Fuzzy Inference System (ANFIS) with Quantum Chemical Descriptors

PubMed Central

Jhin, Changho; Hwang, Keum Taek

2014-01-01

Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS) is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR) models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A) and electronegativity (χ) of flavylium cation, and ionization potential (I) of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively. PMID:25153627

Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm.

PubMed

Jiang, Hui; Liu, Guohai; Mei, Congli; Yu, Shuang; Xiao, Xiahong; Ding, Yuhan

2012-11-01

The feasibility of rapid determination of the process variables (i.e. pH and moisture content) in solid-state fermentation (SSF) of wheat straw using Fourier transform near infrared (FT-NIR) spectroscopy was studied. Synergy interval partial least squares (siPLS) algorithm was implemented to calibrate regression model. The number of PLS factors and the number of subintervals were optimized simultaneously by cross-validation. The performance of the prediction model was evaluated according to the root mean square error of cross-validation (RMSECV), the root mean square error of prediction (RMSEP) and the correlation coefficient (R). The measurement results of the optimal model were obtained as follows: RMSECV=0.0776, R(c)=0.9777, RMSEP=0.0963, and R(p)=0.9686 for pH model; RMSECV=1.3544% w/w, R(c)=0.8871, RMSEP=1.4946% w/w, and R(p)=0.8684 for moisture content model. Finally, compared with classic PLS and iPLS models, the siPLS model revealed its superior performance. The overall results demonstrate that FT-NIR spectroscopy combined with siPLS algorithm can be used to measure process variables in solid-state fermentation of wheat straw, and NIR spectroscopy technique has a potential to be utilized in SSF industry. Copyright © 2012 Elsevier B.V. All rights reserved.

Confounding by dietary patterns of the inverse association between alcohol consumption and type 2 diabetes risk.

PubMed

Imamura, Fumiaki; Lichtenstein, Alice H; Dallal, Gerard E; Meigs, James B; Jacques, Paul F

2009-07-01

The ability to interpret epidemiologic observations is limited because of potential residual confounding by correlated dietary components. Dietary pattern analyses by factor analysis or partial least squares may overcome the limitation. To examine confounding by dietary pattern as well as standard risk factors and selected nutrients, the authors modeled the longitudinal association between alcohol consumption and 7-year risk of type 2 diabetes mellitus in 2,879 healthy adults enrolled in the Framingham Offspring Study (1991-2001) by Cox proportional hazard models. After adjustment for standard risk factors, consumers of > or =9.0 drinks/week had a significantly lower risk of type 2 diabetes mellitus compared with abstainers (hazard ratio = 0.47, 95% confidence interval (CI): 0.27, 0.81). Adjustment for selected nutrients had little effect on the hazard ratio, whereas adjustment for dietary pattern variables by factor analysis significantly shifted the hazard ratio away from null (hazard ratio = 0.33, 95% CI: 0.17, 0.64) by 40.0% (95% CI: 16.8, 57.0; P = 0.002). Dietary pattern variables by partial least squares showed similar results. Therefore, the observed inverse association, consistent with past studies, was confounded by dietary patterns, and this confounding was not captured by individual nutrient adjustment. The data suggest that alcohol intake, not dietary patterns associated with alcohol intake, is responsible for the observed inverse association with type 2 diabetes mellitus risk.

Simultaneous quantitative analysis of olmesartan, amlodipine and hydrochlorothiazide in their combined dosage form utilizing classical and alternating least squares based chemometric methods.

PubMed

Darwish, Hany W; Bakheit, Ahmed H; Abdelhameed, Ali S

2016-03-01

Simultaneous spectrophotometric analysis of a multi-component dosage form of olmesartan, amlodipine and hydrochlorothiazide used for the treatment of hypertension has been carried out using various chemometric methods. Multivariate calibration methods include classical least squares (CLS) executed by net analyte processing (NAP-CLS), orthogonal signal correction (OSC-CLS) and direct orthogonal signal correction (DOSC-CLS) in addition to multivariate curve resolution-alternating least squares (MCR-ALS). Results demonstrated the efficiency of the proposed methods as quantitative tools of analysis as well as their qualitative capability. The three analytes were determined precisely using the aforementioned methods in an external data set and in a dosage form after optimization of experimental conditions. Finally, the efficiency of the models was validated via comparison with the partial least squares (PLS) method in terms of accuracy and precision.

A method to estimate statistical errors of properties derived from charge-density modelling

PubMed Central

Lecomte, Claude

2018-01-01

Estimating uncertainties of property values derived from a charge-density model is not straightforward. A methodology, based on calculation of sample standard deviations (SSD) of properties using randomly deviating charge-density models, is proposed with the MoPro software. The parameter shifts applied in the deviating models are generated in order to respect the variance–covariance matrix issued from the least-squares refinement. This ‘SSD methodology’ procedure can be applied to estimate uncertainties of any property related to a charge-density model obtained by least-squares fitting. This includes topological properties such as critical point coordinates, electron density, Laplacian and ellipticity at critical points and charges integrated over atomic basins. Errors on electrostatic potentials and interaction energies are also available now through this procedure. The method is exemplified with the charge density of compound (E)-5-phenylpent-1-enylboronic acid, refined at 0.45 Å resolution. The procedure is implemented in the freely available MoPro program dedicated to charge-density refinement and modelling. PMID:29724964

The Mississippi Embayment Regional Aquifer Study (MERAS): Documentation of a Groundwater-Flow Model Constructed to Assess Water Availability in the Mississippi Embayment

USGS Publications Warehouse

Clark, Brian R.; Hart, Rheannon M.

2009-01-01

The Mississippi Embayment Regional Aquifer Study (MERAS) was conducted with support from the Groundwater Resources Program of the U.S. Geological Survey Office of Groundwater. This report documents the construction and calibration of a finite-difference groundwater model for use as a tool to quantify groundwater availability within the Mississippi embayment. To approximate the differential equation, the MERAS model was constructed with the U.S. Geological Survey's modular three-dimensional finite-difference code, MODFLOW-2005; the preconditioned conjugate gradient solver within MODFLOW-2005 was used for the numerical solution technique. The model area boundary is approximately 78,000 square miles and includes eight States with approximately 6,900 miles of simulated streams, 70,000 well locations, and 10 primary hydrogeologic units. The finite-difference grid consists of 414 rows, 397 columns, and 13 layers. Each model cell is 1 square mile with varying thickness by cell and by layer. The simulation period extends from January 1, 1870, to April 1, 2007, for a total of 137 years and 69 stress periods. The first stress period is simulated as steady state to represent predevelopment conditions. Areal recharge is applied throughout the MERAS model area using the MODFLOW-2005 Recharge Package. Irrigation, municipal, and industrial wells are simulated using the Multi-Node Well Package. There are 43 streams simulated by the MERAS model. Each stream or river in the model area was simulated using the Streamflow-Routing Package. The perimeter of the model area and the base of the flow system are represented as no-flow boundaries. The downgradient limit of each model layer is a no-flow boundary, which approximates the extent of water with less than 10,000 milligrams per liter of dissolved solids. The MERAS model was calibrated by making manual changes to parameter values and examining residuals for hydraulic heads and streamflow. Additional calibration was achieved through alternate use of UCODE-2005 and PEST. Simulated heads were compared to 55,786 hydraulic-head measurements from 3,245 wells in the MERAS model area. Values of root mean square error between simulated and observed hydraulic heads of all observations ranged from 8.33 feet in 1919 to 47.65 feet in 1951, though only six root mean square error values are greater than 40 feet for the entire simulation period. Simulated streamflow generally is lower than measured streamflow for streams with streamflow less than 1,000 cubic feet per second, and greater than measured streamflow for streams with streamflow more than 1,000 cubic feet per second. Simulated streamflow is underpredicted for 18 observations and overpredicted for 10 observations in the model. These differences in streamflow illustrate the large uncertainty in model inputs such as predevelopment recharge, overland flow, pumpage (from stream and aquifer), precipitation, and observation weights. The groundwater-flow budget indicates changes in flow into (inflows) and out of (outflows) the model area during the pregroundwater-irrigation period (pre-1870) to 2007. Total flow (sum of inflows or outflows) through the model ranged from about 600 million gallons per day prior to development to 18,197 million gallons per day near the end of the simulation. The pumpage from wells represents the largest outflow components with a net rate of 18,197 million gallons per day near the end of the model simulation in 2006. Groundwater outflows are offset primarily by inflow from aquifer storage and recharge.

Validation of a Ground-Water Flow Model of the Mississippi River Valley Alluvial Aquifer Using Water-Level and Water-Use Data for 1998-2005 and Evaluation of Water-Use Scenarios

USGS Publications Warehouse

Gillip, Jonathan A.; Czarnecki, John B.

2009-01-01

A ground-water flow model of the Mississippi River Valley alluvial aquifer in eastern Arkansas, developed in 2003 to simulate the period of 1918-98, was validated with the addition of water-level and water-use data that extended the observation period to 2005. The original model (2003) was calibrated using water-level observations from 1972, 1982, 1992, and 1998, and water-use data through 1997. The original model subsequently was used to simulate water levels from 1999 to 2049 and showed that simulation of continued pumping at the 1997 water-use rate could not be sustained indefinitely without causing dry cells in the model. After publication of the original ground-water flow model, a total of 3,616 water-level observations from 698 locations measured during the period of 1998 to 2005 became available. Additionally, water-use data were compiled and used for the same period, totaling 290,005 discrete water-use values from 43,440 wells with as many as 39,169 wells pumping in any one year. Total pumping (which is primarily agricultural) for this 8-year period was about 2.3 trillion cubic feet of water and was distributed over approximately 10,340 square miles within the model area. An updated version of the original ground-water flow model was used to simulate the period of 1998-2005 with the additional water-level and water-use data. Water-level observations for 1998-2005 ranged from 74 to 293 feet above National Geodetic Vertical Datum of 1929 across the model area. The maximum water-level residual (observed minus simulated water-level values) for the 3,616 water-level observations was 52 feet, the minimum water-level residual was 60 feet, the average annual root mean squared error was 8.2 feet, and the annual average absolute residual was 6.0 feet. A correlation coefficient value of 0.96 was calculated for the line of best fit for observed to simulated water levels for the combined 1998-2005 dataset, indicating a good fit to the data and an acceptable validation of the model. After the validation process was completed, additional ground-water model simulations were run to evaluate the response of the aquifer with the 2005 water-use rate applied through 2049 (scenario 1) and the 2005 water-use rate increased 2 percent annually until 2049 (scenario 2). Scenario 1 resulted in 779 dry cells (779 square miles) by 2049 and scenario 2 resulted in 2,910 dry cells (2,910 square miles) by 2049. In both scenarios, the dry cells are concentrated in the Grand Prairie area and Cache River area west of Crowleys Ridge. However, scenario 2 resulted in dry cells to the east of Crowleys Ridge as well. A simulation applying the 1997 water-use rate contained in the original ground-water flow model resulted in 401 dry cells (401 square miles) in the Grand Prairie and Cache River areas.

A simulation of dielectrophoresis force actuated liquid lens

NASA Astrophysics Data System (ADS)

Yao, Xiaoyin; Xia, Jun

2009-11-01

Dielectrophoresis (DEP) and electrowetting on dielectric (EWOD) are based on the electrokinetic mechanisms which have great potential in microfluidic manipulation. DEP dominate the movement of particles induced by polarization effects in nonuniform electric field ,while EWOD has become one of the most widely used tools for manipulating tiny amounts of liquids on solid surfaces. Liquid lens driven by EWOD have been well studied and developed. But liquid lens driven by DEP has not been studied adequately. This paper focuses on modeling liquid lens driven by DEP force. A simulation of DEP driven droplet dynamics was performed by coupling of the electrostatic field and the two-phase flow field. Two incompressible and dielectric liquids with different permittivity were chosen in the two-phase flow field. The DEP force density, in direct proportion to gradient of the square of the electric field intensity, was used as a body force density in Navier-Stokes equation. When voltage applied, the liquid with high permittivity flowed to the place where the gradient of the square of the electric field intensity was higher, and thus change the curvature of interface between two immiscible liquid. The differences between DEP and EWOD liquid lens were also presented.

Optimized equation of the state of the square-well fluid of variable range based on a fourth-order free-energy expansion.

PubMed

Espíndola-Heredia, Rodolfo; del Río, Fernando; Malijevsky, Anatol

2009-01-14

The free energy of square-well (SW) systems of hard-core diameter sigma with ranges 1 < or = lambda < or = 3 is expanded in a perturbation series. This interval covers most ranges of interest, from short-ranged SW fluids (lambda approximately 1.2) used in modeling colloids to long ranges (lambda approximately 3) where the van der Waals classic approximation holds. The first four terms are evaluated by means of extensive Monte Carlo simulations. The calculations are corrected for the thermodynamic limit and care is taken to evaluate and to control the various sources of error. The results for the first two terms in the series confirm well-known independent results but have an increased estimated accuracy and cover a wider set of well ranges. The results for the third- and fourth-order terms are novel. The free-energy expansion for systems with short and intermediate ranges, 1 < or = lambda < or = 2, is seen to have properties similar to those of systems with longer ranges, 2 < or = lambda < or = 3. An equation of state (EOS) is built to represent the free-energy data. The thermodynamics given by this EOS, confronted against independent computer simulations, is shown to predict accurately the internal energy, pressure, specific heat, and chemical potential of the SW fluids considered and for densities 0 < or = rho sigma(3) < or = 0.9 including subcritical temperatures. This fourth-order theory is estimated to be accurate except for a small region at high density, rho sigma(3) approximately 0.9, and low temperature where terms of still higher order might be needed.

Spectral ageing in the era of big data: integrated versus resolved models

NASA Astrophysics Data System (ADS)

Harwood, Jeremy J.

2017-04-01

Continuous injection models of spectral ageing have long been used to determine the age of radio galaxies from their integrated spectrum; however, many questions about their reliability remain unanswered. With various large area surveys imminent (e.g. LOw Frequency ARray, MeerKAT, Murchison Widefield Array) and planning for the next generation of radio interferometers are well underway (e.g. next generation VLA, Square Kilometre Array), investigations of radio galaxy physics are set to shift away from studies of individual sources to the population as a whole. Determining if and how integrated models of spectral ageing can be applied in the era of big data is therefore crucial. In this paper, I compare classical integrated models of spectral ageing to recent well-resolved studies that use modern analysis techniques on small spatial scales to determine their robustness and validity as a source selection method. I find that integrated models are unable to recover key parameters and, even when known a priori, provide a poor, frequency-dependent description of a source's spectrum. I show a disparity of up to a factor of 6 in age between the integrated and resolved methods but suggest, even with these inconsistencies, such models still provide a potential method of candidate selection in the search for remnant radio galaxies and in providing a cleaner selection of high redshift radio galaxies in z - α selected samples.

Morphology and the gradient of a symmetric potential predict gait transitions of dogs.

PubMed

Wilshin, Simon; Haynes, G Clark; Porteous, Jack; Koditschek, Daniel; Revzen, Shai; Spence, Andrew J

2017-08-01

Gaits and gait transitions play a central role in the movement of animals. Symmetry is thought to govern the structure of the nervous system, and constrain the limb motions of quadrupeds. We quantify the symmetry of dog gaits with respect to combinations of bilateral, fore-aft, and spatio-temporal symmetry groups. We tested the ability of symmetries to model motion capture data of dogs walking, trotting and transitioning between those gaits. Fully symmetric models performed comparably to asymmetric with only a [Formula: see text] increase in the residual sum of squares and only one-quarter of the parameters. This required adding a spatio-temporal shift representing a lag between fore and hind limbs. Without this shift, the symmetric model residual sum of squares was [Formula: see text] larger. This shift is related to (linear regression, [Formula: see text], [Formula: see text]) dog morphology. That this symmetry is respected throughout the gaits and transitions indicates that it generalizes outside a single gait. We propose that relative phasing of limb motions can be described by an interaction potential with a symmetric structure. This approach can be extended to the study of interaction of neurodynamic and kinematic variables, providing a system-level model that couples neuronal central pattern generator networks and mechanical models.

Optimal Partitioning of a Data Set Based on the "p"-Median Model

ERIC Educational Resources Information Center

Brusco, Michael J.; Kohn, Hans-Friedrich

2008-01-01

Although the "K"-means algorithm for minimizing the within-cluster sums of squared deviations from cluster centroids is perhaps the most common method for applied cluster analyses, a variety of other criteria are available. The "p"-median model is an especially well-studied clustering problem that requires the selection of "p" objects to serve as…

Nutritional Status of Rural Older Adults is Linked to Physical and Emotional Health

PubMed Central

Jung, Seung Eun; Bishop, Alex J; Kim, Minjung; Hermann, Janice; Kim, Giyeon; Lawrence, Jeannine

2017-01-01

Background Although nutritional status is influenced by multi-dimensional aspects encompassing physical and emotional well-being, there is limited research on this complex relationship. Objective The purpose of this study was to examine the interplay between indicators of physical health (perceived health status and self-care capacity) and emotional well-being (depressive affect and loneliness) on rural older adults’ nutritional status. Design The cross-sectional study was conducted from June 1, 2007 to June 1, 2008. Participants/setting A total of 171 community-dwelling older adults, 65 years and older, who resided within non-metro rural communities in the U.S. participated in this study. Main outcome measures Participants completed validated instruments measuring self-care capacity, perceived health status, loneliness, depressive affect, and nutritional status. Statistical analyses performed Structural equation modeling (SEM) was employed to investigate the complex interplay of physical and emotional health status with nutritional status among rural older adults, Chi-square statistic, CFI, RMSEA and SRMR were used to assess model fit. Results Chi-square statistic and the other model fit indices showed the hypothesized SEM model provided a good fit to the data (χ2 (2)=2.15, p=0.34; CFI=1.00; RMSEA=0.02; SRMR=0.03). Self-care capacity was significantly related with depressive affect (γ = −0.11, p=0.03) whereas self-care capacity was not significantly related with loneliness. Perceived health status had a significant negative relationship with both loneliness (γ = −0.16, p=0.03) and depressive affect (γ = −0.22, p=0.03). Although loneliness showed no significant direct relationship with nutritional status, it showed a significant direct relationship with depressive affect (β = 0.46, p<0.01). Finally, the results demonstrated that depressive affect had a significant negative relationship with nutritional status (β = −0.30, p<0.01). The results indicated physical health and emotional indicators have significant multi-dimensional associations with nutritional status among rural older adults. Conclusions The present study provides insights into the importance of addressing both physical and emotional well-being together to reduce potential effects of poor emotional well-being on nutritional status, particularly among rural older adults with impaired physical health and self-care capacity. PMID:28274787

Multivariate normality

NASA Technical Reports Server (NTRS)

Crutcher, H. L.; Falls, L. W.

1976-01-01

Sets of experimentally determined or routinely observed data provide information about the past, present and, hopefully, future sets of similarly produced data. An infinite set of statistical models exists which may be used to describe the data sets. The normal distribution is one model. If it serves at all, it serves well. If a data set, or a transformation of the set, representative of a larger population can be described by the normal distribution, then valid statistical inferences can be drawn. There are several tests which may be applied to a data set to determine whether the univariate normal model adequately describes the set. The chi-square test based on Pearson's work in the late nineteenth and early twentieth centuries is often used. Like all tests, it has some weaknesses which are discussed in elementary texts. Extension of the chi-square test to the multivariate normal model is provided. Tables and graphs permit easier application of the test in the higher dimensions. Several examples, using recorded data, illustrate the procedures. Tests of maximum absolute differences, mean sum of squares of residuals, runs and changes of sign are included in these tests. Dimensions one through five with selected sample sizes 11 to 101 are used to illustrate the statistical tests developed.

Comment on ‘A novel method for fast and robust estimation of fluorescence decay dynamics using constrained least-square deconvolution with Laguerre expansion’

NASA Astrophysics Data System (ADS)

Zhang, Yongliang; Day-Uei Li, David

2017-02-01

This comment is to clarify that Poisson noise instead of Gaussian noise shall be included to assess the performances of least-squares deconvolution with Laguerre expansion (LSD-LE) for analysing fluorescence lifetime imaging data obtained from time-resolved systems. Moreover, we also corrected an equation in the paper. As the LSD-LE method is rapid and has the potential to be widely applied not only for diagnostic but for wider bioimaging applications, it is desirable to have precise noise models and equations.

Artificial neural network modeling and cluster analysis for organic facies and burial history estimation using well log data: A case study of the South Pars Gas Field, Persian Gulf, Iran

NASA Astrophysics Data System (ADS)

Alizadeh, Bahram; Najjari, Saeid; Kadkhodaie-Ilkhchi, Ali

2012-08-01

Intelligent and statistical techniques were used to extract the hidden organic facies from well log responses in the Giant South Pars Gas Field, Persian Gulf, Iran. Kazhdomi Formation of Mid-Cretaceous and Kangan-Dalan Formations of Permo-Triassic Data were used for this purpose. Initially GR, SGR, CGR, THOR, POTA, NPHI and DT logs were applied to model the relationship between wireline logs and Total Organic Carbon (TOC) content using Artificial Neural Networks (ANN). The correlation coefficient (R2) between the measured and ANN predicted TOC equals to 89%. The performance of the model is measured by the Mean Squared Error function, which does not exceed 0.0073. Using Cluster Analysis technique and creating a binary hierarchical cluster tree the constructed TOC column of each formation was clustered into 5 organic facies according to their geochemical similarity. Later a second model with the accuracy of 84% was created by ANN to determine the specified clusters (facies) directly from well logs for quick cluster recognition in other wells of the studied field. Each created facies was correlated to its appropriate burial history curve. Hence each and every facies of a formation could be scrutinized separately and directly from its well logs, demonstrating the time and depth of oil or gas generation. Therefore potential production zone of Kazhdomi probable source rock and Kangan- Dalan reservoir formation could be identified while well logging operations (especially in LWD cases) were in progress. This could reduce uncertainty and save plenty of time and cost for oil industries and aid in the successful implementation of exploration and exploitation plans.

Optical Nonlinearities in GaAs/GaAlAs Multiple Quantum Wells Fabricated by Metalorganic Chemical Vapor Deposition for Use in Optical Signal Processing.

DTIC Science & Technology

1987-12-01

larger energy separation of the terminal states. The spectra of the thicker wells show peaks due to transitions from the n=2 and n=3 electron states. The...are found in the theses of H. C. Lee (PhD) and M. Kawase (MS). Section III contains an invited paper submittted to Journal of Quantum Electronics ...steps are associated with the allowed energies of the "square well potential" and are a strong function of the dimensions of the well and the

Antisymmetrization effects and the form factor of the real part of the. cap alpha. -nucleus potential

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

Majka, Z.; Budzanowski, A.; Grotowski, K.

1978-07-01

Antisymmetrization effects in the ..cap alpha..-nucleus interaction are investigated on the basis of a microscopic model in an one nucleon exchange approximation. It influences the form factor, increasing the halfway radius and decreasing the diffuseness as compared with the direct term of the potential only. Antisymmetrization preserves the shape of the potential which can be parametrized by a Woods-Saxon squared form. The phenomenological potential with the energy independent form factor of the above shape fits experimental data in a wide energy region.

Wavelet-based multiscale performance analysis: An approach to assess and improve hydrological models

NASA Astrophysics Data System (ADS)

Rathinasamy, Maheswaran; Khosa, Rakesh; Adamowski, Jan; ch, Sudheer; Partheepan, G.; Anand, Jatin; Narsimlu, Boini

2014-12-01

The temporal dynamics of hydrological processes are spread across different time scales and, as such, the performance of hydrological models cannot be estimated reliably from global performance measures that assign a single number to the fit of a simulated time series to an observed reference series. Accordingly, it is important to analyze model performance at different time scales. Wavelets have been used extensively in the area of hydrological modeling for multiscale analysis, and have been shown to be very reliable and useful in understanding dynamics across time scales and as these evolve in time. In this paper, a wavelet-based multiscale performance measure for hydrological models is proposed and tested (i.e., Multiscale Nash-Sutcliffe Criteria and Multiscale Normalized Root Mean Square Error). The main advantage of this method is that it provides a quantitative measure of model performance across different time scales. In the proposed approach, model and observed time series are decomposed using the Discrete Wavelet Transform (known as the à trous wavelet transform), and performance measures of the model are obtained at each time scale. The applicability of the proposed method was explored using various case studies-both real as well as synthetic. The synthetic case studies included various kinds of errors (e.g., timing error, under and over prediction of high and low flows) in outputs from a hydrologic model. The real time case studies investigated in this study included simulation results of both the process-based Soil Water Assessment Tool (SWAT) model, as well as statistical models, namely the Coupled Wavelet-Volterra (WVC), Artificial Neural Network (ANN), and Auto Regressive Moving Average (ARMA) methods. For the SWAT model, data from Wainganga and Sind Basin (India) were used, while for the Wavelet Volterra, ANN and ARMA models, data from the Cauvery River Basin (India) and Fraser River (Canada) were used. The study also explored the effect of the choice of the wavelets in multiscale model evaluation. It was found that the proposed wavelet-based performance measures, namely the MNSC (Multiscale Nash-Sutcliffe Criteria) and MNRMSE (Multiscale Normalized Root Mean Square Error), are a more reliable measure than traditional performance measures such as the Nash-Sutcliffe Criteria (NSC), Root Mean Square Error (RMSE), and Normalized Root Mean Square Error (NRMSE). Further, the proposed methodology can be used to: i) compare different hydrological models (both physical and statistical models), and ii) help in model calibration.

New bandwidth selection criterion for Kernel PCA: approach to dimensionality reduction and classification problems.

PubMed

Thomas, Minta; De Brabanter, Kris; De Moor, Bart

2014-05-10

DNA microarrays are potentially powerful technology for improving diagnostic classification, treatment selection, and prognostic assessment. The use of this technology to predict cancer outcome has a history of almost a decade. Disease class predictors can be designed for known disease cases and provide diagnostic confirmation or clarify abnormal cases. The main input to this class predictors are high dimensional data with many variables and few observations. Dimensionality reduction of these features set significantly speeds up the prediction task. Feature selection and feature transformation methods are well known preprocessing steps in the field of bioinformatics. Several prediction tools are available based on these techniques. Studies show that a well tuned Kernel PCA (KPCA) is an efficient preprocessing step for dimensionality reduction, but the available bandwidth selection method for KPCA was computationally expensive. In this paper, we propose a new data-driven bandwidth selection criterion for KPCA, which is related to least squares cross-validation for kernel density estimation. We propose a new prediction model with a well tuned KPCA and Least Squares Support Vector Machine (LS-SVM). We estimate the accuracy of the newly proposed model based on 9 case studies. Then, we compare its performances (in terms of test set Area Under the ROC Curve (AUC) and computational time) with other well known techniques such as whole data set + LS-SVM, PCA + LS-SVM, t-test + LS-SVM, Prediction Analysis of Microarrays (PAM) and Least Absolute Shrinkage and Selection Operator (Lasso). Finally, we assess the performance of the proposed strategy with an existing KPCA parameter tuning algorithm by means of two additional case studies. We propose, evaluate, and compare several mathematical/statistical techniques, which apply feature transformation/selection for subsequent classification, and consider its application in medical diagnostics. Both feature selection and feature transformation perform well on classification tasks. Due to the dynamic selection property of feature selection, it is hard to define significant features for the classifier, which predicts classes of future samples. Moreover, the proposed strategy enjoys a distinctive advantage with its relatively lesser time complexity.

40-Hz square-wave stimulation requires less energy to produce muscle contraction: compared with the TASER® X26 conducted energy weapon.

PubMed

Comeaux, James A; Jauchem, James R; Cox, D Duane; Crane, Carrie C; D'Andrea, John A

2013-07-01

Conducted energy weapons (CEWs) (including the Advanced TASER(®) X26 model produced by TASER International, Inc.) incapacitate individuals by causing muscle contractions. In this study using anesthetized swine, the potential incapacitating effect of primarily monophasic, 19-Hz voltage imposed by the commercial CEW was compared with the effect of voltages imposed by a laboratory device that created 40-Hz square waves. Forces of muscle contraction were measured with the use of strain gauges. Stimulation with 40-Hz square waves required less pulse energy than stimulation with the commercial CEW to produce similar muscle contraction. The square-pulse stimulation, at the higher repetition rate, caused a more complete tetanus at a lower energy. Use of such a simple shape of waveform may be used to make future nonlethal weapon devices more efficient. © 2013 American Academy of Forensic Sciences Published 2013. This article is a U.S. Government work and is in the public domain in the U.S.A.

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

Sudiarta, I. Wayan; Angraini, Lily Maysari, E-mail: lilyangraini@unram.ac.id

We have applied the finite difference time domain (FDTD) method with the supersymmetric quantum mechanics (SUSY-QM) procedure to determine excited energies of one dimensional quantum systems. The theoretical basis of FDTD, SUSY-QM, a numerical algorithm and an illustrative example for a particle in a one dimensional square-well potential were given in this paper. It was shown that the numerical results were in excellent agreement with theoretical results. Numerical errors produced by the SUSY-QM procedure was due to errors in estimations of superpotentials and supersymmetric partner potentials.

Effect of short-range correlations on the single proton 3s1/2 wave function in 206Pb

NASA Astrophysics Data System (ADS)

Shlomo, S.; Talmi, I.; Anders, M. R.; Bonasera, G.

2018-02-01

We consider the experimental data for difference, Δρc (r), between the charge density distributions of the isotones 206Pb - 205Tl, deduced by analysis of elastic electron scattering measurements and corresponds to the shell model 3s1/2 proton orbit. We investigate the effects of two-body short-range correlations. This is done by: (a) Determining the corresponding single particle potential (mean-field), employing a novel method, directly from the single particle proton density and its first and second derivatives. We also carried out least-square fits to parametrized single particle potentials; (b) Determining the short-range correlations effect by employing the Jastrow correlated many-body wave function to derive a correlation factor for the single particle density distribution. The 3s 1/2 wave functions of the determined potentials reproduce fairly well the experimental data within the quoted errors. The calculated charge density difference, Δρc (r), obtained with the inclusion of the short-range correlation effect does not reproduce the experimental data.

Landau level splitting due to graphene superlattices

NASA Astrophysics Data System (ADS)

Pal, G.; Apel, W.; Schweitzer, L.

2012-06-01

The Landau level spectrum of graphene superlattices is studied using a tight-binding approach. We consider noninteracting particles moving on a hexagonal lattice with an additional one-dimensional superlattice made up of periodic square potential barriers, which are oriented along the zigzag or along the armchair directions of graphene. In the presence of a perpendicular magnetic field, such systems can be described by a set of one-dimensional tight-binding equations, the Harper equations. The qualitative behavior of the energy spectrum with respect to the strength of the superlattice potential depends on the relation between the superlattice period and the magnetic length. When the potential barriers are oriented along the armchair direction of graphene, we find for strong magnetic fields that the zeroth Landau level of graphene splits into two well-separated sublevels, if the width of the barriers is smaller than the magnetic length. In this situation, which persists even in the presence of disorder, a plateau with zero Hall conductivity can be observed around the Dirac point. This Landau level splitting is a true lattice effect that cannot be obtained from the generally used continuum Dirac-fermion model.

RECOLA2: REcursive Computation of One-Loop Amplitudes 2

NASA Astrophysics Data System (ADS)

Denner, Ansgar; Lang, Jean-Nicolas; Uccirati, Sandro

2018-03-01

We present the Fortran95 program RECOLA2 for the perturbative computation of next-to-leading-order transition amplitudes in the Standard Model of particle physics and extended Higgs sectors. New theories are implemented via model files in the 't Hooft-Feynman gauge in the conventional formulation of quantum field theory and in the Background-Field method. The present version includes model files for Two-Higgs-Doublet Model and the Higgs-Singlet Extension of the Standard Model. We support standard renormalization schemes for the Standard Model as well as many commonly used renormalization schemes in extended Higgs sectors. Within these models the computation of next-to-leading-order polarized amplitudes and squared amplitudes, optionally summed over spin and colour, is fully automated for any process. RECOLA2 allows the computation of colour- and spin-correlated leading-order squared amplitudes that are needed in the dipole subtraction formalism. RECOLA2 is publicly available for download at http://recola.hepforge.org.

Determination of rice syrup adulterant concentration in honey using three-dimensional fluorescence spectra and multivariate calibrations

NASA Astrophysics Data System (ADS)

Chen, Quansheng; Qi, Shuai; Li, Huanhuan; Han, Xiaoyan; Ouyang, Qin; Zhao, Jiewen

2014-10-01

To rapidly and efficiently detect the presence of adulterants in honey, three-dimensional fluorescence spectroscopy (3DFS) technique was employed with the help of multivariate calibration. The data of 3D fluorescence spectra were compressed using characteristic extraction and the principal component analysis (PCA). Then, partial least squares (PLS) and back propagation neural network (BP-ANN) algorithms were used for modeling. The model was optimized by cross validation, and its performance was evaluated according to root mean square error of prediction (RMSEP) and correlation coefficient (R) in prediction set. The results showed that BP-ANN model was superior to PLS models, and the optimum prediction results of the mixed group (sunflower ± longan ± buckwheat ± rape) model were achieved as follow: RMSEP = 0.0235 and R = 0.9787 in the prediction set. The study demonstrated that the 3D fluorescence spectroscopy technique combined with multivariate calibration has high potential in rapid, nondestructive, and accurate quantitative analysis of honey adulteration.

Effects of aspect ratio on the phase diagram of spheroidal particles

NASA Astrophysics Data System (ADS)

Kutlu, Songul; Haaga, Jason; Rickman, Jeffrey; Gunton, James

Ellipsoidal particles occur in both colloidal and protein science. Models of protein phase transitions based on interacting spheroidal particles can often be more realistic than those based on spherical molecules. One of the interesting questions is how the aspect ratio of spheroidal particles affects the phase diagram. Some results have been obtained in an earlier study by Odriozola (J. Chem. Phys. 136:134505 (2012)). In this poster we present results for the phase diagram of hard spheroids interacting via a quasi-square-well potential, for different aspect ratios. These results are obtained from Monte Carlo simulations using the replica exchange method. We find that the phase diagram, including the crystal phase transition, is sensitive to the choice of aspect ratio. G. Harold and Leila Y. Mathers Foundation.

Evaluation of data transformations used with the square root and schoolfield models for predicting bacterial growth rate.

PubMed Central

Alber, S A; Schaffner, D W

1992-01-01

A comparison was made between mathematical variations of the square root and Schoolfield models for predicting growth rate as a function of temperature. The statistical consequences of square root and natural logarithm transformations of growth rate use in several variations of the Schoolfield and square root models were examined. Growth rate variances of Yersinia enterocolitica in brain heart infusion broth increased as a function of temperature. The ability of the two data transformations to correct for the heterogeneity of variance was evaluated. A natural logarithm transformation of growth rate was more effective than a square root transformation at correcting for the heterogeneity of variance. The square root model was more accurate than the Schoolfield model when both models used natural logarithm transformation. PMID:1444367

Band gaps in grid structure with periodic local resonator subsystems

NASA Astrophysics Data System (ADS)

Zhou, Xiaoqin; Wang, Jun; Wang, Rongqi; Lin, Jieqiong

2017-09-01

The grid structure is widely used in architectural and mechanical field for its high strength and saving material. This paper will present a study on an acoustic metamaterial beam (AMB) based on the normal square grid structure with local resonators owning both flexible band gaps and high static stiffness, which have high application potential in vibration control. Firstly, the AMB with variable cross-section frame is analytically modeled by the beam-spring-mass model that is provided by using the extended Hamilton’s principle and Bloch’s theorem. The above model is used for computing the dispersion relation of the designed AMB in terms of the design parameters, and the influences of relevant parameters on band gaps are discussed. Then a two-dimensional finite element model of the AMB is built and analyzed in COMSOL Multiphysics, both the dispersion properties of unit cell and the wave attenuation in a finite AMB have fine agreement with the derived model. The effects of design parameters of the two-dimensional model in band gaps are further examined, and the obtained results can well verify the analytical model. Finally, the wave attenuation performances in three-dimensional AMBs with equal and unequal thickness are presented and discussed.

[Spectral quantitative analysis by nonlinear partial least squares based on neural network internal model for flue gas of thermal power plant].

PubMed

Cao, Hui; Li, Yao-Jiang; Zhou, Yan; Wang, Yan-Xia

2014-11-01

To deal with nonlinear characteristics of spectra data for the thermal power plant flue, a nonlinear partial least square (PLS) analysis method with internal model based on neural network is adopted in the paper. The latent variables of the independent variables and the dependent variables are extracted by PLS regression firstly, and then they are used as the inputs and outputs of neural network respectively to build the nonlinear internal model by train process. For spectra data of flue gases of the thermal power plant, PLS, the nonlinear PLS with the internal model of back propagation neural network (BP-NPLS), the non-linear PLS with the internal model of radial basis function neural network (RBF-NPLS) and the nonlinear PLS with the internal model of adaptive fuzzy inference system (ANFIS-NPLS) are compared. The root mean square error of prediction (RMSEP) of sulfur dioxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 16.96%, 16.60% and 19.55% than that of PLS, respectively. The RMSEP of nitric oxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 8.60%, 8.47% and 10.09% than that of PLS, respectively. The RMSEP of nitrogen dioxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 2.11%, 3.91% and 3.97% than that of PLS, respectively. Experimental results show that the nonlinear PLS is more suitable for the quantitative analysis of glue gas than PLS. Moreover, by using neural network function which can realize high approximation of nonlinear characteristics, the nonlinear partial least squares method with internal model mentioned in this paper have well predictive capabilities and robustness, and could deal with the limitations of nonlinear partial least squares method with other internal model such as polynomial and spline functions themselves under a certain extent. ANFIS-NPLS has the best performance with the internal model of adaptive fuzzy inference system having ability to learn more and reduce the residuals effectively. Hence, ANFIS-NPLS is an accurate and useful quantitative thermal power plant flue gas analysis method.

The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method.

PubMed

Peng, Ying; Li, Su-Ning; Pei, Xuexue; Hao, Kun

2018-03-01

Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.

Determinants of Antibiotic Consumption - Development of a Model using Partial Least Squares Regression based on Data from India.

PubMed

Tamhankar, Ashok J; Karnik, Shreyasee S; Stålsby Lundborg, Cecilia

2018-04-23

Antibiotic resistance, a consequence of antibiotic use, is a threat to health, with severe consequences for resource constrained settings. If determinants for human antibiotic use in India, a lower middle income country, with one of the highest antibiotic consumption in the world could be understood, interventions could be developed, having implications for similar settings. Year wise data for India, for potential determinants and antibiotic consumption, was sourced from publicly available databases for the years 2000-2010. Data was analyzed using Partial Least Squares regression and correlation between determinants and antibiotic consumption was evaluated, formulating 'Predictors' and 'Prediction models'. The 'prediction model' with the statistically most significant predictors (root mean square errors of prediction for train set-377.0 and test set-297.0) formulated from a combination of Health infrastructure + Surface transport infrastructure (HISTI), predicted antibiotic consumption within 95% confidence interval and estimated an antibiotic consumption of 11.6 standard units/person (14.37 billion standard units totally; standard units = number of doses sold in the country; a dose being a pill, capsule, or ampoule) for India for 2014. The HISTI model may become useful in predicting antibiotic consumption for countries/regions having circumstances and data similar to India, but without resources to measure actual data of antibiotic consumption.

Equivalence of binormal likelihood-ratio and bi-chi-squared ROC curve models

PubMed Central

Hillis, Stephen L.

2015-01-01

A basic assumption for a meaningful diagnostic decision variable is that there is a monotone relationship between it and its likelihood ratio. This relationship, however, generally does not hold for a decision variable that results in a binormal ROC curve. As a result, receiver operating characteristic (ROC) curve estimation based on the assumption of a binormal ROC-curve model produces improper ROC curves that have “hooks,” are not concave over the entire domain, and cross the chance line. Although in practice this “improperness” is usually not noticeable, sometimes it is evident and problematic. To avoid this problem, Metz and Pan proposed basing ROC-curve estimation on the assumption of a binormal likelihood-ratio (binormal-LR) model, which states that the decision variable is an increasing transformation of the likelihood-ratio function of a random variable having normal conditional diseased and nondiseased distributions. However, their development is not easy to follow. I show that the binormal-LR model is equivalent to a bi-chi-squared model in the sense that the families of corresponding ROC curves are the same. The bi-chi-squared formulation provides an easier-to-follow development of the binormal-LR ROC curve and its properties in terms of well-known distributions. PMID:26608405

Fuzzy C-mean clustering on kinetic parameter estimation with generalized linear least square algorithm in SPECT

NASA Astrophysics Data System (ADS)

Choi, Hon-Chit; Wen, Lingfeng; Eberl, Stefan; Feng, Dagan

2006-03-01

Dynamic Single Photon Emission Computed Tomography (SPECT) has the potential to quantitatively estimate physiological parameters by fitting compartment models to the tracer kinetics. The generalized linear least square method (GLLS) is an efficient method to estimate unbiased kinetic parameters and parametric images. However, due to the low sensitivity of SPECT, noisy data can cause voxel-wise parameter estimation by GLLS to fail. Fuzzy C-Mean (FCM) clustering and modified FCM, which also utilizes information from the immediate neighboring voxels, are proposed to improve the voxel-wise parameter estimation of GLLS. Monte Carlo simulations were performed to generate dynamic SPECT data with different noise levels and processed by general and modified FCM clustering. Parametric images were estimated by Logan and Yokoi graphical analysis and GLLS. The influx rate (K I), volume of distribution (V d) were estimated for the cerebellum, thalamus and frontal cortex. Our results show that (1) FCM reduces the bias and improves the reliability of parameter estimates for noisy data, (2) GLLS provides estimates of micro parameters (K I-k 4) as well as macro parameters, such as volume of distribution (Vd) and binding potential (BP I & BP II) and (3) FCM clustering incorporating neighboring voxel information does not improve the parameter estimates, but improves noise in the parametric images. These findings indicated that it is desirable for pre-segmentation with traditional FCM clustering to generate voxel-wise parametric images with GLLS from dynamic SPECT data.

Statistical steady states in turbulent droplet condensation

NASA Astrophysics Data System (ADS)

Bec, Jeremie; Krstulovic, Giorgio; Siewert, Christoph

2017-11-01

We investigate the general problem of turbulent condensation. Using direct numerical simulations we show that the fluctuations of the supersaturation field offer different conditions for the growth of droplets which evolve in time due to turbulent transport and mixing. This leads to propose a Lagrangian stochastic model consisting of a set of integro-differential equations for the joint evolution of the squared radius and the supersaturation along droplet trajectories. The model has two parameters fixed by the total amount of water and the thermodynamic properties, as well as the Lagrangian integral timescale of the turbulent supersaturation. The model reproduces very well the droplet size distributions obtained from direct numerical simulations and their time evolution. A noticeable result is that, after a stage where the squared radius simply diffuses, the system converges exponentially fast to a statistical steady state independent of the initial conditions. The main mechanism involved in this convergence is a loss of memory induced by a significant number of droplets undergoing a complete evaporation before growing again. The statistical steady state is characterised by an exponential tail in the droplet mass distribution.

Least-Squares Models to Correct for Rater Effects in Performance Assessment.

ERIC Educational Resources Information Center

Raymond, Mark R.; Viswesvaran, Chockalingam

This study illustrates the use of three least-squares models to control for rater effects in performance evaluation: (1) ordinary least squares (OLS); (2) weighted least squares (WLS); and (3) OLS subsequent to applying a logistic transformation to observed ratings (LOG-OLS). The three models were applied to ratings obtained from four…

Frustrated Magnetism of Dipolar Molecules on a Square Optical Lattice: Prediction of a Quantum Paramagnetic Ground State

NASA Astrophysics Data System (ADS)

Zou, Haiyuan; Zhao, Erhai; Liu, W. Vincent

2017-08-01

Motivated by the experimental realization of quantum spin models of polar molecule KRb in optical lattices, we analyze the spin 1 /2 dipolar Heisenberg model with competing anisotropic, long-range exchange interactions. We show that, by tilting the orientation of dipoles using an external electric field, the dipolar spin system on square lattice comes close to a maximally frustrated region similar, but not identical, to that of the J1-J2 model. This provides a simple yet powerful route to potentially realize a quantum spin liquid without the need for a triangular or kagome lattice. The ground state phase diagrams obtained from Schwinger-boson and spin-wave theories consistently show a spin disordered region between the Néel, stripe, and spiral phase. The existence of a finite quantum paramagnetic region is further confirmed by an unbiased variational ansatz based on tensor network states and a tensor renormalization group.

Systemic inflammatory markers and sources of social support among older adults in the Memory Research Unit cohort.

PubMed

McHugh Power, Joanna; Carney, Sile; Hannigan, Caoimhe; Brennan, Sabina; Wolfe, Hannah; Lynch, Marina; Kee, Frank; Lawlor, Brian

2016-11-01

Potential associations between systemic inflammation and social support received by a sample of 120 older adults were examined here. Inflammatory markers, cognitive function, social support and psychosocial wellbeing were evaluated. A structural equation modelling approach was used to analyse the data. The model was a good fit [Formula: see text], p < 0.001; comparative fit index = 0.973; Tucker-Lewis Index = 0.962; root mean square error of approximation = 0.021; standardised root mean-square residual = 0.074). Chemokine levels were associated with increased age ( β = 0.276), receipt of less social support from friends ( β = -0.256) and body mass index ( β = -0.256). Results are discussed in relation to social signal transduction theory.

Birefringent breakup of Dirac fermions on a square optical lattice

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

Kennett, Malcolm P.; Komeilizadeh, Nazanin; Kaveh, Kamran

2011-05-15

We introduce a lattice model for fermions in a spatially periodic magnetic field that also has spatially periodic hopping amplitudes. We discuss how this model might be realized with cold atoms in an artificial magnetic field on a square optical lattice. When there is an average flux of half a flux quantum per plaquette, the spectrum of low-energy excitations can be described by massless Dirac fermions in which the usually doubly degenerate Dirac cones split into cones with different ''speeds of light.'' These gapless birefringent Dirac fermions arise because of broken chiral symmetry in the kinetic energy term of themore » effective low-energy Hamiltonian. We characterize the effects of various perturbations to the low-energy spectrum, including staggered potentials, interactions, and domain-wall topological defects.« less

A laboratory study to estimate pore geometric parameters of sandstones using complex conductivity and nuclear magnetic resonance for permeability prediction

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

Osterman, Gordon; Keating, Kristina; Binley, Andrew

Here, we estimate parameters from the Katz and Thompson permeability model using laboratory complex electrical conductivity (CC) and nuclear magnetic resonance (NMR) data to build permeability models parameterized with geophysical measurements. We use the Katz and Thompson model based on the characteristic hydraulic length scale, determined from mercury injection capillary pressure estimates of pore throat size, and the intrinsic formation factor, determined from multisalinity conductivity measurements, for this purpose. Two new permeability models are tested, one based on CC data and another that incorporates CC and NMR data. From measurements made on forty-five sandstone cores collected from fifteen different formations,more » we evaluate how well the CC relaxation time and the NMR transverse relaxation times compare to the characteristic hydraulic length scale and how well the formation factor estimated from CC parameters compares to the intrinsic formation factor. We find: (1) the NMR transverse relaxation time models the characteristic hydraulic length scale more accurately than the CC relaxation time (R 2 of 0.69 and 0.33 and normalized root mean square errors (NRMSE) of 0.16 and 0.21, respectively); (2) the CC estimated formation factor is well correlated with the intrinsic formation factor (NRMSE50.23). We demonstrate that that permeability estimates from the joint-NMR-CC model (NRMSE50.13) compare favorably to estimates from the Katz and Thompson model (NRMSE50.074). Lastly, this model advances the capability of the Katz and Thompson model by employing parameters measureable in the field giving it the potential to more accurately estimate permeability using geophysical measurements than are currently possible.« less

A laboratory study to estimate pore geometric parameters of sandstones using complex conductivity and nuclear magnetic resonance for permeability prediction

DOE PAGES

Osterman, Gordon; Keating, Kristina; Binley, Andrew; ...

2016-03-18

Here, we estimate parameters from the Katz and Thompson permeability model using laboratory complex electrical conductivity (CC) and nuclear magnetic resonance (NMR) data to build permeability models parameterized with geophysical measurements. We use the Katz and Thompson model based on the characteristic hydraulic length scale, determined from mercury injection capillary pressure estimates of pore throat size, and the intrinsic formation factor, determined from multisalinity conductivity measurements, for this purpose. Two new permeability models are tested, one based on CC data and another that incorporates CC and NMR data. From measurements made on forty-five sandstone cores collected from fifteen different formations,more » we evaluate how well the CC relaxation time and the NMR transverse relaxation times compare to the characteristic hydraulic length scale and how well the formation factor estimated from CC parameters compares to the intrinsic formation factor. We find: (1) the NMR transverse relaxation time models the characteristic hydraulic length scale more accurately than the CC relaxation time (R 2 of 0.69 and 0.33 and normalized root mean square errors (NRMSE) of 0.16 and 0.21, respectively); (2) the CC estimated formation factor is well correlated with the intrinsic formation factor (NRMSE50.23). We demonstrate that that permeability estimates from the joint-NMR-CC model (NRMSE50.13) compare favorably to estimates from the Katz and Thompson model (NRMSE50.074). Lastly, this model advances the capability of the Katz and Thompson model by employing parameters measureable in the field giving it the potential to more accurately estimate permeability using geophysical measurements than are currently possible.« less

Quantitative study of electrophoretic and electroosmotic enhancement during alternating current iontophoresis across synthetic membranes.

PubMed

Yan, Guang; Li, S Kevin; Peck, Kendall D; Zhu, Honggang; Higuchi, William I

2004-12-01

One of the primary safety and tolerability limitations of direct current iontophoresis is the potential for electrochemical burns associated with the necessary current densities and/or application times required for effective treatment. Alternating current (AC) transdermal iontophoresis has the potential to eliminate electrochemical burns that are frequently observed during direct current transdermal iontophoresis. Although it has been demonstrated that the intrinsic permeability of skin can be increased by applying low-to-moderate AC voltages, transdermal transport phenomena and enhancement under AC conditions have not been systematically studied and are not well understood. The aim of the present work was to study the fundamental transport mechanisms of square-wave AC iontophoresis using a synthetic membrane system. The model synthetic membrane used was a composite Nuclepore membrane. AC frequencies ranging from 20 to 1000 Hz and AC fields ranging from 0.25 to 0.5 V/membrane were investigated. A charged permeant, tetraethyl ammonium, and a neutral permeant, arabinose, were used. The transport studies showed that flux was enhanced by increasing the AC voltage and decreasing AC frequency. Two theoretical transport models were developed: one is a homogeneous membrane model; the other is a heterogeneous membrane model. Experimental transport data were compared with computer simulations based on these models. Excellent agreement between model predictions and experimental data was observed when the data were compared with the simulations from the heterogeneous membrane model. (c) 2004 Wiley-Liss, Inc. and the American Pharmacists Association

Representing uncertainty in objective functions: extension to include the influence of serial correlation

NASA Astrophysics Data System (ADS)

Croke, B. F.

2008-12-01

The role of performance indicators is to give an accurate indication of the fit between a model and the system being modelled. As all measurements have an associated uncertainty (determining the significance that should be given to the measurement), performance indicators should take into account uncertainties in the observed quantities being modelled as well as in the model predictions (due to uncertainties in inputs, model parameters and model structure). In the presence of significant uncertainty in observed and modelled output of a system, failure to adequately account for variations in the uncertainties means that the objective function only gives a measure of how well the model fits the observations, not how well the model fits the system being modelled. Since in most cases, the interest lies in fitting the system response, it is vital that the objective function(s) be designed to account for these uncertainties. Most objective functions (e.g. those based on the sum of squared residuals) assume homoscedastic uncertainties. If model contribution to the variations in residuals can be ignored, then transformations (e.g. Box-Cox) can be used to remove (or at least significantly reduce) heteroscedasticity. An alternative which is more generally applicable is to explicitly represent the uncertainties in the observed and modelled values in the objective function. Previous work on this topic addressed the modifications to standard objective functions (Nash-Sutcliffe efficiency, RMSE, chi- squared, coefficient of determination) using the optimal weighted averaging approach. This paper extends this previous work; addressing the issue of serial correlation. A form for an objective function that includes serial correlation will be presented, and the impact on model fit discussed.

A microscale three-dimensional urban energy balance model for studying surface temperatures

NASA Astrophysics Data System (ADS)

Krayenhoff, E. Scott; Voogt, James A.

2007-06-01

A microscale three-dimensional (3-D) urban energy balance model, Temperatures of Urban Facets in 3-D (TUF-3D), is developed to predict urban surface temperatures for a variety of surface geometries and properties, weather conditions, and solar angles. The surface is composed of plane-parallel facets: roofs, walls, and streets, which are further sub-divided into identical square patches, resulting in a 3-D raster-type model geometry. The model code is structured into radiation, conduction and convection sub-models. The radiation sub-model uses the radiosity approach and accounts for multiple reflections and shading of direct solar radiation. Conduction is solved by finite differencing of the heat conduction equation, and convection is modelled by empirically relating patch heat transfer coefficients to the momentum forcing and the building morphology. The radiation and conduction sub-models are tested individually against measurements, and the complete model is tested against full-scale urban surface temperature and energy balance observations. Modelled surface temperatures perform well at both the facet-average and the sub-facet scales given the precision of the observations and the uncertainties in the model inputs. The model has several potential applications, such as the calculation of radiative loads, and the investigation of effective thermal anisotropy (when combined with a sensor-view model).

All Square Chiliagonal Numbers

ERIC Educational Resources Information Center

A?iru, Muniru A.

2016-01-01

A square chiliagonal number is a number which is simultaneously a chiliagonal number and a perfect square (just as the well-known square triangular number is both triangular and square). In this work, we determine which of the chiliagonal numbers are perfect squares and provide the indices of the corresponding chiliagonal numbers and square…

Manning’s equation and two-dimensional flow analogs

NASA Astrophysics Data System (ADS)

Hromadka, T. V., II; Whitley, R. J.; Jordan, N.; Meyer, T.

2010-07-01

SummaryTwo-dimensional (2D) flow models based on the well-known governing 2D flow equations are applied to floodplain analysis purposes. These 2D models numerically solve the governing flow equations simultaneously or explicitly on a discretization of the floodplain using grid tiles or similar tile cell geometry, called "elements". By use of automated information systems such as digital terrain modeling, digital elevation models, and GIS, large-scale topographic floodplain maps can be readily discretized into thousands of elements that densely cover the floodplain in an edge-to-edge form. However, the assumed principal flow directions of the flow model analog, as applied across an array of elements, typically do not align with the floodplain flow streamlines. This paper examines the mathematical underpinnings of a four-direction flow analog using an array of square elements with respect to floodplain flow streamlines that are not in alignment with the analog's principal flow directions. It is determined that application of Manning's equation to estimate the friction slope terms of the governing flow equations, in directions that are not coincident with the flow streamlines, may introduce a bias in modeling results, in the form of slight underestimation of flow depths. It is also determined that the maximum theoretical bias, occurs when a single square element is rotated by about 13°, and not 45° as would be intuitively thought. The bias as a function of rotation angle for an array of square elements follows approximately the bias for a single square element. For both the theoretical single square element and an array of square elements, the bias as a function of alignment angle follows a relatively constant value from about 5° to about 85°, centered at about 45°. This bias was first noted about a decade prior to the present paper, and the magnitude of this bias was estimated then to be about 20% at about 10° misalignment. An adjustment of Manning's n is investigated based on a considered steady state uniform flow problem, but the magnitude of the adjustment (about 20%) is on the order of the magnitude of the accepted ranges of friction factors. For usual cases where random streamline trajectory variability within the floodplain flow is greater than a few degrees from perfect alignment, the apparent bias appears to be implicitly included in the Manning's n values. It can be concluded that the array of square elements may be applied over the digital terrain model without respect to topographic flow directions.

Experimental and theoretical investigation of the magnetization dynamics of an artificial square spin ice cluster

NASA Astrophysics Data System (ADS)

Pohlit, Merlin; Stockem, Irina; Porrati, Fabrizio; Huth, Michael; Schröder, Christian; Müller, Jens

2016-10-01

We study the magnetization dynamics of a spin ice cluster which is a building block of an artificial square spin ice fabricated by focused electron-beam-induced deposition both experimentally and theoretically. The spin ice cluster is composed of twelve interacting Co nanoislands grown directly on top of a high-resolution micro-Hall sensor. By employing micromagnetic simulations and a macrospin model, we calculate the magnetization and the experimentally investigated stray field emanating from a single nanoisland. The parameters determined from a comparison with the experimental hysteresis loop are used to derive an effective single-dipole macrospin model that allows us to investigate the dynamics of the spin ice cluster. Our model reproduces the experimentally observed non-deterministic sequences in the magnetization curves as well as the distinct temperature dependence of the hysteresis loop.

Simulation of a model nanopore sensor: Ion competition underlies device behavior.

PubMed

Mádai, Eszter; Valiskó, Mónika; Dallos, András; Boda, Dezső

2017-12-28

We study a model nanopore sensor with which a very low concentration of analyte molecules can be detected on the basis of the selective binding of the analyte molecules to the binding sites on the pore wall. The bound analyte ions partially replace the current-carrier cations in a thermodynamic competition. This competition depends both on the properties of the nanopore and the concentrations of the competing ions (through their chemical potentials). The output signal given by the device is the current reduction caused by the presence of the analyte ions. The concentration of the analyte ions can be determined through calibration curves. We model the binding site with the square-well potential and the electrolyte as charged hard spheres in an implicit background solvent. We study the system with a hybrid method in which we compute the ion flux with the Nernst-Planck (NP) equation coupled with the Local Equilibrium Monte Carlo (LEMC) simulation technique. The resulting NP+LEMC method is able to handle both strong ionic correlations inside the pore (including finite size of ions) and bulk concentrations as low as micromolar. We analyze the effect of bulk ion concentrations, pore parameters, binding site parameters, electrolyte properties, and voltage on the behavior of the device.

Simulation of a model nanopore sensor: Ion competition underlies device behavior

NASA Astrophysics Data System (ADS)

Mádai, Eszter; Valiskó, Mónika; Dallos, András; Boda, Dezső

2017-12-01

We study a model nanopore sensor with which a very low concentration of analyte molecules can be detected on the basis of the selective binding of the analyte molecules to the binding sites on the pore wall. The bound analyte ions partially replace the current-carrier cations in a thermodynamic competition. This competition depends both on the properties of the nanopore and the concentrations of the competing ions (through their chemical potentials). The output signal given by the device is the current reduction caused by the presence of the analyte ions. The concentration of the analyte ions can be determined through calibration curves. We model the binding site with the square-well potential and the electrolyte as charged hard spheres in an implicit background solvent. We study the system with a hybrid method in which we compute the ion flux with the Nernst-Planck (NP) equation coupled with the Local Equilibrium Monte Carlo (LEMC) simulation technique. The resulting NP+LEMC method is able to handle both strong ionic correlations inside the pore (including finite size of ions) and bulk concentrations as low as micromolar. We analyze the effect of bulk ion concentrations, pore parameters, binding site parameters, electrolyte properties, and voltage on the behavior of the device.

Evaluating and Improving the SAMA (Segmentation Analysis and Market Assessment) Recruiting Model

DTIC Science & Technology

2015-06-01

and rewarding me with your love every day. xx THIS PAGE INTENTIONALLY LEFT BLANK 1 I. INTRODUCTION A. THE UNITED STATES ARMY RECRUITING...the relationship between the calculated SAMA potential and the actual 2014 performance. The scatterplot in Figure 8 shows a strong linear... relationship between the SAMA calculated potential and the contracting achievement for 2014, with an R-squared value of 0.871. Simple Linear Regression of

Protein simulation using coarse-grained two-bead multipole force field with polarizable water models.

PubMed

Li, Min; Zhang, John Z H

2017-02-14

A recently developed two-bead multipole force field (TMFF) is employed in coarse-grained (CG) molecular dynamics (MD) simulation of proteins in combination with polarizable CG water models, the Martini polarizable water model, and modified big multipole water model. Significant improvement in simulated structures and dynamics of proteins is observed in terms of both the root-mean-square deviations (RMSDs) of the structures and residue root-mean-square fluctuations (RMSFs) from the native ones in the present simulation compared with the simulation result with Martini's non-polarizable water model. Our result shows that TMFF simulation using CG water models gives much stable secondary structures of proteins without the need for adding extra interaction potentials to constrain the secondary structures. Our result also shows that by increasing the MD time step from 2 fs to 6 fs, the RMSD and RMSF results are still in excellent agreement with those from all-atom simulations. The current study demonstrated clearly that the application of TMFF together with a polarizable CG water model significantly improves the accuracy and efficiency for CG simulation of proteins.

Protein simulation using coarse-grained two-bead multipole force field with polarizable water models

NASA Astrophysics Data System (ADS)

Li, Min; Zhang, John Z. H.

2017-02-01

A recently developed two-bead multipole force field (TMFF) is employed in coarse-grained (CG) molecular dynamics (MD) simulation of proteins in combination with polarizable CG water models, the Martini polarizable water model, and modified big multipole water model. Significant improvement in simulated structures and dynamics of proteins is observed in terms of both the root-mean-square deviations (RMSDs) of the structures and residue root-mean-square fluctuations (RMSFs) from the native ones in the present simulation compared with the simulation result with Martini's non-polarizable water model. Our result shows that TMFF simulation using CG water models gives much stable secondary structures of proteins without the need for adding extra interaction potentials to constrain the secondary structures. Our result also shows that by increasing the MD time step from 2 fs to 6 fs, the RMSD and RMSF results are still in excellent agreement with those from all-atom simulations. The current study demonstrated clearly that the application of TMFF together with a polarizable CG water model significantly improves the accuracy and efficiency for CG simulation of proteins.

Partial Least Squares with Structured Output for Modelling the Metabolomics Data Obtained from Complex Experimental Designs: A Study into the Y-Block Coding.

PubMed

Xu, Yun; Muhamadali, Howbeer; Sayqal, Ali; Dixon, Neil; Goodacre, Royston

2016-10-28

Partial least squares (PLS) is one of the most commonly used supervised modelling approaches for analysing multivariate metabolomics data. PLS is typically employed as either a regression model (PLS-R) or a classification model (PLS-DA). However, in metabolomics studies it is common to investigate multiple, potentially interacting, factors simultaneously following a specific experimental design. Such data often cannot be considered as a "pure" regression or a classification problem. Nevertheless, these data have often still been treated as a regression or classification problem and this could lead to ambiguous results. In this study, we investigated the feasibility of designing a hybrid target matrix Y that better reflects the experimental design than simple regression or binary class membership coding commonly used in PLS modelling. The new design of Y coding was based on the same principle used by structural modelling in machine learning techniques. Two real metabolomics datasets were used as examples to illustrate how the new Y coding can improve the interpretability of the PLS model compared to classic regression/classification coding.

On Closed Shells in Nuclei. II

DOE R&D Accomplishments Database

Mayer, M. G.

1949-04-01

Discussion on the use of spins and magnetic moments of the even-odd nuclei by Feenberg and Nordheim to determine the angular momentum of the eigenfunction of the odd particle; discussion of prevalence of isomerism in certain regions of the isotope chart; tabulated data on levels of square well potential, spectroscopic levels, spin term, number of states, shells and known spins and orbital assignments.

Geohydrology and water quality of stratified-drift aquifers in the middle Merrimack River basin, south-central New Hampshire

USGS Publications Warehouse

Ayotte, Joseph D.; Toppin, Kenneth W.

1995-01-01

The U.S. Geological Survey, in cooperation with the State of New Hampshire, Department of Environmental Services, Water Resources Division has assessed the geohydrology and water quality of stratified-drift aquifers in the middle Merrimack River basin in south-central New Hampshire. The middle Merrimack River basin drains 469 square miles; 98 square miles is underlain by stratified-drift aquifers. Saturated thickness of stratified drift within the study area is generally less than 40 feet but locally greater than 100 feet. Transmissivity of stratified-drift aquifers is generally less than 2,000 feet squared per day but locally exceeds 6, 000 feet squared per day. At present (1990), ground-water withdrawals from stratified drift for public supply are about 0.4 million gallons per day within the basin. Many of the stratified-drift aquifers within the study area are not developed to their fullest potential. The geohydrology of stratified-drift aquifers was investigated by focusing on basic aquifer properties, including aquifer boundaries; recharge, discharge, and direction of ground-water flow; saturated thickness and storage; and transmissivity. Surficial geologic mapping assisted in the determination of aquifer boundaries. Data from 757 wells and test borings were used to produce maps of water-table altitude, saturated thickness, and transmissivity of stratified drift. More than 10 miles of seismic-refraction profiling and 14 miles of seismic-reflection profiling were also used to construct the water table and saturated-thickness maps. Stratified-drift aquifers in the southern, western, and central parts of the study area are typically small and discontinuous, whereas aquifers in the eastern part along the Merrimack River valley are continuous. The Merrimack River valley aquifers formed in glacial Lakes Merrimack and Hooksett. Many other smaller discontinuous aquifers formed in small temporary ponds during deglaciation. A stratified-drift aquifer in Goffstown was analyzed for aquifer yield by use of a two-dimensional, finite-difference ground-water-flow model. Yield of the Goffstown aquifer was estimated to be 2.5 million gallons per day. Sensitivity analysis showed that the estimate of aquifer yield was most sensitive to changes in hydraulic conductivity. The amount of water induced into the aquifer from the Piscataquog River was most affected by changes in estimates of streambed conductance. Results of analysis of water samples from 10 test wells indicate that, with some exceptions, water in the stratified-drift aquifers generally meets U.S. Environmental Protection Agency primary and secondary drinking-water regulations. Water from two wells had elevated sodium concentrations, waterfront two wells had elevated concentrations of dissolved iron, and waterfront seven wells had elevated concentrations of manganese. Known areas of contamination were avoided during water-quality sampling.

The development of the ''Sleeping Giant'' deep basin natural gas, Alberta Canada

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

Bowman, D.L.

1984-02-01

During the past seven years attention has been focused on ''mega'' projects and the frontier areas for continental energy self sufficiency. However, a giant conventional resource project has been developing without fanfare. This project has potential impact on the well being of Canada and the North American energy scene. This ''Sleeping Giant'', which delivered its initial sales gas on November 1, 1979 is the Alberta (Elmworth) Deep Basin. The project area covers 67,400 square km (26,000 square miles) and contains potentially hydrocarbon bearing sediments over a thickness of 4,572 meters (15,000 feet). This basin is best equated in terms ofmore » size and reserves to the famous San Juan Basin. Since its discovery in 1976 approximately 1,000 multi-zoned gas wells have been drilled and reserves in the order of 140,000 10/sup 6/m/sup 3/ (5 trillion cubic feet) have been recognized by gas purchasers. Ten gas plants have been constructed with capacity of roughly 28,174 10/sup 3/m/sup 3/ (1 billion cubic feet) per day. This paper documents the development of these reserves and the stages in the construction of field facilities.« less

Overview and benchmark analysis of fuel cell parameters estimation for energy management purposes

NASA Astrophysics Data System (ADS)

Kandidayeni, M.; Macias, A.; Amamou, A. A.; Boulon, L.; Kelouwani, S.; Chaoui, H.

2018-03-01

Proton exchange membrane fuel cells (PEMFCs) have become the center of attention for energy conversion in many areas such as automotive industry, where they confront a high dynamic behavior resulting in their characteristics variation. In order to ensure appropriate modeling of PEMFCs, accurate parameters estimation is in demand. However, parameter estimation of PEMFC models is highly challenging due to their multivariate, nonlinear, and complex essence. This paper comprehensively reviews PEMFC models parameters estimation methods with a specific view to online identification algorithms, which are considered as the basis of global energy management strategy design, to estimate the linear and nonlinear parameters of a PEMFC model in real time. In this respect, different PEMFC models with different categories and purposes are discussed first. Subsequently, a thorough investigation of PEMFC parameter estimation methods in the literature is conducted in terms of applicability. Three potential algorithms for online applications, Recursive Least Square (RLS), Kalman filter, and extended Kalman filter (EKF), which has escaped the attention in previous works, have been then utilized to identify the parameters of two well-known semi-empirical models in the literature, Squadrito et al. and Amphlett et al. Ultimately, the achieved results and future challenges are discussed.

Revealing topographic lineaments through IHS enhancement of DEM data. [Digital Elevation Model

NASA Technical Reports Server (NTRS)

Murdock, Gary

1990-01-01

Intensity-hue-saturation (IHS) processing of slope (dip), aspect (dip direction), and elevation to reveal subtle topographic lineaments which may not be obvious in the unprocessed data are used to enhance digital elevation model (DEM) data from northwestern Nevada. This IHS method of lineament identification was applied to a mosiac of 12 square degrees using a Cray Y-MP8/864. Square arrays from 3 x 3 to 31 x 31 points were tested as well as several different slope enhancements. When relatively few points are used to fit the plane, lineaments of various lengths are observed and a mechanism for lineament classification is described. An area encompassing the gold deposits of the Carlin trend and including the Rain in the southeast to Midas in the northwest is investigated in greater detail. The orientation and density of lineaments may be determined on the gently sloping pediment surface as well as in the more steeply sloping ranges.

Modelling of Folding Patterns in Flat Membranes and Cylinders by Origami

NASA Astrophysics Data System (ADS)

Nojima, Taketoshi

This paper describes folding methods of thin flat sheets as well as cylindrical shells by modelling folding patterns through Japanese traditional Origami technique. New folding patterns have been devised in thin flat squared or circular membrane by modifying so called Miura-Ori in Japan (one node with 4 folding lines). Some folding patterns in cylindrical shells have newly been developed including spiral configurations. Devised foldable cylindrical shells were made by using polymer sheets, and it has been assured that they can be folded quite well. The devised models will make it possible to construct foldable/deployable space structures as well as to manufacture foldable industrial products and living goods, e. g., bottles for soft drinks.

An Intelligent Decision System for Intraoperative Somatosensory Evoked Potential Monitoring.

PubMed

Fan, Bi; Li, Han-Xiong; Hu, Yong

2016-02-01

Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicators of a spinal cord injury is the drop in amplitude of the SEP signal in comparison to the nominal baseline that is assumed to be constant during the surgery. However, in practice, the real-time baseline is not constant and may vary during the operation due to nonsurgical factors, such as blood pressure, anaesthesia, etc. Thus, a false warning is often generated if the nominal baseline is used for SEP monitoring. In current practice, human experts must be used to prevent this false warning. However, these well-trained human experts are expensive and may not be reliable and consistent due to various reasons like fatigue and emotion. In this paper, an intelligent decision system is proposed to improve SEP monitoring. First, the least squares support vector regression and multi-support vector regression models are trained to construct the dynamic baseline from historical data. Then a control chart is applied to detect abnormalities during surgery. The effectiveness of the intelligent decision system is evaluated by comparing its performance against the nominal baseline model by using the real experimental datasets derived from clinical conditions.

Estimation of Foot Plantar Center of Pressure Trajectories with Low-Cost Instrumented Insoles Using an Individual-Specific Nonlinear Model.

PubMed

Hu, Xinyao; Zhao, Jun; Peng, Dongsheng; Sun, Zhenglong; Qu, Xingda

2018-02-01

Postural control is a complex skill based on the interaction of dynamic sensorimotor processes, and can be challenging for people with deficits in sensory functions. The foot plantar center of pressure (COP) has often been used for quantitative assessment of postural control. Previously, the foot plantar COP was mainly measured by force plates or complicated and expensive insole-based measurement systems. Although some low-cost instrumented insoles have been developed, their ability to accurately estimate the foot plantar COP trajectory was not robust. In this study, a novel individual-specific nonlinear model was proposed to estimate the foot plantar COP trajectories with an instrumented insole based on low-cost force sensitive resistors (FSRs). The model coefficients were determined by a least square error approximation algorithm. Model validation was carried out by comparing the estimated COP data with the reference data in a variety of postural control assessment tasks. We also compared our data with the COP trajectories estimated by the previously well accepted weighted mean approach. Comparing with the reference measurements, the average root mean square errors of the COP trajectories of both feet were 2.23 mm (±0.64) (left foot) and 2.72 mm (±0.83) (right foot) along the medial-lateral direction, and 9.17 mm (±1.98) (left foot) and 11.19 mm (±2.98) (right foot) along the anterior-posterior direction. The results are superior to those reported in previous relevant studies, and demonstrate that our proposed approach can be used for accurate foot plantar COP trajectory estimation. This study could provide an inexpensive solution to fall risk assessment in home settings or community healthcare center for the elderly. It has the potential to help prevent future falls in the elderly.

Estimation of Foot Plantar Center of Pressure Trajectories with Low-Cost Instrumented Insoles Using an Individual-Specific Nonlinear Model

PubMed Central

Hu, Xinyao; Zhao, Jun; Peng, Dongsheng

2018-01-01

Postural control is a complex skill based on the interaction of dynamic sensorimotor processes, and can be challenging for people with deficits in sensory functions. The foot plantar center of pressure (COP) has often been used for quantitative assessment of postural control. Previously, the foot plantar COP was mainly measured by force plates or complicated and expensive insole-based measurement systems. Although some low-cost instrumented insoles have been developed, their ability to accurately estimate the foot plantar COP trajectory was not robust. In this study, a novel individual-specific nonlinear model was proposed to estimate the foot plantar COP trajectories with an instrumented insole based on low-cost force sensitive resistors (FSRs). The model coefficients were determined by a least square error approximation algorithm. Model validation was carried out by comparing the estimated COP data with the reference data in a variety of postural control assessment tasks. We also compared our data with the COP trajectories estimated by the previously well accepted weighted mean approach. Comparing with the reference measurements, the average root mean square errors of the COP trajectories of both feet were 2.23 mm (±0.64) (left foot) and 2.72 mm (±0.83) (right foot) along the medial–lateral direction, and 9.17 mm (±1.98) (left foot) and 11.19 mm (±2.98) (right foot) along the anterior–posterior direction. The results are superior to those reported in previous relevant studies, and demonstrate that our proposed approach can be used for accurate foot plantar COP trajectory estimation. This study could provide an inexpensive solution to fall risk assessment in home settings or community healthcare center for the elderly. It has the potential to help prevent future falls in the elderly. PMID:29389857

Rapid activity prediction of HIV-1 integrase inhibitors: harnessing docking energetic components for empirical scoring by chemometric and artificial neural network approaches

NASA Astrophysics Data System (ADS)

Thangsunan, Patcharapong; Kittiwachana, Sila; Meepowpan, Puttinan; Kungwan, Nawee; Prangkio, Panchika; Hannongbua, Supa; Suree, Nuttee

2016-06-01

Improving performance of scoring functions for drug docking simulations is a challenging task in the modern discovery pipeline. Among various ways to enhance the efficiency of scoring function, tuning of energetic component approach is an attractive option that provides better predictions. Herein we present the first development of rapid and simple tuning models for predicting and scoring inhibitory activity of investigated ligands docked into catalytic core domain structures of HIV-1 integrase (IN) enzyme. We developed the models using all energetic terms obtained from flexible ligand-rigid receptor dockings by AutoDock4, followed by a data analysis using either partial least squares (PLS) or self-organizing maps (SOMs). The models were established using 66 and 64 ligands of mercaptobenzenesulfonamides for the PLS-based and the SOMs-based inhibitory activity predictions, respectively. The models were then evaluated for their predictability quality using closely related test compounds, as well as five different unrelated inhibitor test sets. Weighting constants for each energy term were also optimized, thus customizing the scoring function for this specific target protein. Root-mean-square error (RMSE) values between the predicted and the experimental inhibitory activities were determined to be <1 (i.e. within a magnitude of a single log scale of actual IC50 values). Hence, we propose that, as a pre-functional assay screening step, AutoDock4 docking in combination with these subsequent rapid weighted energy tuning methods via PLS and SOMs analyses is a viable approach to predict the potential inhibitory activity and to discriminate among small drug-like molecules to target a specific protein of interest.

Structural and configurational properties of nanoconfined monolayer ice from first principles

PubMed Central

Corsetti, Fabiano; Matthews, Paul; Artacho, Emilio

2016-01-01

Understanding the structural tendencies of nanoconfined water is of great interest for nanoscience and biology, where nano/micro-sized objects may be separated by very few layers of water. Here we investigate the properties of ice confined to a quasi-2D monolayer by a featureless, chemically neutral potential, in order to characterize its intrinsic behaviour. We use density-functional theory simulations with a non-local van der Waals density functional. An ab initio random structure search reveals all the energetically competitive monolayer configurations to belong to only two of the previously-identified families, characterized by a square or honeycomb hydrogen-bonding network, respectively. We discuss the modified ice rules needed for each network, and propose a simple point dipole 2D lattice model that successfully explains the energetics of the square configurations. All identified stable phases for both networks are found to be non-polar (but with a topologically non-trivial texture for the square) and, hence, non-ferroelectric, in contrast to previous predictions from a five-site empirical force-field model. Our results are in good agreement with very recently reported experimental observations. PMID:26728125

Structural and configurational properties of nanoconfined monolayer ice from first principles

NASA Astrophysics Data System (ADS)

Corsetti, Fabiano; Matthews, Paul; Artacho, Emilio

2016-01-01

Understanding the structural tendencies of nanoconfined water is of great interest for nanoscience and biology, where nano/micro-sized objects may be separated by very few layers of water. Here we investigate the properties of ice confined to a quasi-2D monolayer by a featureless, chemically neutral potential, in order to characterize its intrinsic behaviour. We use density-functional theory simulations with a non-local van der Waals density functional. An ab initio random structure search reveals all the energetically competitive monolayer configurations to belong to only two of the previously-identified families, characterized by a square or honeycomb hydrogen-bonding network, respectively. We discuss the modified ice rules needed for each network, and propose a simple point dipole 2D lattice model that successfully explains the energetics of the square configurations. All identified stable phases for both networks are found to be non-polar (but with a topologically non-trivial texture for the square) and, hence, non-ferroelectric, in contrast to previous predictions from a five-site empirical force-field model. Our results are in good agreement with very recently reported experimental observations.

Precision PEP-II optics measurement with an SVD-enhanced Least-Square fitting

NASA Astrophysics Data System (ADS)

Yan, Y. T.; Cai, Y.

2006-03-01

A singular value decomposition (SVD)-enhanced Least-Square fitting technique is discussed. By automatic identifying, ordering, and selecting dominant SVD modes of the derivative matrix that responds to the variations of the variables, the converging process of the Least-Square fitting is significantly enhanced. Thus the fitting speed can be fast enough for a fairly large system. This technique has been successfully applied to precision PEP-II optics measurement in which we determine all quadrupole strengths (both normal and skew components) and sextupole feed-downs as well as all BPM gains and BPM cross-plane couplings through Least-Square fitting of the phase advances and the Local Green's functions as well as the coupling ellipses among BPMs. The local Green's functions are specified by 4 local transfer matrix components R12, R34, R32, R14. These measurable quantities (the Green's functions, the phase advances and the coupling ellipse tilt angles and axis ratios) are obtained by analyzing turn-by-turn Beam Position Monitor (BPM) data with a high-resolution model-independent analysis (MIA). Once all of the quadrupoles and sextupole feed-downs are determined, we obtain a computer virtual accelerator which matches the real accelerator in linear optics. Thus, beta functions, linear coupling parameters, and interaction point (IP) optics characteristics can be measured and displayed.

Nonlinear Constitutive Modeling of Piezoelectric Ceramics

NASA Astrophysics Data System (ADS)

Xu, Jia; Li, Chao; Wang, Haibo; Zhu, Zhiwen

2017-12-01

Nonlinear constitutive modeling of piezoelectric ceramics is discussed in this paper. Van der Pol item is introduced to explain the simple hysteretic curve. Improved nonlinear difference items are used to interpret the hysteresis phenomena of piezoelectric ceramics. The fitting effect of the model on experimental data is proved by the partial least-square regression method. The results show that this method can describe the real curve well. The results of this paper are helpful to piezoelectric ceramics constitutive modeling.

Eta Squared, Partial Eta Squared, and Misreporting of Effect Size in Communication Research.

ERIC Educational Resources Information Center

Levine, Timothy R.; Hullett, Craig R.

2002-01-01

Alerts communication researchers to potential errors stemming from the use of SPSS (Statistical Package for the Social Sciences) to obtain estimates of eta squared in analysis of variance (ANOVA). Strives to clarify issues concerning the development and appropriate use of eta squared and partial eta squared in ANOVA. Discusses the reporting of…

Simulation of Multiscale Ground-Water Flow in Part of the Northeastern San Joaquin Valley, California

USGS Publications Warehouse

Phillips, Steven P.; Green, Christopher T.; Burow, Karen R.; Shelton, Jennifer L.; Rewis, Diane L.

2007-01-01

The transport and fate of agricultural chemicals in a variety of environmental settings is being evaluated as part of the U.S. Geological Survey (USGS) National Water-Quality Assessment Program. One of the locations being evaluated is a 2,700-km2 (square kilometer) regional study area in the northeastern San Joaquin Valley surrounding the city of Modesto, an area dominated by irrigated agriculture in a semi-arid climate. Ground water is a key source of water for irrigation and public supply, and exploitation of this resource has altered the natural flow system. The aquifer system is predominantly alluvial, and an unconfined to semiconfined aquifer overlies a confined aquifer in the southwestern part of the study area; these aquifers are separated by the lacustrine Corcoran Clay. A regional-scale 16-layer steady-state model of ground-water flow in the aquifer system in the regional study area was developed to provide boundary conditions for an embedded 110-layer steady-state local-scale model of part of the aquifer system overlying the Corcoran Clay along the Merced River. The purpose of the local-scale model was to develop a better understanding of the aquifer system and to provide a basis for simulation of reactive transport of agricultural chemicals. The heterogeneity of aquifer materials was explicitly incorporated into the regional and local models using information from geologic and drillers? logs of boreholes. Aquifer materials were differentiated in the regional model by the percentage of coarse-grained sediments in a cell, and in the local model by four hydrofacies (sand, silty sand, silt, and clay). The calibrated horizontal hydraulic conductivity values of the coarse-grained materials in the zone above the Corcoran Clay in the regional model and of the sand hydrofacies used in the local model were about equal (30?80 m/d [meter per day]), and the vertical hydraulic conductivity values in the same zone of the regional model (median of 0.012 m/d), which is dominated by the finer-grained materials, were about an order of magnitude less than that for the clay hydrofacies in the local model. Data used for calibrating both models included long-term hourly water-level measurements in 20 short-screened wells installed by the USGS in the Modesto and Merced River areas. Additional calibration data for the regional model included water-level measurements in 11 wells upslope and 17 wells downslope from these areas. The root mean square error was 2.3 m (meter) for all wells in the regional model and 0.8 m for only the USGS wells; the associated average errors were 0.9 m and 0.3 m, respectively. The root mean square error for the 12 USGS wells along a transect in the local model area was 0.08 m; the average error was 0.0 m. Particle tracking was used with the local model to estimate the concentration of an environmental tracer, sulfur hexafluoride, in 10 USGS transect wells near the Merced River that were sampled for this constituent. Measured and estimated concentrations in the mid-depth and deepest wells, which would be most sensitive to errors in hydraulic conductivity estimates, were consistent. The combined results of particle tracking and sulfur hexafluoride analysis suggest that most water sampled from the transect wells was recharged less that 25 years ago.

Aquifer Tests and Characterization of Transmissivity, Ada-Vamoosa Aquifer on the Osage Reservation, Osage County, Oklahoma, 2006

USGS Publications Warehouse

Abbott, Marvin M.; DeHay, Kelli

2008-01-01

The Ada-Vamoosa aquifer of northeastern Oklahoma is a sedimentary bedrock aquifer of Pennsylvanian age that crops out over 800 square miles of the Osage Reservation. The Osage Nation needed additional information regarding the production potential of the aquifer to aid them in future development planning. To address this need, the U.S. Geological Survey, in cooperation with the Osage Nation, conducted a study of aquifer properties in the Ada-Vamoosa aquifer. This report presents the results of the aquifer tests from 20 wells in the Ada-Vamoosa aquifer and one well in a minor aquifer east of the Ada-Vamoosa outcrop on the Osage Reservation. Well information for 17 of the 21 wells in this report was obtained from the Indian Health Service. Data collected by the U.S. Geological Survey during this investigation are pumping well data from four domestic wells collected during the summer of 2006. Transmissivity values were calculated from well pumping data or were estimated from specific capacity values depending on the reliability of the data. The estimated transmissivity values are 1.1 to 4.3 times greater than the calculated transmissivity values. The calculated and estimated transmissivity values range from 5 to 1,000 feet squared per day.

Physicochemical characterization of Lavandula spp. honey with FT-Raman spectroscopy.

PubMed

Anjos, Ofélia; Santos, António J A; Paixão, Vasco; Estevinho, Letícia M

2018-02-01

This study aimed to evaluate the potential of FT-Raman spectroscopy in the prediction of the chemical composition of Lavandula spp. monofloral honey. Partial Least Squares (PLS) regression models were performed for the quantitative estimation and the results were correlated with those obtained using reference methods. Good calibration models were obtained for electrical conductivity, ash, total acidity, pH, reducing sugars, hydroxymethylfurfural (HMF), proline, diastase index, apparent sucrose, total flavonoids content and total phenol content. On the other hand, the model was less accurate for pH determination. The calibration models had high r 2 (ranging between 92.8% and 99.9%), high residual prediction deviation - RPD (ranging between 4.2 and 26.8) and low root mean square errors. These results confirm the hypothesis that FT-Raman is a useful technique for the quality control and chemical properties' evaluation of Lavandula spp honey. Its application may allow improving the efficiency, speed and cost of the current laboratory analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

[External therapy of plasma cell mastitis by jiuyi powder using partial least-squares discriminant analysis: a safety analysis].

PubMed

Ye, Mei-na; Yang, Ming; Cheng, Yi-qin; Wang, Bing; Zhu, Ying; Xia, Ya-ru; Meng, Tian; Chen, Hao; Chen, Li-ying; Cheng, Hong-feng

2015-04-01

To evaluate the safety and the clinical value of external use of jiuyi Powder (JP) in treating plasma cell mastitis using partial least-squares discriminant analysis (PLSDA). Totally 50 patients with plasma cell mastitis treated by external use of JP were observed and biochemical examinations of blood and urine detected before application, at day 4 after application, at day 1 and 14 after discontinuation. Blood mercury and urinary mercury were detected before application, at day 1, 4, and 7 after application, at day 1 and 14 after discontinuation. Urinary mercury was also detected at 28 after discontinuation and 3 months after discontinuation. The information of wound, days of external application and the total dosage of external application were recorded before application, at day 1, 4, and 7 after application, as well as at day 1 after discontinuation. Then a discriminant model covering potential safety factors was set up by PLSDA after screening safety indices with important effects. The applicability of the model was assessed using area under ROC curve. Potential safety factors were assessed using variable importance in the projection (VIP). Urinary β2-microglobulin (β2-MG), urinary N-acetyl-β-D-glucosaminidase (NAG), 24 h urinary protein, and urinary α1-microglobulin (α1-MG) were greatly affected by external use of JP in treating plasma cell mastitis. The accuracy rate of PLSDA discriminate model was 74. 00%. The sensitivity, specificity, and the area under ROC curve was 0. 7826, 0. 7037, and 0. 8084, respectively. Three factors with greater effect on the potential safety were screened as follows: pre-application volume of the sore cavity, days of external application, and the total dosage of external application. PLSDA method could be used in analyzing bioinformation of clinical Chinese medicine. Urinary β2-MG and urinary NAG were two main safety monitoring indices. Days of external application and the total dosage of external application were main factors influencing blood mercury and urine mercury. A safety classification simulation model of treating plasma cell mastitis by external therapy of JP was established by the two factors, which could be used to assess the safety of external application of JP to some extent.

Vapor-liquid equilibrium and critical asymmetry of square well and short square well chain fluids.

PubMed

Li, Liyan; Sun, Fangfang; Chen, Zhitong; Wang, Long; Cai, Jun

2014-08-07

The critical behavior of square well fluids with variable interaction ranges and of short square well chain fluids have been investigated by grand canonical ensemble Monte Carlo simulations. The critical temperatures and densities were estimated by a finite-size scaling analysis with the help of histogram reweighting technique. The vapor-liquid coexistence curve in the near-critical region was determined using hyper-parallel tempering Monte Carlo simulations. The simulation results for coexistence diameters show that the contribution of |t|(1-α) to the coexistence diameter dominates the singular behavior in all systems investigated. The contribution of |t|(2β) to the coexistence diameter is larger for the system with a smaller interaction range λ. While for short square well chain fluids, longer the chain length, larger the contribution of |t|(2β). The molecular configuration greatly influences the critical asymmetry: a short soft chain fluid shows weaker critical asymmetry than a stiff chain fluid with same chain length.

PREDICTION OF MOLECULAR PROPERTIES WITH MID-INFRARED SPECTRA AND INTERFEROGRAMS

EPA Science Inventory

We have built infrared spectroscopy-based partial least squares (PLS) models for molecular polarizabilities using a 97 member training set and a 59 member independent prediction set. These 156 compounds span a very wide range of chemical structure. Our goal was to use this well...

Time series forecasting using ERNN and QR based on Bayesian model averaging

NASA Astrophysics Data System (ADS)

Pwasong, Augustine; Sathasivam, Saratha

2017-08-01

The Bayesian model averaging technique is a multi-model combination technique. The technique was employed to amalgamate the Elman recurrent neural network (ERNN) technique with the quadratic regression (QR) technique. The amalgamation produced a hybrid technique known as the hybrid ERNN-QR technique. The potentials of forecasting with the hybrid technique are compared with the forecasting capabilities of individual techniques of ERNN and QR. The outcome revealed that the hybrid technique is superior to the individual techniques in the mean square error sense.

Ablation and Thermal Response Property Model Validation for Phenolic Impregnated Carbon Ablator

NASA Technical Reports Server (NTRS)

Milos, F. S.; Chen, Y.-K.

2009-01-01

Phenolic Impregnated Carbon Ablator was the heatshield material for the Stardust probe and is also a candidate heatshield material for the Orion Crew Module. As part of the heatshield qualification for Orion, physical and thermal properties were measured for newly manufactured material, included emissivity, heat capacity, thermal conductivity, elemental composition, and thermal decomposition rates. Based on these properties, an ablation and thermal-response model was developed for temperatures up to 3500 K and pressures up to 100 kPa. The model includes orthotropic and pressure-dependent thermal conductivity. In this work, model validation is accomplished by comparison of predictions with data from many arcjet tests conducted over a range of stagnation heat flux and pressure from 107 Watts per square centimeter at 2.3 kPa to 1100 Watts per square centimeter at 84 kPa. Over the entire range of test conditions, model predictions compare well with measured recession, maximum surface temperatures, and in depth temperatures.

Hyperspectral imaging for predicting the allicin and soluble solid content of garlic with variable selection algorithms and chemometric models.

PubMed

Rahman, Anisur; Faqeerzada, Mohammad A; Cho, Byoung-Kwan

2018-03-14

Allicin and soluble solid content (SSC) in garlic is the responsible for its pungent flavor and odor. However, current conventional methods such as the use of high-pressure liquid chromatography and a refractometer have critical drawbacks in that they are time-consuming, labor-intensive and destructive procedures. The present study aimed to predict allicin and SSC in garlic using hyperspectral imaging in combination with variable selection algorithms and calibration models. Hyperspectral images of 100 garlic cloves were acquired that covered two spectral ranges, from which the mean spectra of each clove were extracted. The calibration models included partial least squares (PLS) and least squares-support vector machine (LS-SVM) regression, as well as different spectral pre-processing techniques, from which the highest performing spectral preprocessing technique and spectral range were selected. Then, variable selection methods, such as regression coefficients, variable importance in projection (VIP) and the successive projections algorithm (SPA), were evaluated for the selection of effective wavelengths (EWs). Furthermore, PLS and LS-SVM regression methods were applied to quantitatively predict the quality attributes of garlic using the selected EWs. Of the established models, the SPA-LS-SVM model obtained an Rpred2 of 0.90 and standard error of prediction (SEP) of 1.01% for SSC prediction, whereas the VIP-LS-SVM model produced the best result with an Rpred2 of 0.83 and SEP of 0.19 mg g -1 for allicin prediction in the range 1000-1700 nm. Furthermore, chemical images of garlic were developed using the best predictive model to facilitate visualization of the spatial distributions of allicin and SSC. The present study clearly demonstrates that hyperspectral imaging combined with an appropriate chemometrics method can potentially be employed as a fast, non-invasive method to predict the allicin and SSC in garlic. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Implementation of neural network for color properties of polycarbonates

NASA Astrophysics Data System (ADS)

Saeed, U.; Ahmad, S.; Alsadi, J.; Ross, D.; Rizvi, G.

2014-05-01

In present paper, the applicability of artificial neural networks (ANN) is investigated for color properties of plastics. The neural networks toolbox of Matlab 6.5 is used to develop and test the ANN model on a personal computer. An optimal design is completed for 10, 12, 14,16,18 & 20 hidden neurons on single hidden layer with five different algorithms: batch gradient descent (GD), batch variable learning rate (GDX), resilient back-propagation (RP), scaled conjugate gradient (SCG), levenberg-marquardt (LM) in the feed forward back-propagation neural network model. The training data for ANN is obtained from experimental measurements. There were twenty two inputs including resins, additives & pigments while three tristimulus color values L*, a* and b* were used as output layer. Statistical analysis in terms of Root-Mean-Squared (RMS), absolute fraction of variance (R squared), as well as mean square error is used to investigate the performance of ANN. LM algorithm with fourteen neurons on hidden layer in Feed Forward Back-Propagation of ANN model has shown best result in the present study. The degree of accuracy of the ANN model in reduction of errors is proven acceptable in all statistical analysis and shown in results. However, it was concluded that ANN provides a feasible method in error reduction in specific color tristimulus values.

A square wave is the most efficient and reliable waveform for resonant actuation of micro switches

NASA Astrophysics Data System (ADS)

Ben Sassi, S.; Khater, M. E.; Najar, F.; Abdel-Rahman, E. M.

2018-05-01

This paper investigates efficient actuation methods of shunt MEMS switches and other parallel-plate actuators. We start by formulating a multi-physics model of the micro switch, coupling the nonlinear Euler-Bernoulli beam theory with the nonlinear Reynolds equation to describe the structural and fluidic domains, respectively. The model takes into account fringing field effects as well as mid-plane stretching and squeeze film damping nonlinearities. Static analysis is undertaken using the differential quadrature method (DQM) to obtain the pull-in voltage, which is verified by means of the finite element model and validated experimentally. We develop a reduced order model employing the Galerkin method for the structural domain and DQM for the fluidic domain. The proposed waveforms are intended to be more suitable for integrated circuit standards. The dynamic response of the micro switch to harmonic, square and triangular waveforms are evaluated and compared experimentally and analytically. Low voltage actuation is obtained using dynamic pull-in with the proposed waveforms. In addition, global stability analysis carried out for the three signals shows advantages of employing the square signal as the actuation method in enhancing the performance of the micro switch in terms of actuation voltage, switching time, and sensitivity to initial conditions.

Comparison of Regression Methods to Compute Atmospheric Pressure and Earth Tidal Coefficients in Water Level Associated with Wenchuan Earthquake of 12 May 2008

NASA Astrophysics Data System (ADS)

He, Anhua; Singh, Ramesh P.; Sun, Zhaohua; Ye, Qing; Zhao, Gang

2016-07-01

The earth tide, atmospheric pressure, precipitation and earthquake fluctuations, especially earthquake greatly impacts water well levels, thus anomalous co-seismic changes in ground water levels have been observed. In this paper, we have used four different models, simple linear regression (SLR), multiple linear regression (MLR), principal component analysis (PCA) and partial least squares (PLS) to compute the atmospheric pressure and earth tidal effects on water level. Furthermore, we have used the Akaike information criterion (AIC) to study the performance of various models. Based on the lowest AIC and sum of squares for error values, the best estimate of the effects of atmospheric pressure and earth tide on water level is found using the MLR model. However, MLR model does not provide multicollinearity between inputs, as a result the atmospheric pressure and earth tidal response coefficients fail to reflect the mechanisms associated with the groundwater level fluctuations. On the premise of solving serious multicollinearity of inputs, PLS model shows the minimum AIC value. The atmospheric pressure and earth tidal response coefficients show close response with the observation using PLS model. The atmospheric pressure and the earth tidal response coefficients are found to be sensitive to the stress-strain state using the observed data for the period 1 April-8 June 2008 of Chuan 03# well. The transient enhancement of porosity of rock mass around Chuan 03# well associated with the Wenchuan earthquake (Mw = 7.9 of 12 May 2008) that has taken its original pre-seismic level after 13 days indicates that the co-seismic sharp rise of water well could be induced by static stress change, rather than development of new fractures.

TH-E-BRF-09: Gaussian Mixture Model Analysis of Radiation-Induced Parotid-Gland Injury: An Ultrasound Study of Acute and Late Xerostomia in Head-And-Neck Radiotherapy

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

Liu, T; Yu, D; Beitler, J

Purpose: Xerostomia (dry mouth), secondary to parotid-gland injury, is a distressing side-effect in head-and-neck radiotherapy (RT). This study's purpose is to develop a novel ultrasound technique to quantitatively evaluate post-RT parotid-gland injury. Methods: Recent ultrasound studies have shown that healthy parotid glands exhibit homogeneous echotexture, whereas post-RT parotid glands are often heterogeneous, with multiple hypoechoic (inflammation) or hyperechoic (fibrosis) regions. We propose to use a Gaussian mixture model to analyze the ultrasonic echo-histogram of the parotid glands. An IRB-approved clinical study was conducted: (1) control-group: 13 healthy-volunteers, served as the control; (2) acutetoxicity group − 20 patients (mean age: 62.5more » ± 8.9 years, follow-up: 2.0±0.8 months); and (3) late-toxicity group − 18 patients (mean age: 60.7 ± 7.3 years, follow-up: 20.1±10.4 months). All patients experienced RTOG grade 1 or 2 salivary-gland toxicity. Each participant underwent an ultrasound scan (10 MHz) of the bilateral parotid glands. An echo-intensity histogram was derived for each parotid and a Gaussian mixture model was used to fit the histogram using expectation maximization (EM) algorithm. The quality of the fitting was evaluated with the R-squared value. Results: (1) Controlgroup: all parotid glands fitted well with one Gaussian component, with a mean intensity of 79.8±4.9 (R-squared>0.96). (2) Acute-toxicity group: 37 of the 40 post-RT parotid glands fitted well with two Gaussian components, with a mean intensity of 42.9±7.4, 73.3±12.2 (R-squared>0.95). (3) Latetoxicity group: 32 of the 36 post-RT parotid fitted well with 3 Gaussian components, with mean intensities of 49.7±7.6, 77.2±8.7, and 118.6±11.8 (R-squared>0.98). Conclusion: RT-associated parotid-gland injury is common in head-and-neck RT, but challenging to assess. This work has demonstrated that the Gaussian mixture model of the echo-histogram could quantify acute and late toxicity of the parotid glands. This study provides meaningful preliminary data from future observational and interventional clinical research.« less

Using Weighted Least Squares Regression for Obtaining Langmuir Sorption Constants

USDA-ARS?s Scientific Manuscript database

One of the most commonly used models for describing phosphorus (P) sorption to soils is the Langmuir model. To obtain model parameters, the Langmuir model is fit to measured sorption data using least squares regression. Least squares regression is based on several assumptions including normally dist...

Application of artificial neural networks to assess pesticide contamination in shallow groundwater

USGS Publications Warehouse

Sahoo, G.B.; Ray, C.; Mehnert, E.; Keefer, D.A.

2006-01-01

In this study, a feed-forward back-propagation neural network (BPNN) was developed and applied to predict pesticide concentrations in groundwater monitoring wells. Pesticide concentration data are challenging to analyze because they tend to be highly censored. Input data to the neural network included the categorical indices of depth to aquifer material, pesticide leaching class, aquifer sensitivity to pesticide contamination, time (month) of sample collection, well depth, depth to water from land surface, and additional travel distance in the saturated zone (i.e., distance from land surface to midpoint of well screen). The output of the neural network was the total pesticide concentration detected in the well. The model prediction results produced good agreements with observed data in terms of correlation coefficient (R = 0.87) and pesticide detection efficiency (E = 89%), as well as good match between the observed and predicted "class" groups. The relative importance of input parameters to pesticide occurrence in groundwater was examined in terms of R, E, mean error (ME), root mean square error (RMSE), and pesticide occurrence "class" groups by eliminating some key input parameters to the model. Well depth and time of sample collection were the most sensitive input parameters for predicting the pesticide contamination potential of a well. This infers that wells tapping shallow aquifers are more vulnerable to pesticide contamination than those wells tapping deeper aquifers. Pesticide occurrences during post-application months (June through October) were found to be 2.5 to 3 times higher than pesticide occurrences during other months (November through April). The BPNN was used to rank the input parameters with highest potential to contaminate groundwater, including two original and five ancillary parameters. The two original parameters are depth to aquifer material and pesticide leaching class. When these two parameters were the only input parameters for the BPNN, they were not able to predict contamination potential. However, when they were used with other parameters, the predictive performance efficiency of the BPNN in terms of R, E, ME, RMSE, and pesticide occurrence "class" groups increased. Ancillary data include data collected during the study such as well depth and time of sample collection. The BPNN indicated that the ancillary data had more predictive power than the original data. The BPNN results will help researchers identify parameters to improve maps of aquifer sensitivity to pesticide contamination. ?? 2006 Elsevier B.V. All rights reserved.

Solar System science with the Large Synoptic Survey Telescope

NASA Astrophysics Data System (ADS)

Jones, Lynne; Brown, Mike; Ivezić, Zeljko; Jurić, Mario; Malhotra, Renu; Trilling, David

2015-11-01

The Large Synoptic Survey Telescope (LSST; http://lsst.org) will be a large-aperture, wide-field, ground-based telescope that will survey half the sky every few nights in six optical bands from 320 to 1050 nm. It will explore a wide range of astrophysical questions, ranging from performing a census of the Solar System, to examining the nature of dark energy. It is currently in construction, slated for first light in 2019 and full operations by 2022.The LSST will survey over 20,000 square degrees with a rapid observational cadence, to typical limiting magnitudes of r~24.5 in each visit (9.6 square degree field of view). Automated software will link the individual detections into orbits; these orbits, as well as precisely calibrated astrometry (~50mas) and photometry (~0.01-0.02 mag) in multiple bandpasses will be available as LSST data products. The resulting data set will have tremendous potential for planetary astronomy; multi-color catalogs of hundreds of thousands of NEOs and Jupiter Trojans, millions of asteroids, tens of thousands of TNOs, as well as thousands of other objects such as comets and irregular satellites of the major planets.LSST catalogs will increase the sample size of objects with well-known orbits 10-100 times for small body populations throughout the Solar System, enabling a major increase in the completeness level of the inventory of most dynamical classes of small bodies and generating new insights into planetary formation and evolution. Precision multi-color photometry will allow determination of lightcurves and colors, as well as spin state and shape modeling through sparse lightcurve inversion. LSST is currently investigating survey strategies to optimize science return across a broad range of goals. To aid in this investigation, we are making a series of realistic simulated survey pointing histories available together with a Python software package to model and evaluate survey detections for a user-defined input population. Preliminary metrics from these simulations are shown here; the community is invited to provide further input.

Digital data base application to porphyry copper mineralization in Alaska; case study summary

USGS Publications Warehouse

Trautwein, Charles M.; Greenlee, David D.; Orr, Donald G.

1982-01-01

The purpose of this report is to summarize the progress in use of digital image analysis techniques in developing a conceptual model for assessing porphyry copper mineral potential. The study area consists of approximately the southern one-half of the 1? by 3? Nabesna quadrangle in east-central Alaska. The digital geologic data base consists of data compiled under the Alaskan Mineral Resource Assessment Program (AMRAP) as well as digital elevation data and Landsat spectral reflectance data from the Multispectral Scanner System. The digital data base used to develop and implement a conceptual model for porphyry-type copper mineralization consisted of 16 original data types and 18 derived data sets formatted in a grid-cell (raster) structure and registered to a map base in the Universal Transverse Mercator (UTM) projection. Minimum curvature and inverse distance squared interpolation techniques were used to generate continuous surfaces from sets of irregularly spaced data points. Processing requirements included: (1) merging or overlaying of data sets, (2) display and color coding of maps and images, (3) univariate and multivariate statistical analyses, and (4) compound overlaying operations. Data sets were merged and processed to create stereoscopic displays of continuous surfaces. The ratio of several data sets were calculated to evaluate relative variations and to enhance the display of surface alteration (gossans). Factor analysis and principal components analysis techniques were used to determine complex relationships and correlations between data sets. The resultant model consists of 10 parameters that identify three areas most likely to contain porphyry copper mineralization; two of these areas are known occurrences of mineralization and the third is not well known. Field studies confirmed that the three areas identified by the model have significant copper potential.

Raman microspectroscopy for in situ examination of carbon-microbe-mineral interactions

NASA Astrophysics Data System (ADS)

Creamer, C.; Foster, A. L.; Lawrence, C. R.; Mcfarland, J. W.; Waldrop, M. P.

2016-12-01

The changing paradigm of soil organic matter formation and turnover is focused at the nexus of microbe-carbon-mineral interactions. However, visualizing biotic and abiotic stabilization of C on mineral surfaces is difficult given our current techniques. Therefore we investigated Raman microspectroscopy as a potential tool to examine microbially mediated organo-mineral associations. Raman microspectroscopy is a non-destructive technique that has been used to identify microorganisms and minerals, and to quantify microbial assimilation of 13C labeled substrates in culture. We developed a partial least squares regression (PLSR) model to accurately quantify (within 5%) adsorption of four model 12C substrates (glucose, glutamic acid, oxalic acid, p-hydroxybenzoic acid) on a range of soil minerals. We also developed a PLSR model to quantify the incorporation of 13C into E. coli cells. Using these two models, along with measures of the 13C content of respired CO2, we determined the allocation of glucose-derived C into mineral-associated microbial biomass and respired CO2 in situ and through time. We observed progressive 13C enrichment of microbial biomass with incubation time, as well as 13C enrichment of CO2 indicating preferential decomposition of glucose-derived C. We will also present results on the application of our in situ chamber to quantify the formation of organo-mineral associations under both abiotic and biotic conditions with a variety of C and mineral substrates, as well as the rate of turnover and stabilization of microbial residues. Application of Raman microspectroscopy to microbial-mineral interactions represents a novel method to quantify microbial transformation of C substrates and subsequent mineral stabilization without destructive sampling, and has the potential to provide new insights to our conceptual understanding of carbon-microbe-mineral interactions.

Elastic Model Transitions: a Hybrid Approach Utilizing Quadratic Inequality Constrained Least Squares (LSQI) and Direct Shape Mapping (DSM)

NASA Technical Reports Server (NTRS)

Jurenko, Robert J.; Bush, T. Jason; Ottander, John A.

2014-01-01

A method for transitioning linear time invariant (LTI) models in time varying simulation is proposed that utilizes both quadratically constrained least squares (LSQI) and Direct Shape Mapping (DSM) algorithms to determine physical displacements. This approach is applicable to the simulation of the elastic behavior of launch vehicles and other structures that utilize multiple LTI finite element model (FEM) derived mode sets that are propagated throughout time. The time invariant nature of the elastic data for discrete segments of the launch vehicle trajectory presents a problem of how to properly transition between models while preserving motion across the transition. In addition, energy may vary between flex models when using a truncated mode set. The LSQI-DSM algorithm can accommodate significant changes in energy between FEM models and carries elastic motion across FEM model transitions. Compared with previous approaches, the LSQI-DSM algorithm shows improvements ranging from a significant reduction to a complete removal of transients across FEM model transitions as well as maintaining elastic motion from the prior state.

An Application of M[subscript 2] Statistic to Evaluate the Fit of Cognitive Diagnostic Models

ERIC Educational Resources Information Center

Liu, Yanlou; Tian, Wei; Xin, Tao

2016-01-01

The fit of cognitive diagnostic models (CDMs) to response data needs to be evaluated, since CDMs might yield misleading results when they do not fit the data well. Limited-information statistic M[subscript 2] and the associated root mean square error of approximation (RMSEA[subscript 2]) in item factor analysis were extended to evaluate the fit of…

Differences in Gaussian diffusion tensor imaging and non-Gaussian diffusion kurtosis imaging model-based estimates of diffusion tensor invariants in the human brain.

PubMed

Lanzafame, S; Giannelli, M; Garaci, F; Floris, R; Duggento, A; Guerrisi, M; Toschi, N

2016-05-01

An increasing number of studies have aimed to compare diffusion tensor imaging (DTI)-related parameters [e.g., mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD)] to complementary new indexes [e.g., mean kurtosis (MK)/radial kurtosis (RK)/axial kurtosis (AK)] derived through diffusion kurtosis imaging (DKI) in terms of their discriminative potential about tissue disease-related microstructural alterations. Given that the DTI and DKI models provide conceptually and quantitatively different estimates of the diffusion tensor, which can also depend on fitting routine, the aim of this study was to investigate model- and algorithm-dependent differences in MD/FA/RD/AD and anisotropy mode (MO) estimates in diffusion-weighted imaging of human brain white matter. The authors employed (a) data collected from 33 healthy subjects (20-59 yr, F: 15, M: 18) within the Human Connectome Project (HCP) on a customized 3 T scanner, and (b) data from 34 healthy subjects (26-61 yr, F: 5, M: 29) acquired on a clinical 3 T scanner. The DTI model was fitted to b-value =0 and b-value =1000 s/mm(2) data while the DKI model was fitted to data comprising b-value =0, 1000 and 3000/2500 s/mm(2) [for dataset (a)/(b), respectively] through nonlinear and weighted linear least squares algorithms. In addition to MK/RK/AK maps, MD/FA/MO/RD/AD maps were estimated from both models and both algorithms. Using tract-based spatial statistics, the authors tested the null hypothesis of zero difference between the two MD/FA/MO/RD/AD estimates in brain white matter for both datasets and both algorithms. DKI-derived MD/FA/RD/AD and MO estimates were significantly higher and lower, respectively, than corresponding DTI-derived estimates. All voxelwise differences extended over most of the white matter skeleton. Fractional differences between the two estimates [(DKI - DTI)/DTI] of most invariants were seen to vary with the invariant value itself as well as with MK/RK/AK values, indicating substantial anatomical variability of these discrepancies. In the HCP dataset, the median voxelwise percentage differences across the whole white matter skeleton were (nonlinear least squares algorithm) 14.5% (8.2%-23.1%) for MD, 4.3% (1.4%-17.3%) for FA, -5.2% (-48.7% to -0.8%) for MO, 12.5% (6.4%-21.2%) for RD, and 16.1% (9.9%-25.6%) for AD (all ranges computed as 0.01 and 0.99 quantiles). All differences/trends were consistent between the discovery (HCP) and replication (local) datasets and between estimation algorithms. However, the relationships between such trends, estimated diffusion tensor invariants, and kurtosis estimates were impacted by the choice of fitting routine. Model-dependent differences in the estimation of conventional indexes of MD/FA/MO/RD/AD can be well beyond commonly seen disease-related alterations. While estimating diffusion tensor-derived indexes using the DKI model may be advantageous in terms of mitigating b-value dependence of diffusivity estimates, such estimates should not be referred to as conventional DTI-derived indexes in order to avoid confusion in interpretation as well as multicenter comparisons. In order to assess the potential and advantages of DKI with respect to DTI as well as to standardize diffusion-weighted imaging methods between centers, both conventional DTI-derived indexes and diffusion tensor invariants derived by fitting the non-Gaussian DKI model should be separately estimated and analyzed using the same combination of fitting routines.

Tree-ring growth of Scots pine, Common beech and Pedunculate oak under future climate in northeastern Germany

NASA Astrophysics Data System (ADS)

Jurasinski, Gerald; Scharnweber, Tobias; Schröder, Christian; Lennartz, Bernd; Bauwe, Andreas

2017-04-01

Tree growth depends, among other factors, largely on the prevailing climatic conditions. Therefore, tree growth patterns are to be expected under climate change. Here, we analyze the tree-ring growth response of three major European tree species to projected future climate across a climatic (mostly precipitation) gradient in northeastern Germany. We used monthly data for temperature, precipitation, and the standardized precipitation evapotranspiration index (SPEI) over multiple time scales (1, 3, 6, 12, and 24 months) to construct models of tree-ring growth for Scots pine (Pinus syl- vestris L.) at three pure stands, and for Common beech (Fagus sylvatica L.) and Pedunculate oak (Quercus robur L.) at three mature mixed stands. The regression models were derived using a two-step approach based on partial least squares regression (PLSR) to extract potentially well explaining variables followed by ordinary least squares regression (OLSR) to consolidate the models to the least number of variables while retaining high explanatory power. The stability of the models was tested with a comprehensive calibration-verification scheme. All models were successfully verified with R2s ranging from 0.21 for the western pine stand to 0.62 for the beech stand in the east. For growth prediction, climate data forecasted until 2100 by the regional climate model WETTREG2010 based on the A1B Intergovernmental Panel on Climate Change (IPCC) emission scenario was used. For beech and oak, growth rates will likely decrease until the end of the 21st century. For pine, modeled growth trends vary and range from a slight growth increase to a weak decrease in growth rates depending on the position along the climatic gradient. The climatic gradient across the study area will possibly affect the future growth of oak with larger growth reductions towards the drier east. For beech, site-specific adaptations seem to override the influence of the climatic gradient. We conclude that in Northeastern Germany Scots pine has great potential to remain resilient to projected climate change without any greater impairment, whereas Common beech and Pedunculate oak will likely face lesser growth under the expected warmer and dryer climate conditions. The results call for an adaptation of forest management to mitigate the negative effects of climate change for beech and oak in the region.

Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network

NASA Astrophysics Data System (ADS)

Fang, Kuai; Shen, Chaopeng; Kifer, Daniel; Yang, Xiao

2017-11-01

The Soil Moisture Active Passive (SMAP) mission has delivered valuable sensing of surface soil moisture since 2015. However, it has a short time span and irregular revisit schedules. Utilizing a state-of-the-art time series deep learning neural network, Long Short-Term Memory (LSTM), we created a system that predicts SMAP level-3 moisture product with atmospheric forcings, model-simulated moisture, and static physiographic attributes as inputs. The system removes most of the bias with model simulations and improves predicted moisture climatology, achieving small test root-mean-square errors (<0.035) and high-correlation coefficients >0.87 for over 75% of Continental United States, including the forested southeast. As the first application of LSTM in hydrology, we show the proposed network avoids overfitting and is robust for both temporal and spatial extrapolation tests. LSTM generalizes well across regions with distinct climates and environmental settings. With high fidelity to SMAP, LSTM shows great potential for hindcasting, data assimilation, and weather forecasting.

Development of a beverage benchtop prototype based on sweet potato peels: optimization of antioxidant activity by a mixture design.

PubMed

Anastácio, Ana; Carvalho, Isabel Saraiva de

2015-08-01

A beverage benchtop prototype related to oxidative stress protection was developed based on sweet potato peels phenolics. Formula components were sweet potato peel (Ipomoeas batatas L.) aqueous extract (SPPE), sweet potato leaves water extract (SPLE) and honey solution (HonS). According to linear squares regression (LSR) models, SPLE presented higher additive effect on total phenolic content (TPC), FRAP and DPPH than the other components. All antagonist interactions were not significant. The optimum formula obtained by artificial neural networks (ANN) analysis was 50.0% of SPPE, 21.5% of SPLE and 28.5% of HonS. Predicted responses of TPC, FRAP, DPPH and soluble solids were 309 mg GAE/L, 476 mg TE/L, 1098 mg TE/L and 12.3 °Brix, respectively. Optimization with LSR models was similar to ANN. Beverage prototype results positioned next to commercial vegetable and fruit beverages, thus it has an interesting potential to the market of health and wellness.

Systematic construction of spin liquids on the square lattice from tensor networks with SU(2) symmetry

NASA Astrophysics Data System (ADS)

Mambrini, Matthieu; Orús, Román; Poilblanc, Didier

2016-11-01

We elaborate a simple classification scheme of all rank-5 SU(2) spin rotational symmetric tensors according to (i) the onsite physical spin S , (ii) the local Hilbert space V⊗4 of the four virtual (composite) spins attached to each site, and (iii) the irreducible representations of the C4 v point group of the square lattice. We apply our scheme to draw a complete list of all SU(2)-symmetric translationally and rotationally invariant projected entangled pair states (PEPS) with bond dimension D ≤6 . All known SU(2)-symmetric PEPS on the square lattice are recovered and simple generalizations are provided in some cases. More generally, to each of our symmetry class can be associated a (D -1 )-dimensional manifold of spin liquids (potentially) preserving lattice symmetries and defined in terms of D -independent tensors of a given bond dimension D . In addition, generic (low-dimensional) families of PEPS explicitly breaking either (i) particular point-group lattice symmetries (lattice nematics) or (ii) time-reversal symmetry (chiral spin liquids) or (iii) SU(2) spin rotation symmetry down to U(1 ) (spin nematics or Néel antiferromagnets) can also be constructed. We apply this framework to search for new topological chiral spin liquids characterized by well-defined chiral edge modes, as revealed by their entanglement spectrum. In particular, we show how the symmetrization of a double-layer PEPS leads to a chiral topological state with a gapless edge described by a SU (2) 2 Wess-Zumino-Witten model.

A nonlinear model of gold production in Malaysia

NASA Astrophysics Data System (ADS)

Ramli, Norashikin; Muda, Nora; Umor, Mohd Rozi

2014-06-01

Malaysia is a country which is rich in natural resources and one of it is a gold. Gold has already become an important national commodity. This study is conducted to determine a model that can be well fitted with the gold production in Malaysia from the year 1995-2010. Five nonlinear models are presented in this study which are Logistic model, Gompertz, Richard, Weibull and Chapman-Richard model. These model are used to fit the cumulative gold production in Malaysia. The best model is then selected based on the model performance. The performance of the fitted model is measured by sum squares error, root mean squares error, coefficient of determination, mean relative error, mean absolute error and mean absolute percentage error. This study has found that a Weibull model is shown to have significantly outperform compare to the other models. To confirm that Weibull is the best model, the latest data are fitted to the model. Once again, Weibull model gives the lowest readings at all types of measurement error. We can concluded that the future gold production in Malaysia can be predicted according to the Weibull model and this could be important findings for Malaysia to plan their economic activities.

Solution of a few nonlinear problems in aerodynamics by the finite elements and functional least squares methods. Ph.D. Thesis - Paris Univ.; [mathematical models of transonic flow using nonlinear equations

NASA Technical Reports Server (NTRS)

Periaux, J.

1979-01-01

The numerical simulation of the transonic flows of idealized fluids and of incompressible viscous fluids, by the nonlinear least squares methods is presented. The nonlinear equations, the boundary conditions, and the various constraints controlling the two types of flow are described. The standard iterative methods for solving a quasi elliptical nonlinear equation with partial derivatives are reviewed with emphasis placed on two examples: the fixed point method applied to the Gelder functional in the case of compressible subsonic flows and the Newton method used in the technique of decomposition of the lifting potential. The new abstract least squares method is discussed. It consists of substituting the nonlinear equation by a problem of minimization in a H to the minus 1 type Sobolev functional space.

Inverse square law isothermal property in relativistic charged static distributions

NASA Astrophysics Data System (ADS)

Hansraj, Sudan; Qwabe, Nkululeko

2017-12-01

We analyze the impact of the inverse square law fall-off of the energy density in a charged isotropic spherically symmetric fluid. Initially, we impose a linear barotropic equation of state p = αρ but this leads to an intractable differential equation. Next, we consider the neutral isothermal metric of Saslaw et al. [Phys. Rev. D 13, 471 (1996)] in an electric field and the usual inverse square law of energy density and pressure results thus preserving the equation of state. Additionally, we discard a linear equation of state and endeavor to find new classes of solutions with the inverse square law fall-off of density. Certain prescribed forms of the spatial and temporal gravitational forms result in new exact solutions. An interesting result that emerges is that while isothermal fluid spheres are unbounded in the neutral case, this is not so when charge is involved. Indeed it was found that barotropic equations of state exist and hypersurfaces of vanishing pressure exist establishing a boundary in practically all models. One model was studied in depth and found to satisfy other elementary requirements for physical admissibility such as a subluminal sound speed as well as gravitational surface redshifts smaller than 2. Buchdahl [Acta Phys. Pol. B 10, 673 (1965)], Böhmer and Harko [Gen. Relat. Gravit. 39, 757 (2007)] and Andréasson [Commum. Math. Phys. 198, 507 (2009)] mass-radius bounds were also found to be satisfied. Graphical plots utilizing constants selected from the boundary conditions established that the model displayed characteristics consistent with physically viable models.

Exactly solved models on planar graphs with vertices in {Z}^3

NASA Astrophysics Data System (ADS)

Kels, Andrew P.

2017-12-01

It is shown how exactly solved edge interaction models on the square lattice, may be extended onto more general planar graphs, with edges connecting a subset of next nearest neighbour vertices of {Z}3 . This is done by using local deformations of the square lattice, that arise through the use of the star-triangle relation. Similar to Baxter’s Z-invariance property, these local deformations leave the partition function invariant up to some simple factors coming from the star-triangle relation. The deformations used here extend the usual formulation of Z-invariance, by requiring the introduction of oriented rapidity lines which form directed closed paths in the rapidity graph of the model. The quasi-classical limit is also considered, in which case the deformations imply a classical Z-invariance property, as well as a related local closure relation, for the action functional of a system of classical discrete Laplace equations.

Experimental and theoretical investigation of the magnetization dynamics of an artificial square spin ice cluster

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

Pohlit, Merlin, E-mail: pohlit@physik.uni-frankfurt.de; Porrati, Fabrizio; Huth, Michael

We study the magnetization dynamics of a spin ice cluster which is a building block of an artificial square spin ice fabricated by focused electron-beam-induced deposition both experimentally and theoretically. The spin ice cluster is composed of twelve interacting Co nanoislands grown directly on top of a high-resolution micro-Hall sensor. By employing micromagnetic simulations and a macrospin model, we calculate the magnetization and the experimentally investigated stray field emanating from a single nanoisland. The parameters determined from a comparison with the experimental hysteresis loop are used to derive an effective single-dipole macrospin model that allows us to investigate the dynamicsmore » of the spin ice cluster. Our model reproduces the experimentally observed non-deterministic sequences in the magnetization curves as well as the distinct temperature dependence of the hysteresis loop.« less

Identification of Anisotropic Criteria for Stratified Soil Based on Triaxial Tests Results

NASA Astrophysics Data System (ADS)

Tankiewicz, Matylda; Kawa, Marek

2017-09-01

The paper presents the identification methodology of anisotropic criteria based on triaxial test results. The considered material is varved clay - a sedimentary soil occurring in central Poland which is characterized by the so-called "layered microstructure". The strength examination outcomes were identified by standard triaxial tests. The results include the estimated peak strength obtained for a wide range of orientations and confining pressures. Two models were chosen as potentially adequate for the description of the tested material, namely Pariseau and its conjunction with the Jaeger weakness plane. Material constants were obtained by fitting the model to the experimental results. The identification procedure is based on the least squares method. The optimal values of parameters are searched for between specified bounds by sequentially decreasing the distance between points and reducing the length of the searched range. For both considered models the optimal parameters have been obtained. The comparison of theoretical and experimental results as well as the assessment of the suitability of selected criteria for the specified range of confining pressures are presented.

Optimal and heuristic algorithms of planning of low-rise residential buildings

NASA Astrophysics Data System (ADS)

Kartak, V. M.; Marchenko, A. A.; Petunin, A. A.; Sesekin, A. N.; Fabarisova, A. I.

2017-10-01

The problem of the optimal layout of low-rise residential building is considered. Each apartment must be no less than the corresponding apartment from the proposed list. Also all requests must be made and excess of the total square over of the total square of apartment from the list must be minimized. The difference in the squares formed due to with the discreteness of distances between bearing walls and a number of other technological limitations. It shown, that this problem is NP-hard. The authors built a linear-integer model and conducted her qualitative analysis. As well, authors developed a heuristic algorithm for the solution tasks of a high dimension. The computational experiment was conducted which confirming the efficiency of the proposed approach. Practical recommendations on the use the proposed algorithms are given.

Broken Squares: A Simulation Exploring Cooperation and Conflict.

ERIC Educational Resources Information Center

Stanford Univ., CA. Stanford Program on International and Cross Cultural Education.

This simulation activity introduces the concepts of cooperation and competition and exploring positive models for problem solving. The activity can be used with elementary and secondary school participants, as well as with adults. Suggestions for adapting discussion for younger participants are provided. The group task is to form five equal-sized…

Modelling duality between bound and resonant meson spectra by means of free quantum motions on the de Sitter space-time dS4

NASA Astrophysics Data System (ADS)

Kirchbach, M.; Compean, C. B.

2016-07-01

The real parts of the complex squared energies defined by the resonance poles of the transfer matrix of the Pöschl-Teller barrier, are shown to equal the squared energies of the levels bound within the trigonometric Scarf well potential. By transforming these potentials into parts of the Laplacians describing free quantum motions on the mutually orthogonal open-time-like hyperbolic-, and closed-space-like spherical geodesics on the conformally invariant de Sitter space-time, dS4, the conformal symmetries of these interactions are revealed. On dS4 the potentials under consideration naturally relate to interactions within colorless two-body systems and to cusped Wilson loops. In effect, with the aid of the dS4 space-time as unifying geometry, a conformal symmetry based bijective correspondence (duality) between bound and resonant meson spectra is established at the quantum mechanics level and related to confinement understood as color charge neutrality. The correspondence allows to link the interpretation of mesons as resonance poles of a scattering matrix with their complementary description as states bound by an instantaneous quark interaction and to introduce a conformal symmetry based classification scheme of mesons. As examples representative of such a duality we organize in good agreement with data 71 of the reported light flavor mesons with masses below ˜ 2350 MeV into four conformal families of particles placed on linear f0, π , η , and a0 resonance trajectories, plotted on the ℓ/ M plane. Upon extending the sec2 χ by a properly constructed conformal color dipole potential, shaped after a tangent function, we predict the masses of 12 "missing" mesons. We furthermore notice that the f0 and π trajectories can be viewed as chiral partners, same as the η and a0 trajectories, an indication that chiral symmetry for mesons is likely to be realized in terms of parity doubled conformal multiplets rather than, as usually assumed, only in terms of parity doubled single SO(3) states. We attribute the striking measured meson degeneracies to conformal symmetry dynamics within color neutral two-body systems, and conclude on the usefulness of the de Sitter space-time, dS4, as a tool for modelling strong interactions, on the one side, and on the relevance of hyperbolic and trigonometric potentials in constituent quark models of hadrons, on the other.

Quasisaddles as relevant points of the potential energy surface in the dynamics of supercooled liquids

NASA Astrophysics Data System (ADS)

Angelani, L.; Di Leonardo, R.; Ruocco, G.; Scala, A.; Sciortino, F.

2002-06-01

The supercooled dynamics of a Lennard-Jones model liquid is numerically investigated studying relevant points of the potential energy surface, i.e., the minima of the square gradient of total potential energy V. The main findings are (i) the number of negative curvatures n of these sampled points appears to extrapolate to zero at the mode coupling critical temperature Tc; (ii) the temperature behavior of n(T) has a close relationship with the temperature behavior of the diffusivity; (iii) the potential energy landscape shows a high regularity in the distances among the relevant points and in their energy location. Finally we discuss a model of the landscape, previously introduced by Madan and Keyes [J. Chem. Phys. 98, 3342 (1993)], able to reproduce the previous findings.

Modeling RP-1 fuel advanced distillation data using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry and partial least squares analysis.

PubMed

Kehimkar, Benjamin; Parsons, Brendon A; Hoggard, Jamin C; Billingsley, Matthew C; Bruno, Thomas J; Synovec, Robert E

2015-01-01

Recent efforts in predicting rocket propulsion (RP-1) fuel performance through modeling put greater emphasis on obtaining detailed and accurate fuel properties, as well as elucidating the relationships between fuel compositions and their properties. Herein, we study multidimensional chromatographic data obtained by comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC × GC-TOFMS) to analyze RP-1 fuels. For GC × GC separations, RTX-Wax (polar stationary phase) and RTX-1 (non-polar stationary phase) columns were implemented for the primary and secondary dimensions, respectively, to separate the chemical compound classes (alkanes, cycloalkanes, aromatics, etc.), providing a significant level of chemical compositional information. The GC × GC-TOFMS data were analyzed using partial least squares regression (PLS) chemometric analysis to model and predict advanced distillation curve (ADC) data for ten RP-1 fuels that were previously analyzed using the ADC method. The PLS modeling provides insight into the chemical species that impact the ADC data. The PLS modeling correlates compositional information found in the GC × GC-TOFMS chromatograms of each RP-1 fuel, and their respective ADC, and allows prediction of the ADC for each RP-1 fuel with good precision and accuracy. The root-mean-square error of calibration (RMSEC) ranged from 0.1 to 0.5 °C, and was typically below ∼0.2 °C, for the PLS calibration of the ADC modeling with GC × GC-TOFMS data, indicating a good fit of the model to the calibration data. Likewise, the predictive power of the overall method via PLS modeling was assessed using leave-one-out cross-validation (LOOCV) yielding root-mean-square error of cross-validation (RMSECV) ranging from 1.4 to 2.6 °C, and was typically below ∼2.0 °C, at each % distilled measurement point during the ADC analysis.

Measurement of non-sugar solids content in Chinese rice wine using near infrared spectroscopy combined with an efficient characteristic variables selection algorithm.

PubMed

Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng

2015-01-01

The non-sugar solids (NSS) content is one of the most important nutrition indicators of Chinese rice wine. This study proposed a rapid method for the measurement of NSS content in Chinese rice wine using near infrared (NIR) spectroscopy. We also systemically studied the efficient spectral variables selection algorithms that have to go through modeling. A new algorithm of synergy interval partial least square with competitive adaptive reweighted sampling (Si-CARS-PLS) was proposed for modeling. The performance of the final model was back-evaluated using root mean square error of calibration (RMSEC) and correlation coefficient (Rc) in calibration set and similarly tested by mean square error of prediction (RMSEP) and correlation coefficient (Rp) in prediction set. The optimum model by Si-CARS-PLS algorithm was achieved when 7 PLS factors and 18 variables were included, and the results were as follows: Rc=0.95 and RMSEC=1.12 in the calibration set, Rp=0.95 and RMSEP=1.22 in the prediction set. In addition, Si-CARS-PLS algorithm showed its superiority when compared with the commonly used algorithms in multivariate calibration. This work demonstrated that NIR spectroscopy technique combined with a suitable multivariate calibration algorithm has a high potential in rapid measurement of NSS content in Chinese rice wine. Copyright © 2015 Elsevier B.V. All rights reserved.

Hyperspectral analysis of soil organic matter in coal mining regions using wavelets, correlations, and partial least squares regression.

PubMed

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Wang, Xuchen

2016-02-01

Hyperspectral estimation of soil organic matter (SOM) in coal mining regions is an important tool for enhancing fertilization in soil restoration programs. The correlation--partial least squares regression (PLSR) method effectively solves the information loss problem of correlation--multiple linear stepwise regression, but results of the correlation analysis must be optimized to improve precision. This study considers the relationship between spectral reflectance and SOM based on spectral reflectance curves of soil samples collected from coal mining regions. Based on the major absorption troughs in the 400-1006 nm spectral range, PLSR analysis was performed using 289 independent bands of the second derivative (SDR) with three levels and measured SOM values. A wavelet-correlation-PLSR (W-C-PLSR) model was then constructed. By amplifying useful information that was previously obscured by noise, the W-C-PLSR model was optimal for estimating SOM content, with smaller prediction errors in both calibration (R(2) = 0.970, root mean square error (RMSEC) = 3.10, and mean relative error (MREC) = 8.75) and validation (RMSEV = 5.85 and MREV = 14.32) analyses, as compared with other models. Results indicate that W-C-PLSR has great potential to estimate SOM in coal mining regions.

Near-infrared hyperspectral imaging and partial least squares regression for rapid and reagentless determination of Enterobacteriaceae on chicken fillets.

PubMed

Feng, Yao-Ze; Elmasry, Gamal; Sun, Da-Wen; Scannell, Amalia G M; Walsh, Des; Morcy, Noha

2013-06-01

Bacterial pathogens are the main culprits for outbreaks of food-borne illnesses. This study aimed to use the hyperspectral imaging technique as a non-destructive tool for quantitative and direct determination of Enterobacteriaceae loads on chicken fillets. Partial least squares regression (PLSR) models were established and the best model using full wavelengths was obtained in the spectral range 930-1450 nm with coefficients of determination R(2)≥ 0.82 and root mean squared errors (RMSEs) ≤ 0.47 log(10)CFUg(-1). In further development of simplified models, second derivative spectra and weighted PLS regression coefficients (BW) were utilised to select important wavelengths. However, the three wavelengths (930, 1121 and 1345 nm) selected from BW were competent and more preferred for predicting Enterobacteriaceae loads with R(2) of 0.89, 0.86 and 0.87 and RMSEs of 0.33, 0.40 and 0.45 log(10)CFUg(-1) for calibration, cross-validation and prediction, respectively. Besides, the constructed prediction map provided the distribution of Enterobacteriaceae bacteria on chicken fillets, which cannot be achieved by conventional methods. It was demonstrated that hyperspectral imaging is a potential tool for determining food sanitation and detecting bacterial pathogens on food matrix without using complicated laboratory regimes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Combination of multiple model population analysis and mid-infrared technology for the estimation of copper content in Tegillarca granosa

NASA Astrophysics Data System (ADS)

Hu, Meng-Han; Chen, Xiao-Jing; Ye, Peng-Chao; Chen, Xi; Shi, Yi-Jian; Zhai, Guang-Tao; Yang, Xiao-Kang

2016-11-01

The aim of this study was to use mid-infrared spectroscopy coupled with multiple model population analysis based on Monte Carlo-uninformative variable elimination for rapidly estimating the copper content of Tegillarca granosa. Copper-specific wavelengths were first extracted from the whole spectra, and subsequently, a least square-support vector machine was used to develop the prediction models. Compared with the prediction model based on full wavelengths, models that used 100 multiple MC-UVE selected wavelengths without and with bin operation showed comparable performances with Rp (root mean square error of Prediction) of 0.97 (14.60 mg/kg) and 0.94 (20.85 mg/kg) versus 0.96 (17.27 mg/kg), as well as ratio of percent deviation (number of wavelength) of 2.77 (407) and 1.84 (45) versus 2.32 (1762). The obtained results demonstrated that the mid-infrared technique could be used for estimating copper content in T. granosa. In addition, the proposed multiple model population analysis can eliminate uninformative, weakly informative and interfering wavelengths effectively, that substantially reduced the model complexity and computation time.

Least-squares deconvolution of evoked potentials and sequence optimization for multiple stimuli under low-jitter conditions.

PubMed

Bardy, Fabrice; Dillon, Harvey; Van Dun, Bram

2014-04-01

Rapid presentation of stimuli in an evoked response paradigm can lead to overlap of multiple responses and consequently difficulties interpreting waveform morphology. This paper presents a deconvolution method allowing overlapping multiple responses to be disentangled. The deconvolution technique uses a least-squared error approach. A methodology is proposed to optimize the stimulus sequence associated with the deconvolution technique under low-jitter conditions. It controls the condition number of the matrices involved in recovering the responses. Simulations were performed using the proposed deconvolution technique. Multiple overlapping responses can be recovered perfectly in noiseless conditions. In the presence of noise, the amount of error introduced by the technique can be controlled a priori by the condition number of the matrix associated with the used stimulus sequence. The simulation results indicate the need for a minimum amount of jitter, as well as a sufficient number of overlap combinations to obtain optimum results. An aperiodic model is recommended to improve reconstruction. We propose a deconvolution technique allowing multiple overlapping responses to be extracted and a method of choosing the stimulus sequence optimal for response recovery. This technique may allow audiologists, psychologists, and electrophysiologists to optimize their experimental designs involving rapidly presented stimuli, and to recover evoked overlapping responses. Copyright © 2013 International Federation of Clinical Neurophysiology. All rights reserved.

Roughness exponent in two-dimensional percolation, Potts model, and clock model

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

Redinz, Jose Arnaldo; Martins, Marcelo Lobato

We present a numerical study of the self-affine profiles obtained from configurations of the q-state Potts (with q=2,3, and 7) and p=10 clock models as well as from the occupation states for site percolation on the square lattice. The first and second order static phase transitions of the Potts model are located by a sharp change in the value of the roughness exponent {alpha} characterizing those profiles. The low temperature phase of the Potts model corresponds to flat ({alpha}{approx_equal}1) profiles, whereas its high temperature phase is associated with rough ({alpha}{approx_equal}0.5) ones. For the p=10 clock model, in addition to themore » flat (ferromagnetic) and rough (paramagnetic) profiles, an intermediate rough (0.5{lt}{alpha}{lt}1) phase{emdash}associated with a soft spin-wave one{emdash}is observed. Our results for the transition temperatures in the Potts and clock models are in agreement with the static values, showing that this approach is able to detect the phase transitions in these models directly from the spin configurations, without any reference to thermodynamical potentials, order parameters, or response functions. Finally, we show that the roughness exponent {alpha} is insensitive to geometric critical phenomena.« less

Application of correlation constrained multivariate curve resolution alternating least-squares methods for determination of compounds of interest in biodiesel blends using NIR and UV-visible spectroscopic data.

PubMed

de Oliveira, Rodrigo Rocha; de Lima, Kássio Michell Gomes; Tauler, Romà; de Juan, Anna

2014-07-01

This study describes two applications of a variant of the multivariate curve resolution alternating least squares (MCR-ALS) method with a correlation constraint. The first application describes the use of MCR-ALS for the determination of biodiesel concentrations in biodiesel blends using near infrared (NIR) spectroscopic data. In the second application, the proposed method allowed the determination of the synthetic antioxidant N,N'-Di-sec-butyl-p-phenylenediamine (PDA) present in biodiesel mixtures from different vegetable sources using UV-visible spectroscopy. Well established multivariate regression algorithm, partial least squares (PLS), were calculated for comparison of the quantification performance in the models developed in both applications. The correlation constraint has been adapted to handle the presence of batch-to-batch matrix effects due to ageing effects, which might occur when different groups of samples were used to build a calibration model in the first application. Different data set configurations and diverse modes of application of the correlation constraint are explored and guidelines are given to cope with different type of analytical problems, such as the correction of matrix effects among biodiesel samples, where MCR-ALS outperformed PLS reducing the relative error of prediction RE (%) from 9.82% to 4.85% in the first application, or the determination of minor compound with overlapped weak spectroscopic signals, where MCR-ALS gave higher (RE (%)=3.16%) for prediction of PDA compared to PLS (RE (%)=1.99%), but with the advantage of recovering the related pure spectral profile of analytes and interferences. The obtained results show the potential of the MCR-ALS method with correlation constraint to be adapted to diverse data set configurations and analytical problems related to the determination of biodiesel mixtures and added compounds therein. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessment of the Effects of Various Precipitation Forcings on Flood Forecasting Potential Using WRF-Hydro Modeling

NASA Astrophysics Data System (ADS)

Zhang, J.; Fang, N. Z.

2017-12-01

A potential flood forecast system is under development for the Upper Trinity River Basin (UTRB) in North Central of Texas using the WRF-Hydro model. The Routing Application for the Parallel Computation of Discharge (RAPID) is utilized as channel routing module to simulate streamflow. Model performance analysis was conducted based on three quantitative precipitation estimates (QPE): the North Land Data Assimilation System (NLDAS) rainfall, the Multi-Radar Multi-Sensor (MRMS) QPE and the National Centers for Environmental Prediction (NCEP) quality-controlled stage IV estimates. Prior to hydrologic simulation, QPE performance is assessed on two time scales (daily and hourly) using the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) and Hydrometeorological Automated Data System (HADS) hourly products. The calibrated WRF-Hydro model was then evaluated by comparing the simulated against the USGS observed using various QPE products. The results imply that the NCEP stage IV estimates have the best accuracy among the three QPEs on both time scales, while the NLDAS rainfall performs poorly because of its coarse spatial resolution. Furthermore, precipitation bias demonstrates pronounced impact on flood forecasting skills, as the root mean squared errors are significantly reduced by replacing NLDAS rainfall with NCEP stage IV estimates. This study also demonstrates that accurate simulated results can be achieved when initial soil moisture values are well understood in the WRF-Hydro model. Future research effort will therefore be invested on incorporating data assimilation with focus on initial states of the soil properties for UTRB.

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

NASA Astrophysics Data System (ADS)

Parmar, Kulwinder Singh; Bhardwaj, Rashmi

2014-12-01

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

A potential energy surface for the process H2 + H2O yielding H + H + H2O - Ab initio calculations and analytical representation

NASA Technical Reports Server (NTRS)

Schwenke, David W.; Walch, Stephen P.; Taylor, Peter R.

1991-01-01

Extensive ab initio calculations on the ground state potential energy surface of H2 + H2O were performed using a large contracted Gaussian basis set and a high level of correlation treatment. An analytical representation of the potential energy surface was then obtained which reproduces the calculated energies with an overall root-mean-square error of only 0.64 mEh. The analytic representation explicitly includes all nine internal degrees of freedom and is also well behaved as the H2 dissociates; it thus can be used to study collision-induced dissociation or recombination of H2. The strategy used to minimize the number of energy calculations is discussed, as well as other advantages of the present method for determining the analytical representation.

On the v-representabilty problem in density functional theory: Application to non-interacting systems

DOE PAGES

Dane, Markus; Gonis, Antonios

2016-07-05

Based on a computational procedure for determining the functional derivative with respect to the density of any antisymmetric N-particle wave function for a non-interacting system that leads to the density, we devise a test as to whether or not a wave function known to lead to a given density corresponds to a solution of a Schrödinger equation for some potential. We examine explicitly the case of non-interacting systems described by Slater determinants. Here, numerical examples for the cases of a one-dimensional square-well potential with infinite walls and the harmonic oscillator potential illustrate the formalism.

Weighted Least Squares Fitting Using Ordinary Least Squares Algorithms.

ERIC Educational Resources Information Center

Kiers, Henk A. L.

1997-01-01

A general approach for fitting a model to a data matrix by weighted least squares (WLS) is studied. The approach consists of iteratively performing steps of existing algorithms for ordinary least squares fitting of the same model and is based on maximizing a function that majorizes WLS loss function. (Author/SLD)

Turbulence Enhancement by Fractal Square Grids: Effects of the Number of Fractal Scales

NASA Astrophysics Data System (ADS)

Omilion, Alexis; Ibrahim, Mounir; Zhang, Wei

2017-11-01

Fractal square grids offer a unique solution for passive flow control as they can produce wakes with a distinct turbulence intensity peak and a prolonged turbulence decay region at the expense of only minimal pressure drop. While previous studies have solidified this characteristic of fractal square grids, how the number of scales (or fractal iterations N) affect turbulence production and decay of the induced wake is still not well understood. The focus of this research is to determine the relationship between the fractal iteration N and the turbulence produced in the wake flow using well-controlled water-tunnel experiments. Particle Image Velocimetry (PIV) is used to measure the instantaneous velocity fields downstream of four different fractal grids with increasing number of scales (N = 1, 2, 3, and 4) and a conventional single-scale grid. By comparing the turbulent scales and statistics of the wake, we are able to determine how each iteration affects the peak turbulence intensity and the production/decay of turbulence from the grid. In light of the ability of these fractal grids to increase turbulence intensity with low pressure drop, this work can potentially benefit a wide variety of applications where energy efficient mixing or convective heat transfer is a key process.

Application of FTIR-ATR spectroscopy coupled with multivariate analysis for rapid estimation of butter adulteration.

PubMed

Fadzlillah, Nurrulhidayah Ahmad; Rohman, Abdul; Ismail, Amin; Mustafa, Shuhaimi; Khatib, Alfi

2013-01-01

In dairy product sector, butter is one of the potential sources of fat soluble vitamins, namely vitamin A, D, E, K; consequently, butter is taken into account as high valuable price from other dairy products. This fact has attracted unscrupulous market players to blind butter with other animal fats to gain economic profit. Animal fats like mutton fat (MF) are potential to be mixed with butter due to the similarity in terms of fatty acid composition. This study focused on the application of FTIR-ATR spectroscopy in conjunction with chemometrics for classification and quantification of MF as adulterant in butter. The FTIR spectral region of 3910-710 cm⁻¹ was used for classification between butter and butter blended with MF at various concentrations with the aid of discriminant analysis (DA). DA is able to classify butter and adulterated butter without any mistakenly grouped. For quantitative analysis, partial least square (PLS) regression was used to develop a calibration model at the frequency regions of 3910-710 cm⁻¹. The equation obtained for the relationship between actual value of MF and FTIR predicted values of MF in PLS calibration model was y = 0.998x + 1.033, with the values of coefficient of determination (R²) and root mean square error of calibration are 0.998 and 0.046% (v/v), respectively. The PLS calibration model was subsequently used for the prediction of independent samples containing butter in the binary mixtures with MF. Using 9 principal components, root mean square error of prediction (RMSEP) is 1.68% (v/v). The results showed that FTIR spectroscopy can be used for the classification and quantification of MF in butter formulation for verification purposes.

Primordial perturbations generated by Higgs field and R2 operator

NASA Astrophysics Data System (ADS)

Wang, Yun-Chao; Wang, Tower

2017-12-01

If the very early Universe is dominated by the nonminimally coupled Higgs field and Starobinsky's curvature-squared term together, the potential diagram would mimic the landscape of a valley, serving as a cosmological attractor. The inflationary dynamics along this valley is studied, model parameters are constrained against observational data, and the effect of isocurvature perturbation is estimated.

Short-range stabilizing potential for computing energies and lifetimes of temporary anions with extrapolation methods.

PubMed

Sommerfeld, Thomas; Ehara, Masahiro

2015-01-21

The energy of a temporary anion can be computed by adding a stabilizing potential to the molecular Hamiltonian, increasing the stabilization until the temporary state is turned into a bound state, and then further increasing the stabilization until enough bound state energies have been collected so that these can be extrapolated back to vanishing stabilization. The lifetime can be obtained from the same data, but only if the extrapolation is done through analytic continuation of the momentum as a function of the square root of a shifted stabilizing parameter. This method is known as analytic continuation of the coupling constant, and it requires--at least in principle--that the bound-state input data are computed with a short-range stabilizing potential. In the context of molecules and ab initio packages, long-range Coulomb stabilizing potentials are, however, far more convenient and have been used in the past with some success, although the error introduced by the long-rang nature of the stabilizing potential remains unknown. Here, we introduce a soft-Voronoi box potential that can serve as a short-range stabilizing potential. The difference between a Coulomb and the new stabilization is analyzed in detail for a one-dimensional model system as well as for the (2)Πu resonance of CO2(-), and in both cases, the extrapolation results are compared to independently computed resonance parameters, from complex scaling for the model, and from complex absorbing potential calculations for CO2(-). It is important to emphasize that for both the model and for CO2(-), all three sets of results have, respectively, been obtained with the same electronic structure method and basis set so that the theoretical description of the continuum can be directly compared. The new soft-Voronoi-box-based extrapolation is then used to study the influence of the size of diffuse and the valence basis sets on the computed resonance parameters.

Predicted pH at the domestic and public supply drinking water depths, Central Valley, California

USGS Publications Warehouse

Rosecrans, Celia Z.; Nolan, Bernard T.; Gronberg, Jo Ann M.

2017-03-08

This scientific investigations map is a product of the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) project modeling and mapping team. The prediction grids depicted in this map are of continuous pH and are intended to provide an understanding of groundwater-quality conditions at the domestic and public supply drinking water zones in the groundwater of the Central Valley of California. The chemical quality of groundwater and the fate of many contaminants is often influenced by pH in all aquifers. These grids are of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to pH. In this work, the median well depth categorized as domestic supply was 30 meters below land surface, and the median well depth categorized as public supply is 100 meters below land surface. Prediction grids were created using prediction modeling methods, specifically boosted regression trees (BRT) with a Gaussian error distribution within a statistical learning framework within the computing framework of R (http://www.r-project.org/). The statistical learning framework seeks to maximize the predictive performance of machine learning methods through model tuning by cross validation. The response variable was measured pH from 1,337 wells and was compiled from two sources: USGS National Water Information System (NWIS) database (all data are publicly available from the USGS: http://waterdata.usgs.gov/ca/nwis/nwis) and the California State Water Resources Control Board Division of Drinking Water (SWRCB-DDW) database (water quality data are publicly available from the SWRCB: http://www.waterboards.ca.gov/gama/geotracker_gama.shtml). Only wells with measured pH and well depth data were selected, and for wells with multiple records, only the most recent sample in the period 1993–2014 was used. A total of 1,003 wells (training dataset) were used to train the BRT model, and 334 wells (hold-out dataset) were used to validate the prediction model. The training r-squared was 0.70, and the root-mean-square error (RMSE) in standard pH units was 0.26. The hold-out r-squared was 0.43, and RMSE in standard pH units was 0.37. Predictor variables consisting of more than 60 variables from 7 sources were assembled to develop a model that incorporates regional-scale soil properties, soil chemistry, land use, aquifer textures, and aquifer hydrology. Previously developed Central Valley model outputs of textures (Central Valley Textural Model, CVTM; Faunt and others, 2010) and MODFLOW-simulated vertical water fluxes and predicted depth to water table (Central Valley Hydrologic Model, CVHM; Faunt, 2009) were used to represent aquifer textures and groundwater hydraulics, respectively. In this work, wells were attributed to predictor variable values in ArcGIS using a 500-meter buffer.Faunt, C.C., ed., 2009, Groundwater availability in the Central Valley aquifer, California: U.S. Geological Survey Professional Paper 1776, 225 p., accessed at https://pubs.usgs.gov/pp/1766/.Faunt, C.C., Belitz, K., and Hanson, R.T., 2010, Development of a three-dimensional model of sedimentary texture in valley-fill deposits of Central Valley, California, USA: Hydrogeology Journal, v. 18, no. 3, p. 625–649, https://doi.org/10.1007/s10040-009-0539-7.

Coupled Aerosol-Chemistry-Climate Twentieth-Century Transient Model Investigation: Trends in Short-Lived Species and Climate Responses

NASA Technical Reports Server (NTRS)

Koch, Dorothy; Bauer, Susanne E.; Del Genio, Anthony; Faluvegi, Greg; McConnell, Joseph R.; Menon, Surabi; Miller, Ronald L.; Rind, David; Ruedy, Reto; Schmidt, Gavin A.;

Multi-element least square HDMR methods and their applications for stochastic multiscale model reduction

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

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn; Li, Xinping, E-mail: exping@126.com

Stochastic multiscale modeling has become a necessary approach to quantify uncertainty and characterize multiscale phenomena for many practical problems such as flows in stochastic porous media. The numerical treatment of the stochastic multiscale models can be very challengeable as the existence of complex uncertainty and multiple physical scales in the models. To efficiently take care of the difficulty, we construct a computational reduced model. To this end, we propose a multi-element least square high-dimensional model representation (HDMR) method, through which the random domain is adaptively decomposed into a few subdomains, and a local least square HDMR is constructed in eachmore » subdomain. These local HDMRs are represented by a finite number of orthogonal basis functions defined in low-dimensional random spaces. The coefficients in the local HDMRs are determined using least square methods. We paste all the local HDMR approximations together to form a global HDMR approximation. To further reduce computational cost, we present a multi-element reduced least-square HDMR, which improves both efficiency and approximation accuracy in certain conditions. To effectively treat heterogeneity properties and multiscale features in the models, we integrate multiscale finite element methods with multi-element least-square HDMR for stochastic multiscale model reduction. This approach significantly reduces the original model's complexity in both the resolution of the physical space and the high-dimensional stochastic space. We analyze the proposed approach, and provide a set of numerical experiments to demonstrate the performance of the presented model reduction techniques. - Highlights: • Multi-element least square HDMR is proposed to treat stochastic models. • Random domain is adaptively decomposed into some subdomains to obtain adaptive multi-element HDMR. • Least-square reduced HDMR is proposed to enhance computation efficiency and approximation accuracy in certain conditions. • Integrating MsFEM and multi-element least square HDMR can significantly reduce computation complexity.« less

[Adaptability of APSIM model in Southwestern China: A case study of winter wheat in Chongqing City].

PubMed

Dai, Tong; Wang, Jing; He, Di; Zhang, Jian-ping; Wang, Na

2015-04-01

Field experimental data of winter wheat and parallel daily meteorological data at four typical stations in Chongqing City were used to calibrate and validate APSIM-wheat model and determine the genetic parameters for 12 varieties of winter wheat. The results showed that there was a good agreement between the simulated and observed growth periods from sowing to emergence, flowering and maturity of wheat. Root mean squared errors (RMSEs) between simulated and observed emergence, flowering and maturity were 0-3, 1-8, and 0-8 d, respectively. Normalized root mean squared errors (NRMSEs) between simulated and observed above-ground biomass for 12 study varieties were less than 30%. NRMSE between simulated and observed yields for 10 varieties out of 12 study varieties were less than 30%. APSIM-wheat model performed well in simulating phenology, aboveground biomass and yield of winter wheat in Chongqing City, which could provide a foundational support for assessing the impact of climate change on wheat production in the study area based on the model.

Validation of drying models and rehydration characteristics of betel (Piper betel L.) leaves.

PubMed

Balasubramanian, S; Sharma, R; Gupta, R K; Patil, R T

2011-12-01

Effect of temperature on drying behaviour of betel leaves at drying air temperatures of 50, 60 and 70°C was investigated in tunnel as well as cabinet dryer. The L* and b* values increased whereas, a* values decreased, as the drying air temperature increased from 50 to 70°C in both the dryers, but the colour values remained higher for cabinet dryer than tunnel dryer in all cases. Eleven different drying models were compared according to their coefficients of determination (R(2)), root mean square error (RMSE) and chi square (χ (2)) to estimate drying curves. The results indicated that, logarithmic model and modified Page model could satisfactorily describe the drying curve of betel leaves for tunnel drying and cabinet dryer, respectively. In terms of colour quality, drying of betel leaves at 60°C in tunnel dryer and at 50°C in cabinet dryer was found optimum whereas, rehydration at 40°C produced the best acceptable product.

Efficient design of gain-flattened multi-pump Raman fiber amplifiers using least squares support vector regression

NASA Astrophysics Data System (ADS)

Chen, Jing; Qiu, Xiaojie; Yin, Cunyi; Jiang, Hao

2018-02-01

An efficient method to design the broadband gain-flattened Raman fiber amplifier with multiple pumps is proposed based on least squares support vector regression (LS-SVR). A multi-input multi-output LS-SVR model is introduced to replace the complicated solving process of the nonlinear coupled Raman amplification equation. The proposed approach contains two stages: offline training stage and online optimization stage. During the offline stage, the LS-SVR model is trained. Owing to the good generalization capability of LS-SVR, the net gain spectrum can be directly and accurately obtained when inputting any combination of the pump wavelength and power to the well-trained model. During the online stage, we incorporate the LS-SVR model into the particle swarm optimization algorithm to find the optimal pump configuration. The design results demonstrate that the proposed method greatly shortens the computation time and enhances the efficiency of the pump parameter optimization for Raman fiber amplifier design.

A Generalization of Pythagoras's Theorem and Application to Explanations of Variance Contributions in Linear Models. Research Report. ETS RR-14-18

ERIC Educational Resources Information Center

Carlson, James E.

2014-01-01

Many aspects of the geometry of linear statistical models and least squares estimation are well known. Discussions of the geometry may be found in many sources. Some aspects of the geometry relating to the partitioning of variation that can be explained using a little-known theorem of Pappus and have not been discussed previously are the topic of…

Thermal vibration of rectangular single-layered black phosphorus predicted by orthotropic plate model

NASA Astrophysics Data System (ADS)

Zhang, Yiqing; Wang, Lifeng; Jiang, Jingnong

2018-03-01

Vibrational behavior is very important for nanostructure-based resonators. In this work, an orthotropic plate model together with a molecular dynamics (MD) simulation is used to investigate the thermal vibration of rectangular single-layered black phosphorus (SLBP). Two bending stiffness, two Poisson's ratios, and one shear modulus of SLBP are calculated using the MD simulation. The natural frequency of the SLBP predicted by the orthotropic plate model agrees with the one obtained from the MD simulation very well. The root of mean squared (RMS) amplitude of the SLBP is obtained by MD simulation and the orthotropic plate model considering the law of energy equipartition. The RMS amplitude of the thermal vibration of the SLBP is predicted well by the orthotropic plate model compared to the MD results. Furthermore, the thermal vibration of the SLBP with an initial stress is also well-described by the orthotropic plate model.

Quantitative determination of polyphosphate in sediments using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy and partial least squares regression.

PubMed

Khoshmanesh, Aazam; Cook, Perran L M; Wood, Bayden R

2012-08-21

Phosphorus (P) is a major cause of eutrophication and subsequent loss of water quality in freshwater ecosystems. A major part of the flux of P to eutrophic lake sediments is organically bound or of biogenic origin. Despite the broad relevance of polyphosphate (Poly-P) in bioremediation and P release processes in the environment, its quantification is not yet well developed for sediment samples. Current methods possess significant disadvantages because of the difficulties associated with using a single extractant to extract a specific P compound without altering others. A fast and reliable method to estimate the quantitative contribution of microorganisms to sediment P release processes is needed, especially when an excessive P accumulation in the form of polyphosphate (Poly-P) occurs. Development of novel approaches for application of emerging spectroscopic techniques to complex environmental matrices such as sediments significantly contributes to the speciation models of P mobilization, biogeochemical nutrient cycling and development of nutrient models. In this study, for the first time Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy in combination with partial least squares (PLS) was used to quantify Poly-P in sediments. To reduce the high absorption matrix components in sediments such as silica, a physical extraction method was developed to separate sediment biological materials from abiotic particles. The aim was to achieve optimal separation of the biological materials from sediment abiotic particles with minimum chemical change in the sample matrix prior to ATR-FTIR analysis. Using a calibration set of 60 samples for the PLS prediction models in the Poly-P concentration range of 0-1 mg g(-1) d.w. (dry weight of sediment) (R(2) = 0.984 and root mean square error of prediction RMSEP = 0.041 at Factor-1) Poly-P could be detected at less than 50 μg g(-l) d.w. Using this technique, there is no solvent extraction or chemical treatment required, sample preparation is minimal and simple, and the analysis time is greatly reduced. The results from this study demonstrated the potential of ATR FT-IR spectroscopy as an alternative method to study Poly-P in sediments.

An Active Fire Temperature Retrieval Model Using Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Quigley, K. W.; Roberts, D. A.; Miller, D.

2017-12-01

Wildfire is both an important ecological process and a dangerous natural threat that humans face. In situ measurements of wildfire temperature are notoriously difficult to collect due to dangerous conditions. Imaging spectrometry data has the potential to provide some of the most accurate and highest temporally-resolved active fire temperature retrieval information for monitoring and modeling. Recent studies on fire temperature retrieval have used have used Multiple Endmember Spectral Mixture Analysis applied to Airborne Visible applied to Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) bands to model fire temperatures within the regions marked to contain fire, but these methods are less effective at coarser spatial resolutions, as linear mixing methods are degraded by saturation within the pixel. The assumption of a distribution of temperatures within pixels allows us to model pixels with an effective maximum and likely minimum temperature. This assumption allows a more robust approach to modeling temperature at different spatial scales. In this study, instrument-corrected radiance is forward-modeled for different ranges of temperatures, with weighted temperatures from an effective maximum temperature to a likely minimum temperature contributing to the total radiance of the modeled pixel. Effective maximum fire temperature is estimated by minimizing the Root Mean Square Error (RMSE) between modeled and measured fires. The model was tested using AVIRIS collected over the 2016 Sherpa Fire in Santa Barbara County, California,. While only in situ experimentation would be able to confirm active fire temperatures, the fit of the data to modeled radiance can be assessed, as well as the similarity in temperature distributions seen on different spatial resolution scales. Results show that this model improves upon current modeling methods in producing similar effective temperatures on multiple spatial scales as well as a similar modeled area distribution of those temperatures.

Prediction of total organic carbon content in shale reservoir based on a new integrated hybrid neural network and conventional well logging curves

NASA Astrophysics Data System (ADS)

Zhu, Linqi; Zhang, Chong; Zhang, Chaomo; Wei, Yang; Zhou, Xueqing; Cheng, Yuan; Huang, Yuyang; Zhang, Le

2018-06-01

There is increasing interest in shale gas reservoirs due to their abundant reserves. As a key evaluation criterion, the total organic carbon content (TOC) of the reservoirs can reflect its hydrocarbon generation potential. The existing TOC calculation model is not very accurate and there is still the possibility for improvement. In this paper, an integrated hybrid neural network (IHNN) model is proposed for predicting the TOC. This is based on the fact that the TOC information on the low TOC reservoir, where the TOC is easy to evaluate, comes from a prediction problem, which is the inherent problem of the existing algorithm. By comparing the prediction models established in 132 rock samples in the shale gas reservoir within the Jiaoshiba area, it can be seen that the accuracy of the proposed IHNN model is much higher than that of the other prediction models. The mean square error of the samples, which were not joined to the established models, was reduced from 0.586 to 0.442. The results show that TOC prediction is easier after logging prediction has been improved. Furthermore, this paper puts forward the next research direction of the prediction model. The IHNN algorithm can help evaluate the TOC of a shale gas reservoir.

Optimization of linear and branched alkane interactions with water to simulate hydrophobic hydration

NASA Astrophysics Data System (ADS)

Ashbaugh, Henry S.; Liu, Lixin; Surampudi, Lalitanand N.

2011-08-01

Previous studies of simple gas hydration have demonstrated that the accuracy of molecular simulations at capturing the thermodynamic signatures of hydrophobic hydration is linked both to the fidelity of the water model at replicating the experimental liquid density at ambient pressure and an accounting of polarization interactions between the solute and water. We extend those studies to examine alkane hydration using the transferable potentials for phase equilibria united-atom model for linear and branched alkanes, developed to reproduce alkane phase behavior, and the TIP4P/2005 model for water, which provides one of the best descriptions of liquid water for the available fixed-point charge models. Alkane site/water oxygen Lennard-Jones cross interactions were optimized to reproduce the experimental alkane hydration free energies over a range of temperatures. The optimized model reproduces the hydration free energies of the fitted alkanes with a root mean square difference between simulation and experiment of 0.06 kcal/mol over a wide temperature range, compared to 0.44 kcal/mol for the parent model. The optimized model accurately reproduces the temperature dependence of hydrophobic hydration, as characterized by the hydration enthalpies, entropies, and heat capacities, as well as the pressure response, as characterized by partial molar volumes.

A non-additive repulsive contribution in an equation of state: The development for homonuclear square well chains equation of state validated against Monte Carlo simulation

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

Trinh, Thi-Kim-Hoang; Laboratoire de Science des Procédés et des Matériaux; Passarello, Jean-Philippe, E-mail: Jean-Philippe.Passarello@lspm.cnrs.fr

This work consists of the adaptation of a non-additive hard sphere theory inspired by Malakhov and Volkov [Polym. Sci., Ser. A 49(6), 745–756 (2007)] to a square-well chain. Using the thermodynamic perturbation theory, an additional term is proposed that describes the effect of perturbing the chain of square well spheres by a non-additive parameter. In order to validate this development, NPT Monte Carlo simulations of thermodynamic and structural properties of the non-additive square well for a pure chain and a binary mixture of chains are performed. Good agreements are observed between the compressibility factors originating from the theory and thosemore » from molecular simulations.« less

Viscoelastic deformation near active plate boundaries

NASA Technical Reports Server (NTRS)

Ward, S. N.

1986-01-01

Model deformations near the active plate boundaries of Western North America using space-based geodetic measurements as constraints are discussed. The first six months of this project were spent gaining familarity with space-based measurements, accessing the Crustal Dynamics Data Information Computer, and building time independent deformation models. The initial goal was to see how well the simplest elastic models can reproduce very long base interferometry (VLBI) baseline data. From the Crustal Dynamics Data Information Service, a total of 18 VLBI baselines are available which have been surveyed on four or more occasions. These data were fed into weighted and unweighted inversions to obtain baseline closure rates. Four of the better quality lines are illustrated. The deformation model assumes that the observed baseline rates result from a combination of rigid plate tectonic motions plus a component resulting from elastic strain build up due to a failure of the plate boundary to slip at the full plate tectonic rate. The elastic deformation resulting from the locked plate boundary is meant to portray interseismic strain accumulation. During and shortly after a large interplate earthquake, these strains are largely released, and points near the fault which were previously retarded suddenly catch up to the positions predicted by rigid plate models. Researchers judge the quality of fit by the sum squares of weighted residuals, termed total variance. The observed baseline closures have a total variance of 99 (cm/y)squared. When the RM2 velocities are assumed to model the data, the total variance increases to 154 (cm/y)squared.

Predictive modeling in Clostridium acetobutylicum fermentations employing Raman spectroscopy and multivariate data analysis for real-time culture monitoring

NASA Astrophysics Data System (ADS)

Zu, Theresah N. K.; Liu, Sanchao; Germane, Katherine L.; Servinsky, Matthew D.; Gerlach, Elliot S.; Mackie, David M.; Sund, Christian J.

2016-05-01

The coupling of optical fibers with Raman instrumentation has proven to be effective for real-time monitoring of chemical reactions and fermentations when combined with multivariate statistical data analysis. Raman spectroscopy is relatively fast, with little interference from the water peak present in fermentation media. Medical research has explored this technique for analysis of mammalian cultures for potential diagnosis of some cancers. Other organisms studied via this route include Escherichia coli, Saccharomyces cerevisiae, and some Bacillus sp., though very little work has been performed on Clostridium acetobutylicum cultures. C. acetobutylicum is a gram-positive anaerobic bacterium, which is highly sought after due to its ability to use a broad spectrum of substrates and produce useful byproducts through the well-known Acetone-Butanol-Ethanol (ABE) fermentation. In this work, real-time Raman data was acquired from C. acetobutylicum cultures grown on glucose. Samples were collected concurrently for comparative off-line product analysis. Partial-least squares (PLS) models were built both for agitated cultures and for static cultures from both datasets. Media components and metabolites monitored include glucose, butyric acid, acetic acid, and butanol. Models were cross-validated with independent datasets. Experiments with agitation were more favorable for modeling with goodness of fit (QY) values of 0.99 and goodness of prediction (Q2Y) values of 0.98. Static experiments did not model as well as agitated experiments. Raman results showed the static experiments were chaotic, especially during and shortly after manual sampling.

Evaluation of the skill of North-American Multi-Model Ensemble (NMME) Global Climate Models in predicting average and extreme precipitation and temperature over the continental USA

NASA Astrophysics Data System (ADS)

Slater, Louise J.; Villarini, Gabriele; Bradley, Allen A.

2016-08-01

This paper examines the forecasting skill of eight Global Climate Models from the North-American Multi-Model Ensemble project (CCSM3, CCSM4, CanCM3, CanCM4, GFDL2.1, FLORb01, GEOS5, and CFSv2) over seven major regions of the continental United States. The skill of the monthly forecasts is quantified using the mean square error skill score. This score is decomposed to assess the accuracy of the forecast in the absence of biases (potential skill) and in the presence of conditional (slope reliability) and unconditional (standardized mean error) biases. We summarize the forecasting skill of each model according to the initialization month of the forecast and lead time, and test the models' ability to predict extended periods of extreme climate conducive to eight `billion-dollar' historical flood and drought events. Results indicate that the most skillful predictions occur at the shortest lead times and decline rapidly thereafter. Spatially, potential skill varies little, while actual model skill scores exhibit strong spatial and seasonal patterns primarily due to the unconditional biases in the models. The conditional biases vary little by model, lead time, month, or region. Overall, we find that the skill of the ensemble mean is equal to or greater than that of any of the individual models. At the seasonal scale, the drought events are better forecast than the flood events, and are predicted equally well in terms of high temperature and low precipitation. Overall, our findings provide a systematic diagnosis of the strengths and weaknesses of the eight models over a wide range of temporal and spatial scales.

Domain-Invariant Partial-Least-Squares Regression.

PubMed

Nikzad-Langerodi, Ramin; Zellinger, Werner; Lughofer, Edwin; Saminger-Platz, Susanne

2018-05-11

Multivariate calibration models often fail to extrapolate beyond the calibration samples because of changes associated with the instrumental response, environmental condition, or sample matrix. Most of the current methods used to adapt a source calibration model to a target domain exclusively apply to calibration transfer between similar analytical devices, while generic methods for calibration-model adaptation are largely missing. To fill this gap, we here introduce domain-invariant partial-least-squares (di-PLS) regression, which extends ordinary PLS by a domain regularizer in order to align the source and target distributions in the latent-variable space. We show that a domain-invariant weight vector can be derived in closed form, which allows the integration of (partially) labeled data from the source and target domains as well as entirely unlabeled data from the latter. We test our approach on a simulated data set where the aim is to desensitize a source calibration model to an unknown interfering agent in the target domain (i.e., unsupervised model adaptation). In addition, we demonstrate unsupervised, semisupervised, and supervised model adaptation by di-PLS on two real-world near-infrared (NIR) spectroscopic data sets.

Potential of Visible and Near Infrared Spectroscopy and Pattern Recognition for Rapid Quantification of Notoginseng Powder with Adulterants

PubMed Central

Nie, Pengcheng; Wu, Di; Sun, Da-Wen; Cao, Fang; Bao, Yidan; He, Yong

2013-01-01

Notoginseng is a classical traditional Chinese medical herb, which is of high economic and medical value. Notoginseng powder (NP) could be easily adulterated with Sophora flavescens powder (SFP) or corn flour (CF), because of their similar tastes and appearances and much lower cost for these adulterants. The objective of this study is to quantify the NP content in adulterated NP by using a rapid and non-destructive visible and near infrared (Vis-NIR) spectroscopy method. Three wavelength ranges of visible spectra, short-wave near infrared spectra (SNIR) and long-wave near infrared spectra (LNIR) were separately used to establish the model based on two calibration methods of partial least square regression (PLSR) and least-squares support vector machines (LS-SVM), respectively. Competitive adaptive reweighted sampling (CARS) was conducted to identify the most important wavelengths/variables that had the greatest influence on the adulterant quantification throughout the whole wavelength range. The CARS-PLSR models based on LNIR were determined as the best models for the quantification of NP adulterated with SFP, CF, and their mixtures, in which the rP values were 0.940, 0.939, and 0.867 for the three models respectively. The research demonstrated the potential of the Vis-NIR spectroscopy technique for the rapid and non-destructive quantification of NP containing adulterants. PMID:24129019

Cortical dipole imaging using truncated total least squares considering transfer matrix error.

PubMed

Hori, Junichi; Takeuchi, Kosuke

2013-01-01

Cortical dipole imaging has been proposed as a method to visualize electroencephalogram in high spatial resolution. We investigated the inverse technique of cortical dipole imaging using a truncated total least squares (TTLS). The TTLS is a regularization technique to reduce the influence from both the measurement noise and the transfer matrix error caused by the head model distortion. The estimation of the regularization parameter was also investigated based on L-curve. The computer simulation suggested that the estimation accuracy was improved by the TTLS compared with Tikhonov regularization. The proposed method was applied to human experimental data of visual evoked potentials. We confirmed the TTLS provided the high spatial resolution of cortical dipole imaging.

STM images and STS for a rectangular quantum corral constructed with δ-function barriers and the effect of an adsorbed atom on STM images and STS

NASA Astrophysics Data System (ADS)

Mitsuoka, Shigenori; Tamura, Akira

2012-04-01

Assuming that an electron confined by double δ-function barriers is in a quasi-stationary state, we derived eigenfunctions and eigenenergies of the electron. Applying this point of view to the electron confined in a rectangular quantum corral (QC), we obtained scanning tunneling microscopic (STM) images and scanning tunneling spectrum (STS). Our results are consistent with experimental ones, which confirms validity of the present model. Comparing with the treatment in which the corral potential is chosen to be of square-barrier type, the present treatment has an advantage that the eigenvalue equations are simple and the number of parameters that specify the potential barrier is only one except the bottom of the potential well. On the basis of a Dyson equation for the Green function we calculated STM images and STS of the QC having an adsorbed atom inside. Our results are consistent with experimental STM images and STS. In contrast to a previous viewpoint that the STS profile is reversed with that of the empty QC, we concluded the STS peaks of the adsorbed QC are shifted downward from those of the empty QC.

Liquid Crystal Phase Behaviour of Attractive Disc-Like Particles

PubMed Central

Wu, Liang; Jackson, George; Müller, Erich A.

2013-01-01

We employ a generalized van der Waals-Onsager perturbation theory to construct a free energy functional capable of describing the thermodynamic properties and orientational order of the isotropic and nematic phases of attractive disc particles. The model mesogen is a hard (purely repulsive) cylindrical disc particle decorated with an anisotropic square-well attractive potential placed at the centre of mass. Even for isotropic attractive interactions, the resulting overall inter-particle potential is anisotropic, due to the orientation-dependent excluded volume of the underlying hard core. An algebraic equation of state for attractive disc particles is developed by adopting the Onsager trial function to characterize the orientational order in the nematic phase. The theory is then used to represent the fluid-phase behaviour (vapour-liquid, isotropic-nematic, and nematic-nematic) of the oblate attractive particles for varying values of the molecular aspect ratio and parameters of the attractive potential. When compared to the phase diagram of their athermal analogues, it is seen that the addition of an attractive interaction facilitates the formation of orientationally-ordered phases. Most interestingly, for certain aspect ratios, a coexistence between two anisotropic nematic phases is exhibited by the attractive disc-like fluids. PMID:23965962

Liquid crystal phase behaviour of attractive disc-like particles.

PubMed

Wu, Liang; Jackson, George; Müller, Erich A

2013-08-08

We employ a generalized van der Waals-Onsager perturbation theory to construct a free energy functional capable of describing the thermodynamic properties and orientational order of the isotropic and nematic phases of attractive disc particles. The model mesogen is a hard (purely repulsive) cylindrical disc particle decorated with an anisotropic square-well attractive potential placed at the centre of mass. Even for isotropic attractive interactions, the resulting overall inter-particle potential is anisotropic, due to the orientation-dependent excluded volume of the underlying hard core. An algebraic equation of state for attractive disc particles is developed by adopting the Onsager trial function to characterize the orientational order in the nematic phase. The theory is then used to represent the fluid-phase behaviour (vapour-liquid, isotropic-nematic, and nematic-nematic) of the oblate attractive particles for varying values of the molecular aspect ratio and parameters of the attractive potential. When compared to the phase diagram of their athermal analogues, it is seen that the addition of an attractive interaction facilitates the formation of orientationally-ordered phases. Most interestingly, for certain aspect ratios, a coexistence between two anisotropic nematic phases is exhibited by the attractive disc-like fluids.

Chimpanzees and the mathematics of battle.

PubMed

Wilson, Michael L; Britton, Nicholas F; Franks, Nigel R

2002-06-07

Recent experiments have demonstrated the importance of numerical assessment in animal contests. Nevertheless, few attempts have been made to model explicitly the relationship between the relative number of combatants on each side and the costs and benefits of entering a contest. One framework that may be especially suitable for making such explicit predictions is Lanchester's theory of combat, which has proved useful for understanding combat strategies in humans and several species of ants. We show, with data from a recent series of playback experiments, that a model derived from Lanchester's 'square law' predicts willingness to enter intergroup contests in wild chimpanzees (Pan troglodytes). Furthermore, the model predicts that, in contests with multiple individuals on each side, chimpanzees in this population should be willing to enter a contest only if they outnumber the opposing side by a factor of 1.5. We evaluate these results for intergroup encounters in chimpanzees and also discuss potential applications of Lanchester's square and linear laws for understanding combat strategies in other species.

Chimpanzees and the mathematics of battle.

PubMed Central

Wilson, Michael L; Britton, Nicholas F; Franks, Nigel R

2002-01-01

Recent experiments have demonstrated the importance of numerical assessment in animal contests. Nevertheless, few attempts have been made to model explicitly the relationship between the relative number of combatants on each side and the costs and benefits of entering a contest. One framework that may be especially suitable for making such explicit predictions is Lanchester's theory of combat, which has proved useful for understanding combat strategies in humans and several species of ants. We show, with data from a recent series of playback experiments, that a model derived from Lanchester's 'square law' predicts willingness to enter intergroup contests in wild chimpanzees (Pan troglodytes). Furthermore, the model predicts that, in contests with multiple individuals on each side, chimpanzees in this population should be willing to enter a contest only if they outnumber the opposing side by a factor of 1.5. We evaluate these results for intergroup encounters in chimpanzees and also discuss potential applications of Lanchester's square and linear laws for understanding combat strategies in other species. PMID:12061952

Modelling the crystallization of the globular proteins

NASA Astrophysics Data System (ADS)

Shiryayev, Andrey S.

Crystallization of globular proteins has become a very important subject in recent yearn. However there is still no understanding of the particular conditions that lead to the crystallization. Since nucleation of a crystalline droplet is the critical step toward the formation of the solid phase from the supersaturated solution, this is the focus of current studies. In this work we use different approaches to investigate the collective behavior of a system of globular proteins. Especially we focused on the models which have a metastable critical point, because this reflects the properties of solutions of globular proteins. The first approach is a continuum model of globular proteins. This model was first presented by Talanquer and Oxtoby and is based on the van der Waals theory. The model can have either a stable or a metastable critical point. For the system with the metastable critical point we studied the behavior of the free energy barrier to nucleation; we found that along particular pathways the barrier to nucleation has a minimim around the critical point. As well, the number of molecules in the critical cluster was found to diverge as one approaches the critical point, though most of the molecules are in the fluid tail of the droplet. Our results are an extension of earlier work [17, 7]. The properties of the solvent affect the behavior of the solution. In our second approach, we proposed a model that takes into account the contribution of the solvent free energy to the free energy of the globular proteins. We show that one can map the phase diagram of a repulsive hard core plus attractive square well interacting system to the same system particles in the solvent environment. In particular we show that this leads to phase diagrams with upper critical points, lower critical points and even closed loops with both upper and lower critical points, similar to the one found before [10]. For systems with interaction different from the square well, in the presence of the solvent this mapping procedure can be a first approximation to understand the phase diagram. The final part of this work is dedicated to the behavior of sickle hemoglobin. While the fluid behavior of the HbS molecules can be approximately explained by the uniform interparticle potential, this model fails to describe the polymerization process and the particular structure of fibers. We develop an anisotropic "patchy" model to describe some features of the HbS polymerization process. To determine the degree of polymerization of the system a "patchy" order parameter was defined. Monte Carlo simulations for the simple two-patch model was performed and reveal the possibility of obtaining chains that can be considered as one dimensional crystals.

Identification of molecular descriptors for design of novel Isoalloxazine derivatives as potential Acetylcholinesterase inhibitors against Alzheimer's disease.

PubMed

Gurung, Arun Bahadur; Aguan, Kripamoy; Mitra, Sivaprasad; Bhattacharjee, Atanu

2017-06-01

In Alzheimer's disease (AD), the level of Acetylcholine (ACh) neurotransmitter is reduced. Since Acetylcholinesterase (AChE) cleaves ACh, inhibitors of AChE are very much sought after for AD treatment. The side effects of current inhibitors necessitate development of newer AChE inhibitors. Isoalloxazine derivatives have proved to be promising (AChE) inhibitors. However, their structure-activity relationship studies have not been reported till date. In the present work, various quantitative structure-activity relationship (QSAR) building methods such as multiple linear regression (MLR), partial least squares ,and principal component regression were employed to derive 3D-QSAR models using steric and electrostatic field descriptors. Statistically significant model was obtained using MLR coupled with stepwise selection method having r 2  = .9405, cross validated r 2 (q 2 ) = .6683, and a high predictability (pred_r 2  = .6206 and standard error, pred_r 2 se = .2491). Steric and electrostatic contribution plot revealed three electrostatic fields E_496, E_386 and E_577 and one steric field S_60 contributing towards biological activity. A ligand-based 3D-pharmacophore model was generated consisting of eight pharmacophore features. Isoalloxazine derivatives were docked against human AChE, which revealed critical residues implicated in hydrogen bonds as well as hydrophobic interactions. The binding modes of docked complexes (AChE_IA1 and AChE_IA14) were validated by molecular dynamics simulation which showed their stable trajectories in terms of root mean square deviation and molecular mechanics/Poisson-Boltzmann surface area binding free energy analysis revealed key residues contributing significantly to overall binding energy. The present study may be useful in the design of more potent Isoalloxazine derivatives as AChE inhibitors.

Fitting membrane resistance along with action potential shape in cardiac myocytes improves convergence: application of a multi-objective parallel genetic algorithm.

PubMed

Kaur, Jaspreet; Nygren, Anders; Vigmond, Edward J

2014-01-01

Fitting parameter sets of non-linear equations in cardiac single cell ionic models to reproduce experimental behavior is a time consuming process. The standard procedure is to adjust maximum channel conductances in ionic models to reproduce action potentials (APs) recorded in isolated cells. However, vastly different sets of parameters can produce similar APs. Furthermore, even with an excellent AP match in case of single cell, tissue behaviour may be very different. We hypothesize that this uncertainty can be reduced by additionally fitting membrane resistance (Rm). To investigate the importance of Rm, we developed a genetic algorithm approach which incorporated Rm data calculated at a few points in the cycle, in addition to AP morphology. Performance was compared to a genetic algorithm using only AP morphology data. The optimal parameter sets and goodness of fit as computed by the different methods were compared. First, we fit an ionic model to itself, starting from a random parameter set. Next, we fit the AP of one ionic model to that of another. Finally, we fit an ionic model to experimentally recorded rabbit action potentials. Adding the extra objective (Rm, at a few voltages) to the AP fit, lead to much better convergence. Typically, a smaller MSE (mean square error, defined as the average of the squared error between the target AP and AP that is to be fitted) was achieved in one fifth of the number of generations compared to using only AP data. Importantly, the variability in fit parameters was also greatly reduced, with many parameters showing an order of magnitude decrease in variability. Adding Rm to the objective function improves the robustness of fitting, better preserving tissue level behavior, and should be incorporated.

Modeling and distributed gain scheduling strategy for load frequency control in smart grids with communication topology changes.

PubMed

Liu, Shichao; Liu, Xiaoping P; El Saddik, Abdulmotaleb

2014-03-01

In this paper, we investigate the modeling and distributed control problems for the load frequency control (LFC) in a smart grid. In contrast with existing works, we consider more practical and real scenarios, where the communication topology of the smart grid changes because of either link failures or packet losses. These topology changes are modeled as a time-varying communication topology matrix. By using this matrix, a new closed-loop power system model is proposed to integrate the communication topology changes into the dynamics of a physical power system. The globally asymptotical stability of this closed-loop power system is analyzed. A distributed gain scheduling LFC strategy is proposed to compensate for the potential degradation of dynamic performance (mean square errors of state vectors) of the power system under communication topology changes. In comparison to conventional centralized control approaches, the proposed method can improve the robustness of the smart grid to the variation of the communication network as well as to reduce computation load. Simulation results show that the proposed distributed gain scheduling approach is capable to improve the robustness of the smart grid to communication topology changes. © 2013 ISA. Published by ISA. All rights reserved.

Self similar solution of superradiant amplification of ultrashort laser pulses in plasma

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

Moghadasin, H.; Niknam, A. R., E-mail: a-niknam@sbu.ac.ir; Shokri, B.

2015-05-15

Based on the self-similar method, superradiant amplification of ultrashort laser pulses by the counterpropagating pump in a plasma is investigated. Here, we present a governing system of partial differential equations for the signal pulse and the motion of the electrons. These equations are transformed to ordinary differential equations by the self-similar method and numerically solved. It is found that the increase of the signal intensity is proportional to the square of the propagation distance and the signal frequency has a red shift. Also, depending on the pulse width, the signal breaks up into a train of short pulses or itsmore » duration decreases with the inverse square root of the distance. Moreover, we identified two distinct categories of the electrons by the phase space analysis. In the beginning, one of them is trapped in the ponderomotive potential well and oscillates while the other is untrapped. Over time, electrons of the second kind also join to the trapped electrons. In the potential well, the electrons are bunched to form an electron density grating which reflects the pump pulse into the signal pulse. It is shown that the backscattered intensity is enhanced with the increase of the electron bunching parameter which leads to the enhanced efficiency of superradiant amplification.« less

Availability of ground water in the lower Pawcatuck River basin, Rhode Island

USGS Publications Warehouse

Gonthier, Joseph B.; Johnston, Herbert E.; Malmberg, Glenn T.

1974-01-01

The lower Pawcatuck River basin in southwestern Rhode Island is an area of about 169 square miles underlain by crystalline bedrock over which lies a relatively thin mantle of glacial till and stratified drift. Stratified drift, consisting dominantly of sand and gravel, occurs in irregularly shaped linear deposits that are generally less than a mile wide and less than 125 feet thick; these deposits are found along the Pawcatuck River, its tributaries, and abandoned preglacial channels. Deposits of stratified sand and gravel constitute the principal aquifer in the lower Pawcatuck basin and the only one capable of sustaining yields of 100 gallons per minute or more to individual wells. Water available for development in this aquifer consists of water in storage--potential ground-water runoff to streams--plus infiltration that can be induced from streams. Minimum annual ground-water runoff from the sand and gravel aquifer is calculated to be at least 1.17 cubic feet per second per square mile, or 0.76 million gallons per day per square mile. Potential recharge by induced infiltration is estimated to range from about 250 to 600 gallons per day per linear foot of streambed for the principal streams. In most areas, induced infiltration from streams constitutes the major source of water potentially available for development by wells. Because subsurface hydraulic connection in the sand and gravel aquifer is poor in several places, the deposits are conveniently divisible into several ground-water reservoirs. The potential yield from five of the most promising ground-water reservoirs is evaluated by means of mathematical models. Results indicate that continuous withdrawals ranging from 1.3 to 10.3 million gallons per day, and totaling 31 million gallons per day, are obtainable from these reservoirs. Larger yields may be recovered by different well placement, spacing, construction and development, pumping practice, and so forth. Withdrawals at the rates indicated will reduce streamflow downstream from pumping centers but generally will not result in streams going dry, provided the water is returned to the basin. Export of water from the basin will require careful consideration of the effects of such withdrawals on low streamflow. Export from the Pawcatuck basin of 27 million gallons per day, estimated to be available from ground-water reservoirs in the upper Pawcatuck basin, in addition to 37.5 million gallons per day available in the lower Pawcatuck basin, will markedly reduce low streamflow. The 90-percent duration flow of the Pawcatuck River at Westerly would be reduced from 75 million gallons per day to perhaps as little as 21 million gallons per day. The chemical quality of water from both the sand and gravel aquifer and associated streams is suitable for most purposes. The water is soft, slightly acidic, and typically has a dissolved-solids content of less than 75 milligrams per liter. Some treatment may be required locally for removal of iron and manganese to meet recommended standards of the U.S. Public Health Service for drinking water.

Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy.

PubMed

Liu, Yan-De; Ying, Yi-Bin; Fu, Xia-Ping

2005-03-01

To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (r2) of 0.759, low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way.

Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy*

PubMed Central

Liu, Yan-de; Ying, Yi-bin; Fu, Xia-ping

2005-01-01

To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (r 2) of 0.759, low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way. PMID:15682498

Efficient Levenberg-Marquardt minimization of the maximum likelihood estimator for Poisson deviates

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

Laurence, T; Chromy, B

2009-11-10

Histograms of counted events are Poisson distributed, but are typically fitted without justification using nonlinear least squares fitting. The more appropriate maximum likelihood estimator (MLE) for Poisson distributed data is seldom used. We extend the use of the Levenberg-Marquardt algorithm commonly used for nonlinear least squares minimization for use with the MLE for Poisson distributed data. In so doing, we remove any excuse for not using this more appropriate MLE. We demonstrate the use of the algorithm and the superior performance of the MLE using simulations and experiments in the context of fluorescence lifetime imaging. Scientists commonly form histograms ofmore » counted events from their data, and extract parameters by fitting to a specified model. Assuming that the probability of occurrence for each bin is small, event counts in the histogram bins will be distributed according to the Poisson distribution. We develop here an efficient algorithm for fitting event counting histograms using the maximum likelihood estimator (MLE) for Poisson distributed data, rather than the non-linear least squares measure. This algorithm is a simple extension of the common Levenberg-Marquardt (L-M) algorithm, is simple to implement, quick and robust. Fitting using a least squares measure is most common, but it is the maximum likelihood estimator only for Gaussian-distributed data. Non-linear least squares methods may be applied to event counting histograms in cases where the number of events is very large, so that the Poisson distribution is well approximated by a Gaussian. However, it is not easy to satisfy this criterion in practice - which requires a large number of events. It has been well-known for years that least squares procedures lead to biased results when applied to Poisson-distributed data; a recent paper providing extensive characterization of these biases in exponential fitting is given. The more appropriate measure based on the maximum likelihood estimator (MLE) for the Poisson distribution is also well known, but has not become generally used. This is primarily because, in contrast to non-linear least squares fitting, there has been no quick, robust, and general fitting method. In the field of fluorescence lifetime spectroscopy and imaging, there have been some efforts to use this estimator through minimization routines such as Nelder-Mead optimization, exhaustive line searches, and Gauss-Newton minimization. Minimization based on specific one- or multi-exponential models has been used to obtain quick results, but this procedure does not allow the incorporation of the instrument response, and is not generally applicable to models found in other fields. Methods for using the MLE for Poisson-distributed data have been published by the wider spectroscopic community, including iterative minimization schemes based on Gauss-Newton minimization. The slow acceptance of these procedures for fitting event counting histograms may also be explained by the use of the ubiquitous, fast Levenberg-Marquardt (L-M) fitting procedure for fitting non-linear models using least squares fitting (simple searches obtain {approx}10000 references - this doesn't include those who use it, but don't know they are using it). The benefits of L-M include a seamless transition between Gauss-Newton minimization and downward gradient minimization through the use of a regularization parameter. This transition is desirable because Gauss-Newton methods converge quickly, but only within a limited domain of convergence; on the other hand the downward gradient methods have a much wider domain of convergence, but converge extremely slowly nearer the minimum. L-M has the advantages of both procedures: relative insensitivity to initial parameters and rapid convergence. Scientists, when wanting an answer quickly, will fit data using L-M, get an answer, and move on. Only those that are aware of the bias issues will bother to fit using the more appropriate MLE for Poisson deviates. However, since there is a simple, analytical formula for the appropriate MLE measure for Poisson deviates, it is inexcusable that least squares estimators are used almost exclusively when fitting event counting histograms. There have been ways found to use successive non-linear least squares fitting to obtain similarly unbiased results, but this procedure is justified by simulation, must be re-tested when conditions change significantly, and requires two successive fits. There is a great need for a fitting routine for the MLE estimator for Poisson deviates that has convergence domains and rates comparable to the non-linear least squares L-M fitting. We show in this report that a simple way to achieve that goal is to use the L-M fitting procedure not to minimize the least squares measure, but the MLE for Poisson deviates.« less

Modelling postharvest quality of blueberry affected by biological variability using image and spectral data.

PubMed

Hu, Meng-Han; Dong, Qing-Li; Liu, Bao-Lin

2016-08-01

Hyperspectral reflectance and transmittance sensing as well as near-infrared (NIR) spectroscopy were investigated as non-destructive tools for estimating blueberry firmness, elastic modulus and soluble solid content (SSC). Least squares-support vector machine models were established from these three spectra based on samples from three cultivars viz. Bluecrop, Duke and M2 and two harvest years viz. 2014 and 2015 for predicting blueberry postharvest quality. One-cultivar reflectance models (establishing model using one cultivar) derived better results than the corresponding transmittance and NIR models for predicting blueberry firmness with few cultivar effects. Two-cultivar NIR models (establishing model using two cultivars) proved to be suitable for estimating blueberry SSC with correlations over 0.83. Rp (RMSEp ) values of the three-cultivar reflectance models (establishing model using 75% of three cultivars) were 0.73 (0.094) and 0.73 (0.186), respectively , for predicting blueberry firmness and elastic modulus. For SSC prediction, the three-cultivar NIR model was found to achieve an Rp (RMSEp ) value of 0.85 (0.090). Adding Bluecrop samples harvested in 2014 could enhance the three-cultivar model robustness for firmness and elastic modulus. The above results indicated the potential for using spatial and spectral techniques to develop robust models for predicting blueberry postharvest quality containing biological variability. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Carbon Nanotubes' Effect on Mitochondrial Oxygen Flux Dynamics: Polarography Experimental Study and Machine Learning Models using Star Graph Trace Invariants of Raman Spectra.

PubMed

González-Durruthy, Michael; Monserrat, Jose M; Rasulev, Bakhtiyor; Casañola-Martín, Gerardo M; Barreiro Sorrivas, José María; Paraíso-Medina, Sergio; Maojo, Víctor; González-Díaz, Humberto; Pazos, Alejandro; Munteanu, Cristian R

2017-11-11

This study presents the impact of carbon nanotubes (CNTs) on mitochondrial oxygen mass flux ( J m ) under three experimental conditions. New experimental results and a new methodology are reported for the first time and they are based on CNT Raman spectra star graph transform (spectral moments) and perturbation theory. The experimental measures of J m showed that no tested CNT family can inhibit the oxygen consumption profiles of mitochondria. The best model for the prediction of J m for other CNTs was provided by random forest using eight features, obtaining test R-squared ( R ²) of 0.863 and test root-mean-square error (RMSE) of 0.0461. The results demonstrate the capability of encoding CNT information into spectral moments of the Raman star graphs (SG) transform with a potential applicability as predictive tools in nanotechnology and material risk assessments.

Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis

PubMed Central

Zhang, Xue-Xi; Yin, Jian-Hua; Mao, Zhi-Hua; Xia, Yang

2015-01-01

Abstract. Fourier transform infrared imaging (FTIRI) combined with chemometrics algorithm has strong potential to obtain complex chemical information from biology tissues. FTIRI and partial least squares-discriminant analysis (PLS-DA) were used to differentiate healthy and osteoarthritic (OA) cartilages for the first time. A PLS model was built on the calibration matrix of spectra that was randomly selected from the FTIRI spectral datasets of healthy and lesioned cartilage. Leave-one-out cross-validation was performed in the PLS model, and the fitting coefficient between actual and predicted categorical values of the calibration matrix reached 0.95. In the calibration and prediction matrices, the successful identifying percentages of healthy and lesioned cartilage spectra were 100% and 90.24%, respectively. These results demonstrated that FTIRI combined with PLS-DA could provide a promising approach for the categorical identification of healthy and OA cartilage specimens. PMID:26057029

Facial Age Synthesis Using Sparse Partial Least Squares (The Case of Ben Needham).

PubMed

Bukar, Ali M; Ugail, Hassan

2017-09-01

Automatic facial age progression (AFAP) has been an active area of research in recent years. This is due to its numerous applications which include searching for missing. This study presents a new method of AFAP. Here, we use an active appearance model (AAM) to extract facial features from available images. An aging function is then modelled using sparse partial least squares regression (sPLS). Thereafter, the aging function is used to render new faces at different ages. To test the accuracy of our algorithm, extensive evaluation is conducted using a database of 500 face images with known ages. Furthermore, the algorithm is used to progress Ben Needham's facial image that was taken when he was 21 months old to the ages of 6, 14, and 22 years. The algorithm presented in this study could potentially be used to enhance the search for missing people worldwide. © 2017 American Academy of Forensic Sciences.

Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis.

PubMed

Zhang, Xue-Xi; Yin, Jian-Hua; Mao, Zhi-Hua; Xia, Yang

2015-06-01

Fourier transform infrared imaging (FTIRI) combined with chemometrics algorithm has strong potential to obtain complex chemical information from biology tissues. FTIRI and partial least squares-discriminant analysis (PLS-DA) were used to differentiate healthy and osteoarthritic (OA) cartilages for the first time. A PLS model was built on the calibration matrix of spectra that was randomly selected from the FTIRI spectral datasets of healthy and lesioned cartilage. Leave-one-out cross-validation was performed in the PLS model, and the fitting coefficient between actual and predicted categorical values of the calibration matrix reached 0.95. In the calibration and prediction matrices, the successful identifying percentages of healthy and lesioned cartilage spectra were 100% and 90.24%, respectively. These results demonstrated that FTIRI combined with PLS-DA could provide a promising approach for the categorical identification of healthy and OA cartilage specimens.

[The effect of tobacco prices on consumption: a time series data analysis for Mexico].

PubMed

Olivera-Chávez, Rosa Itandehui; Cermeño-Bazán, Rodolfo; de Miera-Juárez, Belén Sáenz; Jiménez-Ruiz, Jorge Alberto; Reynales-Shigematsu, Luz Myriam

2010-01-01

To estimate the price elasticity of the demand for cigarettes in Mexico based on data sources and a methodology different from the ones used in previous studies on the topic. Quarterly time series of consumption, income and price for the time period 1994 to 2005 were used. A long-run demand model was estimated using Ordinary Least Squares (OLS) and the existence of a cointegration relationship was investigated. Also, a model using Dinamic Ordinary Least Squares (DOLS) was estimated to correct for potential endogeneity of independent variables and autocorrelation of the residuals. DOLS estimates showed that a 10% increase in cigarette prices could reduce consumption in 2.5% (p<0.05) and increase government revenue in 16.11%. The results confirmed the effectiveness of taxes as an instrument for tobacco control in Mexico. An increase in taxes can be used to increase cigarette prices and therefore to reduce consumption and increase government revenue.

Fearful and Distracted in School: Predicting Bullying among Youths

ERIC Educational Resources Information Center

Brewer, Steven Lawrence, Jr.; Meckley-Brewer, Hannah; Stinson, Philip M.

2017-01-01

Bullying and aggression in schools can have a traumatic and lasting effect on the well-being of children and youths. Using data from the 2013 National Crime Victimization Survey's School Crime Supplement, this study uses a chi-square automatic interaction detection (CHAID) decision tree and logistic regression models to identify factors that…

Audience Diversion Due to Cable Television: A Statistical Analysis of New Data.

ERIC Educational Resources Information Center

Park, Rolla Edward

A statistical analysis of new data suggests that television broadcasting will continue to prosper, despite increasing competition from cable television carrying distant signals. Data on cable and non-cable audiences in 121 counties with well defined signal choice support generalized least squares estimates of two models: total audience and…

Verification of Advances in a Coupled Snow-runoff Modeling Framework for Operational Streamflow Forecasts

NASA Astrophysics Data System (ADS)

Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

2011-12-01

The National Oceanic and Atmospheric Administration's (NOAA's) River Forecast Centers (RFCs) issue hydrologic forecasts related to flood events, reservoir operations for water supply, streamflow regulation, and recreation on the nation's streams and rivers. The RFCs use the National Weather Service River Forecast System (NWSRFS) for streamflow forecasting which relies on a coupled snow model (i.e. SNOW17) and rainfall-runoff model (i.e. SAC-SMA) in snow-dominated regions of the US. Errors arise in various steps of the forecasting system from input data, model structure, model parameters, and initial states. The goal of the current study is to undertake verification of potential improvements in the SNOW17-SAC-SMA modeling framework developed for operational streamflow forecasts. We undertake verification for a range of parameters sets (i.e. RFC, DREAM (Differential Evolution Adaptive Metropolis)) as well as a data assimilation (DA) framework developed for the coupled models. Verification is also undertaken for various initial conditions to observe the influence of variability in initial conditions on the forecast. The study basin is the North Fork America River Basin (NFARB) located on the western side of the Sierra Nevada Mountains in northern California. Hindcasts are verified using both deterministic (i.e. Nash Sutcliffe efficiency, root mean square error, and joint distribution) and probabilistic (i.e. reliability diagram, discrimination diagram, containing ratio, and Quantile plots) statistics. Our presentation includes comparison of the performance of different optimized parameters and the DA framework as well as assessment of the impact associated with the initial conditions used for streamflow forecasts for the NFARB.

Critical asymmetry in renormalization group theory for fluids.

PubMed

Zhao, Wei; Wu, Liang; Wang, Long; Li, Liyan; Cai, Jun

2013-06-21

The renormalization-group (RG) approaches for fluids are employed to investigate critical asymmetry of vapour-liquid equilibrium (VLE) of fluids. Three different approaches based on RG theory for fluids are reviewed and compared. RG approaches are applied to various fluid systems: hard-core square-well fluids of variable ranges, hard-core Yukawa fluids, and square-well dimer fluids and modelling VLE of n-alkane molecules. Phase diagrams of simple model fluids and alkanes described by RG approaches are analyzed to assess the capability of describing the VLE critical asymmetry which is suggested in complete scaling theory. Results of thermodynamic properties obtained by RG theory for fluids agree with the simulation and experimental data. Coexistence diameters, which are smaller than the critical densities, are found in the RG descriptions of critical asymmetries of several fluids. Our calculation and analysis show that the approach coupling local free energy with White's RG iteration which aims to incorporate density fluctuations into free energy is not adequate for VLE critical asymmetry due to the inadequate order parameter and the local free energy functional used in the partition function.

Enhancing prediction power of chemometric models through manipulation of the fed spectrophotometric data: A comparative study

NASA Astrophysics Data System (ADS)

Saad, Ahmed S.; Hamdy, Abdallah M.; Salama, Fathy M.; Abdelkawy, Mohamed

2016-10-01

Effect of data manipulation in preprocessing step proceeding construction of chemometric models was assessed. The same set of UV spectral data was used for construction of PLS and PCR models directly and after mathematically manipulation as per well known first and second derivatives of the absorption spectra, ratio spectra and first and second derivatives of the ratio spectra spectrophotometric methods, meanwhile the optimal working wavelength ranges were carefully selected for each model and the models were constructed. Unexpectedly, number of latent variables used for models' construction varied among the different methods. The prediction power of the different models was compared using a validation set of 8 mixtures prepared as per the multilevel multifactor design and results were statistically compared using two-way ANOVA test. Root mean squares error of prediction (RMSEP) was used for further comparison of the predictability among different constructed models. Although no significant difference was found between results obtained using Partial Least Squares (PLS) and Principal Component Regression (PCR) models, however, discrepancies among results was found to be attributed to the variation in the discrimination power of adopted spectrophotometric methods on spectral data.

Landscape risk factors for Lyme disease in the eastern broadleaf forest province of the Hudson River valley and the effect of explanatory data classification resolution.

PubMed

Messier, Kyle P; Jackson, Laura E; White, Jennifer L; Hilborn, Elizabeth D

2015-01-01

This study assessed how landcover classification affects associations between landscape characteristics and Lyme disease rate. Landscape variables were derived from the National Land Cover Database (NLCD), including native classes (e.g., deciduous forest, developed low intensity) and aggregate classes (e.g., forest, developed). Percent of each landcover type, median income, and centroid coordinates were calculated by census tract. Regression results from individual and aggregate variable models were compared with the dispersion parameter-based R(2) (Rα(2)) and AIC. The maximum Rα(2) was 0.82 and 0.83 for the best aggregate and individual model, respectively. The AICs for the best models differed by less than 0.5%. The aggregate model variables included forest, developed, agriculture, agriculture-squared, y-coordinate, y-coordinate-squared, income and income-squared. The individual model variables included deciduous forest, deciduous forest-squared, developed low intensity, pasture, y-coordinate, y-coordinate-squared, income, and income-squared. Results indicate that regional landscape models for Lyme disease rate are robust to NLCD landcover classification resolution. Published by Elsevier Ltd.

Elastic and inelastic scattering of alpha particles on /sup 5/8Ni and /sup 6/0Ni in a broad range of energy and angle

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

Budzanowski, A.; Dabrowski, H.; Freindl, L.

1978-03-01

The differential cross sections for ..cap alpha.. particles elastically and inelastically scattered from /sup 5/8Ni (at 29, 34, 38, and 58 MeV) and elastically scattered from /sup 6/0Ni (at 29 and 34 MeV), are measured together with excitation functions in the 25--38 MeV region at 178.5/sup 0/ lab. These data together with the data of 26.5, 32.3, 104, and 139 MEV for /sup 5/8Ni and 32.3 and 104 MeV for /sup 6/0Ni from other sources were analyzed using an optical model with volume and surface absorptions and the Saxon-Woods square form factors. The analysis yielded energy dependent depths of bothmore » real and imaginary parts of the potential and constant geometric parameters. The analytical expressions for depths of the real and both absorption potentials are obtained. The coupled channel calculations using the above optical potential were performed for the first excited state of /sup 5/8Ni. Both elastic scattering data and coupling with the first excited state of /sup 5/8Ni are well reproduced using the above potential in the wide scattering energy range.« less

Total energy and potential enstrophy conserving schemes for the shallow water equations using Hamiltonian methods - Part 1: Derivation and properties

NASA Astrophysics Data System (ADS)

Eldred, Christopher; Randall, David

2017-02-01

The shallow water equations provide a useful analogue of the fully compressible Euler equations since they have similar characteristics: conservation laws, inertia-gravity and Rossby waves, and a (quasi-) balanced state. In order to obtain realistic simulation results, it is desirable that numerical models have discrete analogues of these properties. Two prototypical examples of such schemes are the 1981 Arakawa and Lamb (AL81) C-grid total energy and potential enstrophy conserving scheme, and the 2007 Salmon (S07) Z-grid total energy and potential enstrophy conserving scheme. Unfortunately, the AL81 scheme is restricted to logically square, orthogonal grids, and the S07 scheme is restricted to uniform square grids. The current work extends the AL81 scheme to arbitrary non-orthogonal polygonal grids and the S07 scheme to arbitrary orthogonal spherical polygonal grids in a manner that allows for both total energy and potential enstrophy conservation, by combining Hamiltonian methods (work done by Salmon, Gassmann, Dubos, and others) and discrete exterior calculus (Thuburn, Cotter, Dubos, Ringler, Skamarock, Klemp, and others). Detailed results of the schemes applied to standard test cases are deferred to part 2 of this series of papers.

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

Eldred, Christopher; Randall, David

The shallow water equations provide a useful analogue of the fully compressible Euler equations since they have similar characteristics: conservation laws, inertia-gravity and Rossby waves, and a (quasi-) balanced state. In order to obtain realistic simulation results, it is desirable that numerical models have discrete analogues of these properties. Two prototypical examples of such schemes are the 1981 Arakawa and Lamb (AL81) C-grid total energy and potential enstrophy conserving scheme, and the 2007 Salmon (S07) Z-grid total energy and potential enstrophy conserving scheme. Unfortunately, the AL81 scheme is restricted to logically square, orthogonal grids, and the S07 scheme is restrictedmore » to uniform square grids. The current work extends the AL81 scheme to arbitrary non-orthogonal polygonal grids and the S07 scheme to arbitrary orthogonal spherical polygonal grids in a manner that allows for both total energy and potential enstrophy conservation, by combining Hamiltonian methods (work done by Salmon, Gassmann, Dubos, and others) and discrete exterior calculus (Thuburn, Cotter, Dubos, Ringler, Skamarock, Klemp, and others). Lastly, detailed results of the schemes applied to standard test cases are deferred to part 2 of this series of papers.« less

Utilization of electrical impedance imaging for estimation of in-vivo tissue resistivities

NASA Astrophysics Data System (ADS)

Eyuboglu, B. Murat; Pilkington, Theo C.

1993-08-01

In order to determine in vivo resistivity of tissues in the thorax, the possibility of combining electrical impedance imaging (EII) techniques with (1) anatomical data extracted from high resolution images, (2) a prior knowledge of tissue resistivities, and (3) a priori noise information was assessed in this study. A Least Square Error Estimator (LSEE) and a statistically constrained Minimum Mean Square Error Estimator (MiMSEE) were implemented to estimate regional electrical resistivities from potential measurements made on the body surface. A two dimensional boundary element model of the human thorax, which consists of four different conductivity regions (the skeletal muscle, the heart, the right lung, and the left lung) was adopted to simulate the measured EII torso potentials. The calculated potentials were then perturbed by simulated instrumentation noise. The signal information used to form the statistical constraint for the MiMSEE was obtained from a prior knowledge of the physiological range of tissue resistivities. The noise constraint was determined from a priori knowledge of errors due to linearization of the forward problem and to the instrumentation noise.

First-order system least squares and the energetic variational approach for two-phase flow

NASA Astrophysics Data System (ADS)

Adler, J. H.; Brannick, J.; Liu, C.; Manteuffel, T.; Zikatanov, L.

2011-07-01

This paper develops a first-order system least-squares (FOSLS) formulation for equations of two-phase flow. The main goal is to show that this discretization, along with numerical techniques such as nested iteration, algebraic multigrid, and adaptive local refinement, can be used to solve these types of complex fluid flow problems. In addition, from an energetic variational approach, it can be shown that an important quantity to preserve in a given simulation is the energy law. We discuss the energy law and inherent structure for two-phase flow using the Allen-Cahn interface model and indicate how it is related to other complex fluid models, such as magnetohydrodynamics. Finally, we show that, using the FOSLS framework, one can still satisfy the appropriate energy law globally while using well-known numerical techniques.

Radioecological modelling of Polonium-210 and Caesium-137 in lichen-reindeer-man and top predators.

PubMed

Persson, Bertil R R; Gjelsvik, Runhild; Holm, Elis

2018-06-01

This work deals with analysis and modelling of the radionuclides 210 Pb and 210 Po in the food-chain lichen-reindeer-man in addition to 210 Po and 137 Cs in top predators. By using the methods of Partial Least Square Regression (PLSR) the atmospheric deposition of 210 Pb and 210 Po is predicted at the sample locations. Dynamic modelling of the activity concentration with differential equations is fitted to the sample data. Reindeer lichen consumption, gastrointestinal absorption, organ distribution and elimination is derived from information in the literature. Dynamic modelling of transfer of 210 Pb and 210 Po to reindeer meat, liver and bone from lichen consumption, fitted well with data from Sweden and Finland from 1966 to 1971. The activity concentration of 210 Pb in the skeleton in man is modelled by using the results of studying the kinetics of lead in skeleton and blood in lead-workers after end of occupational exposure. The result of modelling 210 Pb and 210 Po activity in skeleton matched well with concentrations of 210 Pb and 210 Po in teeth from reindeer-breeders and autopsy bone samples in Finland. The results of 210 Po and 137 Cs in different tissues of wolf, wolverine and lynx previously published, are analysed with multivariate data processing methods such as Principal Component Analysis PCA, and modelled with the method of Projection to Latent Structures, PLS, or Partial Least Square Regression PLSR. Copyright © 2017 Elsevier Ltd. All rights reserved.

36 CFR 910.3 - Program administration.

Code of Federal Regulations, 2011 CFR

2011-07-01

... DEVELOPMENT AREA General § 910.3 Program administration. (a) This part 910, together with Square Guidelines... understand and participate in the process of square development within the Development Area. (1) This part... provides a glossary of defined terms applicable to this part as well as Square Guidelines. (2) Square...

36 CFR 910.3 - Program administration.

Code of Federal Regulations, 2012 CFR

2012-07-01

... DEVELOPMENT AREA General § 910.3 Program administration. (a) This part 910, together with Square Guidelines... understand and participate in the process of square development within the Development Area. (1) This part... provides a glossary of defined terms applicable to this part as well as Square Guidelines. (2) Square...

36 CFR 910.3 - Program administration.

Code of Federal Regulations, 2010 CFR

2010-07-01

... DEVELOPMENT AREA General § 910.3 Program administration. (a) This part 910, together with Square Guidelines... understand and participate in the process of square development within the Development Area. (1) This part... provides a glossary of defined terms applicable to this part as well as Square Guidelines. (2) Square...

36 CFR 910.3 - Program administration.

Code of Federal Regulations, 2014 CFR

2014-07-01

... DEVELOPMENT AREA General § 910.3 Program administration. (a) This part 910, together with Square Guidelines... understand and participate in the process of square development within the Development Area. (1) This part... provides a glossary of defined terms applicable to this part as well as Square Guidelines. (2) Square...

Distributed multi-criteria model evaluation and spatial association analysis

NASA Astrophysics Data System (ADS)

Scherer, Laura; Pfister, Stephan

2015-04-01

Model performance, if evaluated, is often communicated by a single indicator and at an aggregated level; however, it does not embrace the trade-offs between different indicators and the inherent spatial heterogeneity of model efficiency. In this study, we simulated the water balance of the Mississippi watershed using the Soil and Water Assessment Tool (SWAT). The model was calibrated against monthly river discharge at 131 measurement stations. Its time series were bisected to allow for subsequent validation at the same gauges. Furthermore, the model was validated against evapotranspiration which was available as a continuous raster based on remote sensing. The model performance was evaluated for each of the 451 sub-watersheds using four different criteria: 1) Nash-Sutcliffe efficiency (NSE), 2) percent bias (PBIAS), 3) root mean square error (RMSE) normalized to standard deviation (RSR), as well as 4) a combined indicator of the squared correlation coefficient and the linear regression slope (bR2). Conditions that might lead to a poor model performance include aridity, a very flat and steep relief, snowfall and dams, as indicated by previous research. In an attempt to explain spatial differences in model efficiency, the goodness of the model was spatially compared to these four phenomena by means of a bivariate spatial association measure which combines Pearson's correlation coefficient and Moran's index for spatial autocorrelation. In order to assess the model performance of the Mississippi watershed as a whole, three different averages of the sub-watershed results were computed by 1) applying equal weights, 2) weighting by the mean observed river discharge, 3) weighting by the upstream catchment area and the square root of the time series length. Ratings of model performance differed significantly in space and according to efficiency criterion. The model performed much better in the humid Eastern region than in the arid Western region which was confirmed by the high spatial association with the aridity index (ratio of mean annual precipitation to mean annual potential evapotranspiration). This association was still significant when controlling for slopes which manifested the second highest spatial association. In line with these findings, overall model efficiency of the entire Mississippi watershed appeared better when weighted with mean observed river discharge. Furthermore, the model received the highest rating with regards to PBIAS and was judged worst when considering NSE as the most comprehensive indicator. No universal performance indicator exists that considers all aspects of a hydrograph. Therefore, sound model evaluation must take into account multiple criteria. Since model efficiency varies in space which is masked by aggregated ratings spatially explicit model goodness should be communicated as standard praxis - at least as a measure of spatial variability of indicators. Furthermore, transparent documentation of the evaluation procedure also with regards to weighting of aggregated model performance is crucial but often lacking in published research. Finally, the high spatial association between model performance and aridity highlights the need to improve modelling schemes for arid conditions as priority over other aspects that might weaken model goodness.

Use of a spread sheet to calculate the current-density distribution produced in human and rat models by low-frequency electric fields.

PubMed

Hart, F X

1990-01-01

The current-density distribution produced inside irregularly shaped, homogeneous human and rat models by low-frequency electric fields is obtained by a two-stage finite-difference procedure. In the first stage the model is assumed to be equipotential. Laplace's equation is solved by iteration in the external region to obtain the capacitive-current densities at the model's surface elements. These values then provide the boundary conditions for the second-stage relaxation solution, which yields the internal current-density distribution. Calculations were performed with the Excel spread-sheet program on a Macintosh-II microcomputer. A spread sheet is a two-dimensional array of cells. Each cell of the sheet can represent a square element of space. Equations relating the values of the cells can represent the relationships between the potentials in the corresponding spatial elements. Extension to three dimensions is readily made. Good agreement was obtained with current densities measured on human models with both, one, or no legs grounded and on rat models in four different grounding configurations. The results also compared well with predictions of more sophisticated numerical analyses. Spread sheets can provide an inexpensive and relatively simple means to perform good, approximate dosimetric calculations on irregularly shaped objects.

Potential development and recharge of ground water in Mill Creek Valley, Butler and Hamilton Counties, Ohio, based on analog model analysis

USGS Publications Warehouse

Fidler, Richard E.

1971-01-01

Mill Creek valley is part of the greater Cincinnati industrial area in southwestern Ohio. In 1964, nearly 30 percent of the water supply in the study area of about 27 square miles was obtained from wells in the glacial-outwash aquifer underlying the valley. Ground-water demand has increased steadily since the late 1800's, and excessive pumpage during the years of World War II caused water levels to decline to critical levels. Natural recharge to the aquifer, from precipitation, is about 8.5 mgd (million gallons per day). In 1964, the total water use was about 30 mgd, of which 8.1 mgd was obtained from wells in Mill Creek valley, and the remainder was imported from outside the basin. With rapid industrial expansion and population growth, demand for ground water is continuing to increase. By the year 2000 ground-water pumpage is expected to exceed 25 mgd. At a public hearing before the Ohio Water Commission in 1961, artificial recharge of the aquifer through injection wells was proposed as a possible solution to the Mill Creek valley water-supply problem. The present study attempts to determine the feasibility of injection-well recharge systems in the Mill Creek valley. Although basically simple, the hydrologic system in Mill Creek valley is complex in detail and is difficult to evaluate using conventional quantitative methods. Because of this complexity, an electric analog model was used to test specific development plans. Three hypothetical pumping plans were developed by projecting past pumpage data to the years 1980 and 2000. Various combinations of injection wells were tested on the model under different hypothetical conditions of pumpage. Based on analog model analysis, from three to eight inject-ion wells, with an approximate input of 2 mgd each, would reverse the trend in declining groundwater levels and provide adequate water to meet anticipated future demands.

Modelling the vestibular head tilt response.

PubMed

Heibert, D; Lithgow, B

2005-03-01

This paper attempts to verify the existence of potentially diagnostically significant periodic signals thought to exist in recordings of neural activity originating from the vestibular nerve, following a single tilt of the head. It then attempts to find the physiological basis of this signal, in particular focusing on the mechanical response of the vestibular system. Simple mechanical models of the semi circular canals having angular velocities applied to them were looked at. A simple single canal model was simulated using CFX software. Finally, a simple model of all three canals with elastic duct walls and a moving cupula was constructed. Pressure waves within the canals were simulated using water hammer or pressure transient theory. In particular, it was investigated whether pressure waves within the utricle following a square pulse angular velocity applied to the canal(s) may be responsible for quasi-periodic oscillatory signals. The simulations showed that there are no pressure waves resonating within the canals following a square pulse angular velocity applied to the canal(s). The results show that the oscillatory signals are most likely not mechanical in origin. It was concluded that further investigation is required.

Cosmological evolution of a tachyon-quintom model of dark energy

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

Shi, Shang-Gang; Piao, Yun-Song; Qiao, Cong-Feng, E-mail: shishanggang06@mails.gucas.ac.cn, E-mail: yspiao@gucas.ac.cn, E-mail: qiaocf@gucas.ac.cn

2009-04-15

In this work we study the cosmological evolution of a dark energy model with two scalar fields, i.e. the tachyon and the phantom tachyon. This model enables the equation of state w to change from w > -1 to w < -1 in the evolution of the universe. The phase-space analysis for such a system with inverse square potentials shows that there exists a unique stable critical point, which has power-law solution. In this paper, we also study another form of tachyon-quintom model with two fields, which involves the interactions between both fields.

Prediction of intramuscular fat content and major fatty acid groups of lamb M. longissimus lumborum using Raman spectroscopy.

PubMed

Fowler, Stephanie M; Ponnampalam, Eric N; Schmidt, Heinar; Wynn, Peter; Hopkins, David L

2015-12-01

A hand held Raman spectroscopic device was used to predict intramuscular fat (IMF) levels and the major fatty acid (FA) groups of fresh intact ovine M. longissimus lumborum (LL). IMF levels were determined using the Soxhlet method, while FA analysis was conducted using a rapid (KOH in water, methanol and sulphuric acid in water) extraction procedure. IMF levels and FA values were regressed against Raman spectra using partial least squares regression and against each other using linear regression. The results indicate that there is potential to predict PUFA (R(2)=0.93) and MUFA (R(2)=0.54) as well as SFA values that had been adjusted for IMF content (R(2)=0.54). However, this potential was significantly reduced when correlations between predicted and observed values were determined by cross validation (R(2)cv=0.21-0.00). Overall, the prediction of major FA groups using Raman spectra was more precise (relative reductions in error of 0.3-40.8%) compared to the null models. Copyright © 2015 Elsevier Ltd. All rights reserved.

Development of the first sphingomyelin biomimetic stationary phase for immobilized artificial membrane (IAM) chromatography.

PubMed

Verzele, Dieter; Lynen, Frédéric; De Vrieze, Mike; Wright, Adrian G; Hanna-Brown, Melissa; Sandra, Pat

2012-01-28

A prototype sphingomyelin stationary phase for Immobilized Artificial Membrane (IAM) chromatography was synthesized by an ultra-short, solid-phase inspired methodology, in which an oxidative release monitoring strategy played a vital role. Evaluated in a proof-of-concept model for blood-brain barrier passage, partial least squares regression demonstrated its potential as an in vitro prediction tool.

Diagnosis of North American Multi-Model Ensemble (NMME) skill for predicting floods and droughts over the continental USA

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.; Bradley, A.

2015-12-01

Model predictions of precipitation and temperature are crucial to mitigate the impacts of major flood and drought events through informed planning and response. However, the potential value and applicability of these predictions is inescapably linked to their forecast quality. The North-American Multi-Model Ensemble (NMME) is a multi-agency supported forecasting system for intraseasonal to interannual (ISI) climate predictions. Retrospective forecasts and real-time information are provided by each agency free of charge to facilitate collaborative research efforts for predicting future climate conditions as well as extreme weather events such as floods and droughts. Using the PRISM climate mapping system as the reference data, we examine the skill of five General Circulation Models (GCMs) from the NMME project to forecast monthly and seasonal precipitation and temperature over seven sub-regions of the continental United States. For each model, we quantify the seasonal accuracy of the forecast relative to observed precipitation using the mean square error skill score. This score is decomposed to assess the accuracy of the forecast in the absence of biases (potential skill), and in the presence of conditional (slope reliability) and unconditional (standardized mean error) biases. The quantification of these biases allows us to diagnose each model's skill over a full range temporal and spatial scales. Finally, we test each model's forecasting skill by evaluating its ability to predict extended periods of extreme temperature and precipitation that were conducive to 'billion-dollar' historical flood and drought events in different regions of the continental USA. The forecasting skill of the individual climate models is summarized and presented along with a discussion of different multi-model averaging techniques for predicting such events.

Performance of statistical models to predict mental health and substance abuse cost.

PubMed

Montez-Rath, Maria; Christiansen, Cindy L; Ettner, Susan L; Loveland, Susan; Rosen, Amy K

2006-10-26

Providers use risk-adjustment systems to help manage healthcare costs. Typically, ordinary least squares (OLS) models on either untransformed or log-transformed cost are used. We examine the predictive ability of several statistical models, demonstrate how model choice depends on the goal for the predictive model, and examine whether building models on samples of the data affects model choice. Our sample consisted of 525,620 Veterans Health Administration patients with mental health (MH) or substance abuse (SA) diagnoses who incurred costs during fiscal year 1999. We tested two models on a transformation of cost: a Log Normal model and a Square-root Normal model, and three generalized linear models on untransformed cost, defined by distributional assumption and link function: Normal with identity link (OLS); Gamma with log link; and Gamma with square-root link. Risk-adjusters included age, sex, and 12 MH/SA categories. To determine the best model among the entire dataset, predictive ability was evaluated using root mean square error (RMSE), mean absolute prediction error (MAPE), and predictive ratios of predicted to observed cost (PR) among deciles of predicted cost, by comparing point estimates and 95% bias-corrected bootstrap confidence intervals. To study the effect of analyzing a random sample of the population on model choice, we re-computed these statistics using random samples beginning with 5,000 patients and ending with the entire sample. The Square-root Normal model had the lowest estimates of the RMSE and MAPE, with bootstrap confidence intervals that were always lower than those for the other models. The Gamma with square-root link was best as measured by the PRs. The choice of best model could vary if smaller samples were used and the Gamma with square-root link model had convergence problems with small samples. Models with square-root transformation or link fit the data best. This function (whether used as transformation or as a link) seems to help deal with the high comorbidity of this population by introducing a form of interaction. The Gamma distribution helps with the long tail of the distribution. However, the Normal distribution is suitable if the correct transformation of the outcome is used.

Use of partial least squares path modelling to assess the willingness of Chinese female sex workers to participate in a microbicide trial.

PubMed

Yao, N; Zeng, Q; Zhong, N X; Li, D X; Huang, L A; Shao, M Y; Ruan, H Y

2015-09-01

To investigate the willingness of Chinese female sex workers (FSWs) to participate (WTP) in a clinical trial of microbicides; to explore the potential hindrances and facilitating factors; and to provide support for future microbicide clinical trials by tailoring their design to better meet the specific needs of FSWs. Cross-sectional study. In total, 404 FSWs were investigated using structured questionnaires. Exploratory factor analysis and partial least squares path modelling were used to explore the correlations between several influencing factors and WTP. The WTP of FSWs enrolled in this study was high (53.47%, 216/404). Possible benefits from enrolment in the trial were positively associated with WTP, while concern about a hypothetical microbicide, potential physical harm, economic loss from participation, and fear of family or social isolation were negatively associated with WTP. FSWs are appropriate participants in microbicide clinical trials, and are likely to benefit from effective microbicides. In a microbicide clinical trial, it is imperative to ensure protection of the rights, dignity, safety, confidentiality and welfare of FSW participants. Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Exploring inductive linearization for pharmacokinetic-pharmacodynamic systems of nonlinear ordinary differential equations.

PubMed

Hasegawa, Chihiro; Duffull, Stephen B

2018-02-01

Pharmacokinetic-pharmacodynamic systems are often expressed with nonlinear ordinary differential equations (ODEs). While there are numerous methods to solve such ODEs these methods generally rely on time-stepping solutions (e.g. Runge-Kutta) which need to be matched to the characteristics of the problem at hand. The primary aim of this study was to explore the performance of an inductive approximation which iteratively converts nonlinear ODEs to linear time-varying systems which can then be solved algebraically or numerically. The inductive approximation is applied to three examples, a simple nonlinear pharmacokinetic model with Michaelis-Menten elimination (E1), an integrated glucose-insulin model and an HIV viral load model with recursive feedback systems (E2 and E3, respectively). The secondary aim of this study was to explore the potential advantages of analytically solving linearized ODEs with two examples, again E3 with stiff differential equations and a turnover model of luteinizing hormone with a surge function (E4). The inductive linearization coupled with a matrix exponential solution provided accurate predictions for all examples with comparable solution time to the matched time-stepping solutions for nonlinear ODEs. The time-stepping solutions however did not perform well for E4, particularly when the surge was approximated by a square wave. In circumstances when either a linear ODE is particularly desirable or the uncertainty in matching the integrator to the ODE system is of potential risk, then the inductive approximation method coupled with an analytical integration method would be an appropriate alternative.

Use of geospatial technology for delineating groundwater potential zones with an emphasis on water-table analysis in Dwarka River basin, Birbhum, India

NASA Astrophysics Data System (ADS)

Thapa, Raju; Gupta, Srimanta; Gupta, Arindam; Reddy, D. V.; Kaur, Harjeet

2018-05-01

Dwarka River basin in Birbhum, West Bengal (India), is an agriculture-dominated area where groundwater plays a crucial role. The basin experiences seasonal water stress conditions with a scarcity of surface water. In the presented study, delineation of groundwater potential zones (GWPZs) is carried out using a geospatial multi-influencing factor technique. Geology, geomorphology, soil type, land use/land cover, rainfall, lineament and fault density, drainage density, slope, and elevation of the study area were considered for the delineation of GWPZs in the study area. About 9.3, 71.9 and 18.8% of the study area falls within good, moderate and poor groundwater potential zones, respectively. The potential groundwater yield data corroborate the outcome of the model, with maximum yield in the older floodplain and minimum yield in the hard-rock terrains in the western and south-western regions. Validation of the GWPZs using the yield of 148 wells shows very high accuracy of the model prediction, i.e., 89.1% on superimposition and 85.1 and 81.3% on success and prediction rates, respectively. Measurement of the seasonal water-table fluctuation with a multiplicative model of time series for predicting the short-term trend of the water table, followed by chi-square analysis between the predicted and observed water-table depth, indicates a trend of falling groundwater levels, with a 5% level of significance and a p-value of 0.233. The rainfall pattern for the last 3 years of the study shows a moderately positive correlation ( R 2 = 0.308) with the average water-table depth in the study area.

Molecular hydrogen solvated in water – A computational study

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

Śmiechowski, Maciej, E-mail: Maciej.Smiechowski@pg.gda.pl

2015-12-28

The aqueous hydrogen molecule is studied with molecular dynamics simulations at ambient temperature and pressure conditions, using a newly developed flexible and polarizable H{sub 2} molecule model. The design and implementation of this model, compatible with an existing flexible and polarizable force field for water, is presented in detail. The structure of the hydration layer suggests that first-shell water molecules accommodate the H{sub 2} molecule without major structural distortions and two-dimensional, radial-angular distribution functions indicate that as opposed to strictly tangential, the orientation of these water molecules is such that the solute is solvated with one of the free electronmore » pairs of H{sub 2}O. The calculated self-diffusion coefficient of H{sub 2}(aq) agrees very well with experimental results and the time dependence of mean square displacement suggests the presence of caging on a time scale corresponding to hydrogen bond network vibrations in liquid water. Orientational correlation function of H{sub 2} experiences an extremely short-scale decay, making the H{sub 2}–H{sub 2}O interaction potential essentially isotropic by virtue of rotational averaging. The inclusion of explicit polarizability in the model allows for the calculation of Raman spectra that agree very well with available experimental data on H{sub 2}(aq) under differing pressure conditions, including accurate reproduction of the experimentally noted trends with solute pressure or concentration.« less

Firefly algorithm versus genetic algorithm as powerful variable selection tools and their effect on different multivariate calibration models in spectroscopy: A comparative study

NASA Astrophysics Data System (ADS)

Attia, Khalid A. M.; Nassar, Mohammed W. I.; El-Zeiny, Mohamed B.; Serag, Ahmed

2017-01-01

For the first time, a new variable selection method based on swarm intelligence namely firefly algorithm is coupled with three different multivariate calibration models namely, concentration residual augmented classical least squares, artificial neural network and support vector regression in UV spectral data. A comparative study between the firefly algorithm and the well-known genetic algorithm was developed. The discussion revealed the superiority of using this new powerful algorithm over the well-known genetic algorithm. Moreover, different statistical tests were performed and no significant differences were found between all the models regarding their predictabilities. This ensures that simpler and faster models were obtained without any deterioration of the quality of the calibration.

An Extension of RSS-based Model Comparison Tests for Weighted Least Squares

DTIC Science & Technology

2012-08-22

use the model comparison test statistic to analyze the null hypothesis. Under the null hypothesis, the weighted least squares cost functional is JWLS ...q̂WLSH ) = 10.3040×106. Under the alternative hypothesis, the weighted least squares cost functional is JWLS (q̂WLS) = 8.8394 × 106. Thus the model

Potential Compounds for Oral Cancer Treatment: Resveratrol, Nimbolide, Lovastatin, Bortezomib, Vorinostat, Berberine, Pterostilbene, Deguelin, Andrographolide, and Colchicine

PubMed Central

Bundela, Saurabh; Sharma, Anjana; Bisen, Prakash S.

2015-01-01

Oral cancer is one of the main causes of cancer-related deaths in South-Asian countries. There are very limited treatment options available for oral cancer. Research endeavors focused on discovery and development of novel therapies for oral cancer, is necessary to control the ever rising oral cancer related mortalities. We mined the large pool of compounds from the publicly available compound databases, to identify potential therapeutic compounds for oral cancer. Over 84 million compounds were screened for the possible anti-cancer activity by custom build SVM classifier. The molecular targets of the predicted anti-cancer compounds were mined from reliable sources like experimental bioassays studies associated with the compound, and from protein-compound interaction databases. Therapeutic compounds from DrugBank, and a list of natural anti-cancer compounds derived from literature mining of published studies, were used for building partial least squares regression model. The regression model thus built, was used for the estimation of oral cancer specific weights based on the molecular targets. These weights were used to compute scores for screening the predicted anti-cancer compounds for their potential to treat oral cancer. The list of potential compounds was annotated with corresponding physicochemical properties, cancer specific bioactivity evidences, and literature evidences. In all, 288 compounds with the potential to treat oral cancer were identified in the current study. The majority of the compounds in this list are natural products, which are well-tolerated and have minimal side-effects compared to the synthetic counterparts. Some of the potential therapeutic compounds identified in the current study are resveratrol, nimbolide, lovastatin, bortezomib, vorinostat, berberine, pterostilbene, deguelin, andrographolide, and colchicine. PMID:26536350

Shear-induced inflation of coronal magnetic fields

NASA Technical Reports Server (NTRS)

Klimchuk, James A.

1989-01-01

Using numerical models of force-free magnetic fields, the shearing of footprints in arcade geometries leading to an inflation of the coronal magnetic field was examined. For each of the shear profiles considered, all of the field lines become elevated compared with the potential field. This includes cases where the shear is concentrated well away from the arcade axis, such that B(sub z), the component of field parallel to the axis, increases outward to produce an inward B(sub z)squared/8 pi magnetic pressure gradient force. These results contrast with an earlier claim, shown to be incorrect, that field lines can sometimes become depressed as a result of shear. It is conjectured that an inflation of the entire field will always result from the shearing of simple arcade configurations. These results have implications for prominence formation, the interplanetary magnetic flux, and possibly also coronal holes.

Shear-induced inflation of coronal magnetic fields

NASA Technical Reports Server (NTRS)

Klimchuk, James A.

1990-01-01

Using numerical models of force-free magnetic fields, the shearing of footprints in arcade geometries leading to an inflation of the coronal magnetic field was examined. For each of the shear profiles considered, all of the field lines become elevated compared with the potential field. This includes cases where the shear is concentrated well away from the arcade axis, such that B(sub z), the component of field parallel to the axis, increases outward to produce an inward B(sub z) squared/8 pi magnetic pressure gradient force. These results contrast with an earlier claim, shown to be incorrect, that field lines can sometimes become depressed as a result of shear. It is conjectured that an inflation of the entire field will always result from the shearing of simple arcade configurations. These results have implications for prominence formation, the interplanetary magnetic flux, and possibly also coronal holes.

Thermophysical properties of liquid Ni around the melting temperature from molecular dynamics simulation

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

Rozas, R. E.; Department of Physics, University of Bío-Bío, Av. Collao 1202, P.O. Box 5C, Concepción; Demiraǧ, A. D.

Thermophysical properties of liquid nickel (Ni) around the melting temperature are investigated by means of classical molecular dynamics (MD) simulation, using three different embedded atom method potentials to model the interactions between the Ni atoms. Melting temperature, enthalpy, static structure factor, self-diffusion coefficient, shear viscosity, and thermal diffusivity are compared to recent experimental results. Using ab initio MD simulation, we also determine the static structure factor and the mean-squared displacement at the experimental melting point. For most of the properties, excellent agreement is found between experiment and simulation, provided the comparison relative to the corresponding melting temperature. We discuss themore » validity of the Hansen-Verlet criterion for the static structure factor as well as the Stokes-Einstein relation between self-diffusion coefficient and shear viscosity. The thermal diffusivity is extracted from the autocorrelation function of a wavenumber-dependent temperature fluctuation variable.« less

A method for the microlensed flux variance of QSOs

NASA Astrophysics Data System (ADS)

Goodman, Jeremy; Sun, Ai-Lei

2014-06-01

A fast and practical method is described for calculating the microlensed flux variance of an arbitrary source by uncorrelated stars. The required inputs are the mean convergence and shear due to the smoothed potential of the lensing galaxy, the stellar mass function, and the absolute square of the Fourier transform of the surface brightness in the source plane. The mathematical approach follows previous authors but has been generalized, streamlined, and implemented in publicly available code. Examples of its application are given for Dexter and Agol's inhomogeneous-disc models as well as the usual Gaussian sources. Since the quantity calculated is a second moment of the magnification, it is only logarithmically sensitive to the sizes of very compact sources. However, for the inferred sizes of actual quasi-stellar objects (QSOs), it has some discriminatory power and may lend itself to simple statistical tests. At the very least, it should be useful for testing the convergence of microlensing simulations.

Consumer Adoption of Personal Health Record Systems: A Self-Determination Theory Perspective

PubMed Central

Assadi, Vahid

2017-01-01

Background Personal Health Records (PHR) systems provide individuals with access and control over their health information and consequently can support individuals in becoming active participants, rather than passive recipients, in their own care process. In spite of numerous benefits suggested for consumers’ utilizing PHR systems, research has shown that such systems are not yet widely adopted or well known to consumers. Bearing in mind the potential benefits of PHRs to consumers and their potential interest in these systems—and that similar to any other type of information system, adoption is a prerequisite for realizing the potential benefits of PHR systems—research is needed to understand how to enhance the adoption rates for PHR systems. Objective This research seeks to understand how individuals’ intentions to adopt PHR systems are affected by their self-determination in managing their own health—the extent of their ability to take an active role in managing their own health. As such, this research aims to develop and empirically validate a theoretical model that explains PHR systems adoption by the general public through the integration of theories from the information systems and psychology literatures. Methods This research employs a cross-sectional survey method targeted at the Canadian general public without any prior experience in using PHR systems. A partial least squares approach to structural equation modeling was used to validate the proposed research model of this study (N=159). Results Individuals with higher levels of ability to manage their own health (self-determination) are more likely to adopt PHR systems since they have more positive perceptions regarding the use of such systems. Further, such self-determination is fueled by autonomy support from consumers’ physicians as well as the consumers’ personality trait of autonomy orientation. Conclusions This study advances our theoretical understanding of PHR systems adoption. It also contributes to practice by providing insightful implications for designing, promoting, and facilitating the use of PHR systems among consumers. PMID:28751301

Preliminary gravity inversion model of Frenchman Flat Basin, Nevada Test Site, Nevada

USGS Publications Warehouse

Phelps, Geoffrey A.; Graham, Scott E.

2002-01-01

The depth of the basin beneath Frenchman Flat is estimated using a gravity inversion method. Gamma-gamma density logs from two wells in Frenchman Flat constrained the density profiles used to create the gravity inversion model. Three initial models were considered using data from one well, then a final model is proposed based on new information from the second well. The preferred model indicates that a northeast-trending oval-shaped basin underlies Frenchman Flat at least 2,100 m deep, with a maximum depth of 2,400 m at its northeast end. No major horst and graben structures are predicted. Sensitivity analysis of the model indicates that each parameter contributes the same magnitude change to the model, up to 30 meters change in depth for a 1% change in density, but some parameters affect a broader area of the basin. The horizontal resolution of the model was determined by examining the spacing between data stations, and was set to 500 square meters.

Commercial tree species discrimination using airborne AISA Eagle hyperspectral imagery and partial least squares discriminant analysis (PLS-DA) in KwaZulu-Natal, South Africa

NASA Astrophysics Data System (ADS)

Peerbhay, Kabir Yunus; Mutanga, Onisimo; Ismail, Riyad

2013-05-01

Discriminating commercial tree species using hyperspectral remote sensing techniques is critical in monitoring the spatial distributions and compositions of commercial forests. However, issues related to data dimensionality and multicollinearity limit the successful application of the technology. The aim of this study was to examine the utility of the partial least squares discriminant analysis (PLS-DA) technique in accurately classifying six exotic commercial forest species (Eucalyptus grandis, Eucalyptus nitens, Eucalyptus smithii, Pinus patula, Pinus elliotii and Acacia mearnsii) using airborne AISA Eagle hyperspectral imagery (393-900 nm). Additionally, the variable importance in the projection (VIP) method was used to identify subsets of bands that could successfully discriminate the forest species. Results indicated that the PLS-DA model that used all the AISA Eagle bands (n = 230) produced an overall accuracy of 80.61% and a kappa value of 0.77, with user's and producer's accuracies ranging from 50% to 100%. In comparison, incorporating the optimal subset of VIP selected wavebands (n = 78) in the PLS-DA model resulted in an improved overall accuracy of 88.78% and a kappa value of 0.87, with user's and producer's accuracies ranging from 70% to 100%. Bands located predominantly within the visible region of the electromagnetic spectrum (393-723 nm) showed the most capability in terms of discriminating between the six commercial forest species. Overall, the research has demonstrated the potential of using PLS-DA for reducing the dimensionality of hyperspectral datasets as well as determining the optimal subset of bands to produce the highest classification accuracies.

Determination of suitable drying curve model for bread moisture loss during baking

NASA Astrophysics Data System (ADS)

Soleimani Pour-Damanab, A. R.; Jafary, A.; Rafiee, S.

2013-03-01

This study presents mathematical modelling of bread moisture loss or drying during baking in a conventional bread baking process. In order to estimate and select the appropriate moisture loss curve equation, 11 different models, semi-theoretical and empirical, were applied to the experimental data and compared according to their correlation coefficients, chi-squared test and root mean square error which were predicted by nonlinear regression analysis. Consequently, of all the drying models, a Page model was selected as the best one, according to the correlation coefficients, chi-squared test, and root mean square error values and its simplicity. Mean absolute estimation error of the proposed model by linear regression analysis for natural and forced convection modes was 2.43, 4.74%, respectively.

Risk Factors for Obesity in Adult Survivors of Childhood Cancer: A Report From the Childhood Cancer Survivor Study

PubMed Central

Green, Daniel M.; Cox, Cheryl L.; Zhu, Liang; Krull, Kevin R.; Srivastava, Deo Kumar; Stovall, Marilyn; Nolan, Vikki G.; Ness, Kirsten K.; Donaldson, Sarah S.; Oeffinger, Kevin C.; Meacham, Lillian R.; Sklar, Charles A.; Armstrong, Gregory T.; Robison, Leslie L.

2012-01-01

Purpose Many Childhood Cancer Survivor Study (CCSS) participants are at increased risk for obesity. The etiology of their obesity is likely multifactorial but not well understood. Patients and Methods We evaluated the potential contribution of demographic, lifestyle, treatment, and intrapersonal factors and self-reported pharmaceutical use to obesity (body mass index ≥ 30 kg/m2) among 9,284 adult (> 18 years of age) CCSS participants. Independent predictors were identified using multivariable regression models. Interrelationships were determined using structural equation modeling (SEM). Results Independent risk factors for obesity included cancer diagnosed at 5 to 9 years of age (relative risk [RR], 1.12; 95% CI, 1.01 to 1.24; P = .03), abnormal Short Form–36 physical function (RR, 1.19; 95% CI, 1.06 to 1.33; P < .001), hypothalamic/pituitary radiation doses of 20 to 30 Gy (RR, 1.17; 95% CI, 1.05 to 1.30; P = .01), and paroxetine use (RR, 1.29; 95% CI, 1.08 to 1.54; P = .01). Meeting US Centers for Disease Control and Prevention guidelines for vigorous physical activity (RR, 0.90; 95% CI, 0.82 to 0.97; P = .01) and a medium amount of anxiety (RR, 0.86; 95% CI, 0.75 to 0.99; P = .04) reduced the risk of obesity. Results of SEM (N = 8,244; comparative fit index = 0.999; Tucker Lewis index = 0.999; root mean square error of approximation = 0.014; weighted root mean square residual = 0.749) described the hierarchical impact of the direct predictors, moderators, and mediators of obesity. Conclusion Treatment, lifestyle, and intrapersonal factors, as well as the use of specific antidepressants, may contribute to obesity among survivors. A multifaceted intervention, including alternative drug and other therapies for depression and anxiety, may be required to reduce risk. PMID:22184380

Deconvolution of the vestibular evoked myogenic potential using the power spectrum of the electromyogram.

PubMed

Lütkenhöner, Bernd

2015-10-06

The vestibular evoked myogenic potential (VEMP) can be modelled reasonably well by convolving two functions: one representing an average motor unit action potential (MUAP), the other representing the temporal modulation of the MUAP rate (rate modulation). It is the latter which contains the information of interest, and so it would be desirable to be able to estimate this function from a combination of the VEMP with some other data. As the VEMP is simply a stimulus-triggered average of the electromyogram (EMG), a supplementary, easily accessible source of information is the EMG power spectrum, which can be shown to be roughly proportional to the squared modulus of the Fourier transform of the MUAP. But no phase information is available for the MUAP so that a straightforward deconvolution is not possible. To get around the problem of incomplete information, the rate modulation is described by a thoughtfully chosen function with just a few adjustable parameters. The convolution model is then used to make predictions as to the energy spectral density of the VEMP, and the parameters are optimized using a cost function that quantifies the difference between model prediction and data. The workability of the proposed approach is demonstrated by analysing Monte Carlo simulated data and exemplary data from patients who underwent VEMP testing as part of a clinical evaluation of their dizziness symptoms. The approach is suited, for example, to estimate the duration of the inhibition causing the VEMP or to disentangle a VEMP consisting of more than one component.

New analytical model for the ozone electronic ground state potential surface and accurate ab initio vibrational predictions at high energy range.

PubMed

Tyuterev, Vladimir G; Kochanov, Roman V; Tashkun, Sergey A; Holka, Filip; Szalay, Péter G

2013-10-07

An accurate description of the complicated shape of the potential energy surface (PES) and that of the highly excited vibration states is of crucial importance for various unsolved issues in the spectroscopy and dynamics of ozone and remains a challenge for the theory. In this work a new analytical representation is proposed for the PES of the ground electronic state of the ozone molecule in the range covering the main potential well and the transition state towards the dissociation. This model accounts for particular features specific to the ozone PES for large variations of nuclear displacements along the minimum energy path. The impact of the shape of the PES near the transition state (existence of the "reef structure") on vibration energy levels was studied for the first time. The major purpose of this work was to provide accurate theoretical predictions for ozone vibrational band centres at the energy range near the dissociation threshold, which would be helpful for understanding the very complicated high-resolution spectra and its analyses currently in progress. Extended ab initio electronic structure calculations were carried out enabling the determination of the parameters of a minimum energy path PES model resulting in a new set of theoretical vibrational levels of ozone. A comparison with recent high-resolution spectroscopic data on the vibrational levels gives the root-mean-square deviations below 1 cm(-1) for ozone band centres up to 90% of the dissociation energy. New ab initio vibrational predictions represent a significant improvement with respect to all previously available calculations.

Determination of total flavonoids content in fresh Ginkgo biloba leaf with different colors using near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Shi, Ji-yong; Zou, Xiao-bo; Zhao, Jie-wen; Mel, Holmes; Wang, Kai-liang; Wang, Xue; Chen, Hong

Total flavonoids content is often considered an important quality index of Ginkgo biloba leaf. The feasibility of using near infrared (NIR) spectra at the wavelength range of 10,000-4000 cm-1 for rapid and nondestructive determination of total flavonoids content in G. biloba leaf was investigated. 120 fresh G. biloba leaves in different colors (green, green-yellowish and yellow) were used to spectra acquisition and total flavonoids determination. Partial least squares (PLS), interval partial least squares (iPLS) and synergy interval partial least squares (SiPLS) were used to develop calibration models for total flavonoids content in two colors leaves (green-yellowish and yellow) and three colors leaves (green, green-yellowish and yellow), respectively. The level of total flavonoids content for green, green-yellowish and yellow leaves was in an increasing order. Two characteristic wavelength regions (5840-6090 cm-1 and 6620-6880 cm-1), which corresponded to the absorptions of two aromatic rings in basic flavonoid structure, were selected by SiPLS. The optimal SiPLS model for total flavonoids content in the two colors leaves (r2 = 0.82, RMSEP = 2.62 mg g-1) had better performance than PLS and iPLS models. It could be concluded that NIR spectroscopy has significant potential in the nondestructive determination of total flavonoids content in fresh G. biloba leaf.

Toward quantifying the composition of soft tissues by spectral CT with Medipix3.

PubMed

Ronaldson, J Paul; Zainon, Rafidah; Scott, Nicola Jean Agnes; Gieseg, Steven Paul; Butler, Anthony P; Butler, Philip H; Anderson, Nigel G

2012-11-01

To determine the potential of spectral computed tomography (CT) with Medipix3 for quantifying fat, calcium, and iron in soft tissues within small animal models and surgical specimens of diseases such as fatty liver (metabolic syndrome) and unstable atherosclerosis. The spectroscopic method was applied to tomographic data acquired using a micro-CT system incorporating a Medipix3 detector array with silicon sensor layer and microfocus x-ray tube operating at 50 kVp. A 10 mm diameter perspex phantom containing a fat surrogate (sunflower oil) and aqueous solutions of ferric nitrate, calcium chloride, and iodine was imaged with multiple energy bins. The authors used the spectroscopic characteristics of the CT number to establish a basis for the decomposition of soft tissue components. The potential of the method of constrained least squares for quantifying different sets of materials was evaluated in terms of information entropy and degrees of freedom, with and without the use of a volume conservation constraint. The measurement performance was evaluated quantitatively using atheroma and mouse equivalent phantoms. Finally the decomposition method was assessed qualitatively using a euthanized mouse and an excised human atherosclerotic plaque. Spectral CT measurements of a phantom containing tissue surrogates confirmed the ability to distinguish these materials by the spectroscopic characteristics of their CT number. The assessment of performance potential in terms of information entropy and degrees of freedom indicated that certain sets of up to three materials could be decomposed by the method of constrained least squares. However, there was insufficient information within the data set to distinguish calcium from iron within soft tissues. The quantification of calcium concentration and fat mass fraction within atheroma and mouse equivalent phantoms by spectral CT correlated well with the nominal values (R(2) = 0.990 and R(2) = 0.985, respectively). In the euthanized mouse and excised human atherosclerotic plaque, regions of calcium and fat were appropriately decomposed according to their spectroscopic characteristics. Spectral CT, using the Medipix3 detector and silicon sensor layer, can quantify certain sets of up to three materials using the proposed method of constrained least squares. The system has some ability to independently distinguish calcium, fat, and water, and these have been quantified within phantom equivalents of fatty liver and atheroma. In this configuration, spectral CT cannot distinguish iron from calcium within soft tissues.

Regression model development and computational procedures to support estimation of real-time concentrations and loads of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-9

USGS Publications Warehouse

Lee, Michael T.; Asquith, William H.; Oden, Timothy D.

2012-01-01

In December 2005, the U.S. Geological Survey (USGS), in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (Escherichia coli and total coliform), atrazine, and suspended sediment at two USGS streamflow-gaging stations that represent watersheds contributing to Lake Houston (08068500 Spring Creek near Spring, Tex., and 08070200 East Fork San Jacinto River near New Caney, Tex.). Data from the discrete water-quality samples collected during 2005–9, in conjunction with continuously monitored real-time data that included streamflow and other physical water-quality properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), were used to develop regression models for the estimation of concentrations of water-quality constituents of substantial source watersheds to Lake Houston. The potential explanatory variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, and time (to account for seasonal variations inherent in some water-quality data). The response variables (the selected constituents) at each site were nitrite plus nitrate nitrogen, total phosphorus, total organic carbon, E. coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities to serve as potential surrogate variables to estimate concentrations of the selected constituents through statistical regression. Statistical regression also facilitates accompanying estimates of uncertainty in the form of prediction intervals. Each regression model potentially can be used to estimate concentrations of a given constituent in real time. Among other regression diagnostics, the diagnostics used as indicators of general model reliability and reported herein include the adjusted R-squared, the residual standard error, residual plots, and p-values. Adjusted R-squared values for the Spring Creek models ranged from .582–.922 (dimensionless). The residual standard errors ranged from .073–.447 (base-10 logarithm). Adjusted R-squared values for the East Fork San Jacinto River models ranged from .253–.853 (dimensionless). The residual standard errors ranged from .076–.388 (base-10 logarithm). In conjunction with estimated concentrations, constituent loads can be estimated by multiplying the estimated concentration by the corresponding streamflow and by applying the appropriate conversion factor. The regression models presented in this report are site specific, that is, they are specific to the Spring Creek and East Fork San Jacinto River streamflow-gaging stations; however, the general methods that were developed and documented could be applied to most perennial streams for the purpose of estimating real-time water quality data.

Computational study of the rovibrational spectrum of CO₂-CS₂.

PubMed

Brown, James; Wang, Xiao-Gang; Carrington, Tucker; Grubbs, G S; Dawes, Richard

2014-03-21

A new intermolecular potential energy surface, rovibrational transition frequencies, and line strengths are computed for CO2-CS2. The potential is made by fitting energies obtained from explicitly correlated coupled-cluster calculations using an interpolating moving least squares method. The rovibrational Schrödinger equation is solved with a symmetry-adapted Lanczos algorithm and an uncoupled product basis set. All four intermolecular coordinates are included in the calculation. In agreement with previous experiments, the global minimum of the potential energy surface (PES) is cross shaped. The PES also has slipped-parallel minima. Rovibrational wavefunctions are localized in the cross minima and the slipped-parallel minima. Vibrational parent analysis was used to assign vibrational labels to rovibrational states. Tunneling occurs between the two cross minima. Because more than one symmetry operation interconverts the two wells, the symmetry (-oo) of the upper component of the tunneling doublet is different from the symmetry (-ee) of the tunneling coordinate. This unusual situation is due to the multidimensional nature of the double well tunneling. For the cross ground vibrational state, calculated rotational constants differ from their experimental counterparts by less than 0.0001 cm(-1). Most rovibrational states were found to be incompatible with the standard effective rotational Hamiltonian often used to fit spectra. This appears to be due to coupling between internal and overall rotation of the dimer. A simple 2D model accounting for internal rotation was used for two cross-shaped fundamentals to obtain good fits.

An analytical method to calculate equivalent fields to irregular symmetric and asymmetric photon fields.

PubMed

Tahmasebi Birgani, Mohamad J; Chegeni, Nahid; Zabihzadeh, Mansoor; Hamzian, Nima

2014-01-01

Equivalent field is frequently used for central axis depth-dose calculations of rectangular- and irregular-shaped photon beams. As most of the proposed models to calculate the equivalent square field are dosimetry based, a simple physical-based method to calculate the equivalent square field size was used as the basis of this study. The table of the sides of the equivalent square or rectangular fields was constructed and then compared with the well-known tables by BJR and Venselaar, et al. with the average relative error percentage of 2.5 ± 2.5% and 1.5 ± 1.5%, respectively. To evaluate the accuracy of this method, the percentage depth doses (PDDs) were measured for some special irregular symmetric and asymmetric treatment fields and their equivalent squares for Siemens Primus Plus linear accelerator for both energies, 6 and 18MV. The mean relative differences of PDDs measurement for these fields and their equivalent square was approximately 1% or less. As a result, this method can be employed to calculate equivalent field not only for rectangular fields but also for any irregular symmetric or asymmetric field. © 2013 American Association of Medical Dosimetrists Published by American Association of Medical Dosimetrists All rights reserved.

Empirical study of the perceived ease of use and relative advantage on load-bearing masonry (LBM) technology adoption

NASA Astrophysics Data System (ADS)

Ramli, Nor Azlinda; Abdullah, Che Sobry; Nawi, Mohd Nasrun Mohd

2017-11-01

Load-bearing masonry (LBM) technology has been identified as an alternative method that can potentially encourage the sustainability of the housing industry. The adoption of LBM technology is believed to bring beneficial effects to the housing industry as well as company productivity. The factors related to the adoption LBM technology was revealed to strongly influence the implementation of this system in the housing industry. The aim of this study is to determine the factors influencing the adoption of LBM technology among the developer firms in Malaysia as well as the factors that are highly related to perceived ease of use and relative advantage. A random sampling technique was applied and a questionnaire-based field survey was carried out to obtain the data from the respondents. All the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings of this paper have revealed that perceived ease of use and relative advantage are related to the adoption of LBM technology. The findings also indicated the validity of Technology Acceptance Model TAM (perceived ease of use) and Innovation Diffusion Theory IDT (relative advantage) as the determinant factors in the adoption of LBM technology. Finally, some recommendations for future research are suggested in the final section of this paper.

Renormalization group analysis of dipolar Heisenberg model on square lattice

NASA Astrophysics Data System (ADS)

Keleş, Ahmet; Zhao, Erhai

2018-06-01

We present a detailed functional renormalization group analysis of spin-1/2 dipolar Heisenberg model on square lattice. This model is similar to the well-known J1-J2 model and describes the pseudospin degrees of freedom of polar molecules confined in deep optical lattice with long-range anisotropic dipole-dipole interactions. Previous study of this model based on tensor network ansatz indicates a paramagnetic ground state for certain dipole tilting angles which can be tuned in experiments to control the exchange couplings. The tensor ansatz formulated on a small cluster unit cell is inadequate to describe the spiral order, and therefore the phase diagram at high azimuthal tilting angles remains undetermined. Here, we obtain the full phase diagram of the model from numerical pseudofermion functional renormalization group calculations. We show that an extended quantum paramagnetic phase is realized between the Néel and stripe/spiral phases. In this region, the spin susceptibility flows smoothly down to the lowest numerical renormalization group scales with no sign of divergence or breakdown of the flow, in sharp contrast to the flow towards the long-range-ordered phases. Our results provide further evidence that the dipolar Heisenberg model is a fertile ground for quantum spin liquids.

Modelling the spatial distribution of the nuisance mosquito species Anopheles plumbeus (Diptera: Culicidae) in the Netherlands.

PubMed

Ibañez-Justicia, Adolfo; Cianci, Daniela

2015-05-01

Landscape modifications, urbanization or changes of use of rural-agricultural areas can create more favourable conditions for certain mosquito species and therefore indirectly cause nuisance problems for humans. This could potentially result in mosquito-borne disease outbreaks when the nuisance is caused by mosquito species that can transmit pathogens. Anopheles plumbeus is a nuisance mosquito species and a potential malaria vector. It is one of the most frequently observed species in the Netherlands. Information on the distribution of this species is essential for risk assessments. The purpose of the study was to investigate the potential spatial distribution of An. plumbeus in the Netherlands. Random forest models were used to link the occurrence and the abundance of An. plumbeus with environmental features and to produce distribution maps in the Netherlands. Mosquito data were collected using a cross-sectional study design in the Netherlands, from April to October 2010-2013. The environmental data were obtained from satellite imagery and weather stations. Statistical measures (accuracy for the occurrence model and mean squared error for the abundance model) were used to evaluate the models performance. The models were externally validated. The maps show that forested areas (centre of the Netherlands) and the east of the country were predicted as suitable for An. plumbeus. In particular high suitability and high abundance was predicted in the south-eastern provinces Limburg and North Brabant. Elevation, precipitation, day and night temperature and vegetation indices were important predictors for calculating the probability of occurrence for An. plumbeus. The probability of occurrence, vegetation indices and precipitation were important for predicting its abundance. The AUC value was 0.73 and the error in the validation was 0.29; the mean squared error value was 0.12. The areas identified by the model as suitable and with high abundance of An. plumbeus, are consistent with the areas from which nuisance was reported. Our results can be helpful in the assessment of vector-borne disease risk.

Quantum mechanical tunneling in the automerization of cyclobutadiene

NASA Astrophysics Data System (ADS)

Schoonmaker, R.; Lancaster, T.; Clark, S. J.

2018-03-01

Cyclobutadiene has a four-membered carbon ring with two double bonds, but this highly strained molecular configuration is almost square and, via a coordinated motion, the nuclei quantum mechanically tunnels through the high-energy square state to a configuration equivalent to the initial configuration under a 90° rotation. This results in a square ground state, comprising a superposition of two molecular configurations, that is driven by quantum tunneling. Using a quantum mechanical model, and an effective nuclear potential from density functional theory, we calculate the vibrational energy spectrum and the accompanying wavefunctions. We use the wavefunctions to identify the motions of the molecule and detail how different motions can enhance or suppress the tunneling rate. This is relevant for kinematics of tunneling-driven reactions, and we discuss these implications. We are also able to provide a qualitative account of how the molecule will respond to an external perturbation and how this may enhance or suppress infra-red-active vibrational transitions.

Latin and Magic Squares

ERIC Educational Resources Information Center

Emanouilidis, Emanuel

2005-01-01

Latin squares have existed for hundreds of years but it wasn't until rather recently that Latin squares were used in other areas such as statistics, graph theory, coding theory and the generation of random numbers as well as in the design and analysis of experiments. This note describes Latin and diagonal Latin squares, a method of constructing…

Model of directed lines for square ice with second-neighbor and third-neighbor interactions

NASA Astrophysics Data System (ADS)

Kirov, Mikhail V.

2018-02-01

The investigation of the properties of nanoconfined systems is one of the most rapidly developing scientific fields. Recently it has been established that water monolayer between two graphene sheets forms square ice. Because of the energetic disadvantage, in the structure of the square ice there are no longitudinally arranged molecules. The result is that the structure is formed by unidirectional straight-lines of hydrogen bonds only. A simple but accurate discrete model of square ice with second-neighbor and third-neighbor interactions is proposed. According to this model, the ground state includes all configurations which do not contain three neighboring unidirectional chains of hydrogen bonds. Each triplet increases the energy by the same value. This new model differs from an analogous model with long-range interactions where in the ground state all neighboring chains are antiparallel. The new model is suitable for the corresponding system of point electric (and magnetic) dipoles on the square lattice. It allows separately estimating the different contributions to the total binding energy and helps to understand the properties of infinite monolayers and finite nanostructures. Calculations of the binding energy for square ice and for point dipole system are performed using the packages TINKER and LAMMPS.

Two Enhancements of the Logarithmic Least-Squares Method for Analyzing Subjective Comparisons

DTIC Science & Technology

1989-03-25

error term. 1 For this model, the total sum of squares ( SSTO ), defined as n 2 SSTO = E (yi y) i=1 can be partitioned into error and regression sums...of the regression line around the mean value. Mathematically, for the model given by equation A.4, SSTO = SSE + SSR (A.6) A-4 where SSTO is the total...sum of squares (i.e., the variance of the yi’s), SSE is error sum of squares, and SSR is the regression sum of squares. SSTO , SSE, and SSR are given

A Bayesian model averaging method for the derivation of reservoir operating rules

NASA Astrophysics Data System (ADS)

Zhang, Jingwen; Liu, Pan; Wang, Hao; Lei, Xiaohui; Zhou, Yanlai

2015-09-01

Because the intrinsic dynamics among optimal decision making, inflow processes and reservoir characteristics are complex, functional forms of reservoir operating rules are always determined subjectively. As a result, the uncertainty of selecting form and/or model involved in reservoir operating rules must be analyzed and evaluated. In this study, we analyze the uncertainty of reservoir operating rules using the Bayesian model averaging (BMA) model. Three popular operating rules, namely piecewise linear regression, surface fitting and a least-squares support vector machine, are established based on the optimal deterministic reservoir operation. These individual models provide three-member decisions for the BMA combination, enabling the 90% release interval to be estimated by the Markov Chain Monte Carlo simulation. A case study of China's the Baise reservoir shows that: (1) the optimal deterministic reservoir operation, superior to any reservoir operating rules, is used as the samples to derive the rules; (2) the least-squares support vector machine model is more effective than both piecewise linear regression and surface fitting; (3) BMA outperforms any individual model of operating rules based on the optimal trajectories. It is revealed that the proposed model can reduce the uncertainty of operating rules, which is of great potential benefit in evaluating the confidence interval of decisions.

Fast function-on-scalar regression with penalized basis expansions.

PubMed

Reiss, Philip T; Huang, Lei; Mennes, Maarten

2010-01-01

Regression models for functional responses and scalar predictors are often fitted by means of basis functions, with quadratic roughness penalties applied to avoid overfitting. The fitting approach described by Ramsay and Silverman in the 1990 s amounts to a penalized ordinary least squares (P-OLS) estimator of the coefficient functions. We recast this estimator as a generalized ridge regression estimator, and present a penalized generalized least squares (P-GLS) alternative. We describe algorithms by which both estimators can be implemented, with automatic selection of optimal smoothing parameters, in a more computationally efficient manner than has heretofore been available. We discuss pointwise confidence intervals for the coefficient functions, simultaneous inference by permutation tests, and model selection, including a novel notion of pointwise model selection. P-OLS and P-GLS are compared in a simulation study. Our methods are illustrated with an analysis of age effects in a functional magnetic resonance imaging data set, as well as a reanalysis of a now-classic Canadian weather data set. An R package implementing the methods is publicly available.

Ultrafast quantitation of six quinolones in water samples by second-order capillary electrophoresis data modeling with multivariate curve resolution-alternating least squares.

PubMed

Alcaráz, Mirta R; Vera-Candioti, Luciana; Culzoni, María J; Goicoechea, Héctor C

2014-04-01

This paper presents the development of a capillary electrophoresis method with diode array detector coupled to multivariate curve resolution-alternating least squares (MCR-ALS) to conduct the resolution and quantitation of a mixture of six quinolones in the presence of several unexpected components. Overlapping of time profiles between analytes and water matrix interferences were mathematically solved by data modeling with the well-known MCR-ALS algorithm. With the aim of overcoming the drawback originated by two compounds with similar spectra, a special strategy was implemented to model the complete electropherogram instead of dividing the data in the region as usually performed in previous works. The method was first applied to quantitate analytes in standard mixtures which were randomly prepared in ultrapure water. Then, tap water samples spiked with several interferences were analyzed. Recoveries between 76.7 and 125 % and limits of detection between 5 and 18 μg L(-1) were achieved.

Dynamics in entangled polyethylene melts using coarse-grained models

NASA Astrophysics Data System (ADS)

Peters, Brandon L.; Grest, Gary S.; Salerno, K. Michael; Agrawal, Anupriya; Perahia, Dvora

Polymer dynamics creates distinctive viscoelastic behavior as a result of a coupled interplay of motion on multiple length scales. Capturing the broad time and length scales of polymeric motion however, remains a challenge. Using polyethylene (PE) as a model system, we probe the effects of the degree of coarse graining on polymer dynamics. Coarse-grained (CG) potentials are derived using iterative Boltzmann inversion (iBi) with 2-6 methyl groups per CG bead from all fully atomistic melt simulations for short chains. While the iBi methods produces non-bonded potentials which give excellent agreement for the atomistic and CG pair correlation functions, the pressure P = 100-500MPa for the CG model. Correcting for potential so P 0 leads to non-bonded models with slightly smaller effective diameter and much deeper minimum. However, both the pressure and non-pressure corrected CG models give similar results for mean squared displacement (MSD) and the stress auto correlation function G(t) for PE melts above the melting point. The time rescaling factor between CG and atomistic models is found to be nearly the same for both CG models. Transferability of potential for different temperatures was tested by comparing the MSD and G(t) for potentials generated at different temperatures.

Contribution Of The SWOT Mission To Large-Scale Hydrological Modeling Using Data Assimilation

NASA Astrophysics Data System (ADS)

Emery, C. M.; Biancamaria, S.; Boone, A. A.; Ricci, S. M.; Rochoux, M. C.; Garambois, P. A.; Paris, A.; Calmant, S.

2016-12-01

The purpose of this work is to improve water fluxes estimation on the continental surfaces, at interanual and interseasonal scale (from few years to decennial time period). More specifically, it studies contribution of the incoming SWOT satellite mission to improve hydrology model at global scale, and using the land surface model ISBA-TRIP. This model corresponds to the continental component of the CNRM (French meteorological research center)'s climatic model. This study explores the potential of satellite data to correct either input parameters of the river routing scheme TRIP or its state variables. To do so, a data assimilation platform (using an Ensemble Kalman Filter, EnKF) has been implemented to assimilate SWOT virtual observations as well as discharges estimated from real nadir altimetry data. A series of twin experiments is used to test and validate the parameter estimation module of the platform. SWOT virtual-observations of water heights along SWOT tracks (with a 10 cm white noise model error) are assimilated to correct the river routing model parameters. To begin with, we chose to focus exclusively on the river manning coefficient, with the possibility to easily extend to other parameters such as the river widths. First results show that the platform is able to recover the "true" Manning distribution assimilating SWOT-like water heights. The error on the coefficients goes from 35 % before assimilation to 9 % after four SWOT orbit repeat period of 21 days. In the state estimation mode, daily assimilation cycles are realized to correct TRIP river water storage initial state by assimilating ENVISAT-based discharge. Those observations are derived from ENVISAT water elevation measures, using rating curves from the MGB-IPH hydrological model (calibrated over the Amazon using in situ gages discharge). Using such kind of observation allows going beyond idealized twin experiments and also to test contribution of a remotely-sensed discharge product, which could prefigure the SWOT discharge product. The results show that discharge after assimilation are globally improved : the root-mean-square error between the analysis discharge ensemble mean and in situ discharges is reduced by 30 %, compared to the root-mean-square error between the free run and in situ discharges.

Response functions for dimers and square-symmetric molecules in four-wave-mixing experiments with polarized light

NASA Astrophysics Data System (ADS)

Smith, Eric Ryan; Farrow, Darcie A.; Jonas, David M.

2005-07-01

Four-wave-mixing nonlinear-response functions are given for intermolecular and intramolecular vibrations of a perpendicular dimer and intramolecular vibrations of a square-symmetric molecule containing a doubly degenerate state. A two-dimensional particle-in-a-box model is used to approximate the electronic wave functions and obtain harmonic potentials for nuclear motion. Vibronic interactions due to symmetry-lowering distortions along Jahn-Teller active normal modes are discussed. Electronic dephasing due to nuclear motion along both symmetric and asymmetric normal modes is included in these response functions, but population transfer between states is not. As an illustration, these response functions are used to predict the pump-probe polarization anisotropy in the limit of impulsive excitation.

Magnitude and Temporal Variability of Inter-stimulus EEG Modulate the Linear Relationship Between Laser-Evoked Potentials and Fast-Pain Perception

PubMed Central

Li, Linling; Huang, Gan; Lin, Qianqian; Liu, Jia; Zhang, Shengli; Zhang, Zhiguo

2018-01-01

The level of pain perception is correlated with the magnitude of pain-evoked brain responses, such as laser-evoked potentials (LEP), across trials. The positive LEP-pain relationship lays the foundation for pain prediction based on single-trial LEP, but cross-individual pain prediction does not have a good performance because the LEP-pain relationship exhibits substantial cross-individual difference. In this study, we aim to explain the cross-individual difference in the LEP-pain relationship using inter-stimulus EEG (isEEG) features. The isEEG features (root mean square as magnitude and mean square successive difference as temporal variability) were estimated from isEEG data (at full band and five frequency bands) recorded between painful stimuli. A linear model was fitted to investigate the relationship between pain ratings and LEP response for fast-pain trials on a trial-by-trial basis. Then the correlation between isEEG features and the parameters of LEP-pain model (slope and intercept) was evaluated. We found that the magnitude and temporal variability of isEEG could modulate the parameters of an individual's linear LEP-pain model for fast-pain trials. Based on this, we further developed a new individualized fast-pain prediction scheme, which only used training individuals with similar isEEG features as the test individual to train the fast-pain prediction model, and obtained improved accuracy in cross-individual fast-pain prediction. The findings could help elucidate the neural mechanism of cross-individual difference in pain experience and the proposed fast-pain prediction scheme could be potentially used as a practical and feasible pain prediction method in clinical practice. PMID:29904336

A partial least squares based spectrum normalization method for uncertainty reduction for laser-induced breakdown spectroscopy measurements

NASA Astrophysics Data System (ADS)

Li, Xiongwei; Wang, Zhe; Lui, Siu-Lung; Fu, Yangting; Li, Zheng; Liu, Jianming; Ni, Weidou

2013-10-01

A bottleneck of the wide commercial application of laser-induced breakdown spectroscopy (LIBS) technology is its relatively high measurement uncertainty. A partial least squares (PLS) based normalization method was proposed to improve pulse-to-pulse measurement precision for LIBS based on our previous spectrum standardization method. The proposed model utilized multi-line spectral information of the measured element and characterized the signal fluctuations due to the variation of plasma characteristic parameters (plasma temperature, electron number density, and total number density) for signal uncertainty reduction. The model was validated by the application of copper concentration prediction in 29 brass alloy samples. The results demonstrated an improvement on both measurement precision and accuracy over the generally applied normalization as well as our previously proposed simplified spectrum standardization method. The average relative standard deviation (RSD), average of the standard error (error bar), the coefficient of determination (R2), the root-mean-square error of prediction (RMSEP), and average value of the maximum relative error (MRE) were 1.80%, 0.23%, 0.992, 1.30%, and 5.23%, respectively, while those for the generally applied spectral area normalization were 3.72%, 0.71%, 0.973, 1.98%, and 14.92%, respectively.

Robust Least-Squares Support Vector Machine With Minimization of Mean and Variance of Modeling Error.

PubMed

Lu, Xinjiang; Liu, Wenbo; Zhou, Chuang; Huang, Minghui

2017-06-13

The least-squares support vector machine (LS-SVM) is a popular data-driven modeling method and has been successfully applied to a wide range of applications. However, it has some disadvantages, including being ineffective at handling non-Gaussian noise as well as being sensitive to outliers. In this paper, a robust LS-SVM method is proposed and is shown to have more reliable performance when modeling a nonlinear system under conditions where Gaussian or non-Gaussian noise is present. The construction of a new objective function allows for a reduction of the mean of the modeling error as well as the minimization of its variance, and it does not constrain the mean of the modeling error to zero. This differs from the traditional LS-SVM, which uses a worst-case scenario approach in order to minimize the modeling error and constrains the mean of the modeling error to zero. In doing so, the proposed method takes the modeling error distribution information into consideration and is thus less conservative and more robust in regards to random noise. A solving method is then developed in order to determine the optimal parameters for the proposed robust LS-SVM. An additional analysis indicates that the proposed LS-SVM gives a smaller weight to a large-error training sample and a larger weight to a small-error training sample, and is thus more robust than the traditional LS-SVM. The effectiveness of the proposed robust LS-SVM is demonstrated using both artificial and real life cases.

Energy gain calculations in Penning fusion systems using a bounce-averaged Fokker-Planck model

NASA Astrophysics Data System (ADS)

Chacón, L.; Miley, G. H.; Barnes, D. C.; Knoll, D. A.

2000-11-01

In spherical Penning fusion devices, a spherical cloud of electrons, confined in a Penning-like trap, creates the ion-confining electrostatic well. Fusion energy gains for these systems have been calculated in optimistic conditions (i.e., spherically uniform electrostatic well, no collisional ion-electron interactions, single ion species) using a bounce-averaged Fokker-Planck (BAFP) model. Results show that steady-state distributions in which the Maxwellian ion population is dominant correspond to lowest ion recirculation powers (and hence highest fusion energy gains). It is also shown that realistic parabolic-like wells result in better energy gains than square wells, particularly at large well depths (>100 kV). Operating regimes with fusion power to ion input power ratios (Q-value) >100 have been identified. The effect of electron losses on the Q-value has been addressed heuristically using a semianalytic model, indicating that large Q-values are still possible provided that electron particle losses are kept small and well depths are large.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Early Childhood Developmental Status in Low- and Middle-Income Countries: National, Regional, and Global Prevalence Estimates Using Predictive Modeling.

PubMed

McCoy, Dana Charles; Peet, Evan D; Ezzati, Majid; Danaei, Goodarz; Black, Maureen M; Sudfeld, Christopher R; Fawzi, Wafaie; Fink, Günther

2016-06-01

The development of cognitive and socioemotional skills early in life influences later health and well-being. Existing estimates of unmet developmental potential in low- and middle-income countries (LMICs) are based on either measures of physical growth or proxy measures such as poverty. In this paper we aim to directly estimate the number of children in LMICs who would be reported by their caregivers to show low cognitive and/or socioemotional development. The present paper uses Early Childhood Development Index (ECDI) data collected between 2005 and 2015 from 99,222 3- and 4-y-old children living in 35 LMICs as part of the Multiple Indicator Cluster Survey (MICS) and Demographic and Health Surveys (DHS) programs. First, we estimate the prevalence of low cognitive and/or socioemotional ECDI scores within our MICS/DHS sample. Next, we test a series of ordinary least squares regression models predicting low ECDI scores across our MICS/DHS sample countries based on country-level data from the Human Development Index (HDI) and the Nutrition Impact Model Study. We use cross-validation to select the model with the best predictive validity. We then apply this model to all LMICs to generate country-level estimates of the prevalence of low ECDI scores globally, as well as confidence intervals around these estimates. In the pooled MICS and DHS sample, 14.6% of children had low ECDI scores in the cognitive domain, 26.2% had low socioemotional scores, and 36.8% performed poorly in either or both domains. Country-level prevalence of low cognitive and/or socioemotional scores on the ECDI was best represented by a model using the HDI as a predictor. Applying this model to all LMICs, we estimate that 80.8 million children ages 3 and 4 y (95% CI 48.1 million, 113.6 million) in LMICs experienced low cognitive and/or socioemotional development in 2010, with the largest number of affected children in sub-Saharan Africa (29.4.1 million; 43.8% of children ages 3 and 4 y), followed by South Asia (27.7 million; 37.7%) and the East Asia and Pacific region (15.1 million; 25.9%). Positive associations were found between low development scores and stunting, poverty, male sex, rural residence, and lack of cognitive stimulation. Additional research using more detailed developmental assessments across a larger number of LMICs is needed to address the limitations of the present study. The number of children globally failing to reach their developmental potential remains large. Additional research is needed to identify the specific causes of poor developmental outcomes in diverse settings, as well as potential context-specific interventions that might promote children's early cognitive and socioemotional well-being.

Computational and theoretical studies of globular proteins

NASA Astrophysics Data System (ADS)

Pagan, Daniel L.

Protein crystallization is often achieved in experiment through a trial and error approach. To date, there exists a dearth of theoretical understanding of the initial conditions necessary to promote crystallization. While a better understanding of crystallization will help to create good crystals suitable for structure analysis, it will also allow us to prevent the onset of certain diseases. The core of this thesis is to model and, ultimately, understand the phase behavior of protein particles in solution. Toward this goal, we calculate the fluid-fluid coexistence curve in the vicinity of the metastable critical point of the modified Lennard-Jones potential, where it has been shown that nucleation is increased by many orders of magnitude. We use finite-size scaling techniques and grand canonical Monte Carlo simulation methods. This has allowed us to pinpoint the critical point and subcritical region with high accuracy in spite of the critical fluctuations that hinder sampling using other Monte Carlo techniques. We also attempt to model the phase behavior of the gamma-crystallins, mutations of which have been linked to genetic cataracts. The complete phase behavior of the square well potential at the ranges of attraction lambda = 1.15 and lambda = 1.25 is calculated and compared with that of the gammaII-crystallin. The role of solvent is also important in the crystallization process and affects the phase behavior of proteins in solution. We study a model that accounts for the contribution of the solvent free-energy to the free-energy of globular proteins. This model allows us to model phase behavior that includes solvent.

System identification and model reduction using modulating function techniques

NASA Technical Reports Server (NTRS)

Shen, Yan

1993-01-01

Weighted least squares (WLS) and adaptive weighted least squares (AWLS) algorithms are initiated for continuous-time system identification using Fourier type modulating function techniques. Two stochastic signal models are examined using the mean square properties of the stochastic calculus: an equation error signal model with white noise residuals, and a more realistic white measurement noise signal model. The covariance matrices in each model are shown to be banded and sparse, and a joint likelihood cost function is developed which links the real and imaginary parts of the modulated quantities. The superior performance of above algorithms is demonstrated by comparing them with the LS/MFT and popular predicting error method (PEM) through 200 Monte Carlo simulations. A model reduction problem is formulated with the AWLS/MFT algorithm, and comparisons are made via six examples with a variety of model reduction techniques, including the well-known balanced realization method. Here the AWLS/MFT algorithm manifests higher accuracy in almost all cases, and exhibits its unique flexibility and versatility. Armed with this model reduction, the AWLS/MFT algorithm is extended into MIMO transfer function system identification problems. The impact due to the discrepancy in bandwidths and gains among subsystem is explored through five examples. Finally, as a comprehensive application, the stability derivatives of the longitudinal and lateral dynamics of an F-18 aircraft are identified using physical flight data provided by NASA. A pole-constrained SIMO and MIMO AWLS/MFT algorithm is devised and analyzed. Monte Carlo simulations illustrate its high-noise rejecting properties. Utilizing the flight data, comparisons among different MFT algorithms are tabulated and the AWLS is found to be strongly favored in almost all facets.

PREVAIL: Predicting Recovery through Estimation and Visualization of Active and Incident Lesions.

PubMed

Dworkin, Jordan D; Sweeney, Elizabeth M; Schindler, Matthew K; Chahin, Salim; Reich, Daniel S; Shinohara, Russell T

2016-01-01

The goal of this study was to develop a model that integrates imaging and clinical information observed at lesion incidence for predicting the recovery of white matter lesions in multiple sclerosis (MS) patients. Demographic, clinical, and magnetic resonance imaging (MRI) data were obtained from 60 subjects with MS as part of a natural history study at the National Institute of Neurological Disorders and Stroke. A total of 401 lesions met the inclusion criteria and were used in the study. Imaging features were extracted from the intensity-normalized T1-weighted (T1w) and T2-weighted sequences as well as magnetization transfer ratio (MTR) sequence acquired at lesion incidence. T1w and MTR signatures were also extracted from images acquired one-year post-incidence. Imaging features were integrated with clinical and demographic data observed at lesion incidence to create statistical prediction models for long-term damage within the lesion. The performance of the T1w and MTR predictions was assessed in two ways: first, the predictive accuracy was measured quantitatively using leave-one-lesion-out cross-validated (CV) mean-squared predictive error. Then, to assess the prediction performance from the perspective of expert clinicians, three board-certified MS clinicians were asked to individually score how similar the CV model-predicted one-year appearance was to the true one-year appearance for a random sample of 100 lesions. The cross-validated root-mean-square predictive error was 0.95 for normalized T1w and 0.064 for MTR, compared to the estimated measurement errors of 0.48 and 0.078 respectively. The three expert raters agreed that T1w and MTR predictions closely resembled the true one-year follow-up appearance of the lesions in both degree and pattern of recovery within lesions. This study demonstrates that by using only information from a single visit at incidence, we can predict how a new lesion will recover using relatively simple statistical techniques. The potential to visualize the likely course of recovery has implications for clinical decision-making, as well as trial enrichment.

Cooperation of a Dissatisfied Adaptive Prisoner's Dilemma in Spatial Structures

NASA Astrophysics Data System (ADS)

Zhang, Wen; Li, Yao-Sheng; Du, Peng; Xu, Chen

2013-10-01

We study the cooperative behavior of a dissatisfied adaptive prisoner's dilemma via a pair updating rule. We compare two kinds of relationship among the competing agents, one is the well-mixed population and the other is the two-dimensional square lattice. It is found that the cooperation emerges in both the cases and the frequency of cooperation is enhanced in the square lattice. Though it is impossible for the cooperators to have a higher average payoff than that of the defectors in the well-mixed case, the cooperators in the spatial square lattice could have higher average payoffs in certain regions of the game parameters. We theoretically analyze the well-mixed case exactly and the square lattice by pair approximation. The theoretic results are in agreement with the simulation data.

A finite element model for tides and resonance along the north coast of British Columbia

NASA Astrophysics Data System (ADS)

Foreman, M. G. G.; Henry, R. F.; Walters, R. A.; Ballantyne, V. A.

1993-02-01

A finite element, barotropic, tidal model is developed for the north coast of British Columbia. The model is run with eight tidal constituents and the results are compared with the Flather (1987) finite difference model, and with extensive tide gauge and current meter observations. Although the tidal potential, Earth tide, and loading tide are included in the forcing, their inclusion is shown to change the largest M2 amplitudes by only 2.5% and the largest K1 amplitudes by less than 1%. Root mean square differences between observed and calculated sea level amplitudes and phases are within 1.9 cm and 2.9° for all but one constituent, but the model currents do not in general, compare as favourably. The barotropic currents observed in Hecate Strait are reproduced well, but elsewhere evidence is shown that model inaccuracies are due to baroclinic effects. Tidal residual currents calculated by the model suggest the existence of eddies off the tip of Cape St. James, Cape Chacon, and around Goose Island and Learmonth Banks. The shallow water constituents in Hecate Strait are shown to have significant contributions from the constructive interference of signals propagating into Dixon Entrance and Queen Charlotte Sound. Using the model, the longest resonant period of the system is estimated to be 7.6 hours with an energy dissipation parameter, Q, of 9.5.

Point-particle effective field theory I: classical renormalization and the inverse-square potential

NASA Astrophysics Data System (ADS)

Burgess, C. P.; Hayman, Peter; Williams, M.; Zalavári, László

2017-04-01

Singular potentials (the inverse-square potential, for example) arise in many situations and their quantum treatment leads to well-known ambiguities in choosing boundary conditions for the wave-function at the position of the potential's singularity. These ambiguities are usually resolved by developing a self-adjoint extension of the original prob-lem; a non-unique procedure that leaves undetermined which extension should apply in specific physical systems. We take the guesswork out of this picture by using techniques of effective field theory to derive the required boundary conditions at the origin in terms of the effective point-particle action describing the physics of the source. In this picture ambiguities in boundary conditions boil down to the allowed choices for the source action, but casting them in terms of an action provides a physical criterion for their determination. The resulting extension is self-adjoint if the source action is real (and involves no new degrees of freedom), and not otherwise (as can also happen for reasonable systems). We show how this effective-field picture provides a simple framework for understanding well-known renormalization effects that arise in these systems, including how renormalization-group techniques can resum non-perturbative interactions that often arise, particularly for non-relativistic applications. In particular we argue why the low-energy effective theory tends to produce a universal RG flow of this type and describe how this can lead to the phenomenon of reaction catalysis, in which physical quantities (like scattering cross sections) can sometimes be surprisingly large compared to the underlying scales of the source in question. We comment in passing on the possible relevance of these observations to the phenomenon of the catalysis of baryon-number violation by scattering from magnetic monopoles.

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

Morgan, C.D.; Allison, M.L.

The Bluebell field is productive from the Tertiary lower Green River and Wasatch Formations of the Uinta Basin, Utah. The productive interval consists of thousands of feet of interbedded fractured clastic and carbonate beds deposited in a fluvial-dominated lacustrine environment. Wells in the Bluebell field are typically completed by perforating 40 or more beds over 1,000 to 3,000 vertical feet (300-900 m), then stimulating the entire interval. This completion technique is believed to leave many potentially productive beds damaged and/or untreated, while allowing water-bearing and low-pressure (thief) zones to communicate with the wellbore. Geologic and engineering characterization has been usedmore » to define improved completion techniques. A two-year characterization study involved detailed examination of outcrop, core, well logs, surface and subsurface fractures, produced oil-field waters, engineering parameters of the two demonstration wells, and analysis of past completion techniques and effectiveness. The characterization study resulted in recommendations for improved completion techniques and a field-demonstration program to test those techniques. The results of the characterization study and the proposed demonstration program are discussed in the second annual technical progress report. The operator of the wells was unable to begin the field demonstration this project year (October 1, 1995 to September 20, 1996). Correlation and thickness mapping of individual beds in the Wasatch Formation was completed and resulted in a. series of maps of each of the individual beds. These data were used in constructing the reservoir models. Non-fractured and fractured geostatistical models and reservoir simulations were generated for a 20-square-mile (51.8-km{sup 2}) portion of the Bluebell field. The modeling provides insights into the effects of fracture porosity and permeability in the Green River and Wasatch reservoirs.« less

Analyzing the effect of carbon fiber reinforced polymer on the crashworthiness of aluminum square hollow beam for crash box application

NASA Astrophysics Data System (ADS)

Raman, R.; Jayanth, K.; Sarkar, I.; Ravi, K.

2017-11-01

Crashworthiness of a material is a measure of its ability to absorb energy during a crash. A well-designed crash box is instrumental in protecting the costly vehicle components. A square, hollow, hybrid beam of aluminum/CFRP was subjected to dynamic axial load to analyze the effect of five different lay-up sequences on its crashworthiness. The beam was placed between two plates. Boundary conditions were imposed on them to simulate a frontal body crash test model. Modeling and dynamic analysis of composite structures was done on ABAQUS. Different orientation of carbon fibers varies the crashworthiness of the hybrid beam. Addition of CFRP layer showed clear improvement in specific energy absorption and crush force efficiency compared to pure aluminum beam. Two layers of CFRP oriented at 90° on Aluminum showed 52% increase in CFE.

Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride.

PubMed

Katsarov, Plamen; Gergov, Georgi; Alin, Aylin; Pilicheva, Bissera; Al-Degs, Yahya; Simeonov, Vasil; Kassarova, Margarita

2018-03-01

The prediction power of partial least squares (PLS) and multivariate curve resolution-alternating least squares (MCR-ALS) methods have been studied for simultaneous quantitative analysis of the binary drug combination - doxylamine succinate and pyridoxine hydrochloride. Analysis of first-order UV overlapped spectra was performed using different PLS models - classical PLS1 and PLS2 as well as partial robust M-regression (PRM). These linear models were compared to MCR-ALS with equality and correlation constraints (MCR-ALS-CC). All techniques operated within the full spectral region and extracted maximum information for the drugs analysed. The developed chemometric methods were validated on external sample sets and were applied to the analyses of pharmaceutical formulations. The obtained statistical parameters were satisfactory for calibration and validation sets. All developed methods can be successfully applied for simultaneous spectrophotometric determination of doxylamine and pyridoxine both in laboratory-prepared mixtures and commercial dosage forms.

Geophysical methods for locating abandoned wells

USGS Publications Warehouse

Frischknecht, Frank C.; Muth, L.; Grette, R.; Buckley, T.; Kornegay, B.

1983-01-01

A preliminary study of the feasibility of using geophysical exploration methods to locate abandoned wells containing steel casing indicated that magnetic methods promise to be effective and that some electrical techniques might be useful as auxiliary methods. Ground magnetic measurements made in the vicinity of several known cased wells yielded total field anomalies with peak values ranging from about 1,500 to 6,000 gammas. The anomalies measured on the ground are very narrow and, considering noise due to other cultural and geologic sources, a line spacing on the order of 50 feet (15.2 m) would be necessary to locate all casings in the test area. The mathematical model used to represent a casing was a set of magnetic pole pairs. By use of a non-linear least squares curve fitting (inversion) program, model parameters which characterize each test casing were determined. The position and strength of the uppermost pole was usually well resolved. The parameters of lower poles were not as well resolved but it appears that the results are adequate for predicting the anomalies which would be observed at aircraft altitudes. Modeling based on the parameters determined from the ground data indicates that all of the test casings could be detected by airborne measurements made at heights of 150 to 200 feet (45.7-61.0 m) above the ground, provided lines spaced as closely as 330 feet (100 m) were used and provided noise due to other cultural and geologic sources is not very large. Given the noise levels of currently available equipment and assuming very low magnetic gradients due to geologic sources, the detection range for total field measurements is greater than that for measurements of the horizontal or vertical gradient of the total intensity. Electrical self-potential anomalies were found to be associated with most of the casings where measurements were made. However, the anomalies tend to be very narrow and, in several cases, they are comparable in magnitude to other small anomalies which are not directly associated with casings. Measurements made with a terrain conductivity meter and slingram system were negative. However, from other work it is known that electrical resistivity and induced polarization measurements can be influenced significantly by the presence of a casing. It is concluded that detailed ground magnetic surveys would be effective in locating casings within relatively small areas. It would be very costly to cover large areas with ground surveys but it appears that airborne surveys may be a cost-effective means of locating wells when the search area is on the order of a few square miles or more. Also, airborne methods could be used in some areas where access to the area on the ground is difficult or impossible.

Kinklike structures in models of the Dirac-Born-Infeld type

NASA Astrophysics Data System (ADS)

Bazeia, D.; Lima, Elisama E. M.; Losano, L.

2018-01-01

The present work investigates several models of a single real scalar field, engendering kinetic term of the Dirac-Born- Infeld type. Such theories introduce nonlinearities to the kinetic part of the Lagrangian, which presents a square root restricting the field evolution and including additional powers in derivatives of the scalar field, controlled by a real parameter. In order to obtain topological solutions analytically, we propose a first-order framework that simplifies the equation of motion ensuring solutions that are linearly stable. This is implemented using the deformation method, and we introduce examples presenting two categories of potentials, one having polynomial interactions and the other with nonpolynomial interactions. We also explore how the Dirac-Born-Infeld kinetic term affects the properties of the solutions. In particular, we note that the kinklike solutions are similar to the ones obtained through models with standard kinetic term and canonical potential, but their energy densities and stability potentials vary according to the parameter introduced to control the new models.

Performance of the Generalized S-X[squared] Item Fit Index for the Graded Response Model

ERIC Educational Resources Information Center

Kang, Taehoon; Chen, Troy T.

2011-01-01

The utility of Orlando and Thissen's ("2000", "2003") S-X[squared] fit index was extended to the model-fit analysis of the graded response model (GRM). The performance of a modified S-X[squared] in assessing item-fit of the GRM was investigated in light of empirical Type I error rates and power with a simulation study having…

A comparison of monthly precipitation point estimates at 6 locations in Iran using integration of soft computing methods and GARCH time series model

NASA Astrophysics Data System (ADS)

Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

2017-11-01

Precipitation plays an important role in determining the climate of a region. Precise estimation of precipitation is required to manage and plan water resources, as well as other related applications such as hydrology, climatology, meteorology and agriculture. Time series of hydrologic variables such as precipitation are composed of deterministic and stochastic parts. Despite this fact, the stochastic part of the precipitation data is not usually considered in modeling of precipitation process. As an innovation, the present study introduces three new hybrid models by integrating soft computing methods including multivariate adaptive regression splines (MARS), Bayesian networks (BN) and gene expression programming (GEP) with a time series model, namely generalized autoregressive conditional heteroscedasticity (GARCH) for modeling of the monthly precipitation. For this purpose, the deterministic (obtained by soft computing methods) and stochastic (obtained by GARCH time series model) parts are combined with each other. To carry out this research, monthly precipitation data of Babolsar, Bandar Anzali, Gorgan, Ramsar, Tehran and Urmia stations with different climates in Iran were used during the period of 1965-2014. Root mean square error (RMSE), relative root mean square error (RRMSE), mean absolute error (MAE) and determination coefficient (R2) were employed to evaluate the performance of conventional/single MARS, BN and GEP, as well as the proposed MARS-GARCH, BN-GARCH and GEP-GARCH hybrid models. It was found that the proposed novel models are more precise than single MARS, BN and GEP models. Overall, MARS-GARCH and BN-GARCH models yielded better accuracy than GEP-GARCH. The results of the present study confirmed the suitability of proposed methodology for precise modeling of precipitation.

General background conditions for K-bounce and adiabaticity

NASA Astrophysics Data System (ADS)

Romano, Antonio Enea

2017-03-01

We study the background conditions for a bounce uniquely driven by a single scalar field model with a generalized kinetic term K( X), without any additional matter field. At the background level we impose the existence of two turning points where the derivative of the Hubble parameter H changes sign and of a bounce point where the Hubble parameter vanishes. We find the conditions for K( X) and the potential which ensure the above requirements. We then give the examples of two models constructed according to these conditions. One is based on a quadratic K( X), and the other on a K( X) which is avoiding divergences of the second time derivative of the scalar field, which may otherwise occur. An appropriate choice of the initial conditions can lead to a sequence of consecutive bounces, or oscillations of H. In the region where these models have a constant potential they are adiabatic on any scale and because of this they may not conserve curvature perturbations on super-horizon scales. While at the perturbation level one class of models is free from ghosts and singularities of the classical equations of motion, in general gradient instabilities are present around the bounce time, because the sign of the squared speed of sound is opposite to the sign of the time derivative of H. We discuss how this kind of instabilities could be avoided by modifying the Lagrangian by introducing Galilean terms in order to prevent a negative squared speed of sound around the bounce.

Anisotropic k-essence cosmologies

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

Chimento, Luis P.; Forte, Monica

We investigate a Bianchi type-I cosmology with k-essence and find the set of models which dissipate the initial anisotropy. There are cosmological models with extended tachyon fields and k-essence having a constant barotropic index. We obtain the conditions leading to a regular bounce of the average geometry and the residual anisotropy on the bounce. For constant potential, we develop purely kinetic k-essence models which are dust dominated in their early stages, dissipate the initial anisotropy, and end in a stable de Sitter accelerated expansion scenario. We show that linear k-field and polynomial kinetic function models evolve asymptotically to Friedmann-Robertson-Walker cosmologies.more » The linear case is compatible with an asymptotic potential interpolating between V{sub l}{proportional_to}{phi}{sup -{gamma}{sub l}}, in the shear dominated regime, and V{sub l}{proportional_to}{phi}{sup -2} at late time. In the polynomial case, the general solution contains cosmological models with an oscillatory average geometry. For linear k-essence, we find the general solution in the Bianchi type-I cosmology when the k field is driven by an inverse square potential. This model shares the same geometry as a quintessence field driven by an exponential potential.« less

Self-consistent phonon theory of the crystallization and elasticity of attractive hard spheres.

PubMed

Shin, Homin; Schweizer, Kenneth S

2013-02-28

We propose an Einstein-solid, self-consistent phonon theory for the crystal phase of hard spheres that interact via short-range attractions. The approach is first tested against the known behavior of hard spheres, and then applied to homogeneous particles that interact via short-range square well attractions and the Baxter adhesive hard sphere model. Given the crystal symmetry, packing fraction, and strength and range of attractive interactions, an effective harmonic potential experienced by a particle confined to its Wigner-Seitz cell and corresponding mean square vibrational amplitude are self-consistently calculated. The crystal free energy is then computed and, using separate information about the fluid phase free energy, phase diagrams constructed, including a first-order solid-solid phase transition and its associated critical point. The simple theory qualitatively captures all the many distinctive features of the phase diagram (critical and triple point, crystal-fluid re-entrancy, low-density coexistence curve) as a function of attraction range, and overall is in good semi-quantitative agreement with simulation. Knowledge of the particle localization length allows the crystal shear modulus to be estimated based on elementary ideas. Excellent predictions are obtained for the hard sphere crystal. Expanded and condensed face-centered cubic crystals are found to have qualitatively different elastic responses to varying attraction strength or temperature. As temperature increases, the expanded entropic solid stiffens, while the energy-controlled, fully-bonded dense solid softens.

An Improved Incremental Learning Approach for KPI Prognosis of Dynamic Fuel Cell System.

PubMed

Yin, Shen; Xie, Xiaochen; Lam, James; Cheung, Kie Chung; Gao, Huijun

2016-12-01

The key performance indicator (KPI) has an important practical value with respect to the product quality and economic benefits for modern industry. To cope with the KPI prognosis issue under nonlinear conditions, this paper presents an improved incremental learning approach based on available process measurements. The proposed approach takes advantage of the algorithm overlapping of locally weighted projection regression (LWPR) and partial least squares (PLS), implementing the PLS-based prognosis in each locally linear model produced by the incremental learning process of LWPR. The global prognosis results including KPI prediction and process monitoring are obtained from the corresponding normalized weighted means of all the local models. The statistical indicators for prognosis are enhanced as well by the design of novel KPI-related and KPI-unrelated statistics with suitable control limits for non-Gaussian data. For application-oriented purpose, the process measurements from real datasets of a proton exchange membrane fuel cell system are employed to demonstrate the effectiveness of KPI prognosis. The proposed approach is finally extended to a long-term voltage prediction for potential reference of further fuel cell applications.

Statistical Mechanical Model for Adsorption Coupled with SAFT-VR Mie Equation of State.

PubMed

Franco, Luís F M; Economou, Ioannis G; Castier, Marcelo

2017-10-24

We extend the SAFT-VR Mie equation of state to calculate adsorption isotherms by considering explicitly the residual energy due to the confinement effect. Assuming a square-well potential for the fluid-solid interactions, the structure imposed by the fluid-solid interface is calculated using two different approaches: an empirical expression proposed by Travalloni et al. ( Chem. Eng. Sci. 65 , 3088 - 3099 , 2010 ), and a new theoretical expression derived by applying the mean value theorem. Adopting the SAFT-VR Mie ( Lafitte et al. J. Chem. Phys. , 139 , 154504 , 2013 ) equation of state to describe the fluid-fluid interactions, and solving the phase equilibrium criteria, we calculate adsorption isotherms for light hydrocarbons adsorbed in a carbon molecular sieve and for carbon dioxide, nitrogen, and water adsorbed in a zeolite. Good results are obtained from the model using either approach. Nonetheless, the theoretical expression seems to correlate better the experimental data than the empirical one, possibly implying that a more reliable way to describe the structure ensures a better description of the thermodynamic behavior.

Electrode Coverage Optimization for Piezoelectric Energy Harvesting from Tip Excitation

PubMed Central

Chen, Guangzhu; Bai, Nan

2018-01-01

Piezoelectric energy harvesting using cantilever-type structures has been extensively investigated due to its potential application in providing power supplies for wireless sensor networks, but the low output power has been a bottleneck for its further commercialization. To improve the power conversion capability, a piezoelectric beam with different electrode coverage ratios is studied theoretically and experimentally in this paper. A distributed-parameter theoretical model is established for a bimorph piezoelectric beam with the consideration of the electrode coverage area. The impact of the electrode coverage on the capacitance, the output power and the optimal load resistance are analyzed, showing that the piezoelectric beam has the best performance with an electrode coverage of 66.1%. An experimental study was then carried out to validate the theoretical results using a piezoelectric beam fabricated with segmented electrodes. The experimental results fit well with the theoretical model. A 12% improvement on the Root-Mean-Square (RMS) output power was achieved with the optimized electrode converge ratio (66.1%). This work provides a simple approach to utilizing piezoelectric beams in a more efficient way. PMID:29518934

Visible micro-Raman spectroscopy for determining glucose content in beverage industry.

PubMed

Delfino, I; Camerlingo, C; Portaccio, M; Ventura, B Della; Mita, L; Mita, D G; Lepore, M

2011-07-15

The potential of Raman spectroscopy with excitation in the visible as a tool for quantitative determination of single components in food industry products was investigated by focusing the attention on glucose content in commercial sport drinks. At this aim, micro-Raman spectra in the 600-1600cm(-1) wavenumber shift region of four sport drinks were recorded, showing well defined and separated vibrational fingerprints of the various contained sugars (glucose, fructose and sucrose). By profiting of the spectral separation of some peculiar peaks, glucose content was quantified by using a multivariate statistical analysis based on the interval Partial Least Square (iPLS) approach. The iPLS model needed for data analysis procedure was built by using glucose aqueous solutions at known sugar concentrations as calibration data. This model was then applied to sport drink spectra and gave predicted glucose concentrations in good agreement with the values obtained by using a biochemical assay. These results represent a significant step towards the development of a fast and simple method for the on-line glucose quantification in products of food and beverage industry. Copyright © 2011 Elsevier Ltd. All rights reserved.

Urinary metabonomics elucidate the therapeutic mechanism of Orthosiphon stamineus in mouse crystal-induced kidney injury.

PubMed

Gao, Songyan; Chen, Wei; Peng, Zhongjiang; Li, Na; Su, Li; Lv, Diya; Li, Ling; Lin, Qishan; Dong, Xin; Guo, Zhiyong; Lou, Ziyang

2015-05-26

Orthosiphon stamineus (OS), a traditional Chinese herb, is often used for promoting urination and treating nephrolithiasis. Urolithiasis is a major worldwide public health burden due to its high incidence of recurrence and damage to renal function. However, the etiology for urolithiasis is not well understood. Metabonomics, the systematic study of small molecule metabolites present in biological samples, has become a valid and powerful tool for understanding disease phenotypes. In this study, a urinary metabolic profiling analysis was performed in a mouse model of renal calcium oxalate crystal deposition to identify potential biomarkers for crystal-induced renal damage and the anti-crystal mechanism of OS. Thirty six mice were randomly divided into six groups including Saline, Crystal, Cystone and OS at dosages of 0.5g/kg, 1g/kg, and 2g/kg. A metabonomics approach using ultra-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) was developed to perform the urinary metabolic profiling analysis. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were utilized to identify differences between the metabolic profiles of mice in the saline control group and crystal group. Using partial least squares-discriminant analysis, 30 metabolites were identified as potential biomarkers of crystal-induced renal damage. Most of them were primarily involved in amino acid metabolism, taurine and hypotaurine metabolism, purine metabolism, and the citrate cycle (TCA). After the treatment with OS, the levels of 20 biomarkers had returned to the levels of the control samples. Our results suggest that OS has a protective effect for mice with crystal-induced kidney injury via the regulation of multiple metabolic pathways primarily involving amino acid, energy and choline metabolism. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

In-line Fourier-transform infrared spectroscopy as a versatile process analytical technology for preparative protein chromatography.

PubMed

Großhans, Steffen; Rüdt, Matthias; Sanden, Adrian; Brestrich, Nina; Morgenstern, Josefine; Heissler, Stefan; Hubbuch, Jürgen

2018-04-27

Fourier-transform infrared spectroscopy (FTIR) is a well-established spectroscopic method in the analysis of small molecules and protein secondary structure. However, FTIR is not commonly applied for in-line monitoring of protein chromatography. Here, the potential of in-line FTIR as a process analytical technology (PAT) in downstream processing was investigated in three case studies addressing the limits of currently applied spectroscopic PAT methods. A first case study exploited the secondary structural differences of monoclonal antibodies (mAbs) and lysozyme to selectively quantify the two proteins with partial least squares regression (PLS) giving root mean square errors of cross validation (RMSECV) of 2.42 g/l and 1.67 g/l, respectively. The corresponding Q 2 values are 0.92 and, respectively, 0.99, indicating robust models in the calibration range. Second, a process separating lysozyme and PEGylated lysozyme species was monitored giving an estimate of the PEGylation degree of currently eluting species with RMSECV of 2.35 g/l for lysozyme and 1.24 g/l for PEG with Q 2 of 0.96 and 0.94, respectively. Finally, Triton X-100 was added to a feed of lysozyme as a typical process-related impurity. It was shown that the species could be selectively quantified from the FTIR 3D field without PLS calibration. In summary, the proposed PAT tool has the potential to be used as a versatile option for monitoring protein chromatography. It may help to achieve a more complete implementation of the PAT initiative by mitigating limitations of currently used techniques. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms.

PubMed

Tang, Jie; Nett, Brian E; Chen, Guang-Hong

2009-10-07

Of all available reconstruction methods, statistical iterative reconstruction algorithms appear particularly promising since they enable accurate physical noise modeling. The newly developed compressive sampling/compressed sensing (CS) algorithm has shown the potential to accurately reconstruct images from highly undersampled data. The CS algorithm can be implemented in the statistical reconstruction framework as well. In this study, we compared the performance of two standard statistical reconstruction algorithms (penalized weighted least squares and q-GGMRF) to the CS algorithm. In assessing the image quality using these iterative reconstructions, it is critical to utilize realistic background anatomy as the reconstruction results are object dependent. A cadaver head was scanned on a Varian Trilogy system at different dose levels. Several figures of merit including the relative root mean square error and a quality factor which accounts for the noise performance and the spatial resolution were introduced to objectively evaluate reconstruction performance. A comparison is presented between the three algorithms for a constant undersampling factor comparing different algorithms at several dose levels. To facilitate this comparison, the original CS method was formulated in the framework of the statistical image reconstruction algorithms. Important conclusions of the measurements from our studies are that (1) for realistic neuro-anatomy, over 100 projections are required to avoid streak artifacts in the reconstructed images even with CS reconstruction, (2) regardless of the algorithm employed, it is beneficial to distribute the total dose to more views as long as each view remains quantum noise limited and (3) the total variation-based CS method is not appropriate for very low dose levels because while it can mitigate streaking artifacts, the images exhibit patchy behavior, which is potentially harmful for medical diagnosis.

Error propagation of partial least squares for parameters optimization in NIR modeling.

PubMed

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-05

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.

Error propagation of partial least squares for parameters optimization in NIR modeling

NASA Astrophysics Data System (ADS)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-01

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.

Hydrogeology of well-field areas near Tampa, Florida; Phase I, development and documentation of a two-dimensional finite-difference model for simulation of steady-state ground-water flow

USGS Publications Warehouse

Hutchinson, C.B.; Johnson, Dale M.; Gerhart, James M.

1981-01-01

A two-dimensional finite-difference model was developed for simulation of steady-state ground-water flow in the Floridan aquifer throughout a 932-square-mile area, which contains nine municipal well fields. The overlying surficial aquifer contains a constant-head water table and is coupled to the Floridan aquifer by a leakage term that represents flow through a confining layer separating the two aquifers. Under the steady-state condition, all storage terms are set to zero. Utilization of the head-controlled flux condition allows head and flow to vary at the model-grid boundaries. Procedures are described to calibrate the model, test its sensitivity to input-parameter errors, and verify its accuracy for predictive purposes. Also included are attachments that describe setting up and running the model. An example model-interrogation run shows anticipated drawdowns that should result from pumping at the newly constructed Cross Bar Ranch and Morris Bridge well fields. (USGS)

Rabbit Feces as Feed for Ruminants and as an Energy Source.

PubMed

Peiretti, Pier Giorgio; Tassone, Sonia; Gai, Francesco; Gasco, Laura; Masoero, Giorgio

2014-12-05

There are prospects for using novel feeds from various sources to provide ruminants with alternative sources of protein and energy such as by-products, and animal wastes. Rabbit feces are a concentrated source of fiber and could have commercial potential both as input biomass in anaerobic processes for biogas production, as well as a fibrous source for ruminal degradation. The aims of this work were to assess the potential as ruminant feeding and as biogas production of rabbit feces, in comparison with 12 crops. The chemical composition and the potential and experimental in vitro true digestibility (IVTD) and neutral detergent fiber digestibility (NDFD) of 148 feces samples were determined by using chemical methods, Daisy system digestibility and/or NIRS predictions. The average biomethane potential (BMP) was 286 ± 10 lCH4/kg SV with -4% vs. the crops average. Milk forage unit (milk FU), IVTD and NDFD of feces were 0.54 ± 0.06 milk FU/kg DM, 74% ± 3% and 50% ± 5%, respectively, with comparisons of -19%, -11% and -24% vs. the crops average. Reconstruction of the potential values based on the chemical constituents but using the crop partial least square model well agreed with the NIRS calibrations and cross-validation. In a global NIRS calibration of the feces and crops the relative predicted deviation for IVTD, NDFD and milk FU were 3.1, 2.9 and 2.6, respectively, and only 1.5 for BMP. Running the Daisy system for rabbit feces in rumen fluid gave some inconsistencies, weakened the functional relationships, and appeared not to be correlated with the potential values of IVTD and NDFD. Nevertheless, the energetic potential of feces appears to be similar to some conventional crops at different degrees of maturity. Thus we conclude that rabbit feces has potential value as a ruminant feed and for biogas production.

A total variation diminishing finite difference algorithm for sonic boom propagation models

NASA Technical Reports Server (NTRS)

Sparrow, Victor W.

1993-01-01

It is difficult to accurately model the rise phases of sonic boom waveforms with traditional finite difference algorithms because of finite difference phase dispersion. This paper introduces the concept of a total variation diminishing (TVD) finite difference method as a tool for accurately modeling the rise phases of sonic booms. A standard second order finite difference algorithm and its TVD modified counterpart are both applied to the one-way propagation of a square pulse. The TVD method clearly outperforms the non-TVD method, showing great potential as a new computational tool in the analysis of sonic boom propagation.

Speckle noise removal applied to ultrasound image of carotid artery based on total least squares model.

PubMed

Yang, Lei; Lu, Jun; Dai, Ming; Ren, Li-Jie; Liu, Wei-Zong; Li, Zhen-Zhou; Gong, Xue-Hao

2016-10-06

An ultrasonic image speckle noise removal method by using total least squares model is proposed and applied onto images of cardiovascular structures such as the carotid artery. On the basis of the least squares principle, the related principle of minimum square method is applied to cardiac ultrasound image speckle noise removal process to establish the model of total least squares, orthogonal projection transformation processing is utilized for the output of the model, and the denoising processing for the cardiac ultrasound image speckle noise is realized. Experimental results show that the improved algorithm can greatly improve the resolution of the image, and meet the needs of clinical medical diagnosis and treatment of the cardiovascular system for the head and neck. Furthermore, the success in imaging of carotid arteries has strong implications in neurological complications such as stroke.

Modeling the Afferent Dynamics of the Baroreflex Control System

PubMed Central

Mahdi, Adam; Sturdy, Jacob; Ottesen, Johnny T.; Olufsen, Mette S.

2013-01-01

In this study we develop a modeling framework for predicting baroreceptor firing rate as a function of blood pressure. We test models within this framework both quantitatively and qualitatively using data from rats. The models describe three components: arterial wall deformation, stimulation of mechanoreceptors located in the BR nerve-endings, and modulation of the action potential frequency. The three sub-systems are modeled individually following well-established biological principles. The first submodel, predicting arterial wall deformation, uses blood pressure as an input and outputs circumferential strain. The mechanoreceptor stimulation model, uses circumferential strain as an input, predicting receptor deformation as an output. Finally, the neural model takes receptor deformation as an input predicting the BR firing rate as an output. Our results show that nonlinear dependence of firing rate on pressure can be accounted for by taking into account the nonlinear elastic properties of the artery wall. This was observed when testing the models using multiple experiments with a single set of parameters. We find that to model the response to a square pressure stimulus, giving rise to post-excitatory depression, it is necessary to include an integrate-and-fire model, which allows the firing rate to cease when the stimulus falls below a given threshold. We show that our modeling framework in combination with sensitivity analysis and parameter estimation can be used to test and compare models. Finally, we demonstrate that our preferred model can exhibit all known dynamics and that it is advantageous to combine qualitative and quantitative analysis methods. PMID:24348231

Firefly algorithm versus genetic algorithm as powerful variable selection tools and their effect on different multivariate calibration models in spectroscopy: A comparative study.

PubMed

Attia, Khalid A M; Nassar, Mohammed W I; El-Zeiny, Mohamed B; Serag, Ahmed

2017-01-05

For the first time, a new variable selection method based on swarm intelligence namely firefly algorithm is coupled with three different multivariate calibration models namely, concentration residual augmented classical least squares, artificial neural network and support vector regression in UV spectral data. A comparative study between the firefly algorithm and the well-known genetic algorithm was developed. The discussion revealed the superiority of using this new powerful algorithm over the well-known genetic algorithm. Moreover, different statistical tests were performed and no significant differences were found between all the models regarding their predictabilities. This ensures that simpler and faster models were obtained without any deterioration of the quality of the calibration. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluation of some random effects methodology applicable to bird ringing data

USGS Publications Warehouse

Burnham, K.P.; White, Gary C.

2002-01-01

Existing models for ring recovery and recapture data analysis treat temporal variations in annual survival probability (S) as fixed effects. Often there is no explainable structure to the temporal variation in S1,..., Sk; random effects can then be a useful model: Si = E(S) + ??i. Here, the temporal variation in survival probability is treated as random with average value E(??2) = ??2. This random effects model can now be fit in program MARK. Resultant inferences include point and interval estimation for process variation, ??2, estimation of E(S) and var (E??(S)) where the latter includes a component for ??2 as well as the traditional component for v??ar(S??\\S??). Furthermore, the random effects model leads to shrinkage estimates, Si, as improved (in mean square error) estimators of Si compared to the MLE, S??i, from the unrestricted time-effects model. Appropriate confidence intervals based on the Si are also provided. In addition, AIC has been generalized to random effects models. This paper presents results of a Monte Carlo evaluation of inference performance under the simple random effects model. Examined by simulation, under the simple one group Cormack-Jolly-Seber (CJS) model, are issues such as bias of ??s2, confidence interval coverage on ??2, coverage and mean square error comparisons for inference about Si based on shrinkage versus maximum likelihood estimators, and performance of AIC model selection over three models: Si ??? S (no effects), Si = E(S) + ??i (random effects), and S1,..., Sk (fixed effects). For the cases simulated, the random effects methods performed well and were uniformly better than fixed effects MLE for the Si.

Compatible Models of Carbon Content of Individual Trees on a Cunninghamia lanceolata Plantation in Fujian Province, China

PubMed Central

Zhuo, Lin; Tao, Hong; Wei, Hong; Chengzhen, Wu

2016-01-01

We tried to establish compatible carbon content models of individual trees for a Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantation from Fujian province in southeast China. In general, compatibility requires that the sum of components equal the whole tree, meaning that the sum of percentages calculated from component equations should equal 100%. Thus, we used multiple approaches to simulate carbon content in boles, branches, foliage leaves, roots and the whole individual trees. The approaches included (i) single optimal fitting (SOF), (ii) nonlinear adjustment in proportion (NAP) and (iii) nonlinear seemingly unrelated regression (NSUR). These approaches were used in combination with variables relating diameter at breast height (D) and tree height (H), such as D, D2H, DH and D&H (where D&H means two separate variables in bivariate model). Power, exponential and polynomial functions were tested as well as a new general function model was proposed by this study. Weighted least squares regression models were employed to eliminate heteroscedasticity. Model performances were evaluated by using mean residuals, residual variance, mean square error and the determination coefficient. The results indicated that models with two dimensional variables (DH, D2H and D&H) were always superior to those with a single variable (D). The D&H variable combination was found to be the most useful predictor. Of all the approaches, SOF could establish a single optimal model separately, but there were deviations in estimating results due to existing incompatibilities, while NAP and NSUR could ensure predictions compatibility. Simultaneously, we found that the new general model had better accuracy than others. In conclusion, we recommend that the new general model be used to estimate carbon content for Chinese fir and considered for other vegetation types as well. PMID:26982054

[Analysis of the impact of job characteristics and organizational support for workplace violence].

PubMed

Li, M L; Chen, P; Zeng, F H; Cui, Q L; Zeng, J; Zhao, X S; Li, Z N

2017-12-20

Objective: To analyze the effect of job characteristics and organizational support for workplace violence, explore the influence path and the theoretical model, and provide a theoretical basis for reducing workplace violence. Methods: Stratified random sampling was used to select 813 medical staff, conductors and bus drivers in Chongqing with a self-made questionnaire to investigate job characteristics, organization attitude toward workplace violence, workplace violence, fear of violence, workplace violence, etc from February to October, 2014. Amos 21.0 was used to analyze the path and to establish a theoretical model of workplace violence. Results: The odds ratio of work characteristics and organizational attitude to workplace violence were 6.033 and 0.669, respectively, and the path coefficients were 0.41 and-0.14, respectively ( P <0.05). The Fitting indexes of the model: Chi-square (χ(2)) =67.835, The ratio of the chi-square to the degree of freedom (χ(2)/df) =5.112, Good-of-fit index (GFI) =0.970, Adjusted good-of-fit index (AGFI) =0.945, Normed fit index (NFI) =0.923, Root mean square error of approximation (RMSEA) =0.071, Fit criterion (Fmin) =0.092, so the model fit well with the data. Conclusion: The job characteristic is a risk factor for workplace violence while organizational attitude is a protective factor for workplace violence, so changing the job characteristics and improving the enthusiasm of the organization to deal with workplace violence are conducive to reduce workplace violence and increase loyalty to the unit.

D Virtual Reconstruction of AN Urban Historical Space: a Consideration on the Method

NASA Astrophysics Data System (ADS)

Galizia, M.; Santagati, C.

2011-09-01

Urban historical spaces are often characterized by a variety of shapes, geometries, volumes, materials. Their virtual reconstruction requires a critical approach in terms of acquired data's density, timing optimization, final product's quality and slimness. The research team has focused its attention on the study on Francesco Neglia square (previously named Saint Thomas square) in Enna. This square is an urban space fronted by architectures which present historical and stylistic differences. For example you can find the Saint Thomas'church belfry (in aragounese-catalan stile dated XIV century) and the porch, the Anime Sante baroque's church (XVII century), Saint Mary of the Grace's nunnery (XVIII century) and as well as some civil buildings of minor importance built in the mid twentieth century. The research has compared two different modeling tools approaches: the first one is based on the construction of triangulated surfaces which are segmented and simplified; the second one is based on the detection of surfaces geometrical features, the extraction of the more significant profiles by using a software dedicated to the elaboration of cloud points and the subsequent mathematical reconstruction by using a 3d modelling software. The following step was aimed to process the virtual reconstruction of urban scene by assembling the single optimized models. This work highlighted the importance of the image of the operator and of its cultural contribution, essential to recognize geometries which generates surfaces in order to create high quality semantic models.

Detection and quantification of adulteration in sandalwood oil through near infrared spectroscopy.

PubMed

Kuriakose, Saji; Thankappan, Xavier; Joe, Hubert; Venkataraman, Venkateswaran

2010-10-01

The confirmation of authenticity of essential oils and the detection of adulteration are problems of increasing importance in the perfumes, pharmaceutical, flavor and fragrance industries. This is especially true for 'value added' products like sandalwood oil. A methodical study is conducted here to demonstrate the potential use of Near Infrared (NIR) spectroscopy along with multivariate calibration models like principal component regression (PCR) and partial least square regression (PLSR) as rapid analytical techniques for the qualitative and quantitative determination of adulterants in sandalwood oil. After suitable pre-processing of the NIR raw spectral data, the models are built-up by cross-validation. The lowest Root Mean Square Error of Cross-Validation and Calibration (RMSECV and RMSEC % v/v) are used as a decision supporting system to fix the optimal number of factors. The coefficient of determination (R(2)) and the Root Mean Square Error of Prediction (RMSEP % v/v) in the prediction sets are used as the evaluation parameters (R(2) = 0.9999 and RMSEP = 0.01355). The overall result leads to the conclusion that NIR spectroscopy with chemometric techniques could be successfully used as a rapid, simple, instant and non-destructive method for the detection of adulterants, even 1% of the low-grade oils, in the high quality form of sandalwood oil.