Time Extrapolation Research Articles

Temporally Coarse-Grained All-Atom Molecular Dynamics Achieved via Stochastic Padé Approximants.

A Padé approximant scheme for realizing the discrete-time evolution of the state of a many-atom system is introduced. This temporal coarse-graining scheme accounts for the underlying Newtonian physics and avoids the need for construction of spatially coarse-grained variables. Newtonian physics is incorporated through short molecular dynamics simulations at the beginning of each of the large coarse-grained timesteps. The balance between stochastic and coherent dynamics expressed by many-atom systems is captured via incorporation of the Ito formula into a Padé approximant for the time dependence of individual atom positions over large timesteps. Since the time for a many-atom system to express a characteristic ensemble of atomic velocity fluctuations is typically short relative to the characteristic time of large-scale atomic displacements, a computationally efficient and accurate temporal coarse-graining of the atom-resolved Newtonian dynamics is formulated, denoted all-atom Padé-Ito molecular dynamics (APIMD). Evolution of the system over a time step much longer than that required for standard molecular dynamics (MD) is achieved via incorporation of information from the short MD simulations into a Padé approximant extrapolation in time. The extrapolated atomic configuration is subjected to energy minimization and, when needed, thermal equilibration so as to avoid occasional unphysical close encounters deriving from the Padé approximant extrapolation and to represent configurations appropriate for the temperature of interest. APIMD is implemented and tested via comparison with traditional MD simulations of five phenomena: (1) pertussis toxin subunit deformation, (2) structural transition in a T = 1 capsid-like structure of HPV16 L1 protein, (3) coalescence of argon nanodroplets, and structural transitions in dialanine in (4) vacuum, and (5) water. Accuracy of APIMD is demonstrated using semimicroscopic descriptors (rmsd, radius of gyration, residue-residue contact maps, and densities) and the free energy. Significant computational acceleration relative to traditional molecular dynamics is illustrated.

Health economic evaluation of gene replacement therapies: methodological issues and recommendations

ABSTRACT Objective: To provide recommendations for addressing previously identified key challenges in health economic evaluations of Gene Replacement Therapies (GRTs), including: 1) the assessment of clinical effectiveness; 2) the valuation of health outcomes; 3) the time horizon and extrapolation of effects beyond trial duration; 4) the estimation of costs; 5) the selection of appropriate discount rates; 6) the incorporation of broader elements of value; and 7) affordability. Methods: A literature review on economic evaluations of GRT was performed. Interviews were conducted with 8 European and US health economic experts with experience in evaluations of GRT. Targeted literature reviews were conducted to investigate further potential solutions to specific challenges. Recommendations: Experts agreed on factors to be considered to ensure the acceptability of historical cohorts by HTA bodies. Existing prospective registries or, if not available, retrospective registries, may be used to analyse different disease trajectories and inform extrapolations. The importance of expert opinion due to limited data was acknowledged. Expert opinion should be obtained using structured elicitation techniques. Broader elements of value, beyond health gains directly related to treatment, can be considered through the application of a factor to inflate the quality-adjusted life years (QALYs) or a higher cost-effectiveness threshold. Additionally, the use of cost-benefit analysis and saved young life equivalents (SAVE) were proposed as alternatives to QALYs for the valuations of outcomes of GRT as they can incorporate broader elements of value and avoid problems of eliciting utilities for paediatric diseases. Conclusions: While some of the limitations of economic evaluations of GRT are inherent to limited clinical data and lack of experience with these treatments, others may be addressed by methodological research to be conducted by health economists.

Production of Various Types of Poultry in Bulgaria for the Period 2010-2018

Poultry farming has always been a major part of animal husbandry in every country. Bulgaria is no exception and has a long-standing tradition in the breeding and production of various types of poultry. In reality, our country was mainly producing chickens, laying hens and eggs in the beginning, but was also successful in the breeding of ducks, turkeys, geese, yurts and other feathered more extravagant species, such as quails, ostriches, pheasants, etc. The main purpose of this article is to analyze the production of different types of poultry in Bulgaria for a sufficiently long period of 9 years, to be able to predict trends and changes that may occur in different types of poultry in the country and to determine not only which ones shall have a leading role for specific regions in Bulgaria, but also the ways to increase their effective production in the direction of closing the production and sales cycle with poultry products processing and reaching the end customer. The article uses methods of situation analysis, time series analysis, induction, deduction, extrapolation, trend derivation and logical dependencies, method of adding value and creating a final product.

Modeling of dynamic delayed systems by using general runge-kutta methods

A system of differential equations with several variable delays is considered, which is a mathematical model of many technical processes with time delay. Most often, numerical Runge-Kutta methods and the Taylor series expansion by delay method are used to model such systems. Previously, Runge-Kutta methods were used for systems of differential equations with one variable delay. A generalization of the Runge-Kutta methods for systems of differential equations with a finite number of variable delays is obtained, which significantly expands the class of problems for which this method is applicable. Also, this method has advantages over the Taylor expansion method in terms of delay since it is applicable to systems with several variable delays, is convenient for programming, and has no restrictions on the value of delay. To generalize the Runge-Kutta methods for systems with delay, we used Runge-Kutta methods for systems of differential equations without delay in time and interpolation and extrapolation of the redistribution. The approximation properties of the generalization of Runge-Kutta methods for systems with delay are established. Namely, the connection between the approximation order of the Runge-Kutta methods for systems with delay and the approximation order of the Runge-Kutta methods for systems without delay and the approximation order of interpolation and extrapolation of the model history is shown. Thus, it was established that the approximation order of the Runge-Kutta method for a system with delay will be the minimum of the approximation orders of the Runge-Kutta method for a system without delay and the approximation order of interpolation and extrapolation of the model history will be increased by one. Based on this statement, it is concluded that if we use the Lagrange polynomial in the number of nodes that coincides with the approximation order of the Runge-Kutta method for a system without delay, then, with a sufficiently small step, the Runge-Kutta method for a system with delay retains the approximation order of the method Runge-Kutta without delay. Without limiting the step length when using the Euler method for extrapolating a solution, it was found that in this case the approximation order of the Runge-Kutta methods for a system with a delay of more than two.

Delay in diagnosing patients with right-sided glioblastoma induced by hemispheric-specific clinical presentation.

Cognitive functions are differentially represented in brain hemispheres. Aphasia is an "easy to recognize" symptom of diseases affecting the left side. In contrast, lesions in the right hemisphere cause subtle neuropsychological deficits such as neglect and anosognosia. We evaluated whether right-sided malignant brain tumors are on average larger at the time of first diagnosis as compared to left-sided tumors, and extrapolated the delay in diagnosing right-sided tumors compared to the left side. All first-ever diagnosed glioblastoma (GBM) patients between 2005 and 2012 were identified using our hospital-based prospective research registry. Baseline data, information on initial clinical presentation and imaging findings (including tumor volume) were collected. Extrapolation of time since tumor initiation was based on an established gompertzian growth model. We included 173 patients. Mean age of the study population was 58 ± 13years. Tumors located in the right hemisphere (n = 96) were larger as compared to tumors located in the left hemisphere (n = 77) (median 36.4mL [interquartile range 13.0-56.0; minimum 0.2, maximum 140.0] vs. 17.2mL [7.7-45.1mL; 0.4, 105.2]; p = 0.011). Right-sided tumors grew longer than left-sided tumors (378 ± 95days vs. 341 ± 74days; p = 0.006). Initial neuropsychological symptoms differed depending on the affected hemisphere. Right-hemispheric symptoms appear to be less clinically conspicuous resulting in a delayed diagnosis of GBM, which might be improved by raising awareness for the corresponding neuropsychological deficits. Whether our findings have prognostic implications needs to be evaluated in future studies.

Relationship between aged and vapor-deposited organic glasses: Secondary relaxations in methyl-m-toluate.

In situ interdigitated electrode broadband dielectric spectroscopy was used to characterize the excess wing relaxations in vapor-deposited and aged glasses of methyl-m-toluate (MMT, Tg = 170 K). MMT displays typical excess wing relaxations in dielectric spectra of its supercooled liquid and glasses. Physical vapor deposition produced glasses with degrees of suppression of the excess wing relaxation that varied systematically with deposition conditions, up to a maximum suppression of more than a factor of 3. The glass deposited at a relatively high temperature, 0.96 Tg (163 K), showed the same amount of suppression as that of a liquid-cooled glass aged to equilibrium at this temperature. The suppression of the excess wing relaxation was strongly correlated with the kinetic stability of the vapor-deposited glasses. Comparisons with aged MMT glasses allowed an estimate of the structural relaxation time of the vapor-deposited glasses. The dependence of the estimated structural relaxation times upon the substrate temperature was found to be stronger than Arrhenius but weaker than Vogel-Fulcher-Tammann dependence predicted from extrapolation of relaxation times in the supercooled liquid. Additionally, this work provides the first example of the separation of primary and secondary relaxations using physical vapor deposition.

Up/down acoustic wavefield decomposition using a single propagation and its application in reverse time migration

The separation of up- and downgoing wavefields is an important technique in the processing of multicomponent recorded data, propagating wavefields, and reverse time migration (RTM). Most of the previous methods for separating up/down propagating wavefields can be grouped according to their implementation strategy: a requirement to save time steps to perform Fourier transform over time or construction of the analytical wavefield through a solution of the wave equation twice (one for the source and another for the Hilbert-transformed source), in which both strategies have a high computational cost. For computing the analytical wavefield, we are proposing an alternative method based on the first-order partial equation in time and by just solving the wave equation once. Our strategy improves the computation of wavefield separation, and it can bring the causal imaging condition into practice. For time extrapolation, we are using the rapid expansion method to compute the wavefield and its first-order time derivative and then we can compute the analytical wavefield. By computing the analytical wavefield, we can, therefore, separate the wavefield into up- and downgoing components for each time step in an explicit way. Applications to synthetic models indicate that our method allows performing the wavefield decomposition similarly to the conventional method, as well as a potential application for the 3D case. For RTM applications, we can now use the causal imaging condition for several synthetic examples. Acoustic RTM up/down decomposition demonstrates that it can successfully remove the low-frequency noise, which is common in the typical crosscorrelation imaging condition, and it is usually removed by applying a Laplacian filter. Moreover, our method is efficient in terms of computational time when compared to RTM using an analytical wavefield computed by two propagations, and it is a little more costly than conventional RTM using the crosscorrelation imaging condition.

ECOLOGY OF NUTRITION AND PROMISING TRENDS IN PRODUCTION OF DIETARY FIBER BASED INSTANT FOODS

The article presents the development of a new formulation of instant noodles based on dietary fiber. Given the trend for functional foods that provide balanced nutrition, the enrichment of instant noodles with micronutrients is becoming increasingly important. The aim of the work was to study the content of dietary fiber in instant noodles with introduced inulin Fibruline XL, fiber SUPERCEL WF600, and methyl cellulose VIVAPUR MC A 4M. It was determined if dietary fiber was preserved after technological processing of the raw material. Buckwheat flour, which has a number of advantages in nutrient composition in comparison with wheat flour, was used as a raw material. Generally accepted and special methods of studying the properties of raw materials, semi-finished foodproducts and finished food products were used. Lipid content, nutritional and caloric values were determined. The effect of dietary fibers with different average lengths on the gluten complex of high grade wheat flour was studied. Organoleptic evaluation was made. The shelf life of the product was calculated using the Rancimat-743 device, with extrapolation of the induction time to room temperature and storage. As a result, we obtained a new, physiologically conditioned product having a balanced composition, low caloric content, and low fat content and enriched with dietary fibers and minerals.

Time Stable Reduced Order Modeling by an Enhanced Reduced Order Basis of the Turbulent and Incompressible 3D Navier–Stokes Equations

In the following paper, we consider the problem of constructing a time stable reduced order model of the 3D turbulent and incompressible Navier–Stokes equations. The lack of stability associated with the order reduction methods of the Navier–Stokes equations is a well-known problem and, in general, it is very difficult to account for different scales of a turbulent flow in the same reduced space. To remedy this problem, we propose a new stabilization technique based on an a priori enrichment of the classical proper orthogonal decomposition (POD) modes with dissipative modes associated with the gradient of the velocity fields. The main idea is to be able to do an a priori analysis of different modes in order to arrange a POD basis in a different way, which is defined by the enforcement of the energetic dissipative modes within the first orders of the reduced order basis. This enables us to model the production and the dissipation of the turbulent kinetic energy (TKE) in a separate fashion within the high ranked new velocity modes, hence to ensure good stability of the reduced order model. We show the importance of this a priori enrichment of the reduced basis, on a typical aeronautical injector with Reynolds number of 45,000. We demonstrate the capacity of this order reduction technique to recover large scale features for very long integration times (25 ms in our case). Moreover, the reduced order modeling (ROM) exhibits periodic fluctuations with a period of 2 . 2 ms corresponding to the time scale of the precessing vortex core (PVC) associated with this test case. We will end this paper by giving some prospects on the use of this stable reduced model in order to perform time extrapolation, that could be a strategy to study the limit cycle of the PVC.

Optimizing time-pickup algorithms in radiation detectors with a genetic algorithm

Pulse digitization at high rates has paved the way for the use of complex, non-standard algorithms, beyond the conventional constant fraction discriminator (CFD) option to obtain the time-stamps of gamma photons arriving to nuclear detectors. Detector pulses can be shaped with digital filters in digital signal processing (DSP) hardware or software, and timestamps can be derived by interpolating or extrapolating the acquired samples. Digitized pulses can be stored in a computer for off-line analysis allowing for many different algorithm variations to be tried on the same data. One difficulty is that the number of filters and parameters to be tuned in order to optimize the timing performance may become too large to be done by hand. For this, in this work we use a genetic algorithm to tune in-silico digital filters, digital time pickup algorithms and their associated parameters. The data set consisted of 500,000 pulses obtained from the last dynode of two ultrafast photomultiplier tubes (model R9779 by Hamamatsu) coupled to monolithic fast inorganic LaBr3(Ce) scintillators, in a truncated cone geometry 1.5×1×1.5” . With finely tuned conventional (CFD+TAC) timing electronics, a CRT of 155 ps (FWHM) for a 60Co source has been measured by our group, within the state of the art for detectors of this size. Our alternate digital, in-silico implementation of CFD+TAC, fine-tuned with the same parameters obtained during manual adjustment of the conventional DAQ and applied to pulses digitized at 5 GS/s and 14 bits of vertical resolution, reproduces the performance of the conventional DAQ. On the other hand, a genetic algorithm (GA) is employed to optimize digital recursive filters with up to 8 parameters, and different time-pickup strategies (upper level thresholding, CFD, time extrapolation). The same 500,000 pulses are employed for which the GA finds several families of filters outperforming the manually tuned algorithm by more than 10%.

The high accuracy conserved splitting domain decomposition scheme for solving the parabolic equations

Abstract In this paper, the high accuracy mass-conserved splitting domain decomposition method for solving the parabolic equations is proposed. In our scheme, the time extrapolation and local multi-point weighted average schemes are used to approximate the interface fluxes on interfaces of sub-domains, while the interior solutions are computed by one dimension high-order implicit schemes in sub-domains. The important feature is that the developed scheme keeps mass conservation and are of second-order convergent in time and fourth-order convergent in space. Numerical experiments confirm the convergence.

Testing the performance of field calibration techniques for low-cost gas sensors in new deployment locations: across a county line and across Colorado

Abstract. We assessed the performance of ambient ozone (O3) and carbon dioxide (CO2) sensor field calibration techniques when they were generated using data from one location and then applied to data collected at a new location. This was motivated by a previous study (Casey et al., 2018), which highlighted the importance of determining the extent to which field calibration regression models could be aided by relationships among atmospheric trace gases at a given training location, which may not hold if a model is applied to data collected in a new location. We also explored the sensitivity of these methods in response to the timing of field calibrations relative to deployment periods. Employing data from a number of field deployments in Colorado and New Mexico that spanned several years, we tested and compared the performance of field-calibrated sensors using both linear models (LMs) and artificial neural networks (ANNs) for regression. Sampling sites covered urban and rural–peri-urban areas and environments influenced by oil and gas production. We found that the best-performing model inputs and model type depended on circumstances associated with individual case studies, such as differing characteristics of local dominant emissions sources, relative timing of model training and application, and the extent of extrapolation outside of parameter space encompassed by model training. In agreement with findings from our previous study that was focused on data from a single location (Casey et al., 2018), ANNs remained more effective than LMs for a number of these case studies but there were some exceptions. For CO2 models, exceptions included case studies in which training data collection took place more than several months subsequent to the test data period. For O3 models, exceptions included case studies in which the characteristics of dominant local emissions sources (oil and gas vs. urban) were significantly different at model training and testing locations. Among models that were tailored to case studies on an individual basis, O3 ANNs performed better than O3 LMs in six out of seven case studies, while CO2 ANNs performed better than CO2 LMs in three out of five case studies. The performance of O3 models tended to be more sensitive to deployment location than to extrapolation in time, while the performance of CO2 models tended to be more sensitive to extrapolation in time than to deployment location. The performance of O3 ANN models benefited from the inclusion of several secondary metal-oxide-type sensors as inputs in five of seven case studies.

Voltage-Dependent Activation Energy Maps for Analytic Lifetime Modeling of NBTI Without Time Extrapolation

To enable MOSFETs lifetime extrapolation of up to 10 years, bias temperature instability (BTI) is commonly accelerated via increased stress voltage and increased temperature. We demonstrate that BTI can be described by a unique activation energy map including the voltage and temperature dependence of stress and recovery and use capture and emission time maps to model the time dynamics responsible for the threshold voltage shift of BTI. Based on this approach, we present a new measurement technique, further called temperature-accelerated measure-stress-measurements (TA-MSM) enabling lifetime modeling of BTI without any time extrapolation. We show the application of this technique to simulate standard qualification measurements, fast wafer-level reliability measurements as well as the degradation after ac and dc burn-in stress. In addition, we show that the TA-MSM technique is a valuable tool for the study of the permanent component and the recently discovered reverse recovery effect.

Оперативный прогноз МПЧ радиотрасс по текущим данным наклонного зондирования ионосферы непрерывным ЛЧМ-сигналом

We present a technique of MUF real-time forecast based on time extrapolation for maximum observed frequencies smoothed over a long-term forecast along a given path. We have validated the technique of fitting current data from the long-term forecast, using the OPEMI model, transmission curve method for short paths, and method of normal waves for long paths (over 2000 km). This technique has been tested using data obtained at the chirp sounding network of ISTP SB RAS during periods of strong and weak solar activity. The quality of the forecast has been found to significantly improve in comparison to the long-term forecast, with advance intervals of real-time forecast from 15 to 30 min. The sessions, in which the real-time forecast error is less than 10 % for 15-min advance interval, comprise from 67 to 96 % of all sessions depending on season and radio path orientation.

Real-time forecast of MUF for radio paths from current data obtained from oblique sounding with continuous chirp signal

We present a technique of MUF real-time forecast based on time extrapolation for maximum observed frequencies smoothed over a long-term forecast along a given path. We have validated the technique of fitting current data from the long-term forecast, using the OPEMI model, transmission curve method for short paths, and method of normal waves for long paths (over 2000 km). This technique has been tested using data obtained at the chirp sounding network of ISTP SB RAS during periods of strong and weak solar activity. The quality of the forecast has been found to significantly improve in comparison to the long-term forecast, with advance intervals of real-time forecast from 15 to 30 min. The sessions, in which the real-time forecast error is less than 10 % for 15-min advance interval, comprise from 67 to 96 % of all sessions depending on season and radio path orientation.

Implicit boundary equations for conservative Navier–Stokes equations

Co-existence of the physical and numerical boundary conditions makes implicit boundary treatment a particularly difficult problem in modern CFD simulations. Previous studies adopted space–time extrapolation or specially designed partial differential equations on the boundaries that are different from those of interior points. They are often formulated in terms of primitive variables, and are very challenging for complicated boundary types to be converted to, and implemented in, the conservative variables that are preferred in numerical simulations. More importantly, different boundary equations or different extrapolation techniques may compromise the stability, accuracy, or convergence rate of the A-stable schemes that are developed for interior points. A new methodology for implicit boundary treatment is proposed in this study. By introducing a simple correction matrix T, a set of generalized equations ∂Q/∂t=(I+T)R are developed in terms of conservative variables. It is applicable for both the interior domain (T=0) and the boundaries (T≠0). It is in a partial differential equation form, satisfies the boundary conditions accurately, independent of the time and spatial discretizations. Any one-sided schemes can be used on the boundaries but still maintain the upwind property. Implicit solution techniques are made significantly easy to implement using, for example, the data-parallel lower–upper relation method and the Newton method (combined with the GMRES method for subsidiary iterations). Numerical experiments show that the proposed methodology produces stable simulations for very large CFL numbers and preserve the imposed boundary values accurately.

Comphy — A compact-physics framework for unified modeling of BTI

Metal-oxide-semiconductor (MOS) devices are affected by generation, transformation, and charging of oxide and interface defects. Despite 50 years of research, the defect structures and the generation mechanisms are not fully understood. Most light has been shed onto the charging mechanisms of pre-existing oxide defects by using the non-radiative multi-phonon theory. In this work we present how the gist of physical models for pre-existing oxide defects can be efficiently abstracted at a minimal loss of physical foundation and accuracy. Together with a semi-empirical model for the generation and transformation of defects we establish a reaction-limited framework for unified simulation of bias temperature instabilities (BTI). The applications of the framework we present here cover simulation of BTI for negative (NBTI) and positive (PBTI) gate voltages, life time extrapolation, AC stress with arbitrary signals and duty cycles, and gate stack engineering.

Analysis of a decoupled time‐stepping algorithm for reduced MHD system modeling magneto‐convection

In this article, we analyze the stability and error estimate of a decoupled algorithm for a magneto‐convection problem. Magneto‐convection is assumed to be modeled by a coupled system of reduced magneto‐hydrodynamic (RMHD) equations and convection‐diffusion equation. The proposed algorithm applies the second‐order backward difference formula in time and finite element in space. To obtain a noniterative decouple algorithm from the fully discrete nonlinear system, we use a second‐order extrapolation in time to the nonlinear terms such that their skew symmetry properties are preserved. We prove the stability of the algorithm and derive error estimates without assuming any stability conditions. The algorithm is unconditionally stable and requires the solution of one RMHD problem and one convection‐diffusion equation per time step. Numerical test is presented that illustrates the accuracy and efficiency of the algorithm.

True amplitude recovery in reverse time extrapolation of plane and spherical waves

A challenging outstanding problem in reverse time extrapolation is recovering accurate amplitudes at reflectors from the receiver wavefield. Various migrations have been developed to produce accurate image locations rather than correct amplitude information because of inadequate compensation of attenuation, dispersion, and transmission losses. We have evaluated the requirements, and determined the theoretical feasibility, of true amplitude recovery of 2D acoustic and elastic seismic data by using the analytic Zoeppritz equations for plane-wave reflection and transmission coefficients. Then, we used synthetic acoustic and elastic wavefield data generated by elastodynamic finite differences to verify the recovery, in the reverse time propagation, of spherical waves and illustrated the salient differences between the incident wavefields reconstructed from reflection data only and from the combination of reflection and transmission data. These examples quantitatively verify that recovering an incident plane or a spherical wave requires the reverse time propagation of all reflections and transmissions in a model with the correct velocity and density. Accurate reconstruction of an incident wave is not possible by backward propagation of only reflections. As an application, we removed downgoing internal multiple reflections generated by upgoing waves incident at reflectors shallower than a horizontal well, in which geophones are deployed. The subtraction of the downgoing reflection involves wavefield reconstruction at depths shallower than the horizontal well and separation of upgoing and downgoing wavefields. This approach assumes that the correct acoustic (or elastic) velocity and density models are available in, and shallower than, the layer where the horizontal well is located. Incident-wave reconstruction works equally well for smooth models, as for models with sharp boundaries. Uncertainties in the model used for reconstruction, and incompleteness of the data aperture are propagated into the equivalent uncertainties, and incompleteness of the reconstruction.

Fast computational approach to the Delta Greek of non-linear Black–Scholes equations

In this paper, we consider a class of non-linear option pricing models. The focus is on the numerical investigation of Delta equation, where the unknown solution is the first spatial derivative of the option value. We construct and analyze monotone and sign-preserving finite difference schemes for the problems. Newton’s and Picard’s iterative procedures for solving the non-linear systems of algebraic equations are proposed. On this base, in order to improve the computational efficiency, we develop fast two-grid algorithms. Numerical experiments, using also Richardson extrapolation in time, are discussed in terms of accuracy, convergence and efficiency.