Extrapolation Research Articles

Comparison of Sampling and Grid Methods for Regional Soil Erosion Assessment

To control soil erosion, the intensity, area, and distribution of regional soil erosion must be determined to accurately plan and implement corresponding soil conservation measures. Therefore, regional soil erosion assessment has received extensive attention worldwide. At present, a sampling survey approach and full-coverage grid-based calculation are mainly applied in regional soil erosion assessment. The quantitative evaluation of the entire region depends on the quality of the data source. Furthermore, owing to the greatness of the evaluation object, the difficulty of data acquisition, the high cost, and poor usability, the present approach is bound to be at the expense of data accuracy, spatial resolution, time resolution, etc. The sampling survey approach can obtain high-precision data of soil erosion factors. Therefore, it can accurately quantify soil erosion in a field investigation unit. However, the sampling method, sampling density, and extrapolation methods have a significant impact on regional soil erosion assessments. This study considers the case of Baiquan County in the rolling hills of Northeast China as an example. Regional soil erosion evaluation using sampling survey and grid computing were compared. The impact of the data source accuracy on the soil erosion assessment was also quantitatively evaluated. The results of grid method showed a phenomenon of large rates of soil erosion and the ratio of the soil erosion area (the share of areas above the mild level), which were overestimated by 20% and 6%, respectively. A digital elevation model (DEM) with a resolution of 30 m can be used for soil erosion evaluation in plain areas, but that with the same resolution in hilly areas has insufficient calculation accuracy and provides large errors. The grid method can be adopted when land use and soil conservation measures are accurate. Otherwise, the sampling method is recommended. Interpolation of the ratio of the soil erosion area in the survey unit based on land use can better evaluate regional soil erosion.

Retrospective Comparison of Survival Projections for CAR T-Cell Therapies in Large B-Cell Lymphoma.

Durable remission has been observed in patients with relapsed or refractory (R/R) large B-cell lymphoma (LBCL) treated with chimeric antigen receptor (CAR) T-cell therapy. Consequently, hazard functions for overall survival (OS) are often complex, requiring the use of flexible methods for extrapolations. We aimed to retrospectively compare the predictive accuracy of different survival extrapolation methods and evaluate the validity of goodness-of-fit (GOF) criteria-based model selection for CAR T-cell therapies in R/R LBCL. OS data were sourced from JULIET, ZUMA-1, and TRANSCEND NHL 001. Standard parametric, mixture cure, cubic spline, and mixture models were fit to multiple database locks (DBLs), with varying follow-up durations. GOF was assessed using the Akaike information criterion and Bayesian information criterion. Predictive accuracy was calculated as the mean absolute error (MAE) relative to OS observed in the most mature DBL. For all studies, mixture cure and cubic spline models provided the best predictive accuracy for the least mature DBL (MAE 0.013‒0.085 and 0.014‒0.128, respectively). The predictive accuracy of the standard parametric and mixture models showed larger variation (MAE 0.024‒0.162 and 0.013‒0.176, respectively). With increasing data maturity, the predictive accuracy of standard parametric models remained poor. Correlation between GOF criteria and predictive accuracy was low, particularly for the least mature DBL. Our analyses demonstrated that mixture cure and cubic spline models provide the most accurate survival extrapolations of CAR T-cell therapies in LBCL. Furthermore, GOF should not be the only criteria used when selecting the optimal survival model.

EXTRAPOLATION USAGE FOR PREDICTING CRYPTOCURRENCY PRICING

In this article, we delve into the challenging problem of forecasting cryptocurrency prices using mathematical extrapolation techniques. We highlight the scarcity of research in this domain, underlining the necessity for in-depth investigation. The article outlines the unresolved issues related to extrapolation-based cryptocurrency price prediction, such as market volatility and non-linearity. It primarily aims to showcase the potential of extrapolation for predicting bitcoin prices. The analysis involves a year-long bitcoin price trend, with the application of linear and polynomial extrapolation methods. While some correlation exists, notable discrepancies, especially during abrupt price changes, are evident. The conclusion emphasizes the limitations of extrapolation and advises a diversified approach to cryptocurrency investment decisions, considering various factors beyond mathematical data. In this article, we delve into the challenging problem of forecasting cryptocurrency prices using mathematical extrapolation techniques. We highlight the scarcity of research in this domain, underlining the necessity for in-depth investigation. The article outlines the unresolved issues related to extrapolation-based cryptocurrency price prediction, such as market volatility and non-linearity. It primarily aims to showcase the potential of extrapolation for predicting bitcoin prices. The analysis involves a year-long bitcoin price trend, with the application of linear and polynomial extrapolation methods. While some correlation exists, notable discrepancies, especially during abrupt price changes, are evident. The conclusion emphasizes the limitations of extrapolation and advises a diversified approach to cryptocurrency investment decisions, considering various factors beyond mathematical data.

Evaluating the accuracy of liquid permeability measurements in shale and tight rocks using transient flow method and comparison with gas permeability

The transient flow method for measuring permeability to liquid is a useful technique for shale and tight rocks; however, it is not as popular as the steady-state method in these rocks. One of the issues is the lack of clarity on a key term of compressibility of the fluid and rock system. Various forms of compressibility have been used in literature, which can lead to inconsistent results of liquid permeability. Using gas for the permeability measurement is more common in shale, and the Klinkenberg corrected permeability is often used to represent liquid permeability; however, how the Klinkenberg permeability is compared to liquid permeability in shale or tight rocks is not adequately addressed. This paper presents a study using the transient flow method for water and oil permeability measurement in three Eagle Ford Shale samples. Gas permeability was also measured for these samples. Different forms of the total compressibility of the fluid-rock system (Ct) are summarized from literature, and a new form of Ct is proposed. The accuracy of the calculations based on different forms of Ct is evaluated through the comparison between water and oil permeabilities and the comparison with gas permeability. The results are also compared with oil permeability obtained from the steady-state method. The new form of Ct provided the most accurate results, whereas the other forms of Ct led to errors. However, for samples with bulk compressibility of less than 1 × 10−7 psi−1, the error using those forms of Ct was negligible. The study also found that the Klinkenberg permeability obtained from the linear extrapolation is larger than the oil permeability for two samples by 12% and 37%, respectively, whereas it is smaller than the oil permeability for the other sample. This comparison suggests that a nonlinear gas slippage effect may exist in the high pressure range (>2000 psi) for shale or tight rock samples.

A change in perspective: downhole cosmic-ray neutron sensing for the estimation of soil moisture

Abstract. Above-ground cosmic-ray neutron sensing (CRNS) allows for the non-invasive estimation of the field-scale soil moisture content in the upper decimetres of the soil. However, large parts of the deeper vadose zone remain outside of its observational window. Retrieving soil moisture information from these deeper layers requires extrapolation, modelling or other methods, all of which come with methodological challenges. Against this background, we investigate CRNS for downhole soil moisture measurements in deeper layers of the vadose zone. To render calibration with in situ soil moisture measurements unnecessary, we rescaled neutron intensities observed below the terrain surface with intensities measured above a waterbody. An experimental set-up with a CRNS sensor deployed at different depths of up to 10 m below the surface in a groundwater observation well combined with particle transport simulations revealed the response of downhole thermal neutron intensities to changes in the soil moisture content at the depth of the downhole neutron detector as well as in the layers above it. The simulation results suggest that the sensitive measurement radius of several decimetres, which depends on soil moisture and soil bulk density, exceeds that of a standard active neutron probe (which is only about 30 cm). We derived transfer functions to estimate downhole neutron signals from soil moisture information, and we describe approaches for using these transfer functions in an inverse way to derive soil moisture from the observed neutron signals. The in situ neutron and soil moisture observations confirm the applicability of these functions and prove the concept of passive downhole soil moisture estimation, even at larger depths, using cosmic-ray neutron sensing.

Potential risk of drug-drug interactions of ponatinib via inhibition against human UDP-glucuronosyltransferases

Ponatinib is an efficient oral tyrosine kinase inhibitor (TKI) for T315I-positive Ph + ALL and T315I-positive chronic myeloid leukemia (CML) or BCR-ABL when no other TKIs can be prescribed. In this research, we evaluated the inhibitory effects of ponatinib on human recombinant UDP-glucuronosyltransferases (UGTs) and predicted the magnitude of potential drug-drug interaction (DDI) risk of co-treatment with ponatinib and UGTs substrates by using in vitro-in vivo extrapolation (IVIVE) method. Our study presented that ponatinib showed a broad-spectrum inhibition against UGTs. Particularly, ponatinib exhibited potent inhibitory effects towards UGT1A7, UGT1A1, and UGT1A9 with IC50 values of 0.37, 0.41, and 0.89 μM, respectively, which might lead to clinically significant DDI.

Correlation of Accelerated Corrosion and Real Reinforced Concrete Water Structures

The service life of reinforced concrete constitutes the initiation and propagation period. Accelerated corrosion tests are carried out to obtain results in modelling the Service life of reinforced concrete structures. Its erroneous to undertake a direct linear extrapolation of accelerated test results to real structures in predicting their service life. This research examines the relationship between the result from accelerated corrosion and real reinforced concrete water structures. The physical and chemical properties of the materials used in the study were investigated for compliance for use in reinforced concrete water structures. Concrete of three classes M25, M30 and M35 were used to cast accelerated corrosion test samples. For each class 9 concrete samples of diameter 100 mm,130 mm and 150mm respectively and 300mm long were prepared. A 10 mm diameter bar,400mm long was centrally inserted during casting. After curing the test samples were immersed in a 3.5% solution of sodium chloride solution under 6 V. The accelerated corrosion specimens were monitored for onset of cracks and stopped when the cracks were 0.2 mm in width. Using the accelerated corrosion and real reinforced concrete results, a parametric study of the propagation period was done and a model proposed. From the results the proposed and published propagation period model compares well. The result from accelerated corrosion and real reinforced concrete water structures lineally increase for the propagation period. The proposed model can be considered as an input parameter for the service life of actual reinforced concrete water structures and contribute to their optimum performance.

Non-iterative pulse tail extrapolation algorithms for correcting nuclear pulse pile-up

Radiation detection systems working at high count rates suffer from the overlapping of their output electric pulses, known as pulse pile-up phenomenon, resulting in spectrum distortion and degradation of the energy resolution. Pulse tail extrapolation is a pile-up correction method which tries to restore the shifted baseline of a piled-up pulse by extrapolating the overlapped part of its preceding pulse. This needs a mathematical model which is almost always nonlinear, fitted usually by a nonlinear least squares (NLS) technique. NLS is an iterative, potentially time-consuming method.The main idea of the present study is to replace the NLS technique by an integration-based non-iterative method (NIM) for pulse tail extrapolation by an exponential model. The idea of linear extrapolation, as another non-iterative method, is also investigated. Analysis of experimental data of a NaI(Tl) radiation detector shows that the proposed non-iterative method is able to provide a corrected spectrum quite similar with the NLS method, with a dramatically reduced computation time and complexity of the algorithm. The linear extrapolation approach suffers from a poor energy resolution and throughput rate in comparison with NIM and NLS techniques, but provides the shortest computation time.

The challenges of defining hormesis in epidemiological studies: The case of radiation hormesis

In the current radiation protection system, preventive measures and occupational exposure limits for controlling occupational exposure to ionizing radiation are based on the linear no-threshold extrapolation model. However, currently an increasing body of evidence indicates that this paradigm predicts very poorly biological responses in the low-dose exposure region. In addition, several in vitro and in vivo studies demonstrated the presence of hormetic dose response curves correlated to ionizing radiation low exposure. In this regard, it is noteworthy that also the findings of different epidemiological studies, conducted in different categories of occupationally exposed workers (e.g., healthcare, nuclear industrial and aircrew workers), observed lower rates of mortality and/or morbidity from cancer and/or other diseases in exposed workers than in unexposed ones or in the general population, then suggesting the possible occurrence of hormesis. Nevertheless, these results should be considered with caution since the identification of hormetic response in epidemiological studies is rather challenging because of a number of major limitations. In this regard, some of the most remarkable shortcomings found in epidemiological studies performed in workers exposed to ionizing radiation are represented by lack or inadequate definition of exposure doses, use of surrogates of exposure, narrow dose ranges, lack of proper control groups and poor evaluation of confounding factors. Therefore, considering the valuable role and contribution that epidemiological studies might provide to the complex risk assessment and management process, there is a clear and urgent need to overcome the aforementioned limits in order to achieve an adequate, useful and more real-life risk assessment that should also include the key concept of hormesis. Thus, in the present conceptual article we also discuss and provide possible approaches to improve the capacity of epidemiological studies to identify/define the hormetic response and consequently improve the complex process of risk assessment of ionizing radiation at low exposure doses.

A CFD-based evaluation of ship speed at EEXI draft

This paper presents a simulation of ship speed for an existing containership at EEXI draft using Computational Fluid Dynamics (CFD). The simulation is divided into two steps namely (a) the numerical prediction of ship performance at model scale, and (b) the extrapolation of results to full scale. Model scale numerical simulations of ship resistance, open-water propeller and ship-propeller-rudder interactions at demonstrated. The method is at first validated by comparing against available experiments and at second stage full-scale ship performance is assessed by an extrapolation method. Comparison of the ship speed predicted by CFD against experiments demonstrates a difference of 0.05 knots when the same extrapolation coefficients are applied.

Effect of Nb Addition on Corrosion Resistance of U-6Zr Alloys

The fuel element plates in a research reactor can be exposed to an acidic, neutral, or alkaline environment based on its surroundings. This study aimed to investigate the effect of Nb addition on the corrosion properties of U-6Zr alloys in various environments. U-6Zr-xNb alloys (U-6Zr-2Nb, U-6Zr-5Nb, and U-6Zr-8Nb) with different Nb compositions of 2, 5, and 8 wt%, respectively, were prepared and cut into smaller pieces. The pieces were then mounted with chemical resin equipped with copper wire cables and metallography prepared by grinding using sandpaper with grit sizes ranging from 320 to 1200. The electrochemical corrosion tests used in this work were the polarization test and Tafel extrapolation method. In the first step of corrosion testing, the corrosion potential and polarization resistance were measured using standard settings from a voltage range of −0.02 to 0.02 V with a scanning rate of 0.05 mV/s. In the next step, a destructive method, called the Tafel extrapolation method, was used. Corrosion tests were carried out on U-6Zr-xNb alloys (x = 2, 5, 8) under various environmental conditions using electrochemical methods. Polarization resistance test and Tafel extrapolation methods revealed that the U-6Zr-2Nb alloy exhibited good corrosion resistance in an acidic HNO3 environment with a pH of 1.18. The best corrosion resistance of the U-6Zr-5Nb alloy was observed in demineralized water. Meanwhile, the U-6Zr-8Nb alloy showed the best corrosion resistance in an alkaline NaOH environment with a pH of 11.02. It can be concluded that the higher Nb composition added to U-6Zr alloys, the better their corrosion resistance in higher pH environments.

Image Processing-Based Method of Evaluation of Stress from Grain Structures of Through Silicon Via (TSV)

Visualization of material composition across numerous grains and complicated networks of grain boundaries using image processing techniques can reveal fresh insights into the material’s structural evolution and upcoming functional capabilities for a variety of applications. Three-dimensional integrated circuits (3D IC) are the most practical technology for increasing transistor density in future semiconductor applications. One of the key benefits of 3D IC is heterogeneous integration, which results in shorter interconnections due to vertical stacking. However, one of the most significant challenges in building higher-density microelectronics devices is the stress generated by material mismatches in the coefficient of thermal expansion (CTE). The purpose of this study is to analyze grain boundary migration caused by variations in strain energy density using image processing methods for 3D grain continuum modeling. Temperature changes in polycrystalline structures generate stresses and strain energy densities, which may be calculated using FEM software. Single crystal Cu’s anisotropic elastic properties are twisted to suit grain orientation in space and each grain is treated as a single crystal. Grain boundary speeds are calculated using a simple model that relates grain boundary mobility to variations in strain energy density on both sides of grain boundaries. Using the grain continuum model, researchers will be able to investigate the effect of thermally generated stresses on grain boundary motion caused by atomic flux driven by strain energy. Using finite-element modeling of the grain structure in a Through Silicon Via, the stress effect on grain boundaries caused by grain rotation due to CTE mismatch was investigated (TSV). The structure must be modeled using a scanning electron microscopes Electron Backscatter Diffraction (EBSD) image (SEM). Grain growth and subsequent grain boundary rotation can be performed using the appropriate extrapolation method to measure their influence on stress and, as a result, the TSV’s overall reliability.

Estimates for certain class of rough generalized Marcinkiewicz functions along submanifolds

Abstract We establish certain delicate L p {L}^{p} bounds for a class of generalized Marcinkiewicz integral operators along submanifolds with rough kernels. These bounds allow us to use Yano’s extrapolation method to prove the L p {L}^{p} boundedness of the aforementioned integral operators under very weak assumptions on the kernels. Our results in this article improve and generalize many previously known results.

Idealizing Tauc Plot for Accurate Bandgap Determination of Semiconductor with Ultraviolet-Visible Spectroscopy: A Case Study for Cubic Boron Arsenide.

The Tauc plot is widely used to determine the bandgap of semiconductors, but the actual plot often exhibits significant baseline absorption below the expected bandgap, leading to bandgap discrepancies from two different extrapolations. In this work, we first discuss the origin of baseline absorption and show that both extrapolation methods can produce significant errors by simulating Tauc plots with varying levels of baseline absorption. We then propose and experimentally verify a new method that idealizes the absorption spectrum by removing its baseline before constructing the Tauc plot. Finally, we apply this new method to cubic boron arsenide (c-BAs), resolve its bandgap discrepancies, and obtain a converging bandgap of 1.835 eV based on both previous and new transmission spectra. The method is applicable to both indirect and direct bandgap semiconductors with absorption spectrum measured via transmission or diffuse reflectance, which will become essential to obtain accurate values of their bandgaps.

A robust fitted numerical scheme for singularly perturbed parabolic reaction–diffusion problems with a general time delay

The present paper deals with the class of time-delayed, singularly perturbed parabolic reaction–diffusion problems. In the x−t plane, parabolic boundary layers appear on the two lateral sides of the domain when a small parameter is multiplied by the second-order space derivative. A fitted operator-based numerical method is developed to solve the considered problem, and its detailed analysis is done. To discretize the spatial domain, an exponentially fitted cubic B-spline scheme is used, and for the discretization of the time derivative, we use the implicit Euler scheme on the uniform mesh. We improve accuracy in the temporal direction using Richardson’s extrapolation method, which results in second-order parameter-uniform convergence. The stability and uniform convergence analysis of the scheme are studied. The present scheme gives a more accurate solution than existing methods in the literature. To ensure that the established numerical scheme is applicable, two test examples are carried out. The obtained numerical results support the estimated value in theory.

Technical note: estimating longer drug shelf-life with reliability plotting

A graphical plot of drug stability-study data can be extrapolated to estimate the drug’s percent degradation and therefore its shelf-life beyond the time period of the study. However, after a statistical confidence limit is applied, that shelf-life estimate is significantly reduced. Such a reduction can be minimized by transforming the data so that it plots as close as possible to linearity, a process that is called reliability plotting. Reliability plotting seems to have been rarely if ever used on drug stability data, despite its being mentioned in relevant guidance documents and its ability to justify longer shelf-life at no additional cost. For example, an 18-month stability study resulted in a 19-month shelf-life using standard extrapolation methods but resulted in a 23 month shelf-life using reliability plotting.

Multi-Zone Integrated Iterative-Decoupling Control of Temperature Field of Large-Scale Vertical Quenching Furnaces Based on ESRNN

Temperature uniformity within a large vertical quenching furnace is the key factor to determine the properties of aluminum workpieces. The existing temperature control method for quenching furnaces cannot overcome the influence of multi-zone coupling issues, which lead to unstable product performance and a lack of key performance. Based on a workpiece temperature field model, a spatial-temporal dimensional extrapolation method is proposed to realize fast and accurate solving of the temperature model. In view of the over-burning and under-burning problems during the temperature rising period, a self-incentive nonparametric adaptive iterative control algorithm is presented, which realizes consistent temperature rising of multiple heating zones. Aiming at the strong coupling problem of the multi-zone heating manner during the temperature holding period, the decoupling problem of multiple control loops is converted into a multi-loop integrated control optimization problem. An eigenvector self-update recurrent neural network (ESRNN) is constructed to determine the Jacobian information and tune the control parameters of each loop controller in real time, thereby realizing the integrated intelligent decoupling control of multiple heating loops. Simulation and industrial results verify the superiority of the proposed method, which can realize high-precision and high-uniformity control of a large-scale temperature field and effectively improve the quality and performance of aluminum alloy workpieces.

Parameter Estimation in Spectral Resolution Enhancement Based on Forward-Backward Linear Prediction Total Least Square Method.

In a Fourier transform infrared (IR) spectrometer, the Michelson interference signal extrapolation method based on linear prediction is often used to improve spectral resolution. In this method, an autoregressive (AR) model is established for the Michelson interference signal in the spectrometer. Once the AR model parameters are determined, the AR process is predictable. The interference signal can be used to figure out the AR model's parameters. Based on this, the AR model can be used to extrapolate the interference signal to improve the spectral resolution. In this paper, the forward-backward linear prediction total least squares (FB-TLS) method is proposed to estimate the parameters of the AR model. The parameters that are estimated are used to improve the IR spectral resolution. By simulating different order and signal-to-noise ratio situations, the effects of the Burg, the least square, and the FB-TLS parameter estimation methods on spectral resolution enhancement are studied. The simulation results demonstrate that the FB-TLS parameter estimation method can effectively suppress noise and avoid spurious peaks. The experimental results demonstrate that the FB-TLS parameter estimation method is effective for spectral resolution enhancement technology based on linear prediction. When the FB-TLS method is used to enhance NH3 IR spectral resolution from 2 cm-1 to 1 cm-1, the spectral prediction error in the NH3 characteristic band is only 0.21% compared with the measured NH3 spectrum, whose spectral resolution is 1 cm-1.

Stock Price Prediction Using Formula From Data Scale Analysis Extrapolation Method

Public awareness about stocks is increasing every year. This needs to be balanced with advances in science to help investors make more measurable and systematic decisions. The purpose of this study is to apply Extrapolation of Data Scale Analysis (DSA) in predicting stock prices. The DSA Extrapolation method will produce a new formula called JIC-FLY 3 which is used to process big data in predicting prices at a certain time. The population in this study is the share price of the telecommunications sub-sector with EXCL (PT XL Axiata Tbk.) as a sample. The error value measurement method used is the Mean Absolute Percentage Error (MAPE). The result of this study is that the DSA 19 extrapolation method using the JIC-FLY 3 formula is able to predict the share price of the telecommunication subsector with the best error giving the smallest error value of 0.193%.

Examining the continuum of resistance model in two population-based screening studies in Sweden

In studies recruited on a voluntary basis, lack of representativity may impair the ability to generalize findings to the target population. Previous studies, primarily based on surveys, have suggested that generalizability may be improved by exploiting data on individuals who agreed to participate only after receiving one or several reminders, as such individuals may be more similar to non-participants than what early participants are. Assessing this idea in the context of screenings, we compared sociodemographic characteristics and health across early, late, and non-participants in two large population-based screening studies in Sweden: STROKESTOP II (screening for atrial fibrillation; 6,867 participants) and SCREESCO (screening for colorectal cancer; 39,363 participants). We also explored the opportunities to reproduce the distributions of characteristics in the full invited populations, either by assuming that the non-participants were similar to the late participants, or by applying a linear extrapolation model based on both early and late participants. Findings showed that early and late participants exhibited similar characteristics along most dimensions, including civil status, education, income, and health examination results. Both these types of participants in turn differed from the non-participants, with fewer married, lower educational attainments, and lower incomes. Compared to early participants, late participants were more likely to be born outside of Sweden and to have comorbidities, with non-participants similar or even more so. The two empirical models improved representativity in some cases, but not always. Overall, we found mixed support that data on late participation may be useful for improving representativeness of screening studies.