Simple Scaling Method Research Articles

Gait alteration strategies for knee osteoarthritis: a comparison of joint loading via generic and patient-specific musculoskeletal model scaling techniques

ABSTRACT Gait modifications and laterally wedged insoles are non-invasive approaches used to treat medial compartment knee osteoarthritis. However, the outcome of these alterations is still a controversial topic. This study investigates how gait alteration techniques may have a unique effect on individual patients; and furthermore, the way we scale our musculoskeletal models to estimate the medial joint contact force may influence knee loading conditions. Five patients with clinical evidence of medial knee osteoarthritis were asked to walk at a normal walking speed over force plates and simultaneously 3D motion was captured during seven conditions (0°-, 5°-, 10°-insoles, shod, toe-in, toe-out, and wide stance). We developed patient-specific musculoskeletal models, using segmentations from magnetic resonance imaging to morph a generic model to patient-specific bone geometries and applied this morphing to estimate muscle insertion sites. Additionally, models were created of these patients using a simple linear scaling method. When examining the patients’ medial compartment contact force (peak and impulse) during stance phase, a ‘one-size-fits-all’ gait alteration aimed to reduce medial knee loading did not exist. Moreover, the different scaling methods lead to differences in medial contact forces; highlighting the importance of further investigation of musculoskeletal modeling methods prior to use in the clinical setting.

Scaling of Hydraulic Functions in Heterogeneous Soil Using Nonlinear Least Squares Minimization Method

Presenting soil heterogeneity precisely in various spatial scales is the main key to simulate water and solute transport through it. The method described by Richards is mostly used to study water flow through vadose zone. It requires spatial representation of hydraulic functions and water retention relationship in the soil. To represent the spatial relationship of soil hydraulic functions, scaling approach is being used since the last few decades. In this study, a simple scaling method using nonlinear least squares minimization technique has been used to scale soil matric potential, hydraulic conductivity as well as simultaneous scaling of soil matric potential and hydraulic conductivity data. Simultaneous scaling is necessary as it reduces the volume of data by producing a single set of scale factors for hydraulic functions in a heterogeneous soil. Van Genuchten’s semi-empirical expressions were used in this study to parameterize soil hydraulic functions. Results showed that correlation coefficient from raw and descaled data was superior when soil matric potential and hydraulic conductivity data were scaled separately than simultaneously. Improvement of correlation coefficient in simultaneous scaling can be obtained by adding more weight to the soil matric potential data than unsaturated hydraulic conductivity data, which enhances the overall correlation coefficient in simultaneously scaling. Statistical analysis of the scale factors showed that they are lognormally distributed. Scale factors calculated by solving simple equations obtained using the method described in this study can be used to simulate water movement through heterogeneous soil conditions using HYDRUS model.

Constructing short‐duration IDF curves using coupled dynamical–statistical approach to assess climate change impacts

This study demonstrates a methodology to construct short‐duration rainfall intensity–duration–frequency (IDF) curves and to quantify the variability in the rainfall intensities for different return periods with respect to the changing climate. A dynamical downscaling approach using the regional climate model (RCM) Weather Research and Forecasting (WRF) has been used to assess present and future climates using the downscaling of an ensemble of three global climate models (GCMs) (CSIRO‐ACCESS1.3, MPI‐ESM‐MR ECHAM6 and NIES‐MIROC5) under the Coupled Model Intercomparison Project phase 5 (CMIP5). Furthermore, a statistical approach using the well‐known simple scaling method has been applied to extend the 6‐hourly WRF precipitation output to the finer temporal scale of 10 min. The short‐duration IDF curves were then constructed for the present and future climates under two representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5. A preliminary examination for this case study over Bac Ninh, an industrial area in the northern Vietnam, shows that there is a substantial increase in short‐duration rainfall intensity in the future with respect to the baseline climate. The highest increase is towards the end of the century (2071–2100) ranging from 56 to 61% for a 10‐ and 100‐year return period for 24‐hr duration, respectively, while the increase is about 40–45% for the 10‐min duration. These results strongly suggest that severe flooding in the future climate over the study region may be likely. The study results might be useful for policymakers and infrastructure planning and for insurance companies around the study area.

Finding Horndeski theories with Einstein gravity limits

The Horndeski action is the most general scalar-tensor theory with at most second-order derivatives in the equations of motion, thus evading Ostrogradsky instabilities and making it of interest when modifying gravity at large scales. To pass local tests of gravity, these modifications predominantly rely on nonlinear screening mechanisms that recover Einstein's Theory of General Relativity in regions of high density. We derive a set of conditions on the four free functions of the Horndeski action that examine whether a specific model embedded in the action possesses an Einstein gravity limit or not. For this purpose, we develop a new and surprisingly simple scaling method that identifies dominant terms in the equations of motion by considering formal limits of the couplings that enter through the new terms in the modified action. This enables us to find regimes where nonlinear terms dominate and Einstein's field equations are recovered to leading order. Together with an efficient approximation of the scalar field profile, one can then further evaluate whether these limits can be attributed to a genuine screening effect. For illustration, we apply the analysis to both a cubic galileon and a chameleon model as well as to Brans-Dicke theory. Finally, we emphasise that the scaling method also provides a natural approach for performing post-Newtonian expansions in screened regimes.

SU-F-R-33: Can CT and CBCT Be Used Simultaneously for Radiomics Analysis

Purpose: To investigate whether CBCT and CT can be used in radiomics analysis simultaneously. To establish a batch correction method for radiomics in two similar image modalities. Methods: Four sites including rectum, bladder, femoral head and lung were considered as region of interest (ROI) in this study. For each site, 10 treatment planning CT images were collected. And 10 CBCT images which came from same site of same patient were acquired at first radiotherapy fraction. 253 radiomics features, which were selected by our test-retest study at rectum cancer CT (ICC>0.8), were calculated for both CBCT and CT images in MATLAB. Simple scaling (z-score) and nonlinear correction methods were applied to the CBCT radiomics features. The Pearson Correlation Coefficient was calculated to analyze the correlation between radiomics features of CT and CBCT images before and after correction. Cluster analysis of mixed data (for each site, 5 CT and 5 CBCT data are randomly selected) was implemented to validate the feasibility to merge radiomics data from CBCT and CT. The consistency of clustering result and site grouping was verified by a chi-square test for different datasets respectively. Results: For simple scaling, 234 of the 253 features have correlation coefficient ρ>0.8 among which 154 features haveρ>0.9 . For radiomics data after nonlinear correction, 240 of the 253 features have ρ>0.8 among which 220 features have ρ>0.9. Cluster analysis of mixed data shows that data of four sites was almost precisely separated for simple scaling(p=1.29 * 10−7, χ2 test) and nonlinear correction (p=5.98 * 10−7, χ2 test), which is similar to the cluster result of CT data (p=4.52 * 10−8, χ2 test). Conclusion: Radiomics data from CBCT can be merged with those from CT by simple scaling or nonlinear correction for radiomics analysis.

Huss Receives 2013 Cryosphere Young Investigator Award: Citation

Matthias Huss is an outstanding young glaciologist who completed his Ph.D. in 2009 at the Swiss Federal Institute of Technology (ETH) in Zurich, Switzerland, and currently has a joint appointment there and at the University of Fribourg. During his short scientific career, Matthias has made substantial and innovative contributions to a broad range of topics in glaciology, including modeling and projection of glacier mass and runoff changes, glacier outburst floods, glacier dynamics, and climate‐glacier interactions. His work ranges from local‐scale to regional‐ and global‐scale studies. Of note, he developed a new cutting‐edge and already widely used parameterization to model glacier retreat, which fills the gap between complex ice flow models and simple scaling methods. He also computed ice thickness distribution maps of all 200,000 glaciers in the world based on principles of flow dynamics. This unique data set has many applications, of which perhaps the most significant is the estimation of the total volume of stored ice, a quantity that is critical for projections of sea level rise and water resources during the 21st century.

A relatively simple scaling method for describing the unsaturated hydraulic functions of stony soils

AbstractFew if any methods exist to estimate the effects of stone content (stoniness) on the unsaturated soil hydraulic properties. A relatively simple scaling method is presented to estimate the hydraulic conductivity of unsaturated stony soils having different stone contents. A key assumption of the method is that van Genuchten's water retention parameters α and n of the fine soil fraction are the same as those of the stony soil. The method further assumes a linearly decreasing relationship between the saturated hydraulic conductivity and the stone content, based on previous numerical simulations. Using the proposed method, it is possible to calculate the hydraulic conductivity of unsaturated stony soils, knowing the saturated hydraulic conductivity of the fine soil fraction, the retention curve of the fine soil fraction, and the particular stoniness of the soil.

Assessment of future flood intensification in Central Vietnam using a super-high-resolution climate model output

This paper presents an assessment of the changes in future floods. The ranked area-average heavy daily rainfall amounts simulated by a super-high-resolution (20 km mesh) global climate model output are corrected with consideration of the effects of the topography on heavy rainfall patterns and used as a basis to model design storm hyetographs. The rainfall data are then used as the input for a nearly calibration-free parameter rainfall–runoff model to simulate floods in the future climate (2075–2099) at the Upper Thu Bon River basin in Central Vietnam. The results show that although the future mean annual rainfall will not be considerably different compared to the present-day climate (1979–2003), extreme rainfall is projected to increase vigorously, leading to a similar order of intensification of future floods. It is very likely that the flood peak with a 25-year recurrence will increase approximately 42% relative to the present-day climate. The occurrence of floods with a 10-year recurrence may exceed those with a 25-year recurrence in the present-day climate. The projection results also exhibit insignificant uncertainties caused by an artificial neural network-based bias correction model. Additionally, the presented bias correction model shows advantages over a simple climatology scaling method.

Response of Summer Vegetation in Mongolia to the Range of Future Climate Conditions Projected by CMIP3 Models: Study Using a Simple Scaling Method

Response of Summer Vegetation in Mongolia to the Range of Future Climate Conditions Projected by CMIP3 Models: Study Using a Simple Scaling Method

Anthropogenic radiative forcing time series from pre-industrial times until 2010

Abstract. In order to use knowledge of past climate change to improve our understanding of the sensitivity of the climate system, detailed knowledge about the time development of radiative forcing (RF) of the earth atmosphere system is crucial. In this study, time series of anthropogenic forcing of climate from pre-industrial times until 2010, for all well established forcing agents, are estimated. This includes presentation of RF histories of well mixed greenhouse gases, tropospheric ozone, direct- and indirect aerosol effects, surface albedo changes, stratospheric ozone and stratospheric water vapour. For long lived greenhouse gases, standard methods are used for calculating RF, based on global mean concentration changes. For short lived climate forcers, detailed chemical transport modelling and radiative transfer modelling using historical emission inventories is performed. For the direct aerosol effect, sulphate, black carbon, organic carbon, nitrate and secondary organic aerosols are considered. For aerosol indirect effects, time series of both the cloud lifetime effect and the cloud albedo effect are presented. Radiative forcing time series due to surface albedo changes are calculated based on prescribed changes in land use and radiative transfer modelling. For the stratospheric components, simple scaling methods are used. Long lived greenhouse gases (LLGHGs) are the most important radiative forcing agent with a RF of 2.83±0.28 W m−2 in year 2010 relative to 1750. The two main aerosol components contributing to the direct aerosol effect are black carbon and sulphate, but their contributions are of opposite sign. The total direct aerosol effect was −0.48±0.32 W m−2 in year 2010. Since pre-industrial times the positive RF (LLGHGs and tropospheric O3) has been offset mainly by the direct and indirect aerosol effects, especially in the second half of the 20th century, which possibly lead to a decrease in the total anthropogenic RF in the middle of the century. We find a total anthropogenic RF in year 2010 of 1.4 W m−2. However, the uncertainties in the negative RF from aerosols are large, especially for the cloud lifetime effect.

Robust assessment of future changes in extreme precipitation over the Rhine basin using a GCM

Abstract. Estimates of future changes in extremes of multiday precipitation sums are critical for estimates of future discharge extremes of large river basins. Here we use a large ensemble of global climate model SRES A1b scenario simulations to estimate changes in extremes of 1–20 day precipitation sums over the Rhine basin, projected for the period 2071–2100 with reference to 1961–1990. We find that in winter, an increase of order 10%, for the 99th percentile precipitation sum, is approximately fixed across the selected range of multiday sums, whereas in summer, the changes become increasingly negative as the summation time lengthens. Explanations for these results are presented that have implications for simple scaling methods for creating time series of a future climate. We show that the dependence of quantile changes on summation time is sensitive to the ensemble size and indicate that currently available discharge estimates from previous studies are based on insufficiently long time series.

Abstract 2663: Preclinical pharmacokinetic characterizations and human pharmacokinetic prediction of AMG 900, an orally available small molecule inhibitor of aurora kinases

Abstract Introduction: AMG 900 is a small molecule being developed as an orally administered, highly potent and selective pan-aurora kinase inhibitor. AMG 900 is currently undergoing phase 1 clinical evaluation in patients with advanced solid tumors. The objectives of the studies were to characterize single dose pharmacokinetics (PK) of AMG 900 in preclinical species and use the preclinical PK data to predict its human PK. Methods: Following a single intravenous and oral administration of AMG 900 to mice, rats, dogs, and monkeys, blood samples were collected and processed for plasma by centrifugation. AMG 900 plasma concentrations were determined by LC-MS/MS. Non-compartmental analysis of the concentration - time data was performed to calculate PK parameters of AMG 900. Human PK were predicted based on data from preclinical species using the simple allometric scaling method assuming a human body weight of 60 kg. Results: AMG 900 exhibited low (mouse, monkey and dog) to moderate (rat) clearance in the species evaluated. The volume of distribution at steady state was less than 0.5 L/kg across species. Following intravenous administration, the compound had terminal elimination half-life ranging from 0.6 to 2.4 hours. AMG 900 was well absorbed in fasted animals across species with an oral bioavailability ranging from 31% to 104%. The clearance and volume of distribution at steady state in humans were predicted to be 0.03 L/hr/kg and 0.1 L/kg, respectively, with the predicted half-life to be approximately 2.3 hours. Bioavailability after oral administration of AMG 900 was predicted to be 75%, calculated from the mean values observed in non-clinical species. Conclusion: AMG 900 exhibits good PK properties in preclinical species and it was predicted to have low clearance and good oral bioavailability in human. Available PK results from the on-going phase 1 trial are consistent with the allometric scaling predictions. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2663.

Prediction of human clearance of therapeutic proteins: simple allometric scaling method revisited

In this report, the utility of a commonly used interspecies scaling method to predict the systemic clearance (CL) of therapeutic proteins in humans was evaluated. Based on analysis of a pharmacokinetic data set of 34 therapeutic proteins, including 12 monoclonal antibodies (mAbs) and Fc fusion proteins, human CL can generally be predicted reasonably well with simple allometric scaling and a fixed exponent of 0.8: approximately 95% of the cases predicted values within 2-fold of the observed values when using CL data from multiple species, or approximately 90% simply using CL from monkeys. Specific to mAbs/Fc fusion proteins, scaling from monkey CL using a fixed exponent of 0.8 gave an excellent prediction; all predicted CL values were within 2-fold of the corresponding observed values. Compared with the simple allometric scaling method that uses a fitted exponent from CL data of > or =3 preclinical species, the fixed exponent approach with 1-2 preclinical species is simple, resource-saving and minimizes systematic bias. Together with its overall satisfactory prediction accuracy, especially in the absence of non-linear pharmacokinetics and species-specific clearance mechanisms, this fixed exponent method affords a viable alternative to other published allometric methods, including the Rule of Exponents (ROE).

Comment on “Elastic constants from microscopic strain fluctuations”

Sengupta [Phys. Rev. E 61, 1072 (2000)] presented an elegant and simple finite-size scaling method for the calculation of elastic constants and their corresponding correlation lengths, which is suitable for many finite discrete systems considered through simulations or experiments. We take into account a mathematical finite-size effect that was neglected by the authors in order to propose a more accurate method. Consequences on the authors' results are also discussed.

Unified scaling factor approach for turbo decoding algorithms

Turbo (iterative) decoding can be implemented with a large family of soft-input soft-output (SISO) algorithms, including suboptimal but practical algorithms such as the soft-output Viterbi algorithm (SOVA) and max-log-MAP algorithm. The performance with these practical algorithms can be improved with simple scaling factor methods. However, their theoretical analysis was mainly based on the relaxed assumption proposed by Papke et al. that the extrinsic information is Gaussian distributed. This study proposes a novel scaling factor approach for reducing both the overestimation of reliability values and the correlation between the intrinsic and extrinsic information. Explicit formulae for computing the scaling factors are derived based on mathematical statistics. A key difference compared to the scaling factor method of Papke et al. is that the proposed scaling factors can be computed off-line. The numerical results show that when implemented in the decoding algorithm of block component codes, the proposed scaling factor approach improves the performance of turbo decoding over additive white Gaussian noise and Rayleigh fading channels. It is superior than the method by Papke et al. in both performance and complexity.

Influence of Rainfall Scenario Construction Methods on Runoff Projections

Abstract The future rainfall series used to drive hydrological models in most climate change impact studies is informed by global climate models (GCMs). This paper compares future runoff projections in ∼11 000 0.25° grid cells across Australia from a daily rainfall–runoff model driven with future daily rainfall series obtained using three simple scaling methods, informed by 14 GCMs. In the constant scaling and daily scaling methods, the historical daily rainfall series is scaled by the relative difference between GCM simulations for the future and historical climates. The constant scaling method scales all the daily rainfall by the same factor, and the daily scaling method takes into account changes in the daily rainfall distribution by scaling the different daily rainfall amounts differently. In the daily translation method, the GCM future daily rainfall series is translated to a 0.25° gridcell rainfall series using the relationship established between the historical GCM-scale rainfall and 0.25° gridcell rainfall data. The daily scaling and daily translation methods generally give higher extreme and annual runoff than the constant scaling method because they take into account the increase in extreme daily rainfall (which generates significant runoff) simulated by the large majority of the GCMs. However, the difference between the mean annual runoff simulated with future daily rainfall series obtained using the constant versus daily scaling methods is generally less than 5%, which is relatively smaller than the range of runoff results from the different GCMs of 30%–40%.

Finite-Level Quantized Feedback Control for Linear Systems

This technical note studies quantized output feedback control of discrete-time linear systems using a finite-level quantizer. The main objective is to find a quantization strategy which is easily implementable and achieves asymptotic stabilization. Based on a known logarithmic quantization scheme, we introduce a simple dynamic scaling method for the quantizer. A suboptimal approach for the optimization of the number of quantization levels and the design of a corresponding quantized dynamic output feedback controller is given. The robustness of the dynamic quantization scheme with respect to input disturbances is also examined.

Detection of the fractal character of compact adsorbed layers by the dropping mercury electrode

The development of compact adsorbed layers at the dropping mercury electrode is used for the detection of resulting changes in the geometry of the electrode–solution interface from Euclidean to fractal. A simple size scaling method of the Hg drop surface is applied, which focus on the time dependence of the drop area under conditions of constant adsorbate and base electrolyte concentration, constant potential and constant mercury flow rate. It is found that the slope of the log–log plots of capacitance or capacitance current against electrode surface area or electrode radius is increasing upon the formation of a compact adsorbed layer. Under equilibrium conditions the slope values of the linear log–log plots can be reasonably identified with the fractal dimension of the electrode/solution interface. However, due to the limited extent of the power-law range of the feature vs. scale relation, the size scaling method of the dropping mercury electrode can be used to probe fractal adsorbate films on a strictly qualitative level.

Identifying Noncooperative Subjects at a Distance Using Face Images and Inferred Three-Dimensional Face Models

We present an approach to identify noncooperative individuals at a distance from a sequence of images, using 3-D face models. Most biometric features (such as fingerprints, hand shape, iris, or retinal scans) require cooperative subjects in close proximity to the biometric system. We process images acquired with an ultrahigh-resolution video camera, infer the location of the subjects' head, use this information to crop the region of interest, build a 3-D face model, and use this 3-D model to perform biometric identification. To build the 3-D model, we use an image sequence, as natural head and body motion provides enough viewpoint variation to perform stereomotion for 3-D face reconstruction. We have conducted experiments on a 2-D and 3-D databases collected in our laboratory. First, we found that metric 3-D face models can be used for recognition by using simple scaling method even though there is no exact scale in the 3-D reconstruction. Second, experiments using a commercial 3-D matching engine suggest the feasibility of the proposed approach for recognition against 3-D galleries at a distance (3, 6, and 9 m). Moreover, we show initial 3-D face modeling results on various factors including head motion, outdoor lighting conditions, and glasses. The evaluation results suggest that video data alone, at a distance of 3 to 9 meters, can provide a 3-D face shape that supports successful face recognition. The performance of 3-D-3-D recognition with the currently generated models does not quite match that of 2-D-2-D. We attribute this to the quality of the inferred models, and this suggests a clear path for future research.

Towards quantitative chemical imaging with ToF-SIMS

Methods for processing ToF-SIMS spectra and images have advanced significantly in recent years to include multivariate analysis methods. Multivariate methods can reduce noise, identify and quantify chemical components, and segment images into discrete chemical phases. To date, these methods have focused on the analysis of single images; however, quantitative or semi-quantitative methods for comparison of multiple images collected across multiple samples have lagged in development. This study evaluates simple noise reduction and scaling methods to facilitate semi-quantitative comparison of images collected across several samples with varying acquisition conditions. Down-binning, Poisson-scaling, and nearest-neighbor smoothing methods improved signal-to-noise in image datasets, with nearest-neighbor smoothing providing the greatest improvement. Image scaling methods including pixel-by-pixel (PbP) normalization and scalar multiplication were found to improve the relative quantification of images. While PbP normalization methods performed well for relatively flat samples, such methods were not suitable for samples with significant topography. Scaling methods using scalar multiplication of individual secondary ion images and histogram analyses facilitated semi-quantitative comparison of these samples.