Scaling Model Research Articles

Dynamics Versus Development in Numerosity Estimation: A Computational Model Accurately Predicts a Developmental Reversal.

Perceptual judgments result from a dynamic process, but little is known about the dynamics of number-line estimation. A recent study proposed a computational model that combined a model of trial-to-trial changes with a model for the internal scaling of discrete numbers. Here, we tested a surprising prediction of the model-a situation in which children's estimates of numerosity would be better than those of adults. Consistent with the model simulations, task contexts led to a clear developmental reversal: children made more adult-like, linear estimates when to-be-estimated numbers were descending over trials (i.e., backward condition), whereas adults became more like children with logarithmic estimates when numbers were ascending (i.e., forward condition). In addition, adults' estimates were subject to inter-trial differences regardless of stimulus order. In contrast, children were not able to use the trial-to-trial dynamics unless stimuli varied systematically, indicating the limited cognitive capacity for dynamic updates. Together, the model adequately predicts both developmental and trial-to-trial changes in number-line tasks.

A review of the models of near-Earth object impact cratering on Earth

Near-Earth object (NEO) impact cratering is one of the frontier themes of planetary research. The cratering process and types, laboratory impact cratering phenomena, and cratering scaling are introduced. The hypervelocity impact-cratering process is conventionally divided into three successive stages: contact and compression, excavation, and modification. When large impact craters are formed in geological materials, shearing is the main deformation mode. At small scales, cratering in brittle materials is dominated by surface spalling; much of the crater volume consists of a wide, flat spall zone. According to the morphological characteristics of impact craters, impact craters are generally divided into two groups: simple and complex craters. The cratering mechanism of NEO impact cratering and the deficiency of point source model are analyzed. The cratering mechanism can be divided into strength regime and gravity regime. In the strength regime, the cratering results are controlled by strength, and in the gravity regime, the cratering results are dominated by gravity. Crater scaling laws have been established based on dimensional analysis, point source approximation and the results of experimental and numerical impact. The scaling law is a specific power rate form, which describes well the scaling of crater size, ejecta, and crater growth. But the scaling law of the point source model is not applicable to the experimental phenomenon in several impactor radii. The suggestions for future research of NEO impact cratering are pointed out:(1) scaling where the point source hypothesis is not applicable; (2) the effect of melting, gasification, atmosphere and temperature on the cratering process; (3) scaling law and model of oblique impact; (4) momentum enhancement effect of impact; (5) experimental and numerical methods to simulate the formation of impact craters.

Influence of crystallinity on the electrical conductivity of individual carbon nanotubes

The material properties of graphene and carbon nanotubes are highly sensitive to defects. Future exploitation of these materials will thereby rely on both a detailed understanding and classification schemes for material quality. Here we have used electron diffraction to measure the mean effective crystallite size of individual multiwalled carbon nanotubes, while also probing their electrical resistance. At room temperature we find a drastic shift in linear resistance of two orders of magnitude at a critical grain size of about 11 nm, which we interpret as an effect from quantum confinement and edge effects in the individual crystallites. For the regions above and below the critical grain size value we suggest a scaling model for the electrical conductivity within a single layer of a multiwalled carbon nanotube which connects its electrical conductivity with the effective crystallite size and tube diameter.

On the thermocapillary migration between parallel plates

In this work, the thermocapillary migration of liquid bridges and air bubbles between parallel plates is studied. The factors influencing the thermocapillary migration are discussed, especially the magnitudes of the thermal gradient, the liquid or gas volume and the tilt angle of the parallel plates against gravity. The experimental trends are explained based on scaling models. It is found that a critical tilt angle exists at which the thermocapillary migration of liquid bridges is suspended. A simple two-dimensional theoretical model for the migration of liquid bridges is formulated. The model is able to predict the critical tilt angles in an approximate manner. An application perspective of this work lies in tribological systems in which liquid lubricant is replenished using applied thermal gradients.

Tough Hydrogels with Dynamic H-Bonds: Structural Heterogeneities and Mechanical Performances

The recently developed tough and self-healing hydrogels, containing a large number of physical bonds, have found widespread applications in bioengineering and soft electronics. Owing to the sophisticated physical interactions and organization, these hydrogels often demonstrate structural heterogeneities, which strongly influence their mechanical performances. Using poly(N,N-dimethyl acrylamide-co-methacrylic acid) hydrogels (P(DMAA-co-MAAc)) with dynamic hydrogen bonds (H-bonds) as a model system, the structural characterization has been carried out in this study using small-angle X-ray scattering (SAXS) and small-angle neutron scattering (SANS) analyses, along with exploring the influence of the structure on the mechanical properties. By systematically tuning the polymer composition, including the monomer fraction and chemical cross-linking density, two different hydrogel regions with distinct mechanical properties were observed: the swollen regions and shrunk regions. The former was mechanically weak, whereas the latter exhibited a tough behavior. Both types of hydrogels were noted to be highly heterogeneous, which results from the nanoscale spatial polymer concentration fluctuations at ∼100 nm scale. Combined with the contrast variation utilizing SANS, the structure parameters, including the polymer volume fraction of the dense and sparse regions, volume fraction occupied in the space, and average correlation length of the long-range and short-range heterogeneous structures, were explored using a scaling model based on a two-phase system composed of the densely and sparsely cross-linked regions. Using in situ SAXS, the microscopic deformation of the tough and shrunk hydrogels was noted to follow the affine deformation, while a significantly non-affine deformation was observed in the swollen hydrogels, which might have led to the different mechanical performances of these materials.

Establishing realistic exposure estimates of solitary bee larvae via pollen for use in risk assessment.

Bees foraging in agricultural habitats can be exposed to plant protection products. To limit the risk of adverse events, a robust risk assessment is needed, which requires reliable estimates for the expected exposure. The exposure pathways to developing solitary bees in particular are not well described and, in the currently proposed form, rely on limited information. To build a scaling model predicting the amount of protein developing solitary bees need based on adult body weight, we used published data on the volume of pollen solitary bees provide for their offspring. This model was tested against and ultimately updated with additional literature data on bee weight and protein content of emerged bees. We rescaled this model, based on the known pollen protein content of bee‐visited flowers, to predict the expected amount of pollen a generalist solitary bee would likely provide based on its adult body weight, and tested these predictions in the field. We found overall agreement between the models' predictions and the measured values in the field, but additional data are needed to confirm these initial results. Our study suggests that scaling models in the bee risk assessment could complement existing risk assessment approaches and facilitate the further development of accurate risk characterization for solitary bees; ultimately the models will help to protect them during their foraging activity in agricultural settings. Integr Environ Assess Manag 2022;18:308–313. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Modeling Riverine N2O Sources, Fates, and Emission Factors in a Typical River Network of Eastern China.

Estimates of riverine N2O emission contain great uncertainty because of the lack of quantitative knowledge concerning riverine N2O sources and fates. Using a 3.5-year record of monthly N2O measurements from the Yongan River network of eastern China, we developed a mass-balance model to address the riverine N2O source and sink processes. We achieved reasonable model efficacies (R2 = 0.44-0.84, Nash-Sutcliffe coefficients = 0.40-0.80) across three tributaries and the entire river system. Estimated riverine N2O loads originated from groundwater (38-88%), surface runoff (3-26%), and in-stream production (4-48%). Estimated in-stream losses via atmospheric release + complete denitrification accounted for 76, 95, 25, and 89% of riverine N2O fate for the agricultural, residential, forest, and entire river system, respectively. Considering limited complete denitrification, the model estimated an upper-bound riverine N2O emission rate of 2.65 ton N2O-N km-2 year-1 for the entire river system. Riverine N2O emission estimates were of comparable magnitude to those estimated with a power-law scaling model. Riverine N2O emissions using the IPCC default emission factor (0.26%) overestimated emissions by 3-15 times, whereas the dissolved N2O concentration-based emission factor overestimated or underestimated emissions. This study highlights the importance of combining comprehensive information on N2O sources and fates to achieve accurate riverine N2O emission estimates.

Obstruction scaling model for the diffusion of the outer electrolyte leading to Liesegang patterns of (AgNO3 + KCl) system in agarose hydrogel

Obstruction scaling model for the diffusion of the outer electrolyte leading to Liesegang patterns of (AgNO3 + KCl) system in agarose hydrogel

Improved Scaling Relationships for Seismic Moment and Average Slip of Strike-Slip Earthquakes Incorporating Fault-Slip Rate, Fault Width, and Stress Drop

ABSTRACT We develop a self-consistent scaling model relating magnitude Mw to surface rupture length (LE), surface displacement DE, and rupture width WE, for strike-slip faults. Knowledge of the long-term fault-slip rate SF improves magnitude estimates. Data are collected for 55 ground-rupturing strike-slip earthquakes that have geological estimates of LE, DE, and SF, and geophysical estimates of WE. We begin with the model of Anderson et al. (2017), which uses a closed form equation for the seismic moment of a surface-rupturing strike-slip fault of arbitrary aspect ratio and given stress drop, ΔτC. Using WE estimates does not improve Mw estimates. However, measurements of DE plus the relationship between ΔτC and surface slip provide an alternate approach to study WE. A grid of plausible stress drop and width pairs were used to predict displacement and earthquake magnitude. A likelihood function was computed from within the uncertainty ranges of the corresponding observed Mw and DE values. After maximizing likelihoods over earthquakes in length bins, we found the most likely values of WE for constant stress drop; these depend on the rupture length. The best-fitting model has the surprising form WE∝logLE—a gentle increase in width with rupture length. Residuals from this model are convincingly correlated to the fault-slip rate and also show a weak correlation with the crustal thickness. The resulting model thus supports a constant stress drop for ruptures of all lengths, consistent with teleseismic observation. The approach can be extended to test other observable factors that might improve the predictability of magnitude from a mapped fault for seismic hazard analyses.

Energy‐aware autoscaling for scientific workflow in cloud environment

SummaryThe devices used for information and communication purpose consume an increasing amount of energy. As a result, the datacenters consume a lot of energy. Due to the expanding use of cloud services, there is considerable interest in reducing the energy consumption of datacenters. Effective resource utilization techniques and reduction in energy consumption are two crucial metrics in today's cloud computing environment. Many issues come along with contradicting objectives, viz., minimizing energy consumption raising the expenses of service supply. Autoscaling features of the cloud can bundle these issues. The major hurdle for effective resource scalability is the lack of proper management of energy supply to devices of servers in the datacenter. The main objective of the article is to supply energy to devices as per the allocated job‐size on the interaction of complex energy, to increase the energy utilization of servers. Also, using renewable energy (RE) to supplement the operational energy of the cloud datacenter. In this direction, the article presents a predator‐prey‐based mathematical model for energy scaling that leverages the accessibility of RE source to decrease the high energy demands of the datacenter. It is formalized using ecological concepts of metabolism and allometric scaling. An allometric energy scaling (AES) algorithm is presented. The performance and evaluation of the proposed algorithm are implemented with the Cloudsim 4.0 simulator. The results are compared with the HEFT algorithm, and AES algorithm gives slightly better results in the case of optimum energy consumption and processing cost compared with the HEFT algorithm.

High pressure viscosity measurements of ternary (methane + propane + heptane) mixtures

Prediction of thermophysical properties for natural gas mixtures close to the mixture's critical point and cricondenbar (the maximum pressure at which two fluid phases can co-exist) is challenging but important as often natural gas processes operate close to these conditions. Here we present a comprehensive study of the viscosity of (CH4 + C3H8 + C7H16) mixtures with heptane fractions up to 15 mol%. Accurate measurements of saturated-phase and compressed-fluid (single phase) viscosities, at temperatures from 200 K to 423 K and pressures up to 35 MPa, are presented. The collected data were compared with the prediction of the extended corresponding states (ECS) model, with relative deviations spanning between (−20 to 11) % from the model. Additionally, pure component parameters needed for the residual entropy scaling (RES) model were fit to literature data and then applied predictively to mixtures viscosity without any additional fit parameters. The relative deviation of the measured viscosities from values calculated with the RES model is generally within 15%. This work demonstrates that no current model satisfactorily predict mixtures viscosity, and that high quality experimental data are needed to anchor the methods used to design and optimize natural gas processing.

Forest above-ground volume assessments with terrestrial laser scanning: a ground-truth validation experiment in temperate, managed forests.

Quantifying the Earth's forest above-ground biomass (AGB) is indispensable for effective climate action and developing forest policy. Yet, current allometric scaling models (ASMs) to estimate AGB suffer several drawbacks related to model selection and uncertainties about calibration data traceability. Terrestrial laser scanning (TLS) offers a promising non-destructive alternative. Tree volume is reconstructed from TLS point clouds with quantitative structure models (QSMs) and converted to AGB with wood basic density. Earlier studies have found overall TLS-derived forest volume estimates to be accurate, but highlighted problems for reconstructing finer branches. Our objective was to evaluate TLS for estimating tree volumes by comparison with reference volumes and volumes from ASMs. We quantified the woody volume of 65 trees in Belgium (from 77 to 2800 L; Pinus sylvestris, Fagus sylvatica, Larix decidua, and Fraxinus excelsior) with QSMs and destructive reference measurements. We tested a volume expansion factor (VEF) approach by multiplying the solid and merchantable volume from QSMs by literature VEF values. Stem volume was reliably estimated with TLS. Total volume was overestimated by +21 % using original QSMs, by +9 % and -12 % using two sets of VEF-augmented QSMs, and by -7.3 % using best-available ASMs. The most accurate method differed per site, and the prediction errors for each method varied considerably between sites. VEF-augmented QSMs were only slightly better than original QSMs for estimating tree volume for common species in temperate forests. Despite satisfying estimates with ASMs, the model choice was a large source of uncertainty, and species-specific models did not always exist. Therefore, we advocate for further improving tree volume reconstructions with QSMs, especially for fine branches, instead of collecting more ground-truth data to calibrate VEF and allometric models. Promising developments such as improved co-registration and smarter filtering approaches are ongoing to further constrain volumetric errors in TLS-derived estimates.

Performance evaluation of low-GWP refrigerants in 1–100 ton scroll compressors

• Method to scale the scroll compressor for different cooling capacities and refrigerants. • Validation of scroll compressor model in PDSim. • Performance evaluation of low-GWP refrigerants in scroll compressor. Performance evaluation of low-GWP refrigerants in scroll compressor is carried out to aid the selection of suitable refrigerant for different applications. The open-source modeling platform PDSim, used for this study, is based on the mechanistic chamber model that has the accuracy comparable to the heuristic methods. A scaling model is developed to design and select the scroll geometry for 1–100 ton range of cooling capacity and seven refrigerants. This method is based on manufacturing constraints and minimization of leakage. Additionally, the ports and the bearings are scaled to make their effect fair for a range of capacities and refrigerants. The simulation model is validated using two example scroll compressors. The predicted mass flow rate and power are within 3% MAE while the isentropic efficiency is within 4% mean absolute error. A validated model and standard AHRI conditions are used for the performance evaluation of the refrigerants over a range of 1 to 100 tons of refrigeration capacity. Seven refrigerants are studied including low-pressure refrigerants, R1234ze(E) and R1234yf, medium-pressure refrigerants, R410A, R32, R454B, and R452B and high-pressure R744. The results suggest that an optimum range exists for each refrigerant to achieve good compressor performance. The leakage area is the primary contributor to the scroll compressor performance.

Dynamic Model of Spatial Scaling of the Initial Excited State upon Reconstructive Martensitic Transformations

Dynamic Model of Spatial Scaling of the Initial Excited State upon Reconstructive Martensitic Transformations

Conductivity Estimates of Fractal Models of Geological Media

AbstractGeological media are inherently fractal over multiple length scales, exhibiting a wide range of fractal dimensions . We study the size dependent conductivity of models of geological media based on so called regular random fractals. Specifically, we consider generalizations of the classic Menger sponges where the impermeable cells can take random locations. This results, for a given random fractal generator and a given construction order, in multiple realizations of the target media, each one maintaining the same . We use direct numerical simulation to estimate the conductivity, over a number of patterns, with orders . The conductivity bounds and estimates for regular fractal media are, in general, not applicable to these random fractal models. The conductivity of a specific realization may differ from the ensemble average by a few percents, which suggests a lack of self‐averaging; however, the self‐averaging is regained if the size of the domain of interest is beyond the maximal fractality length scale. We propose a low computational cost approach for estimating the ensemble average conductivity of a given random fractal at a given order, which matches the order of magnitude predicted from more intensive calculations. Through tabulation of conductivities of generators of random fractals with small scaling factors and fitting models, we explain how these fractals can model geological media in which fractal dimensions and conductivities (or effective diffusion coefficients) are measured.

Diffusion and Viscosity of Unentangled Polyelectrolytes

We report chain self-diffusion and viscosity data for sodium polystyrene sulfonate (NaPSS) in semidilute salt-free aqueous solutions measured by pulsed-field gradient NMR and rotational rheometry, respectively. The molecular weight of NaPSS is characterized using five techniques. Relationships between Mw and the intrinsic viscosity and diffusion coefficient in excess salt are established. These are helpful for the accurate determination of the molar mass of NaPSS. The observed concentration dependence of η and D are consistent with the Rouse–Zimm scaling model if the monomeric friction coefficient (ζ) is concentration-dependent. The concentration dependence of ζ exceeds that expected from free-volume models of diffusion, and its origin remains unclear, possibly being related to electrostatic effects. Correlation blobs and dilute chains with equivalent end-to-end distances exhibit nearly equal friction coefficients, in agreement with scaling. Viscosity and diffusion data are combined using the Rouse model to calculate the single-chain dimensions of NaPSS in salt-free solution, and the results overpredict direct SANS measurements of the radii of gyration by a factor of ≃1.4.

Multi-Dimensional Scaling Analysis of Key Regulatory Genes in Prostate Cancer Using the TCGA Database.

Prostate cancer (PC) is a polygenic disease with multiple gene interactions. Therefore, a detailed analysis of its epidemiology and evaluation of risk factors can help to identify more accurate predictors of aggressive disease. We used the transcriptome data from a cohort of 243 patients from the Cancer Genome Atlas (TCGA) database. Key regulatory genes involved in proliferation activity, in the regulation of stress, and in the regulation of inflammation processes of the tumor microenvironment were selected to test a priori multi-dimensional scaling (MDS) models and create a combined score to better predict the patients’ survival and disease-free intervals. Survival was positively correlated with cortisol expression and negatively with Mini-Chromosome Maintenance 7 (MCM7) and Breast-Related Cancer Antigen2 (BRCA2) expression. The disease-free interval was negatively related to the expression of enhancer of zeste homolog 2 (EZH2), MCM7, BRCA2, and programmed cell death 1 ligand 1 (PD-L1). MDS suggested two separate pathways of activation in PC. Within these two dimensions three separate clusters emerged: (1) cortisol and brain-derived neurotrophic factor BDNF, (2) PD-L1 and cytotoxic-T-lymphocyte-associated protein 4 (CTL4); (3) and finally EZH2, MCM7, BRCA2, and c-Myc. We entered the three clusters of association shown in the MDS in several Kaplan–Meier analyses. It was found that only Cluster 3 was significantly related to the interval-disease free, indicating that patients with an overall higher activity of regulatory genes of proliferation and DNA repair had a lower probability to have a longer disease-free time. In conclusion, our data study provided initial evidence that selecting patients with a high grade of proliferation and DNA repair activity could lead to an early identification of an aggressive PC with a potentials for metastatic development.

Urban population size and road traffic collisions in Europe.

Millions of road traffic collisions take place every year, leading to significant knock-on effects. Many of these traffic collisions take place in urban areas, where traffic levels can be elevated. Yet, little is known about the extent to which urban population size impacts road traffic collision rates. Here, we use urban scaling models to analyse geographic and road traffic collision data from over 300 European urban areas in order to study this issue. Our results show that there is no significant change in the number of road traffic collisions per person for urban areas of different sizes. However, we find individual urban locations with traffic collision rates which are remarkably high. These findings have the potential to inform policies for the allocation of resources to prevent road traffic collisions across the different cities.

Rain Attenuation Scaling in South Korea: Experimental Results and Artificial Neural Network

Scaling rain attenuation parameters will significantly benefit the quick monitoring of rain attenuation in a particular channel with previously known results or in situ setup attenuation measurements. Most of the rain attenuation scaling techniques have been derived for slant links. In this study, we also applied frequency and polarization scaling techniques for terrestrial link applications. We collected real measured datasets from research paper publications and examined those datasets using International Telecommunication Union-Radiocommunication sector (ITU-R) models (P.530-17, P.618-13). Our analyzed results show that existing long-term frequency and polarization scaling rain attenuation models (ITU-R P.618-13 for slant links and ITU-R P.530-17 for terrestrial links) show reduced performance for frequency and polarization scaling measured locations in South Korea. Hence, we proposed a new scaling technique using artificial neural networks from the measured rain attenuation data of slant and terrestrial links in South Korea. The experimental results confirm that the proposed Artificial Neural Network (ANN)-based scaling model shows satisfactory performance to predict attenuation for frequency and vertical polarization scaling.

Effect of Viscosity and Scale on De-/Anti-Icing Fluid Flow-Off

The flow-off process of de-/anti-icing fluid on a flat plate subjected to an accelerating airflow was studied both experimentally and using computational fluid dynamics (CFD) simulations. The effect of fluid viscosity on the fluid flow-off was examined experimentally in a wind tunnel. Two models with different chords (0.6 and 1.8 m) were experimented with. Type I fluid with different viscosities and Type IV fluids were tested. The CFD simulations considered only 0.6 m plate model. The effect of viscosity alteration causes an ensemble of consequences, which together caused a delay and decrease in the initial flow-off rate. These are the alterations in the wind tunnel speed for wave onset, in the wave speeds and in the flow-off process at the trailing edge. The CFD simulations supported most of the reasoning for fluid viscosity effects on fluid flow-off. However, the effect of viscosity was considerably exaggerated in simulations. Based on a simplified relation between air velocity and fluid flow-off rate, a scaling model for wind tunnel tests was created. A dimensionless parameter was found to scale the model dimensions and to consider the wind tunnel speed sequence.