Final Scaling Research Articles

Ejecta splashing and scaling of projectile oblique impact on granular media

Ejecta splashing is accompanied by the formation of impact craters in oblique impact of a sphere onto a granular target. We investigated the morphology and scaling of the ejection, together with the evolution and final size of crater by performing a series of experiments, varying the impact angle θ and impact speed V0. The experiment categorized the crater shapes in the space parameters Fr and θ and revealed that the maximum ejecta height exhibits two regimes related to Froude number, while the crater length, width, and depth are all collapsed to a master line. Then, the evolution characteristics of the corolla dimensions (top diameter, neck size, bottom diameter, and height) are determined. Moreover, a simple ballistic model taking into account the air drag force acting on the ejecta has been proposed to predict the dynamic processes of the corolla in oblique impacts. Furthermore, the opening of the crater formation deduced by the dynamics of the corolla formed and the collapsing process (i.e., the splashed sand avalanching down along the wall of the crater) have been investigated in detail using a simplified Bouchaud–Cates–Ravi–Edwards model. Our theoretical model demonstrated high accuracy in reproducing the evolution of a crater during impacting and in predicting the final crater scaling after avalanching.

Research on image scaling algorithm for granular image detection

AbstractIn order to improve the accuracy of granular image detection during image scaling, an image scaling algorithm combining the interpolation algorithm of protective features and Kalman filtering of neurons is proposed. Firstly, the interpolation algorithm of protective features is de‐designed according to the phenomenon of sudden change of edge grey values, and the difference and trend of grey values in horizontal and vertical directions are used to obtain the pre‐scaled image with maximum contrast. Then the grey value data input of the pre‐scaled image is introduced into the Kalman filter of neurons, and the filtering process is optimized by using the black‐box thinking of neurons, and the pre‐scaled image is smoothed. Finally, the scale transformation is implemented to obtain the final grey value to complete the final scaling, so that the image has both visual experience and features. Comparison with mainstream image scaling algorithms shows that the proposed algorithm can effectively overcome the degradation of granularity image detection accuracy due to image scaling, with point acutance value (PAV) improved by 10%–41%, and the granularity detection error caused by image scaling algorithms reduced from about 0.7% to about 0.1%, with a relative improvement of 85%.

Validation of symmetry-induced high moment velocity and temperature scaling laws in a turbulent channel flow.

The symmetry-based turbulence theory has been used to derive new scaling laws for the streamwise velocity and temperature moments of arbitrary order. For this, it has been applied to an incompressible turbulent channel flow driven by a pressure gradient with a passive scalar equationcoupled in. To derive the scaling laws, symmetries of the classical Navier-Stokes and the thermal energy equationshave been used together with statistical symmetries, i.e., the statistical scaling and translation symmetries of the multipoint moment equations. Specifically, the multipoint moments are built on the instantaneous velocity and temperature fields other than in the classical approach, where moments are based on the fluctuations of these fields. With this instantaneous approach, a linear system of multipoint correlation equationshas been obtained, which greatly simplifies the symmetry analysis. The scaling laws have been derived in the limit of zero viscosity and heat conduction, i.e., Re_{τ}→∞ and Pr>1, and they apply in the center of the channel, i.e., they represent a generalization of the deficit law, thus extending the work of Oberlack etal. [Phys. Rev. Lett. 128, 024502 (2022)0031-900710.1103/PhysRevLett.128.024502]. The scaling laws are all power laws, with the exponent of the high moments all depending exclusively on those of the first and second moments. To validate the new scaling laws, the data from a large number of direct numerical simulations (DNS) for different Reynolds and Prandtl numbers have been used. The results show a very high accuracy of the scaling laws to represent the DNS data. The statistical scaling symmetry of the multipoint moment equations, which characterizes intermittency, has been the key to the new results since it generates a constant in the exponent of the final scaling law. Most important, since this constant is independent of the order of the moments, it clearly indicates anomalous scaling.

Subdiffusive dynamics and hydrodynamic fluctuations: how the latter affect the former.

The characteristics of subdiffusion are influenced by hydrodynamic fluctuations, not the scaling of the mean square displacement (MSD) at the long time limit, but rather the transition of this property from ballistic behaviour at early times to its final scaling at large times. Additionally, since a significant portion of the normalised velocity autocorrelation function (NVAF), a widely used motion descriptor, no longer adequately describes the antipersistent character that is typical of a subdiffusive motion, it is also impacted by these fluctuations. The combined findings can lead to misleading conclusions if hydrodynamic fluctuations are not taken into account. Diffusing and vorticity time scales are crucial for the way the motion turns into the final subdiffusion dynamics, whose exponent is determined by the scaling of the friction.

The Morphology-dependent Black Hole–Host Galaxy Correlations: A Consequence of Physical Formation Processes

For decades, astronomers have been investigating how the central supermassive black hole (BH) may govern the host galaxy’s properties and vice versa. Our work adds another step to this study. We have performed state-of-theart 2D modeling and multi-component photometric decompositions of the largest-to-date sample of galaxies with dynamically-measured black hole masses (MBH). The multi-component decomposition allows us to accurately extract the bulge (spheroid) stellar luminosity/mass and structural parameters (also for other galaxy components) and provides detailed galaxy morphologies. We investigated the correlations between MBH and various host galaxy properties, including the bulge (M*,sph) and total galaxy (M*,gal) stellar masses discussed here. Importantly, we analyzed the role of galaxy morphology in these correlations. Our work reveals that the BH scaling relations depend on galaxy morphology and thus depend on the galaxy’s formation and evolution physics. Here we discuss that in the MBH–M*,sph diagram, early-type galaxies (ETGs) with a disk, ETGs without a disk, and late-type galaxies (LTG-spirals) define distinct relations, with quadratic slopes but different zero-points. We also review the MBH–M*,gal relation, where ETGs and LTGs define different relations. Notably, the existence of the MBH–M*,gal relations enables one to quickly estimate MBH in other galaxies without going through the multi-component decomposition process to obtain M*,sph. The final morphology-dependent black hole scaling relations provide tests for morphology-aware simulations of galaxies with a central BH and hold insights for BH-galaxy co-evolution theories based on BH accretion and feedback.

Stoichiometric interactions explain spindle dynamics and scaling across 100 million years of nematode evolution.

The spindle shows remarkable diversity, and changes in an integrated fashion, as cells vary over evolution. Here, we provide a mechanistic explanation for variations in the first mitotic spindle in nematodes. We used a combination of quantitative genetics and biophysics to rule out broad classes of models of the regulation of spindle length and dynamics, and to establish the importance of a balance of cortical pulling forces acting in different directions. These experiments led us to construct a model of cortical pulling forces in which the stoichiometric interactions of microtubules and force generators (each force generator can bind only one microtubule), is key to explaining the dynamics of spindle positioning and elongation, and spindle final length and scaling with cell size. This model accounts for variations in all the spindle traits we studied here, both within species and across nematode species spanning over 100 million years of evolution.

Artificial intelligence assisted bone lesion detection and classification in computed tomography scans of prostate cancer patients.

e17567 Background: Patients diagnosed with prostate cancer undergo computed tomography (CT) for pretreatment staging to rule out bone metastases. However, detection and classification of bone lesions on CT is challenging and subject to inter-reader variability. We present a cascaded deep learning algorithm for automatic detection and classification of bone lesions on staging CT in patients diagnosed with prostate cancer. Methods: CT scans from 56 patients with histopathologically proven prostate cancer were included. An expert radiologist annotated the extent of individual bone lesions (N = 4217) and labelled all regions as either benign or malignant. All scans were anonymized and normalized at the patient-level prior to training. Our method can be described as a two-stage framework, 1) A detection algorithm: Inspired by Yolo-v3 detection method, we designed a network with a backbone of darknet-53 pretrained on Coco dataset and four final scaling blocks to compensate for wide range of lesion diameters, 2) A classification algorithm: we formed a binary classifier based on ResNet-50 pretrained using the ImageNet dataset. We used a train/validation split equal to 90%/10% for this study. To facilitate the learning process, horizontal flipping, relative zooming and mean weighted averaging were used for data augmentation in stage 1. Instead, the classification algorithm took advantage of synthesized patches generated by Deep Convolutional Generative Adversarial Network (DC-GAN) for augmentation. Results: We could achieve a real-time (~120ms per slice) performance on our validation set with a median penalty of 0.3(0.02-0.78) false positives per true positive within each patient. Overall performance of our detection algorithm was 81% sensitivity and 86% positive predictive value. In stage 2, we obtained an accuracy of 89% for correct classification of benign from malignant bone lesions with no augmentation which was improved to 91% when we incorporated the augmented data for training. Conclusions: Our 2-stage algorithm sequentially detects and classifies bone lesions on CT of prostate cancer patients with a significant performance. To further improve our results and for generalizability we are accruing more data from different centers. Eventually, with greater dataset, both algorithms will be cascaded and trained as a whole unit to become one single tool for fully automatic detection and classification which serves as an aid for radiologists who read the staging CTs.

Leading-order Stokes flows near a corner

Singular solutions of the Stokes equations play important roles in a variety of fluid dynamics problems. They allow the calculation of exact flows, are the basis of the boundary integral methods used in numerical computations, and can be exploited to derive asymptotic flows in a wide range of physical problems. The most fundamental singular solution is the flow's Green function due to a point force, termed the Stokeslet. Its expression is classical both in free space and near a flat surface. Motivated by problems in biological physics occurring near corners, we derive in this paper the asymptotic behaviour for the Stokeslet both near and far from a corner geometry by using complex analysis on a known double integral solution for corner flows. We investigate all possible orientations of the point force relative to the corner and all corner geometries from acute to obtuse. The case of salient corners is also addressed for point forces aligned with both walls. We use experiments on beads sedimenting in corn syrup to qualitatively test the applicability of our results. The final results and scaling laws will allow to address the role of hydrodynamic interactions in problems from colloidal science to microfluidics and biological physics.

Free Final Time Input Design Problem for Robust Entropy-Like System Parameter Estimation.

In this paper, a novel method is proposed to design a free final time input signal, which is then used in the robust system identification process. The solution of the constrained optimal input design problem is based on the minimization of an extra state variable representing the free final time scaling factor, formulated in the Bolza functional form, subject to the D-efficiency constraint as well as the input energy constraint. The objective function used for the model of the system identification provides robustness regarding the outlying data and was constructed using the so-called Entropy-like estimator. The perturbation time interval has a significant impact on the cost of the real-life system identification experiment. The contribution of this work is to examine the economic aspects between the imposed constraints on the input signal design, and the experiment duration while undertaking an identification experiment in the real operating conditions. The methodology is applicable to the general class of systems and was supported by numerical examples. Illustrative examples of the Least Squares, and the Entropy-Like estimators for the system parameter data validation where measurements include additive white noise are compared using ellipsoidal confidence regions.

Lepton number violation at colliders from kinematically inaccessible gauge bosons

We reevaluate the necessity of W_R gauge bosons being kinematically accessible to test the left–right symmetric model (LRSM) at hadron colliders. In the limit that W_R are too heavy, resonant production of sub-TeV Majorana neutrinos N can still proceed at the Large Hadron Collider (LHC) via the process pprightarrow W_R^{pm *}rightarrow N ell ^pm rightarrow ell ^pm ell ^pm +nj if mediated by a far off-shell W_R. Traditional searches strategies are insensitive to this regime as they rely on momenta of final states scaling with TeV-scale M_{W_R}. For such situations, the process is actually kinematically and topologically identical to the direct production (DP) process pprightarrow W_mathrm{SM}^{pm *} rightarrow N ell ^pm rightarrow ell ^pm ell ^pm +nj. In this context, we reinterpret sqrt{s}=8 TeV LHC constraints on DP rates for the minimal LRSM. For m_N = 200–500 GeV and right–left coupling ratio kappa _R = g_R/g_L, we find (M_{W_R} / kappa _R)> 1.1–1.8 TeV at 95% CLs. Expected sensitivities to DP at 14 (100) TeV are also recast: with mathscr {L}=1~(10) ab^{-1}, one can probe (M_{W_R} / kappa _R) < 7.9–8.9 (14–40) TeV for m_N = 100–700 (1200) GeV, well beyond the anticipated sensitivity of resonant W_R searches. Findings in terms of gauge invariant dimension-six operators with heavy N are also reported.

Effects of cytochrome P450 3A4 and non-genetic factors on initial voriconazole serum trough concentrations in hematological patients with different cytochrome P450 2C19 genotypes

1. Polymorphisms of cytochrome P450 2C19 (CYP2C19) is an important factor contributing to variability of voriconazole pharmacokinetics. Polymorphisms of CYP3A4, CYP3A5, CYP2C9 and non-genetic factors such as age, gender, body mass index (BMI), transaminase levels, concomitant medications might also affect voriconazole initial steady serum trough concentration (VICmin) in haematological patients, but the effects were not clear.2. Eighteen single-nucleotide polymorphisms in CYP2C19, CYP3A4, CYP3A5, CYP2C9 were genotyped. Patients were stratified into two groups according to CYP2C19 genotype. Group 1 were patients with CYP2C19*2 or CYP2C19*3, and Group 2 were homozygous extensive metabolizers. The effects were studied in different groups. VICmin was adjusted on daily dose (VICmin/D) for overcoming effect of dose.3. A total of 106 blood samples from 86 patients were included. In final optimal scaling regression models, polymorphisms of rs4646437 (CYP3A4), age, BMI was identified to be factors of VICmin/D in Group 1 (R2 = .255, p < .001). Only age was confirmed as a factor of VICmin/D in Group 2 (R2 = 0.144, p = .021).4. Besides polymorphisms of CYP2C19, in individualized medication of voriconazole in haematological patients, polymorphisms of CYP3A4, and non-genetic factors as BMI, age should also be taken into account, especially for individuals with CYP2C19*2 or CYP2C19*3.

Rheological Characterization and CFD Simulation of Soy White Flakes Based Dough in a Single Screw Extruder

AbstractUnderstanding the rheological properties such as shear profile, viscosity of a dough inside the extruder is very important for product development, process control, final product quality and scaling up operations. This study aims to characterize the rheological properties of high‐protein dough and perform isothermal flow simulation in a complex geometry for generalized Newtonian fluids. The flow of soy white flakes based dough in a single screw extruder was simulated by using computational fluid dynamics. Process conditions considered were screw speeds (40, 80, 120, 160 and 200 rpm), barrel temperature (100, 120 and 140C) and soy white flakes contents (30, 40 and 50% db). A mesh superposition technique was used to reduce the geometrical complexity. Simulation results were validated quantitatively by experimental data. The results showed good agreement between experimental and computational results. Moreover, the flow profile in the extruder was analyzed by using the influence of screw speed and level of soy white flakes content. Qualitative behavior of local shear rate and viscosity along the screw are analyzed and comparisons of different process conditions are presented. The results of these simulations can be used to optimize processing conditions and also to improve the product quality of extrudates.Practical ApplicationsThe flow of material within the extruder is complicated due to its helical screw configuration and the different zones of solids‐conveying, melting and melts conveying. Shear profile and viscosity of dough within the extruder directly influences the product quality. In the present study, rheological characterization of dough inside the extruder was done by using online capillary die rheometer. The flow of dough during extrusion processing was simulated using computational fluid dynamics. The results of the simulation can be used to optimize the extrusion process influenced by complex flows of relatively high concentration of soy white flakes based dough in an extruder and also to improve the product quality.

Melodic interval perception by normal-hearing listeners and cochlear implant users.

The perception of melodic intervals (sequential pitch differences) is essential to music perception. This study tested melodic interval perception in normal-hearing (NH) listeners and cochlear implant (CI) users. Melodic interval ranking was tested using an adaptive procedure. CI users had slightly higher interval ranking thresholds than NH listeners. Both groups' interval ranking thresholds, although not affected by root note, significantly increased with standard interval size and were higher for descending intervals than for ascending intervals. The pitch direction effect may be due to a procedural artifact or a difference in central processing. In another test, familiar melodies were played with all the intervals scaled by a single factor. Subjects rated how in tune the melodies were and adjusted the scaling factor until the melodies sounded the most in tune. CI users had lower final interval ratings and less change in interval rating as a function of scaling factor than NH listeners. For CI users, the root-mean-square error of the final scaling factors and the width of the interval rating function were significantly correlated with the average ranking threshold for ascending rather than descending intervals, suggesting that CI users may have focused on ascending intervals when rating and adjusting the melodies.

Scaling behavior of universal pinch-off in two-dimensional foam

We study the power-law scaling behavior and pinch-off morphology of two-dimensional bubble rafts under tension. As a function of pulling speed, we observe two distinct pinch-off morphologies that have been observed in other fluid systems: long threads (LT) and double-cone (DC). At any given pulling speed, there is a nonzero probability of observing LT or DC, with the probability of observing LT modes increasing with pulling velocity. The bubble rafts are composed of millimeter scale bubbles, and we are able to directly observe pinch-off to the point of final separation and measure the scaling of the minimum width in time. For both the LT and DC modes, the final scaling regime before pinch-off exhibits a universal power-law scaling behavior, with power-law fitting exponents of 0.73 ± 0.01. However, the final cone angle is different for states that initially exhibit LT or DC pinch-off, and for the LT case, the final scaling is best described as a local double-cone mode.

Experimental study of counter-rotating vortex pair trajectories induced by a round jet in cross-flow at low velocity ratios

Circular flush Jets In Cross-Flow were experimentally studied in a water tunnel using Volumetric Particle Tracking Velocimetry, for a range of jet to cross-flow velocity ratios, r, from 0.5 to 3, jet exit diameters d from 0.8 to 1 cm and cross-flow boundary layer thickness δ from 1 to 2.5 cm. The analysis of the 3D mean velocity fields allows for the definition, computation and study of Counter-rotating Vortex Pair trajectories. The influences of r, d and δ were investigated. A new scaling based on momentum ratio r m taking into account jet and cross-flow momentum distributions is introduced based on the analysis of jet trajectories published in the literature. Using a rigorous scaling quality factor Q to quantify how well a given scaling successfully collapses trajectories, we show that the proposed scaling also improves the collapse of CVP trajectories, leading to a final scaling law for these trajectories.

Charge-based nonvolatile memory: Near the end of the roadmap?

The floating gate cell has been the workhorse for nonvolatile memories for over 40 years now. Indeed, the original concept as proposed by Kahng and Sze in 1967 [1] has survived the subsequent generations of nonvolatile memory types going from EPROMs and One-Time-Programmable (OTP) memories to EEPROMs and finally ending with the major success technology based on the same concept: Flash memory. The success of Flash has recently made it into the technology driver for the entire silicon industry, not in the least in the area of lithography. However, with this major success, final scaling limitations come into sight at an increasingly more rapid pace and several red brick walls have been identified on the not-so-far horizon. This paper will elaborate on these limitations and challenges and will also propose solutions or onsets of solutions to allow for further conceptual improvement in the area of these charge-based memories with long-term data retention.

Anomalous scaling of a passive vector advected by the Navier–Stokes velocity field

Using the field theoretic renormalization group and the operator-product expansion, the model of a passive vector field (a weak magnetic field in the framework of the kinematic MHD) advected by the velocity field which is governed by the stochastic Navier–Stokes equation with the Gaussian random stirring force δ-correlated in time and with the correlator proportional to k4−d−2ε is investigated to the first order in ε (one-loop approximation). It is shown that the single-time correlation functions of the advected vector field have anomalous scaling behavior and the corresponding exponents are calculated in the isotropic case, as well as in the case with the presence of large-scale anisotropy. The hierarchy of the anisotropic critical dimensions is briefly discussed and the persistence of the anisotropy inside the inertial range is demonstrated on the behavior of the skewness and hyperskewness (dimensionless ratios of correlation functions) as functions of the Reynolds number Re. It is shown that even though the present model of a passive vector field advected by the realistic velocity field is mathematically more complicated than, on one hand, the corresponding models of a passive vector field advected by ‘synthetic’ Gaussian velocity fields and, on the other hand, than the corresponding model of a passive scalar quantity advected by the velocity field driven by the stochastic Navier–Stokes equation, the final one-loop approximate asymptotic scaling behavior of the single-time correlation or structure functions of the advected fields of all models are defined by the same anomalous dimensions (up to normalization).

A preconditioned Newton algorithm for the nearest correlation matrix

Various methods have been developed for computing the correlation matrix nearest in the Frobenius norm to a given matrix. We focus on a quadratically convergent Newton algorithm recently derived by Qi and Sun. Various improvements to the efficiency and reliability of the algorithm are introduced. Several of these relate to the linear algebra: the Newton equations are solved by minres instead of the conjugate gradient method, as it more quickly satisfies the inexact Newton condition; we apply a Jacobi preconditioner, which can be computed efficiently even though the coefficient matrix is not explicitly available; an efficient choice of eigensolver is identified; and a final scaling step is introduced to ensure that the returned matrix has unit diagonal. Potential difficulties caused by rounding errors in the Armijo line search are avoided by altering the step selection strategy. These and other improvements lead to a significant speedup over the original algorithm and allow the solution of problems of dimension a few thousand in a few tens of minutes.

Polarizable empirical force field for nitrogen‐containing heteroaromatic compounds based on the classical Drude oscillator

The polarizable empirical CHARMM force field based on the classical Drude oscillator has been extended to the nitrogen-containing heteroaromatic compounds pyridine, pyrimidine, pyrrole, imidazole, indole, and purine. Initial parameters for the six-membered rings were based on benzene with nonbond parameter optimization focused on the nitrogen atoms and adjacent carbons and attached hydrogens. In the case of five-member rings, parameters were first developed for imidazole and transferred to pyrrole. Optimization of all parameters was performed against an extensive set of quantum mechanical and experimental data. Ab initio data were used for the determination of initial electrostatic parameters, the vibrational analysis, and in the optimization of the relative magnitudes of the Lennard-Jones (LJ) parameters, through computations of the interactions of dimers of model compounds, model compound-water interactions, and interactions of rare gases with model compounds. The absolute values of the LJ parameters were determined targeting experimental heats of vaporization, molecular volumes, heats of sublimation, crystal lattice parameters, and free energies of hydration. Final scaling of the polarizabilities from the gas-phase values by 0.85 was determined by reproduction of the dielectric constants of pyridine and pyrrole. The developed parameter set was extensively validated against additional experimental data such as diffusion constants, heat capacities, and isothermal compressibilities, including data as a function of temperature.

Assessing clinically meaningful change following a programme for managing chronic pain

Objectives: (1) To identify criteria for clinically meaningful change scores in commonly used measures of pain and related disability, using Goal Attainment Scaling as an external indicator of success. (2) To investigate the chances of achieving these scores following a pain management programme versus remaining on the waiting list. Design: Participants were assessed on entry to waiting list, on admission and at follow-up from the pain management programme. Three groups of Goal Attainment Scaling scores (-1.0, +1) were created from final Goal Attainment Scaling achievements. Mean scores on other measures were analysed in relation to Goal Attainment Scaling score groups by ANOVA. Differences in numbers achieving clinically meaningful changes when on the pain management programme or waiting list were compared. Subjects: Chronic musculoskeletal pain participants (N = 73) attending a rehabilitation centre, mean age (range) 44.8 (24—70) years, mean age (range) 44.8 (24—70), mean pain duration 7.7 (1—32) years. Intervention: Three-week (15-day) pain management programme based on cognitive behavioural principles. Measures: McGill Pain Questionnaire, 0—10 Pain Intensity Numerical Rating Scale (NRS), Oswestry Disability Questionnaire (ODQ), General Health Questionnaire (GHQ), 5 minute walk, 1 minute sit/stand, 1 minute stair-climbing, and Goal Attainment Scaling (GAS). Results: Mean change scores differed significantly for three GAS groups and were highest in the most successful (+1) group. These scores were used to define clinically meaningful changes on the NRS (-3), ODQ (-12), walk (+87) and stairs (+14). Significantly more participants on the pain management programme achieved these scores than those on the waiting list. Conclusion: Using GAS as a criterion of patient-perceived improvement enabled identification of clinically meaningful changes on some other common measures. These successfully differentiated achievement between patients on the pain management programme and those on the waiting list.