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Accurate predictions of bus service time are a prerequisite to improve the efficiency of bus transit. Field observations identified the degree of passenger crowding on the bus as one of the primary causes for the unpredictability of passengers' average boarding time (ABT). Consequently, the internal areas of buses were divided for the first time to assess the impact of the passenger density distribution (PDD) on the ABT, using field data. An effective BPR function was proposed that accurately predicts the passengers' ABT. Then, to show the influence of passenger movement preference and density distribution on ABT, a new floor field model was developed. Calibration and validation results indicate that the model can reproduce the dynamic moving process of passengers' distribution on the bus and clarify the influence of PDD on ABT. Finally, three bus design strategies are proposed to enhance boarding efficiency, and the simulation results show that the optimal strategy improves passenger ABT and improve the operational performance of bus transit. These findings provide theoretical support for bus design as well as for bus operation.

Nitrogen (N), magnesium (Mg), and potassium (K) deficiency all result in the decrease of chlorophyll density (CH.D) in cucumber leaf, but it is difficult to differentiate N/Mg/K-deficient leaves using CH.D. New nutrient indicators based on CH.D distribution features of the whole cucumber leaf were proposed to simultaneously diagnose N/Mg/K-deficient cucumber plants. CH.D distribution map in N/Mg/K-deficient and control leaves were determined non-destructively using hyperspectral imaging with the wavelength range of 430–960 nm. Compared with the CH.D distribution map of control group leaves, a decrease in CH.D could be observed on the whole area of N-deficient leaves, Mg-deficient leaves presented pixels with low CH.D between main leaf vein, and pixels with low CH.D at the border of K-deficient leaves. Distribution features were extracted from the CH.D distribution map and were employed to diagnose N/Mg/K-deficient leaves simultaneously, with the diagnostics rates of 96.67%. The results indicated that CH.D distribution features can realize the simultaneous diagnosing in the early stage of N/Mg/K deficiency and timely guidance of top dressing is of great significance to increase yield.

We propose vector modes based on inhomogeneously polarized Hermite–Gaussian (HG) vector beams, providing complete structural conservation of the beams during propagation. Like uniformly polarized mode beams, these beams provide structural stability (or invariance) of both the intensity and the polarization state, in turn ensuring the stability of other field characteristics, including the angular momentum. We determine the conditions imposed on the HG mode composition in the transverse components of the electromagnetic field in order to control the three-dimensional characteristics of the field, such as intensity, polarization, and spin angular momentum (SAM). For the visual analysis of the polarization state of inhomogeneously polarized beams, we use the transverse distribution of the vector of three Stokes parameters. The correspondence of the third Stokes parameter to the distribution of the longitudinal component of the SAM is used for experimental measurements. The theoretical analysis is clearly illustrated by numerical simulations and confirmed by experimental results.

Population management of herbivores is widely applied to decrease damage to forests in the northern hemisphere. Culling more antlerless deer, including females and fawns, is an effective means of reducing the population and helps to improve management efficiency. To increase the efficiency of antlerless-biased culling, we assessed the spatiotemporal distribution of the antlerless ratio in culled sika deer (Cervus nippon) in relation to population density. We hypothesized that the antlerless ratio is higher at the center of the distribution than at the margins of the deer’s range, because dispersal processes differ according to sex and age: Young male deer first disperse into an unoccupied area, and then males may become established in the new area for approximately 10–15 years before the number of females increases. A statistical model revealed spatiotemporal changes in the antlerless ratio of culled sika deer. The change in the ratio basically fit the density distribution of the deer, which was estimated independently on the basis of fecal pellet count surveys. The antlerless ratio estimated from the model increased asymptotically as deer density rose. The results support our hypothesis and suggest that antlerless sika deer will be more easily culled at the center rather than at the margins of the distribution range. These findings should help to increase the efficiency of managing the deer via antlerless-biased culling.

Biomass and species composition of demersal fish in the bottom biotopes of Peter the Great Bay (Japan Sea) are considered on the data of 2428 trawl catches in 36 surveys conducted by Pacific Res. Inst. of Fisheries and Oceanography (TINRO) in 1978–2009. The most common 20 species are ranked, as the basis of ichthyocenoses, by areas of the bay. The long-term mean total biomass of fish in the bay is estimated as 75,500 t. Arabesque greenling Pleurogrammus azonus, japanese flounder Pseudopleuronectes yokohamae and saffron cod Eleginus gracilis are distinguished by the highest mean biomass. Mean density of fish distribution varied from 6.2 to 19.4 t/km2. It was the highest in the middle Ussuri Bay (13.95 t/km2; mean fish biomass in the area 18,230 t) and in the estuarine areas. Besides, the data on long-term mean biomass of benthos collected in the same trawl surveys and zooplankton sampled in 117 plankton surveys in 1988–2013 are presented.

We studied the temperature-dependent behavior of dark solitons in superfluid Fermi gases along the BCS–BEC crossover by solving the finite-temperature Bogoliubov-de Gennes equations. The notch depth of the soliton density distribution decreases with the increase in temperature in the whole BCS–BEC crossover. In particular, the notch depth has an obvious different temperature-dependent behavior from the BCS regime to the BEC regime, i.e, it has a concave function in the BCS regime, linear function in the unitary regime and convex function in the BEC regime.

The accelerated failure time mixture cure (AFTMC) model is widely used for survival data when a portion of patients can be cured. In this paper, a Bayesian semiparametric method is proposed to obtain the estimation of parameters and density distribution for both the cure probability and the survival distribution of the uncured patients in the AFTMC model. Specifically, the baseline error distribution of the uncured patients is nonparametrically modeled by a mixture of Dirichlet process. Based on the stick-breaking formulation of the Dirichlet process, the techniques of retrospective and slice sampling, an efficient and easy-to-implement Gibbs sampler is developed for the posterior calculation. The proposed approach can be easily implemented in commonly used statistical softwares, and its performance is comparable to fully parametric method via comprehensive simulation studies. Besides, the proposed approach is adopted to the analysis of a colorectal cancer clinical trial data.

This paper studies the influence of water systems and roads on the distribution of the western Sichuan Linpan in Deyuan Town of Chengdu City in China. The amount and ratio of Linpan in a specific buffer zone were calculated and analyzed by buffer analysis, and the specific distance that each density distribution zone of Linpan away from water systems and roads was determined. Based on these above data, the effects of the distribution of water systems and roads on the distribution of Linpan were studied quantitatively. It is found that most of the Linpans are distributed in the area of 0–60 m from the water system and 0–40 m from the road. Linpan tends to be located close to the water systems and roads. And through analysis, it is found that the optimal distribution distance of Linpan is 10–20 m and 30–40 m from the water system and less than 5 m from the road. Through quantitative analysis of the impact of water systems and roads on the distribution of Linpan settlements, it provides important theoretical support for the further guiding the site selection of the Linpan center, the construction of surrounding villages, and township land planning and improvement.

[Correction Notice: An Erratum for this article was reported in Vol 115(6) of Journal of Personality and Social Psychology (see record 2018-63189-002). In the article, the original supplemental material has been revised to include a clarifying note to the Tests of model fit over larger sample (Samples C-G) section and post-peer review analyses added to the Post-peer review Factor Analytic Tests section. All versions of this article have been corrected.] Philosophers and behavioral scientists refer to wisdom as unbiased reasoning that guides one toward a balance of interests and promotes a good life. However, major instruments developed to test wisdom appear biased, and it is unclear whether they capture balance-related tendencies. We examined whether shifting from global, de-contextualized reports to state-level reports about concrete situations provides a less biased method to assess wise reasoning (e.g., intellectual humility, recognition of uncertainty and change, consideration of the broader context at hand and perspectives of others, integration of these perspectives or compromise), which may be aligned with the notion of balancing interests. Results of a large-scale psychometric investigation (N = 4,463) revealed that the novel Situated WIse Reasoning Scale (SWIS) is reliable and appears independent of psychological biases (attribution bias, bias blind spot, self-deception, and impression management), whereas global wisdom reports are subject to such biases. Moreover, SWIS scores were positively related to indices of living well (e.g., adaptive emotion regulation, mindfulness), and balancing of cooperative and self-protective interests, goals (influence-vs.-adjustment), and causal inferences about conflict (attribution to the self-vs.-other party). In contrast, global wisdom reports were unrelated or negatively related to balance-related measures. Notably, people showed modest within-person consistency in wise reasoning across situations or over time, suggesting that a single-shot measurement may be insufficient for whole understanding of trait-level wisdom. We discuss theoretical and practical implications for research on wisdom, judgment and decision making, well-being, and prosociality. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Reported in this paper is an exercise that contributes to the fire load database for fire severity analysis. The movable fuel load data was collected by the weight-inventory method from a specific building type, namely school buildings located within the metropolitan area of Sydney, Australia. The data was analysed to obtain statistical descriptions of fire load density in terms of probability density distributions. The results were compared with the similar data obtained from other countries. It was found that while basic statistical characteristics show similarities globally, some other characteristics, particularly the 90th percentile, may differ from one country to the other. This outcome suggests that fire load selection for design fires in fire safety engineering design and assessment should be better based on local data and a careful review of the unified approach in the international fire engineering guidelines is warranted.

The elastic scattering angular distributions of the weakly bound $${}^{9}$$ Be projectile by $${}^{27}$$ Al, $${}^{64}$$ Zn, $${}^{89}$$ Y, $${}^{120}$$ Sn, and $${}^{208}$$ Pb target nuclei at various incident energies are analyzed within the framework of optical model-based double-folding model. The aim is to examine the sensitivity of the elastic scattering cross sections to different density distributions of the projectile nucleus. For this purpose, the real part of the optical potantial was obtained for five different projectile density distributions, namely Moszkowski, Gupta 1, Gupta 2, Schechter, and Ngo–Ngo density distributions. The imaginary part is taken as the Woods-Saxon potential. The theoretical results are in good agreement with the experimental data.

PurposeIn order to explore the damaging effect of behind-armor debris of explosively formed projectile (EFP) attack on the top armor of tank and the internal parts of vehicles, a method of damage probability calculation based on experiments is proposed.Design/methodology/approachThe equivalent target structure of rear-effect damage of the equipment and personnel in the vehicle is determined based on the analysis of the vulnerability of internal equipment and personnel in the tank. The experimental scheme to obtain the density distribution of behind-armor debris is designed, and the calculation model of the damage probability of cavitating antipersonnel debris to the key components of the vehicle is given in the range of scattering angles and different broken pieces.FindingsThe examples show that the damage probability calculation model can be used in the process of evaluating the damage of the equipment and personnel in the tank by behind-armor debris.Originality/valueAn experimental model based on the analysis of the vulnerability of the equipment and personnel is proposed to calculate the damage probability from debris falling on the equipment and personnel in the vehicle. The results are of great value to the calculation of damage evaluation of the equipment and personnel in the tank.

Clustering is an important part of data mining. The existing clustering algorithm failed in the data set with uneven density distribution. In this paper, we propose a novel clustering algorithm relative density-based clustering algorithm for identifying diverse density clusters effectively called IDDC. It can effectively identify clusters in data sets with different densities and can also handle outliers. We first compute relative density for each data point. Then, the density peak points are screened and the initial clusters are obtained according to these peak points. The strategy for assigning the remaining points is to find unallocated points from the perspective of the cluster, which can effectively identify different density. In experiments, we compare the proposed algorithm IDDC with some existing algorithms on synthetic and real-world data sets. The results show that IDDC performs better than those existing algorithms, especially clustering on data set with uneven density distribution.

Molecular models of pristine graphene (GN) and GN with Thrower–Stone–Wales (TSW) defect-reinforced polymethyl methacrylate (PMMA) composites were established. The pure PMMA matrix was developed as a benchmark to study the effect of TSW defective GN (TSW-GN) on the glass transition temperature (Tg) of PMMA composites based on molecular dynamics simulations. The Tg values of these composites were obtained by fitting the scatter plots of the temperature versus the specific volume of the models. The results showed that the introduction of TSW defects can effectively increase the Tg of the PMMA composites. Additionally, the Tg of the PMMA composites gradually increased with an increase in TSW defects on the GN surface. The interaction energy between the TSW-GN and PMMA matrix, the density distribution of PMMA, the mean square displacements of the PMMA chains, and the free volume of these models were analyzed to understand the internal mechanisms with respect to the variations in the Tg from an atomic perspective. It can be concluded that the appropriate introduction of TSW-GN can improve the upper limit of the applied temperature of PMMA composites. In addition, guidance for the use of TSW-GN in different application environments of polymer composites was proposed.

The difficulty of deploying remaining oil from unconventional reservoirs and the increasing CO2 emissions has prompted researchers to delve into carbon emissions through Carbon Capture, Utilization, and Storage (CCUS) technologies. Under the confinement of nanopore in unconventional formation, CO2 and hydrocarbon molecules show different density distribution from in the bulk phase, which leads to a unique phase state and interface behavior that affects fluid migration. At the same time, mineral reactions, asphaltene deposition, and CO2 pressurization will cause the change of porous media geometry, which will affect the multiphase flow. This review highlights the physical and chemical effects of CO2 injection into unconventional reservoirs containing a large number of micro-nanopores. The interactions between CO2 and in situ fluids and the resulting unique fluid phase behavior, gas-liquid equilibrium calculation, CO2 adsorption/desorption, interfacial tension, and minimum miscible pressure (MMP) are reviewed. The pore structure changes and stress distribution caused by the interactions between CO2, in situ fluids, and rock surface are discussed. The experimental and theoretical approaches of these fluid-fluid and fluid-solid reactions are summarized. Besides, deficiencies in the application and safety assessment of CCUS in unconventional reservoirs are described, which will help improve the design and operation of CCUS.

The effects of yield stress of poplar ( Poplar × euramericana cv. ‘Neva’) on temperature (60–210°C), moisture content (oven dry-30%) and grain response mechanism and as well as its role in the formation of sandwich compressed wood were studied in this paper. The results showed that the yield stress of wood was significantly affected by moisture content(MC), temperature and their interaction. Compared with temperature, the relative change rate of yield stress was nearly 10 times higher for each 1% increase in MC than for each 1°C increase in temperature. The experimental data revealed that the relative change rate of yield stress depended on the softening effect of wood by moisture and temperature. The asymmetry of yield stress in different grain direction also depended on wood hydrothermal softening effect. Raising the temperature or increasing the MC could make wood radial vs tangential asymmetry decrease and radial vs radial tangential asymmetry disappear. In the process of hydrothermal compression, the yield stress gradient caused by the hydrothermal softening inside the wood was the main reason for the formation of sandwich compressed wood, and provided a scientific basis for the controllability of the position and thickness of the compressed layer(s).

In the context of the double folding optical model, the elastic and inelastic scattering of 9Be + 120Sn at Elab (9Be) = 31, 42 and 50 MeV and 9,10,11Be + 64Zn elastic scattering at Ec.m. = 24.5 MeV are investigated. Real folded potentials are generated using the DDM3Y interaction based on the suggested density distributions for the 9,10,11Be nuclei. The imaginary potential is taken in the traditional standard Woods–Saxon form. Coupled channel (CC) calculations using a rotational model are performed for 9Be inelastically scattered from 120Sn, leading to different 120Sn excited states. Successful reproduction of the observed angular distributions of the elastic and inelastic scattering differential cross-sections has been achieved using the derived potentials. Special attention is paid to the previously suggested ( $$ {3}_1^{-} $$ , Ex = 2.40 MeV) 120Sn excited state in order to present the contributions come from - $$ {3}_1^{-} $$ at 2.40030(5) MeV, $$ {2}_3^{+} $$ at 2.42090(3) MeV, $$ {2}_2^{+} $$ at 2.355383(24) MeV, and $$ {4}_1^{+} $$ at 2.465632(23) MeV—in forming the inelastic data observed at Ex = 2.41 MeV.

Through measuring the intensity of the fluorescence X-rays emitted by the elements of interest, X-ray fluorescence computed tomography (XFCT) is capable of mapping the elemental distribution inside an object without destructively sectioning it. With the recent advances in XFCT utilizing polychromatic microfocus X-ray sources, it is expected that the popularity of such imaging modality will rise further. However, XFCT suffers from self-absorption effects, which make it challenging to reconstruct the elemental distribution inside the sample accurately. For this reason, polychromatic XFCT is mainly used to retrieve the distribution of elements with a relatively high atomic number (Z) when compared to the matrix of the sample. To enable the quantitative reconstruction of trace and low Z elements with polychromatic XFCT, a novel reconstruction method has been proposed in this manuscript. Through examining the proposed method on both simulation data and experimental data, its capacity on retrieving the density distribution of relatively low Z elements has been confirmed.

The study of densification on the porous surface of cross-section bilayer Iron powder compact was covered in this work. Both manipulated layers consisted of similar mechanical properties of powder ...

The flux density distribution and the temperature of the receiver are important parameters to assess the net thermal energy of any Solar Power Concentrator. In the present work, a heliostat field utilizing ganged type of heliostats for process heating application has been designed. A prototype model of the central receiver system consisting of ganged heliostats has been constructed and installed at Pune, Maharashtra, India. A thermocouple method was used to evaluate the total energy focused by the model heliostat system on a flat receiver. The flux density distribution was validated with the ray tracing simulation software ‘SolTrace’. The simulated flux density distribution was found to be in agreement with the measured one for a surface normal error of 10 milliradian. A heliostat field having 100 m2 total mirror area was designed in the north south cornfield layout. This heliostat field was simulated in ‘SolTrace’ software by considering the surface normal errors as 10 milliradian and the total energy gain was estimated. For the purpose of simulation to investigate the solar flux falling on the receiver, four days of the year were selected. It includes the March equinox, summer solstice, September equinox, and winter solstice.

Double-stranded DNA is under extreme confinement when packed in phage phi29 with osmotic pressures approaching 60 atm and densities near liquid crystalline. The shape of the capsid determined from experiment is elongated. We consider the effects of the capsid shape and volume on the DNA distribution. We propose simple models for the capsid of phage phi29 to capture volume, shape, and wall flexibility, leading to an accurate DNA density profile. The effect of the packaging motor twisting the DNA on the resulting density distribution has been explored. We find packing motor induced twisting leads to a greater numbers of defects formed. The emergence of defects such as bubbles or large roll angles along the DNA shows a sequence dependence, and the resulting flexibility leads to an inhomogeneous distribution of defects occurring more often at TpA steps and AT-rich regions. In conjunction with capsid elongation, this has effects on the global DNA packing structures.

This report describes the methodologies and algorithms that NASA’s Meteoroid Environment Office (MEO) currently utilizes to measure meteoroid densities. We discuss the needs for an accurate model for the meteoroid density distribution in its Meteoroid Engineering Model (MEM), and its potential implications for spacecraft design. The recently developed process is heavily derived from that of previous work [4], although subtle differences exist. A thorough comparison of the best-fit densities derived for sixty meteoroids in [4] and with the process described here shows that discrepancies in final densities larger than a factor of two are measured for ~ 20% of our test events. Such a level of discrepancy suggests that any density calculated using similar methods cannot be assumed to represent a unique fit to the data. Additional observational data for meteoroids beyond those utilized in this work will be essential for producing more reliable and repeatable density measurements.

Introduction: Estimating the risk of occurrence of a fire contributes to reducing human, infrastructure and natural resource losses; promoting activities to maintain and restore fire regimes; and optimizing resources for suppression. Objective: To develop an index of occurrence of forest fires on large areas, called Area at risk of fire (SeR). Materials and methods: The index corresponds to the area associated with a probability level measured at the right tail of the density distribution of the area affected annually by forest fires. The density distribution was estimated from the history of the area affected (1970-2018) in Mexico by state. The fit was performed by minimizing the Kolmogorov- Smirnov statistic with four models: exponential, gamma, lognormal and Weibull. Two related indicators are proposed: proportion of forest area affected by wildfires (PSeR) and incremental area at risk (ISeR). Results and discussion: all models showed a statistically significant fit (P Conclusion: SeR is an extreme event risk index that provides useful information and has a statistically acceptable predictive power.

This paper is the third step of project “Static mantle distribution, Equation, Solution and Application”. It consists of < Static Mantle Distribution 1 Equation>, , and this paper. Our result on shape of core is a “X type”, which differs from the traditional view that core is a sphere. Which one is correct? or, both are not correct? The aim of thispaper is to study dimpling and bucking of the spherical crust under mantle loading. Dimpling analysis depends on the outer solution of non-homogeneous non-linear D.E., while bucking analysis depends on non-linear Eigen value of the homogeneous D. E The results based on two models and governing equations show that crust dimpled at poles is proved theoretically and numerical result well consists with pole radius, while the non-linear bucking Eigen value boundary problem is solved by decomposition method. The results show that bucking can occur, and the un-continuity of internal force per unit length causes un-continuity of masses by mantle material emitting to crust at turning point of “X”. The growing of Tibet high-land might be viewed as an evidence of the mass ms(θ0)increasing due to mantle emission. Both poles radius and equatorial radius have been used to support our analysis. Question: how the nature makes cold at poles?

In this article, we develop method of linear and exponential quantization of neural network weights. We improve it by means of maximizing correlations between the initial and quantized weights taking into account the weight density distribution in each layer. We perform the quantization after the neural network training without a subsequent post-training and compare our algorithm with linear and exponential quantization. The quality of the neural network VGG-16 is already satisfactory (top5 accuracy 76%) in the case of 3-bit exponential quantization. The ResNet50 and Xception neural networks show top5 accuracy at 4 bits 79% and 61%, respectively.

Abstract. The Density Distribution approach to personality characterizes traits using both mean levels and within-person variability of behaviors. Recent theory highlights that emotion regulation (ER) is inherently variable, and this Density Distribution approach seems particularly suitable to understand both average tendencies and dynamics of ER as person-specific characteristics. However, there is not yet empirical evidence for this suggestion. To fill this gap, we investigated the reliability of density distribution information gathered from repeated assessments of state ER (within-person mean levels and standard deviations). Specifically, we studied the reliability of ER strategy use in terms of internal consistency and short- and long-term stability within and across two waves of experience sampling ( N = 153, M = 70 measurement occasions). Across both average tendencies and within-person variation, we found that individuals used different ER strategies relatively consistently. Overall, within-person ER mean levels and standard deviations were stable within and across the waves. Taken together, this suggests that the person-specific overall pattern of ER use in daily life is captured reliably using experience-sampling methodology (ESM).

The elastic scattering angular distributions of 32 S projectile by 12 C, 27 Al, 40 Ca, 48 Ca, 48 Ti, 58 Ni, 63 Cu, 64 Ni, 76 Ge, 96 Mo and 100 Mo targets over the energy range 83.3 - 180 MeV are analyzed in the framework of the double folding model based on the optical model. The real part of the optical model potential is obtained by using double folding model for eight different density distributions of 32 S which consist of Ngo, SP, 2pF, G1, G2, S, 3pF, and HFB. The imaginary part of the optical model potential is accepted as the Woods-Saxon (WS) potential. The theoretical results successfully reproduce the experimental data over both a wide energy and a wide target nucleus. Finally, simple and useful formulas which predict imaginary potential depths of each density are derived based on the elastic scattering results.

Areas, such as coastal eastern Gulf of Maine (GOM), perceived to have low density of target fish species and having high density fixed gear, are often subject to low fishing pressure and not well monitored. This can lead to a shortage of information regarding the fine scale dynamics of groundfish populations. Sentinel surveys are commonly developed for such areas with little monitoring and commercial fishing activity as a cost effective way to collect relevant data for monitoring the dynamics of fish stocks. In this study, we outline an approach that utilizes information from other survey programs and pilot study for designing a survey that satisfies both the wish of fishermen participants to contribute their knowledge and experience in determining groundfish abundance and distribution and the statistical rigor required for stock assessments. Through an analysis of spatial and density distribution of groundfish populations based on data from pilot seasons of the sentinel survey and other monitoring programs, we designed a survey that has good spatial and temporal coverage and captures the spatial variability in species composition and size structure of key species. The spatially explicit data collected in the program can contribute to a better understanding of groundfish stock status in the eastern GOM. The approach, although developed for the coastal eastern GOM, is also applicable to other areas with similar issues. Keywords: Coastal Eastern Gulf of Maine, Sentinel survey, Groundfish, Longline/jig, Survey design

On the basis of theoretical analysis of the rheodynamics of a powder material in the process of its indirect compaction with active action of an external friction force, the influence of this friction force on the density distribution of the material in the bulk of its sample was investigated. The advantages of the indicated compaction method over the one-side high-temperature compaction of powder materials, used most frequently in power metallurgy and in self-propagating high-temperature synthesis technologies, were substantiated.

The linear magnetic sensor is widely used in a high precision positioning system. In the installation of the linear magnetic system, any curved or uneven surfaces of the magnetic medium would result in significant fluctuations in the final recording accuracy during the position sensing process. This article investigates the effect of medium curvature on recording accuracy through experimental approaches. The results suggest that significant recording accuracy can be affected by the magnetic-flux density distribution over the medium caused by the medium curvature during installation. Through magneto-characteristic analysis, it also suggests that if the medium can be flattened, the recording accuracy can be improved.

With the widespread use of mobile devices, location-based services (LBSs), which provide useful services adjusted to users’ locations, have become indispensable to our daily lives. However, along with several benefits, LBSs also create problems for users because to use LBSs, users are required to disclose their sensitive location information to the service providers. Hence, several studies have focused on protecting the location privacy of individual users when using LBSs. Geo-indistinguishability (Geo-I), which is based on the well-known differential privacy, has recently emerged as a de-facto privacy definition for the protection of location data in LBSs. However, LBS providers require aggregate statistics, such as user density distribution, for the purpose of improving their service quality, and deriving them accurately from the location dataset received from users is difficult owing to the data perturbation of Geo-I. Thus, in this study, we investigated two different approaches, the expectation-maximization (EM) algorithm and the deep learning based approaches, with the aim of precisely computing the density distribution of LBS users while preserving the privacy of location datasets. The evaluation results show that the deep learning approach significantly outperforms other alternatives at all privacy protection levels. Furthermore, when a low level of privacy protection is sufficient, the approach based on the EM algorithm shows performance results similar to those of the deep learning solution. Thus, it can be used instead of a deep learning approach, particularly when training datasets are not available.

A halo-based non-projection approach is proposed to study the scale and redshift dependence of density and velocity distributions (PDF) in dark matter flow. All particles are divided into halo and out-of-halo particles such that PDF can be studied separately. Without projecting particle fields onto grid, scale dependence is analyzed by counting all pairs on different scales $r$. Redshift dependence is studied via generalized kurtosis. From this analysis, we can demonstrate: i) Delaunay tessellation can be used to reconstruct density field. Density correlations/spectrum are obtained, modeled and compared with theory; ii) $m$th moment of pairwise velocity can be analytically modelled. On small scale, even order moments can be modelled by a two-thirds law $\langle(\Delta u_L)^{2n}\rangle\propto{(-\epsilon_ur)}^{2/3}$, while odd order moments $\langle(\Delta u_L)^{2n+1}\rangle=(2n+1)\langle(\Delta u_L)^{2n}\rangle\langle\Delta u_L\rangle\propto{r}$ and satisfy a generalized stable clustering hypothesis (GSCH); iii) Scale dependence is studied for longitudinal velocity $u_L$ or $u_L^{'}$, pairwise velocity (velocity difference) $\Delta u_L$=$u_L^{'}$-$u_L$ and velocity sum $\Sigma u_L$=$u^{'}_L$+$u_L$. Fully developed velocity fields are never Gaussian on any scale; iv) On small scale, both $u_L$ and $\Sigma u_L$ can be modelled by a $X$ distribution to maximize system entropy. Distributions of $\Delta u_L$ is different with its moments analytically derived; v) On large scale, both $\Delta u_L$ and $\Sigma u_L$ can be modelled by a logistic function; vi) Redshift evolution of velocity distributions follows prediction of $X$ distribution with a decreasing shape parameter $\alpha(z)$ to continuously maximize system entropy., Comment: Reformatted with data source provided

The solution of the problem of dynamic stabilization of the Rayleigh–Taylor instability of the interface between two heavy fluids with an inverse density distribution is considered within the framework of the linear model of an ideal fluid. A necessity condition for the stabilization of an unstable equilibrium is concluded for the frequency and amplitude of vertical oscillations of a vessel with a liquid, which is in agreement with the previously obtained experimental data.

A study is performed of the acceleration of cosmic rays by shock waves propagating in bubbles of hot rarefied gas created by the stellar wind of supernova progenitors. Spectra of accelerated particles produced in type Ib/c supernova remnants are determined.

Predicting the power distribution within nuclear fuel is essential for predicting reactor fuel performance, since power distributions can impact pellet temperature distributions and fission product transport and migration. Analytical expressions for radial power distribution in fuel pellets were sought using lattice physics calculations to generate data and a machine learning technique to find representative expressions. Analytical approximations can be useful in nuclear fuel performance codes, such as element simulation and stresses (ELESTRES)/ element simulation code in a loss of coolant accident (ELOCA) for providing very rapid predictions of power distributions with reduced computational effort and memory requirements, relative to using an embedded or coupled neutron transport/burnup reactor physics code. Radial power distributions were calculated a priori using lattice physics codes to model mixed oxide (MOX) 37-element fuel bundles in pressure tube heavy water reactors. Such advanced fuels are of interest for future fuel cycles. Several datasets were generated with different amounts of PuO2 and variable neutron energy spectrum. Results of preliminary studies with the least absolute shrinkage and selection operator (LASSO) regression machine learning method have obtained analytical fitting functions with a mean maximum relative error (MRE) of 0.056 and a maximum MRE of 0.152 on the test set. However, using LASSO to estimate the coefficients of a physically motivated modified Bessel plus an exponential function, results in a lower MRE (mean MRE 0.041 and maximum MRE 0.11) on the same test set. Further potential improvements in both the curve fit and the machine learning methods are discussed.

Species distributions are influenced by processes occurring at multiple spatial scales. It is therefore insufficient to model species distribution at a single geographic scale, as this does not provide the necessary understanding of determining factors. Instead, multiple approaches are needed, each differing in spatial extent, grain, and research objective. Here, we present the first attempt to model continent-wide great ape density distribution. We used site-level estimates of African great ape abundance to (1) identify socioeconomic and environmental factors that drive densities at the continental scale, and (2) predict range-wide great ape density. We collated great ape abundance estimates from 156 sites and defined 134 pseudo-absence sites to represent additional absence locations. The latter were based on locations of unsuitable environmental conditions for great apes, and on existing literature. We compiled seven socioeconomic and environmental covariate layers and fitted a generalized linear model to investigate their influence on great ape abundance. We used an Akaike-weighted average of full and subset models to predict the range-wide density distribution of African great apes for the year 2015. Great ape densities were lowest where there were high Human Footprint and Gross Domestic Product values; the highest predicted densities were in Central Africa, and the lowest in West Africa. Only 10.7% of the total predicted population was found in the International Union for Conservation of Nature Category I and II protected areas. For 16 out of 20 countries, our estimated abundances were largely in line with those from previous studies. For four countries, Central African Republic, Democratic Republic of the Congo, Liberia, and South Sudan, the estimated populations were excessively high. We propose further improvements to the model to overcome survey and predictor data limitations, which would enable a temporally dynamic approach for monitoring great apes across their range based on key indicators.

It is important to monitor the plasma concentration degree in kidney transplantation and adjust drug dosages accordingly. The selection of plasma concentration sampling time points is a challenging task and the limited sampling strategy is used traditionally. The existing solutions have not considered characteristics of individual patients and had room for improvement. In this work, we propose a new deep learning model, Deep Personalized Prediction of Mycophenolic Acid Area Under Curve with Attentive Interactions (DPMPA-AUC) to select the plasma concentration sampling time points. This model has the capability to take account of the factors of individual patients. We use the soft attention method to select the sampling time points for the plasma concentration. We analyze the correlation between plasma concentration degree and the Mycophenolic Acid density distribution after kidney transplantation. We consider 2 to 4 sampling time points in this work. We use individual factors as the attention weights of the plasma concentration degree. We develop a Long Short Term Memory Dilated Convolutional Neural Networks with the soft attention mechanism to predict Mycophenolic Acid density during 12 hours after taking the drug. The experimental results show that our solution has better performance comparing with existing solutions.

Understanding the spatial distribution characteristics and formation mechanism of urban facilities (city functional components) constitutes the basis of urban layout optimization. Currently, research on the overall distribution of the various types of city functional components is lacking. In this study, by applying the gradient analysis method common in ecology, we considered 13 types of city functional components (80,214 individuals in total) in large, medium and small Chinese cities (9 cities in total) to carry out quantitative analysis of the distribution of components along urban–rural gradients through density distribution curves. The results indicated that: (1) a higher density of city functional components near the city centre revealed an obvious aggregated distribution; (2) the spatial distribution dynamics of city functional components were related to the city size, providing a reference for the rational distribution of components in cities of different sizes; (3) the distribution of city functional components was affected by their ecosystem services. This study offers a new perspective for the application of ecological methods in the examination of the distribution of city functional components.

Diffuse gliomas are highly infiltrative tumors whose early diagnosis and follow-up usually rely on magnetic resonance imaging (MRI). However, the limited sensitivity of this technique makes it impossible to directly assess the extent of the glioma cell invasion, leading to sub-optimal treatment planing. Reaction-diffusion growth models have been proposed for decades to extrapolate glioma cell infiltration beyond margins visible on MRI and predict its spatial-temporal evolution. These models nevertheless require an initial condition, that is the tumor cell density values at every location of the brain at diagnosis time. Several works have proposed to relate the tumor cell density function to abnormality outlines visible on MRI but the underlying assumptions have never been verified so far. In this work we propose to verify these assumptions by stereotactic histological analysis of a non-operated brain with glioblastoma using a tailored 3D-printed slicer. Cell density maps are computed from histological slides using a deep learning approach. The density maps are then registered to a postmortem MR image and related to an MR-derived geodesic distance map to the tumor core. The relation between the edema outlines visible on T2 FLAIR MRI and the distance to the core is also investigated. Our results suggest that (i) the previously suggested exponential decrease of the tumor cell density with the distance to the tumor core is not unreasonable but (ii) the edema outlines may in general not correspond to a cell density iso-contour and (iii) the commonly adopted tumor cell density value at these outlines is likely overestimated. These findings highlight the limitations of using conventional MRI to derive glioma cell density maps and point out the need of validating other methods to initialize reaction-diffusion growth models and make them usable in clinical practice.

We investigate the quantum walks of a three-boson system on one-dimensional lattice by using the Bose–Hubbard model with two- and three-body interactions. We focus on the propagation of two- and three-particle correlations as well as density distributions for different typical initial states, thereby analyzing the formation of particle pairs and trios for the specific initial states after an evolution time. For the two cases of only considering two-body interaction and including the two- and three-body interactions simultaneously with a fixed strength ratio, we discuss in detail the variations of correlations and density distribution with the interaction strength.

In this work, a database containing thermochemical and structural information about 208 monotropic polymorphic forms has been created and analyzed. Most of the identified compounds (77 cases) have been found to have two polymorphs, 14 compounds have three forms and there are only three examples of systems with four polymorphs. The analysis of density distribution within the database has revealed that only 62 out of 114 metastable polymorphs (referred to as group I) obey the `density rule' proposed by Burger and Ramberger [(1979), Mikrochim. Acta, 72, 259–271], while the remaining 45% of the monotropic systems (group II) violate the rule. A number of physicochemical, structural and molecular descriptors have been used to find and highlight the differences between group I and group II of the polymorphs. Group II is characterized (on average) by higher values of descriptors, which are responsible for conformational flexibility of molecules. An algorithm has been proposed for carrying out bivariate statistical analysis. It implies partitioning the database into structurally related clusters based on Tanimoto similarity coefficients and subsequent analysis of each cluster in terms of the number of hydrogen bonds per molecule.

Finite-element models are used to estimate numerically the distribution of bone mineral density (BMD) as a result of bone remodelling process from the loads applied. However, the effect of initial BMD distribution on trabecular-bone remodelling is still unknown. In this paper, the effect of initial density distributions as an input in the finite-element model on a structural-functional relationship of trabecular bone was investigated. A multi-material model representing a realistic density distribution was used based on the grey-scale value (GV) distribution and compared with a traditional single-material model. Different trabecular morphologies with density distributions were observed for these two material models. Similar character of the occurrence of density (in terms of element and volume fraction) of trabecular bone from a femur head were found, with the same highest number of elements in the density range from 1.25 to 1.35 g/cm3. These results indicate that previous simplified models using single-material properties for trabecular bone may not lead to considerable errors.

In this article, the applicability of the Wentzel–Kramer–Brillouin (WKB) method in studying inhomogeneous dusty plasma is discussed. First the power transmission coefficient of electromagnetic waves in inhomogeneous dusty plasma is derived based on the WKB method. Then, the power transmission coefficients of the double exponential and hyperbolic electron number density distribution models are numerically simulated. The numerical results reveal that the power transmission coefficient increases with the increase of incident wave frequency. Furthermore, comparing the power transmission coefficient of the WKB method and the analytical method in common plasma and dusty plasma, it is found that the WKB method is more applicable for common plasma. Finally, the applicable region of the WKB method for dusty plasma is discussed. The results reveal that the electron number density distribution is crucial for the applicable region of the WKB method, as well as for the incident wave frequency.

© 2019 Journal of Shoulder and Elbow Surgery Board of Trustees Background: Little is known about the cortical-like and cancellous bone density variations in superiorly eroded glenoids due to cuff tear arthropathy. The purpose of this study was to analyze regional bone density in type E2 glenoids. Methods: Clinical shoulder computed tomography scans were obtained from 32 patients with a type E2 superior erosion (10 men and 22 women; mean age, 73 years). Measurement regions were organized into quadrants (superior, inferior, anterior, and posterior) and depth regions. The depth regions were incremented by 2 mm from 0 to 10 mm. A repeated-measures multiple analysis of variance was performed to assess differences and interactions between mean densities (cortical-like and cancellous bone) in each depth, in each quadrant, and between sexes. Results: The lowest cancellous bone density was found in the inferior glenoid quadrant compared with all other quadrants (307 ± 50 Hounsfield units [HU], P < .001). At the glenoid surface, the superior quadrant contained the highest mean density for cortical-like bone (895 ± 97 HU); this differed significantly from the posterior, anterior, and inferior quadrants (P ≤ .033). As for depth of measurement, cortical-like bone was most dense at the glenoid surface (0-2 mm, 892 ± 91 HU), and density decreased significantly at depths greater than 2 mm (P ≤ .019). Conclusion: In patients with type E2 glenoids due to cuff tear arthropathy, the densest bone was found in the superior quadrant in the area of erosion. The inferior quadrant, which tends to be unloaded as the humeral head migrates superiorly, had the lowest density bone. In addition, the best-quality bone was located at the glenoid surface as compared with deeper in the vault.