Angular Index Research Articles

The Angular Spectrum of the Scattering Coefficient Map Reveals Subsurface Colorectal Cancer

Colorectal cancer diagnosis currently relies on histological detection of endoluminal neoplasia in biopsy specimens. However, clinical visual endoscopy provides no quantitative subsurface cancer information. In this ex vivo study of nine fresh human colon specimens, we report the first use of quantified subsurface scattering coefficient maps acquired by swept-source optical coherence tomography to reveal subsurface abnormities. We generate subsurface scattering coefficient maps with a novel wavelet-based-curve-fitting method that provides significantly improved accuracy. The angular spectra of scattering coefficient maps of normal tissues exhibit a spatial feature distinct from those of abnormal tissues. An angular spectrum index to quantify the differences between the normal and abnormal tissues is derived, and its strength in revealing subsurface cancer in ex vivo samples is statistically analyzed. The study demonstrates that the angular spectrum of the scattering coefficient map can effectively reveal subsurface colorectal cancer and potentially provide a fast and more accurate diagnosis.

Symmetry in the diffraction of beams carrying orbital angular momentum

Diffraction of orbital-angular-momentum--carrying Laguerre-Gauss vortex (LGV) beams by $N$-fold rotationally symmetric regular polygons is studied analytically and experimentally. The structure, symmetry, and dependence of the diffraction pattern on the angular momentum index of the LGV beam and the number of sides in the polygon are systematically investigated, and features and trends are identified. The evolution of the diffraction pattern and its symmetry with the aperture position relative to the waist is also studied, leading to a generalized Friedel's law for diffraction of LGV beams.

Influence of Particle Geometry Assessed via Image Processing on Broken Sandstone Strength

Particle geometry has an impact on the behavior and strength of broken rock, where particle shape characteristics affect the ability of particles to rotate or slide relative to each other. Form, angularity and texture are three independent parameters that describe the geometry of such a particle. In this paper the geometry of crushed Berea sandstone was determined through image processing, where the results showed that form and angularity indices describe the geometry characteristics of broken Berea sandstone better than the other geometry indices. A correction coefficient that has previously been introduced to predict a sieve size distribution from image processing was shown to be a function of form index for the sandstone fragments. Triaxial compression tests were performed on the broken sandstone, showing that confining pressure and void ratio have an impact on broken rock strength. Increasing confining pressure was shown to enhance the strength of broken rock, while void ratio was shown to be inversely related to broken rock strength. Void ratio can also be affected by particle geometry. Increasing particles form index increases the void ratio where particles angularity index and void ratio are inversely related.

On size-dependent dynamic behavior of rotating functionally graded Kirchhoff microplates

A size-dependent model for free vibration and transient response of rotating functionally graded (FG) microplates is established on the basis of the Kirchhoff plate theory and modified couple stress theory. A microplate made of a two-constituent material with a continuous through-thickness power-law variation is considered. The governing equations of motion as well as boundary conditions containing the von Kármán geometric nonlinearity, Coriolis effect and centrifugal stiffening effect are derived by using Hamilton's principle. An assumed-mode discretization approach is applied to solve these equations numerically. The convergence and comparison studies are presented to prove the effectiveness of the current model. Numerical examples are presented for investigating the effects of the size-dependency, non-dimensional angular velocity, FG index and aspect ratio on dynamic properties of rotating FG microplates. It is revealed that the increase of non-dimensional material length scale parameter increases the stiffness of the plate, which accordingly, results in an increase in natural frequencies and a decline of transient responses. The FG index and angular velocity noticeably affect the size dependency of rotating FG microplates.

Accelerometric outcomes of motor function related to clinical evaluations and muscle involvement in dystrophic dogs.

Duchenne muscular dystrophy (DMD) is an X-linked muscle disorder characterized by primary muscle degeneration. Patients with DMD reveal progressive muscle weakness leading to ambulatory dysfunction. Novel outcome measures are needed for more sensitive evaluation of therapeutic effects in clinical trials. Multiple parameters of acceleration and angular velocity are used as efficient indicators to quantify the motion of subjects, and these parameters have been recently applied for evaluation of motor function in DMD. In the present study, we evaluated gait in a dystrophic dog model, CXMDJ, by measuring three-axial acceleration and angular velocity over the course of months. Hybrid sensors were placed on the dorsal thoracic and lumbar regions of dogs to detect a wide range of acceleration (±8 G) and angular velocity (±1000 degrees per second). Multiple parameters showed lower values in dystrophic dogs compared to wild-type (WT) dogs, and declined over the course of months. Acceleration magnitude (AM) at the thoracic region in dystrophic dogs was prominently lower compared with WT dogs, even at the age of 2 months, the onset of muscle weakness, whereas AM at the lumbar region drastically declined throughout the disease course. The angular velocity index in the vertical direction in the lumbar region increased in dystrophic dogs, suggesting waddling at the girdle. These parameters also accordingly decreased with exacerbation of clinical manifestations and a decrease in spontaneous locomotor activity. The AM of dystrophic dogs was analyzed with magnetic resonance imaging to look for a correlation with crus muscle involvement. Results showed that acceleration and angular velocity are multifaceted kinematic indices that can be applied to assess outcomes in clinical trials for hereditary neuromuscular disorders including DMD.

Degeneracy in the diffraction of orbital angular momentum carrying beams.

Symmetry constraints on the far-field diffraction of Laguerre-Gauss vortex beams by planar aperture arrays with N-fold rotational symmetry are considered. The experiments reveal a simple structure for the diffraction pattern and high degree of degeneracy in its dependence on the orbital angular momentum index of the incident beam in agreement with analytical and numerical results.

Development of Hard and Soft Palate During the Fetal Period and Hard Palate Asymmetry

In the present study, it was aimed to perform the morphometric analysis of the hard and soft palate in fetal cadavers and evaluate hard palate asymmetry during the fetal development. The development of the palate was investigated in 40 (21 males, 19 females) fetal materials aged between the 17th and 40th gestational week. In this study, distances between the incisive papilla-staurion (Ip-Sr), staurion-posterior nasal spine (Sr-Pns), incisive papilla-greater palatine foramen (Ip-Gpf) on the right and left sides, Sr-Gpf, and Pns-Gpf were measured. In cases with asymmetry, the ratio of asymmetry was determined in percentage using the asymmetry index. Moreover, angular values between Ip-Sr-Gpf and Ip-Pns-Gpf on the right and left sides were measured, and the right and left side values were compared with each other. The hard and soft palate lengths were measured on the planum medianum. Upon comparing the measured parameters between males and females, the mean values of male fetuses were higher in all parameters, but a significant difference was found only in the Sr-Pns distance among these parameters. Upon comparing the angular data and asymmetry index data on the hard palate between the trimester groups, a significant difference was found only in the Ip-Sr-Gpf (left) parameter. The mean ratio of the hard palate to the soft palate was found as 1.90. It is believed that the obtained data will contribute to studies to be conducted in fields such as plastic surgery, maxillofacial surgery, intrauterine surgery, fetopathology, embryology, anatomy, and obstetrics.

Wall Shear Stress Directional Abnormalities in BAV Aortas: Toward a New Hemodynamic Predictor of Aortopathy?

The bicuspid aortic valve (BAV) generates wall shear stress (WSS) abnormalities in the ascending aorta (AA) that may be responsible for the high prevalence of aortopathy in BAV patients. While previous studies have analyzed the magnitude and oscillatory characteristics of the total or streamwise WSS in BAV AAs, the assessment of the circumferential component is lacking despite its expected significance in this highly helical flow environment. This gap may have hampered the identification of a robust hemodynamic predictor of BAV aortopathy. The objective of this study was to perform a global and component-specific assessment of WSS magnitude, oscillatory and directional characteristics in BAV AAs. The WSS environments were computed in the proximal and middle convexity of tricuspid aortic valve (TAV) and BAV AAs using our previous valve-aorta fluid-structure interaction (FSI) models. Component-specific WSS characteristics were investigated in terms of temporal shear magnitude (TSM) and oscillatory shear index (OSI). WSS directionality was quantified in terms of mean WSS vector magnitude and angle, and angular dispersion index (Dα). Local WSS magnitude and multidirectionality were captured in a new shear magnitude and directionality index (SMDI) calculated as the product of the mean WSS magnitude and Dα. BAVs subjected the AA to circumferential TSM overloads (2.4-fold increase vs. TAV). TAV and BAV AAs exhibited a unidirectional circumferential WSS (OSI < 0.04) and an increasingly unidirectional longitudinal WSS between the proximal (OSI > 0.21) and middle (OSI < 0.07) sections. BAVs generated mean WSS vectors skewed toward the anterior wall and WSS angular distributions exhibiting decreased uniformity in the proximal AA (0.27-point increase in Dα vs. TAV). SMDI was elevated in all BAV AAs but peaked in the proximal LR-BAV AA (3.6-fold increase vs. TAV) and in the middle RN-BAV AA (1.6-fold increase vs. TAV). This analysis demonstrates the significance of the circumferential WSS component and the existence of substantial WSS directional abnormalities in BAV AAs. SMDI abnormality distributions in BAV AAs follow the morphotype-dependent occurrence of dilation in BAV AAs, suggesting the predictive potential of this metric for BAV aortopathy.

Algorithm for Virtual Aggregates’ Reconstitution Based on Image Processing and Discrete-Element Modeling

Based on the Aggregate Imaging Measurement System (AIMS) and the Particle Flow Code in Two Dimensions (PFC2D), an algorithm for modeling two-dimensional virtual aggregates was proposed in this study. To develop the virtual particles precisely, the realistic shapes of the aggregates were captured by the AIMS firstly. The shape images were then processed, and the morphological characteristics of aggregates were quantified by the angularity index. By dividing the particle irregular shape into many triangle areas and adjusting the positions of the generated balls via coordinate systems’ conversion within PFC2D, the virtual particles could be reconstructed accurately. By calculating the mapping area, the gradations in two-dimensions could be determined. Controlled by two variables (μ_1 and μ_2), which were drawn from the uniform distribution (0, 1), the virtual particles forming the specimens could be developed with random sizes and angular shapes. In the end, the rebuilt model of the SMA-13 aggregate skeleton was verified by the virtual penetration tests. The results indicated that the proposed algorithm can not only model the realistic particle shape and gradations precisely, but also predict its mechanical behavior well.

An algorithm for the retrieval of the clumping index (CI) from the MODIS BRDF product using an adjusted version of the kernel-driven BRDF model

The clumping index (CI) characterizes the grouping of foliage relative to a random spatial distribution of leaves and is an important structural parameter for plant canopies that can influence canopy radiation regimes. Consequently, the CI is very useful for ecological and meteorological models. One method used to retrieve the CIs of plant canopies is to construct a linear relationship between the CI and the normalized difference between hotspot and dark spot (NDHD) angular index. This method requires a particularly accurate reconstruction of hotspot signatures, which are difficult to measure. In this study, we propose a framework to retrieve CIs from Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) parameters, which are generally based on linear CI-NDHD equations. The main algorithm is designed to retrieve CIs in the closed interval [0.33, 1.00]. This range is derived from the CI-NDHD equations and is thus called as the physical range here, although a modified lower boundary can be implemented in the future if necessary. If CIs are outside of this range, then a backup algorithm is designed to reprocess these so-called outlier CIs. The hotspot-adjusted version of the RossThick-LiSparseReciprocal (RTLSR) model (i.e., the RTCLSR model) is employed to reconstruct the hotspot signatures for the MODIS BRDF parameters. This method simplifies the hotspot reconstruction by using two hotspot parameters that are not distinctly scale-dependent particularly in the context of an inhomogeneous coarse spatial resolution. To evaluate this algorithm framework, we collect dozens of global field-measured CIs and calculate their determination coefficient (R2), root mean square error (RMSE) and bias relative to MODIS CIs derived using both the main algorithm and the backup algorithm. Our results show that this framework can derive MODIS CIs with a high accuracy (i.e., R2 = 0.80 (0.72), RMSE = 0.07 (0.12), bias = −0.03 (−0.10)) using the main (backup) algorithms and that it shows promise for various ecological applications, especially in combination with the leaf area index (LAI).

Morphology characterization of irregular particles using image analysis. Application to solid inorganic fertilizers

This research deals with how to characterize the morphology of mineral fertilizers using dynamic image analysis. A machine-vision system was first developed to capture digital images of irregular particles. The vision system was designed as a mechanical assembly to generate a flow of separated grains passing in front of a camera, combined with a flash. The vision system’s parameters were then calibrated and optimized – particularly in terms of image resolution, light sources and exposure time. An optimal value of 34 pixels/mm was obtained for the image resolution. Then, the system was tested and validated by imaging perfect plastic spheres of known size. Secondly, an image-processing algorithm was developed to extract geometrical and morphological information for various particles. Various shape parameters, describing the differences of a particle from a reference geometric form (e.g. a circle or ellipse), were calculated as outputs of the image-processing treatment. Statistical analysis was then applied to determine the convergence of shape parameter distributions and also the repeatability of measurements. 45 fertilizers, with grain shapes ranging from highly irregular to nearly spherical, were prepared and imaged. For all these fertilizers, the distribution of shape parameters was quantitative, representative, repeatable and reproducible using the machine-vision system developed. In order to investigate the best parameters for characterizing particle morphology, statistical correlation was applied to deduce a list of independent shape parameters. These parameters were relevant and could further be used to characterize the morphology of any fertilizer. The independent parameters thus obtained were subsequently used to detect the correlation between morphology and distance traveled by fertilizer particles thrown out by a centrifugal spreader. Experimental tests were conducted using the CEMIB device to determine fertilizer spread pattern from spinning discs. Results showed that, within the same range of size, mass density and spreader operating parameters, spherical and rounded particles traveled further than elongated and angular particles. The angularity index parameter, denoted by ANGInd (which characterizes whether a particle is rounded or angular), showed most potential application to explain the aerodynamic behavior of irregular particles spread by spinning discs.

Modelling of thermally affected elastic wave propagation within rotating Mori–Tanaka-based heterogeneous nanostructures

In this article, wave dispersion responses of a temperature-dependent functionally graded (FG) nanobeam undergoing rotation and exposed to thermal load are presented based on nonlocal strain gradient theory. Mori–Tanaka model has been considered to express the gradual variation of material properties across thickness. Governing equations are derived as a function of axial force due to centrifugal stiffening and displacements by applying Hamilton’s principle in context of Euler–Bernoulli theory. Dispersion relations of rotating FG nanobeam are analytically derived by solving an eigenvalue problem. Obviously, numerical results indicate that different parameters such as angular velocity, gradient index, temperature change, wave number, and nonlocality parameter have significant influences on wave characteristics of rotating FG nanobeams. Hence, results of this research can provide useful information for the next generation studies and accurate deigns of nanomachines including nanoscale molecular bearings and nanogears.

Design functionally graded rotating disks under thermoelastic loads: Weight optimization

In this work, an advanced algorithm is employed to optimize the weight of a functionally graded hollow circular disk of varied thickness rotating at a constant angular velocity about its central axis. The disk is under thermoelastic load conditions. The material properties, encompassing elastic modulus thermal expansion coefficient, thermal conductivity, and density and thickness of the disk are assumed to be graded in the radial direction, and the Poisson's ratios are assumed to be constant. A combination of a co-evolutionary particle swarm optimization (CPSO) approach coupled with a differential quadrature (DQ) method is applied to obtain minimized stress and displacement fields through the geometry of the disk. The role of DQ is discretizing and solving the governing equations including motion and boundary conditions existing in the goal function of the CPSO method. In comparisons with other optimization results in the literature, the weight reduction results of this algorithm show much superior responses, demonstrating the effectiveness of this algorithm for optimizing constrained complex problems in engineering structures. Also, in numerical simulation, a study is performed to determine the effects of angular velocity and gradient index variations on the distribution of stress and displacement fields.

An Analysis of Angular Indexing Error of a Gear Measuring Machine

In gear measuring machines (GMMs), the tested gear is mounted on a mandrel, which is pivoted at both ends by two centers in a vertical arrangement. The upper center is fixed and the lower center is driven by the spindle of rotation. The coaxiality error between the central line of the mandrel and the spindle average line of a GMM always exists in terms of the offset and angle measured in one plane. Such a coaxiality error would cause an angular indexing error of tested gear resulting in measurement error. This phenomenon has rarely been investigated. In this paper, a GMM is taken as an example and its coaxiality error of the mandrel and spindle error of the rotary stage are measured. The difference of rotated angles between the mandrel and spindle is theoretically analyzed by derived formulae. Calibrated by a precision polygon and an autocollimator, the predicted angular index error of the mandrel was consistent with experimental results. Through the experimental verification, it was found that, when the coaxial deviation between the two centers was 10 μm and the lower center tip’s radial motion error was 1.6 μm, the angular indexing deviation of the mandrel was ±5″. If the errors were compensated according to the analyzed model, the residual error was reduced to ±2″. A significant improvement in the angular positioning accuracy of the GMM can be achieved.

Quantification of angularity of general-shape particles by using Fourier series and a gradient-based approach

Particle angularity significantly affects the macroscopic mechanical behavior of aggregate assemblages. However, most of the current approaches used for quantifying particle angularity are only applicable to star-like particles. This study presents a new approach allowing the quantification of angularity of general-shape particles. The method first reconstructs the particle morphology by applying Fourier series analysis to the two-dimensional image of the particle. The gradient-based angularity index (AIg) is then evaluated from the reconstructed morphology through numerical integration. AIg is zero for images of any circularly shaped particles, including circles and ellipses, and it increases with increasing particle angularity. Images included in commonly used standard charts are evaluated for their AIgs. The results show a consistent pattern in regard to the qualitative angularity ranking of the particles. Based on the findings, a simple-to-use criterion is suggested for the quantitative classification of particle angularity.

Innovation for evaluating aggregate angularity based upon 3D convolutional neural network

The performance of asphalt pavement is significantly influenced by the morphological characteristics of its aggregates, especially on its angularity. Evaluation of aggregate angularity is considered to be challenging because aggregates often have various shapes. Therefore, utilization of digital images in the evaluation of angularity has gained significant research interest in recent years. However, conventional manually processed images for evaluating the angularity of aggregates have the disadvantages of low efficiency and insufficient accuracy. This paper presents a novel application of convolutional neural networks (CNN) using digital images for evaluating aggregate angularity automatically. The research procedure is as follows: (a) develop a self-developed device for the acquisition of aggregate images; (b) establish an evaluation criterion for the angularity index (AI); (c) design a localization CNN and five AI CNNs; and (d) conduct a sensitivity analysis of the CNNs. First, a self-developed device is established based on the view-based approach to extract the 3D information of aggregates. Then, an evaluation criterion that is suitable for 3D images from aggregates is presented. Based on the 3D images and evaluation criterion, one localization CNN and five AI CNNs are jointly used to evaluate the AI of each aggregate. Finally, statistical analysis is performed to seek the optimal parameters for AI CNN, especially the kernel size, and to verify the sensitivity of AI CNN. The analysis includes the sensitivity to kernels size, image resolution, light, texture and aggregate size. The results indicate that the localization CNN is able to locate and abstract each aggregate from the images. The best size of the kernels is 6×6, and an AI CNN with a kernel size of 6×6has a 0.0938 relative error for evaluating the AI using 300PPI images. Moreover, AI CNN with a kernel size of 6×6 shows remarkable robustness under different light conditions, sizes and textures of aggregates.

Morphological characterization and mechanical analysis for coarse aggregate skeleton of asphalt mixture based on discrete-element modeling

Focused on the aggregate microstructures to characterize the aggregate mechanical properties, this paper proposed a modeling method of coarse aggregate based on the particle morphological characteristics. By using the Aggregate Image Measurement System (AIMS), the realistic shape of granular aggregates was captured and the statistical analysis was made to quantify the morphological differences firstly. Then by using Discrete-Element Method (DEM) software named as Particle Flow Code in two dimensions (PFC2D) and with the help of the image processing techniques, an algorithm was developed to model the two-dimensional shape of aggregates. Through linking the shape to the morphological index for each aggregate, the coarse aggregate skeleton was built which is consistent with the actual composition and structure of the laboratory specimens. After that, based on laboratory penetration test for granular aggregates, virtual penetration test was built by PFC2D to verify the validity of the developed modeling algorithm. An optimized method was proposed further then to improve the simulation efficiency. This is because of the time-consuming process when modeling the actual specimen which was composed of numerous coarse aggregates with various shapes. Some representative particles were selected and reconstructed based on the angularity index to form the virtual specimens with aggregates of gradations AC-13 and SMA-13. At last the virtual penetration test of AC-13, SMA-13 was conducted to predict the mechanical behavior and the coarse aggregate skeleton structure characteristics were analyzed from the point of micro-contact state. It is proved that the proposed modeling algorithm could well capture the realistic shape of aggregates and virtual test based on the aggregates model could characterize the granular aggregates mechanical properties accurately.

Evaluation of morphological properties of railway ballast particles by image processing method

Abstract The properties of individual ballast particles affect the behavior of ballast layer under train loading. One of the most important individual properties is the morphological characteristics of ballast particles represented by surface texture and angularity. In the present study, the morphological properties of ballast particles are quantified by developing surface texture (ST) index and angularity index (AI) determined on two-dimensional aggregate images. For this purpose, four different types of fresh ballast aggregates (basalt, marl, dolomite and trachyte), rounded river aggregate and degraded ballast sample obtained from railway track are analyzed for each specific sieve size fraction by developed image processing method. Comparison of the developed method in the present study for determination of ST and AI with the previously developed morphological indices shows that there is a reasonable correlation between them. In addition, the results obtained from the air void contents of aggregates in loose condition validate that the developed indices for the evaluation of morphological properties of aggregates can characterize the angularity and surface texture of each individual ballast particle properly.

Wave propagation analysis of size-dependent rotating inhomogeneous nanobeams based on nonlocal elasticity theory

The present research deals with the wave dispersion behavior of a rotating functionally graded material (FGMs) nanobeam applying nonlocal elasticity theory of Eringen. Material properties of rotating FG nanobeam are spatially graded according to a power-law model. The governing equations as functions of axial force due to centrifugal stiffening and displacements are obtained by employing Hamilton’s principle based on the Euler–Bernoulli beam theory. By using an analytical model, the dispersion relations of the FG nanobeam are derived by solving an eigenvalue problem. Numerical results clearly show that various parameters, such as angular velocity, gradient index, wave number and nonlocal parameter, are significantly effective to characteristics of wave propagations of rotating FG nanobeams. The results can be useful for next generation study and design of nanomachines, such as nanoturbines, nanoscale molecular bearings and nanogears, etc.

Crystal structure, DNA interaction and thermal analysis data of two new antimicrobial active binuclear cadmium and mercury complexes

Two new binuclear Schiff base complexes with the general formula [CdLBr(μ-Br)]2 (1) and [Hg2L(μ-I)2I2] (2) were prepared by the reaction of 2,2-dimethyl-N,N'- bis-(3-phenyl-allylidene)-propane-1,3-diamine (L), CdBr2 and HgI2. The crystal structure of two complexes was determined by X-ray crystallography. The common structures for four-coordinated compounds are square planar or the tetrahedral geometries, which is evaluated by the Houser angular index (τ4). In [CdLBr(μ-Br)]2 (1), each cadmium center is five-coordinated by two iminic nitrogen atoms from Schiff base ligand, two μ2-bridging bromide anions and one terminal coordinating bromide anion. The metal center in this centrosymmetric dimer has a distorted square-pyramidal geometry. [Hg2L(μ-I)2I2] (2) consists of two four-coordinated mercury centers with different coordination spheres (HgN2I2 for Hg1 and HgI4 for Hg2). The TG/DTG diagrams showed that both complexes were completely decomposed under a nitrogen atmosphere. Furthermore, antibacterial activities of compounds have been screened against various bacteria and fungi by Disk diffusion method. Mercury complex inhibited the growth of the microorganisms more efficient than cadmium complex. DNA cleavage potential of compounds was evaluated by agarose gel electrophoresis method. Finally, nano-structure cadmium complex was sono-chemically synthesized and applied as precursor for preparation of cadmium oxide nanoparticles.