Shape Of Distribution Research Articles

Transport properties of polydisperse hard-sphere fluid: effect of distribution shape and mass scaling

Transport properties of polydisperse hard-sphere fluid: effect of distribution shape and mass scaling

Automated Analysis of Nuclear Parameters in Oral Exfoliative Cytology Using Machine Learning.

As oral cancer remains a major worldwide health concern, sophisticated diagnostic tools are needed to aid in early diagnosis. Non-invasive methods like exfoliative cytology, albeit with the help of artificial intelligence (AI), have drawn additional interest. The study aimed to harness the power of machine learning algorithms for the automated analysis of nuclear parameters in oral exfoliative cytology. Further, the analysis of two different AI systems, namely convoluted neural networks (CNN) and support vector machine (SVM), were compared for accuracy. A comparative diagnostic study was performed in two groups of patients (n=60). The control group without evidence of lesions (n=30) and the other group with clinically suspicious oral malignancy (n=30) were evaluated. All patients underwent cytological smears using an exfoliative cytology brush, followed by routine Hematoxylin and Eosin staining. Image preprocessing, data splitting, machine learning, model development, feature extraction, and model evaluation were done. An independent t-test was run on each nuclear characteristic, and Pearson's correlation coefficient test was performed with Statistical Package for the Social Sciences(SPSS) software (IBM SPSS Statistics for Windows, Version 28.0. IBM Corp, Armonk, NY, USA). The study found substantial variations between the study and control groups in nuclear size (p<0.05), nuclear shape (p<0.01), and chromatin distribution (p<0.001). The Pearson correlation coefficient of SVM was 0.6472, and CNN was 0.7790, showing that SVM had more accuracy. The availability of multidimensional datasets, combined with breakthroughs in high-performance computers and new deep-learning architectures, has resulted in an explosion of AI use in numerous areas of oncology research. The discerned diagnostic accuracy exhibited by the SVM and CNN models suggests prospective improvements in early detection rates, potentially improving patient outcomes and enhancing healthcare practices.

Morphological and molecular characterization of cubios (Tropaeolum tuberosum Ruiz &amp; Pavón) collected in two municipalities in Boyaca - Colombia

In this study, we aimed to determine the extent of genetic variation among cubios (Tropaeolum tuberosum) in a diversity micro-center in the department of Boyacá, Colombia, with morphological and ISSR (Inter Simple Sequence Repeats) molecular markers. Twenty-five cubio morphotypes were collected across different farms within the municipalities of Belén and Ventaquemada in Boyacá and were sown for subsequent morphological and molecular characterizations. Tuber features were evaluated according to descriptors of the International Potato Center, namely predominant tuber surface color, secondary tuber surface color, secondary tuber surface color distribution, predominant tuber pulp color, secondary tuber pulp color, distribution of secondary tuber pulp color, tuber shape, and depth of tuber eyes. Molecular variation was assessed via eight ISSR primers. Morphological and molecular characterizations allowed us to identify 25 cubio morphotypes with significant genetic variation in the study area. This finding is likely attributed to mechanisms maintaining genetic variability, such as naturally occurring crosses between morphotypes modulated by environmental conditions and local agricultural practices, including seed exchange and a preference for given morphotypes.

Design of rose thorn biomimetic micro-protrusion for metals and CFRTP easily disassembled joining

This study focuses on the joining techniques for metals and carbon fiber reinforced thermoplastic (CFRTP) to address the pursuit of lightweight vehicles and high recycling efficiency. The innovative concept of ‘easy-disassembly joining’ is introduced for the first time, aiming for robust joint strength and efficient disassembly/recycling of end-of-life vehicles. Inspired by rose thorn morphology and natural performances, bionic micro-protrusions are explored as intermediate structures to facilitate the easy disassembly joining between metals and CFRTP. The primary focus of the study revolves around the design strategy of micro-protrusions inspired by rose thorns. The objective is to identify the most effective micro-protrusion shapes by understanding the interplay of its geometrical parameters, including base shape, apex position, profile curvature, and stress distribution under diverse loads. Utilizing static stress numerical simulations, the study conclusively identifies an elliptical base shape with the apex positioned slightly above the right edge of the structure. The outer profile adopts a circular arc, and the inner profile follows a conical curve. This configuration effectively mitigates stress concentration at the bottom, which interfaces with the metal substrate and the smaller areas around the apex. This research introduces an innovative concept for metal-CFRTP joining and applies bionic principles in engineering solutions. By promoting lightweight and sustainable structures through enhanced disassembly efficiency, it contributes to groundbreaking advancements in the field.

Experimental and mechanism study of asphaltene on formation and stabilization of oil-based foam

Stable foam will be generated in the separation equipment after pressure reduction of crude oil, which reduce the separation efficiency and damage the power equipment. It is found that the foam formed by asphaltene-rich crude oil is particularly stable in oilfield production, and the action mechanism of asphaltene for foam remains unclear. Hence, a self-made foaming device was performed to investigate the foamability and foam stability of oil-based foam, and the impact of asphaltene concentration and oil phase composition on foam properties was elucidated from the interfacial properties, viscosity, foam structure and the microstructure of asphaltene. Results show that low asphaltene concentrations promote foaming and mitigate the foam destruction. In contrast, high asphaltene concentrations are detrimental to foaming and reduce foam stability. The changes in interfacial properties and viscosity caused by asphaltene are not the main factors affecting foam performance. Besides, we proposed that asphaltene present in the oil phase as non-adsorbed particle, and the foam stability is influenced by the shape, volume fraction and size distribution of the particles. Furthermore, the boundary conditions for the effect of asphaltene on foam performance are innovatively put forward. This work contributes to understand the mechanism by which the asphaltene enhances foam stability and provides theoretical support for defoaming techniques in crude oil foam.

Particle size dependence of nanoclustered ceria abrasives on surface activity and chemical mechanical planarization performance

The particle size of cerium oxide (ceria) abrasives plays a crucial role in the design and development of advanced self-stopping slurries for the chemical mechanical planarization (CMP) process in semiconductor device manufacturing. However, a lack of ceria nanoparticles (NPs) with a narrow size distribution and uniform shape poses challenges in investigating the fundamental principles of the relationship between abrasive size and CMP performance. In this study, we thoroughly investigated the effect of ceria NP size on the removal rate (RR) of silicon oxide using uniform-sized nanoclustered (NC) ceria NPs with three diameters: 51.4 nm (NC51), 68.6 nm (NC69), and 108.0 nm (NC108). While all three types of ceria NPs shared a crystallinity of ∼ 70.6 %, they exhibited distinct physicochemical characteristics. As the particle size decreased, the specific surface area and chemical activity (i.e., Ce3+/Ce4+) increased by 155 % and 69 %, respectively. In the CMP process, where direct contact between the abrasives and wafer occurs, the abrasive size influences CMP performance. Experimentally, NC51 achieved the highest RR among the three slurries, along with complex size-dependent contact properties and chemical activities. These experimental results offer significant insights into precise semiconductor manufacturing in a practical manner.

Shape functions to scanner comparison

In the optical scanning, the processed data are in the form of point clouds that can be organised into the triangular meshes and can represent the surface with the given inaccuracy of the scanner. Meshes of special surfaces (such as sphere or ball bar) are used for the scanner calibration, qualification and verification. These artefacts restrict the calibration process, because their sizes must be periodically calibrated by the relevant institutions.The aim of this paper is to present new possibilities for optical laser scanner accuracy comparison. Three types of laser scanners with different accuracies were used. The calibration sphere was used to compare the results of the deviations (the commonly used method for scanner accuracy verification) from calibrated value with the results of new methods that use shape functions measuring distances, cone heights or curvatures. The measurement system analysis was used to verify that these functions can be used for scanners comparison. The comparison of shape distributions obtained from results of shape functions in the form of polylines was used to compare scanners according to their accuracies. The comparison of shape distribution results was done using ranges and Minkowski L1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${L}_{1}$$\\end{document} norm.

Study on monitoring broken rails of heavy haul railway based on ultrasonic guided wave

Real-time monitoring of broken rails in heavy haul railways is crucial for ensuring the safe operation of railway lines. U78CrV steel is a common material used for heavy haul line rails in China. In this study, the semi-analytical finite element (SAFE) method is employed to calculate the dispersion curves and modal shapes of ultrasonic guided waves in U78CrV heavy steel rails. Guided wave modes that are suitable for detecting rail cracks across the entire cross-section are selected based on the total energy of each mode and the vibration energy in the rail head, web, and foot. The excitation method for the chosen mode is determined by analyzing the energy distribution of the mode shape on the rail surface. The ultrasonic guided wave (UGW) signal in the rail is analyzed using ANSYS three-dimensional finite element simulation. The group velocity of the primary mode in the guided wave signal is obtained through continuous wavelet transform to confirm the existence of the selected mode. It is validated that the selected mode can be excited by examining the similarity between the vibration shapes of a specific rail section and all modal vibration shapes obtained through SAFE. Through simulation and field verification, the guided wave mode selected and excited in this study demonstrates good sensitivity to cracks at the rail head, web, and foot, and it can propagate over distances exceeding 1 km in the rail. By detecting the reflected signal of the selected mode or the degree of attenuation of the transmitted wave, long-distance monitoring of broken rails in heavy-haul railway tracks can be achieved.

Understanding the influence of tree size distribution on the CTL harvesting productivity of two different size harvesting machines

Tree size is one of the major factors that determines harvester productivity and is heavily influenced by forest managerial activities. Stand silvicultural management can lead to managing tree size, the distribution of tree size, and tree height amongst others. Understanding the effect of tree size distribution on harvesting productivity is central for optimizing management of operations. To investigate the effects of tree size distribution on harvester productivity, productivity functions for a medium and larger-sized harvester were applied to harvester derived tree size distributions from 35 clearfelled pine stands. These functions were applied to a normal distribution of trees covering the same tree size ranges. Productivity differences were analysed on a stand-by-stand basis. Results showed that for the larger harvester, productivity rates remained constant (67.1 vs. 67.6 m3·PMH− 1) indicating relatively little sensitivity to variations in tree size distributions. Although the standard deviation (SD) halved from 11.6 to 5.6 in the case of the uniform tree distribution. The smaller harvester productivity decreased by 15% from 47.3 to 40.1 m3·PMH− 1 and the coefficient of variation (CV) by 6% in the same transition to a uniform distribution. Further investigation was done on more skewed tree size distributions, a family of nine Weibull distributions was generated, representing combinations of three mean DBH classes (25 cm, 30 cm, and 35 cm) and three levels of CV (15%, 20%, 25%), for each DBH class. Results clearly indicate that different distribution shapes have different effects on different machine sizes, and that a low CV correlates to a higher productivity in larger tree sizes. A more uniform tree size distribution also provides more predictable results (lower CV), which would promote machine scheduling and result in fewer discrepancies on production rates.

Influence of approach shape of debris flow on impact load to open Sabo dam in experiment

Recently, the magnitude of landslide caused by torrential rain and typhoons is increasing in Japan. This high intensity rainfall disaster induces some structural failure of steel pipe open Sabo dams. Thus, current static design loads and impact loads are being considered. To prevent some structural failure of the dam, a new design concept is necessary at the severe load that is exceeding the present design load. However, the influence of debris flow impact load on steel pipe open Sabo dam is not clear to make a design load. The study experimentally approaches a vertical load distribution shape and its time history based on a comparison with a wedge approach shape and a front boulder concentrated shape. The load and moment action of a front boulder concentrated shape debris flow is greater than that of a wedge approach shape. Mechanism making the difference is made clear by observation of vertical detail measurement of impact load.

Analytical methodology for determining the extent of pumped freshwater lenses in recharge-limited, circular islands

Island freshwater lenses are often subjected to pumping to support the freshwater needs of isolated communities. Investigations of the lens extent commonly involve the application of analytical solutions, although the effects of pumping from circular island aquifers have not been assessed in previous analytical methodologies. In this study, a new analytical solution is derived based on Green's functions that accommodate freshwater inputs (recharge) and outputs (multiple wells) when obtaining the head distribution and sharp-interface lens shape. The solution is verified using a finite-element model for an illustrative pumping scenario. The solution is also differentiated with respect to pumping rates, recharge, and island radius to obtain vulnerability indices to characterize the lens sensitivity to changes in stresses. Finally, the analytical methodology is modified to examine the effects of non-uniform recharge. Python code incorporating the new solution is included to enable users to investigate a range of recharge and pumping scenarios.

On the provision of excludable public goods: General taxes or user prices?

AbstractThis paper compares some of the most common ways of financing the provision of publicly provided impure public goods/services in a unified dynamic general equilibrium framework with heterogeneous income groups. The focus is on the effects of user prices on individual incentives and how the latter shape aggregate outcomes and distribution. We show that a market‐like mechanism of user prices not only improves individual incentives and enhances aggregate efficiency, but it is also Pareto improving. However, such a mechanism is not beneficial or simply collapses when social externalities are strong, when the government adopts a mixed system that combines user prices with heavy subsidization of user costs, and when there is a minimum amount of the good that everybody needs.

Detection and characterisation of microplastics in tap water from Gauteng, South Africa

This study reports the presence, concentration, and characteristics of microplastics (MPs) in tap water in three suburbs in Gauteng Province in South Africa. Physical characterisation was conducted using stereomicroscopy and scanning electron microscopy following staining of MPs with the Rose Bengal dye. The concentrations of MPs in all samples ranged from 4.7 to 31 particles/L, with a mean of 14 ± 5.6 particles/L. Small-sized (<1 mm) and fibrous-shaped MPs were most abundant in all samples. Fibers accounted for 83.1% of MPs in samples from all the three areas, followed by fragments (12.4%), pellets/beads (3.1%), and films (1.5%), with a minor variation in the distribution of shapes and sizes in samples from each area. Raman microspectroscopy was used for chemical analysis, and five polymers were identified, namely: high-density polyethylene, polyurethane, polyethylene terephthalate, poly(hexamethylene terephtalamide), and poly(acrylamide-co-acrylic acid). C.I Pigment Red 1, C.I. Solvent Yellow 4, Potassium indigotetrasulphonate, and C.I Pigment Black 7 were the colourants detected. These colourants are carcinogenic and mutagenic and are potentially toxic to humans. The prevalence of MPs in tap water implies their inadequate removal during water treatment. For instance, the presence of poly(AM-co-AA) suggests that drinking water treatment plants may be a potential source of MPs in tap water. Other polymers, e.g., high-density polyethylene may be released from pipes during the transportation of drinking water. The estimated daily consumption of MPs from tap water was 1.2, 0.71, and 0.50 particles/kg.day for children, men, and women, respectively. The findings of this study provide evidence of the presence of MPs in drinking water in South Africa, thus giving some insights into the performance of treatment plants in removing these contaminants and a benchmark for the formulation of standard limits for the amount of MPs in drinking water.

Effect of distribution shape on the melting transition, local ordering, and dynamics in a model size-polydisperse two-dimensional fluid

Abstract We study the effect of particle size polydispersity (δ) on the melting transition (T *), local ordering, solid–liquid coexistence phase and dynamics of two-dimensional Lennard–Jones fluids up to moderate polydispersity by means of computer simulations. The particle sizes are drawn at random from the Gaussian (G) and uniform (U) distribution functions. For these systems, we further consider two different kinds of particles, viz., particles having the same mass irrespective of size, and in the other case the mass of the particle scales with its size. It is observed that with increasing polydispersity, the value of T * initially increases due to improved packing efficiency (ϕ) followed by a decrease and terminates at δ ≈ 8% (U-system) and 14% (G-system) with no significant difference for both mass types. The interesting observation is that the particular value at which ϕ drops suddenly coincides with the peak of the heat capacity (CP ) curve, indicating a transition. The quantification of local particle ordering through the hexatic order parameter (Q 6), Voronoi construction and pair correlation function reveals that the ordering decreases with increasing δ and T. Furthermore, the solid–liquid coexistence region for the G-system is shown to be comparatively wider in the T–δ plane phase diagram than that for the U system. Finally, the study of dynamics reveals that polydisperse systems relax faster compared to monodisperse systems; however, no significant qualitative differences, depending on the distribution type and mass polydispersity, are observed.

Monte Carlo tree search control scheme for multibody dynamics applications

There is considerable interest in applying reinforcement learning (RL) to improve machine control across multiple industries, and the automotive industry is one of the prime examples. Monte Carlo Tree Search (MCTS) has emerged and proven powerful in decision-making games, even without understanding the rules. In this study, multibody system dynamics (MSD) control is first modeled as a Markov Decision Process and solved with Monte Carlo Tree Search. Based on randomized search space exploration, the MCTS framework builds a selective search tree by repeatedly applying a Monte Carlo rollout at each child node. However, without a library of available choices, deciding among the many possibilities for agent parameters can be intimidating. In addition, the MCTS poses a significant challenge for searching due to the large branching factor. This challenge is typically overcome by appropriate parameter design, search guiding, action reduction, parallelization, and early termination. To address these shortcomings, the overarching goal of this study is to provide needed insight into inverted pendulum controls via vanilla and modified MCTS agents, respectively. A series of reward functions are well-designed according to the control goal, which maps a specific distribution shape of reward bonus and guides the MCTS-based control to maintain the upright position. Numerical examples show that the reward-modified MCTS algorithms significantly improve the control performance and robustness of the default choice of a constant reward that constitutes the vanilla MCTS. The exponentially decaying reward functions perform better than the constant value or polynomial reward functions. Moreover, the exploitation vs. exploration trade-off and discount parameters are carefully tested. The study’s results can guide the research of RL-based MSD users.

Analysis of hydraulic losses in the series from 1990 to 2022 at the Retiro small hydroelectric power plant

Hydraulic losses are a crucial variable in hydroelectric ventures as they can cause significant reductions in power generation. This article analyses the impact of hydraulic losses on the Retiro Small Hydroelectric Power Plant (SHPP), investigating their effect on monthly average power and, consequently, the efficiency of electricity generation. This study examines the historical series of load losses at the Retiro SHPP from 1990 to 2022. The calculations are based on flow data available in HidroWeb. The study considered the maximum and minimum flow rates in the historical flow series as constraints for hydropower generation. We used a multivariable function to calculate the efficiency of the hydraulic turbine, relating the turbine flow rate and the net water head. We developed mathematical relationships for head losses that occur in the grid, at the water intake, and due to friction from the intake to the turbine of the Retiro SHPP. The article presents a comparison between the actual monthly average power of the Small Hydroelectric Power Plant (SHPP) and the simulated monthly average power. We normalized the data for turbine flow and load loss to conduct statistical analysis. Kernel probability density was applied to understand the distribution shape of the data. Findings show that average monthly capacity is lowest in September, at approximately 0.81 MW. In March, the highest power occurs, approximately 14.19 MW. During the high flow period, the simulated average power, which accounts for load losses, closely matched the actual average power generated at the Retiro SHPP. In the months from July to October, despite being the period with the lowest head losses, it is the time when there is a greater opportunity to maximize energy generation at the power plant. An inefficient power generation system experiences significant load losses during specific periods of the year. To minimize this effect, it is crucial to understand the behavior of hydraulic losses and consider implementing mitigating measures.

Dynamic sampling for scanned microscopy modalities

We present an unsupervised heuristic-based batched dynamic algorithm for pixel-wise image sampling in a variety of scanned imaging modalities. Our algorithm offers improved performance over static Sobol sampling at a low computational cost. We evaluate the algorithm using three datasets to highlight potential savings in both two and three dimensional characterization contexts. Significantly, the implementation speed lends the approach runtime compatibility with electron microscopy. Reconstructed grain shape distributions for the sampled data sets are shown to be close to those of the original microstructures.

Which environmental factors influence the distribution patterns of an endangered freshwater mussel (Unio crassus)?

Freshwater mussels (Bivalvia: Unionida) are valuable components of river ecosystems. Among them, the thick-shelled river mussel (Unio crassus) is globally endangered, and its populations are decreasing in many European catchments. Over the last decade, it has become a focal point of environmental conservation programs. A comprehensive understanding of the relationship between the species and its environment is therefore required to optimize those programs. Yet, despite being increasingly studied, freshwater mussel ecological requirements remain complex to establish as they appear to be species- and region-related. We reviewed the potential environmental factors which have been showed to impact freshwater mussels, and therefore possibly U. crassus. We compiled datasets of environmental factors and occurrence of U. crassus across the study area (Wallonia, Belgium). Logistic regression models were built to identify the main driving factors. Results underscore the predominant significance of hydro-geomorphological variables in shaping distribution patterns. Specific stream power had a significantly negative impact on the distribution of U. crassus, while the probability of occurrence increased with catchment area, and with contrasted high- and low flows during the year. The high prediction accuracy of the hydro-geomorphological model supports the idea of a considerable influence of hydro-geomorphological habitat on the species. Other parameters are also relevant in predicting mussel distribution, like the percentage of land covered by meadows, elevated heavy metals concentrations and fish richness.

Application of computer vision techniques for 3D matching and retrieval of archaeological objects

Background As cultural institutions embark in projects oriented to digitise art and archaeological collections in three dimensions, the need for developing means to access the resulting 3D models has become imperative. Shape recognition techniques developed in the field of computer vision can help in this task. Methods This paper describes the implementation of three shape descriptors, specifically shape distributions, reflective symmetry and spherical harmonics as part of the development of a search engine that retrieves 3D models from an archaeological database without the need of using keywords as query criteria. Use case The usefulness of this system is obvious in the context of cultural heritage museums, where it is essential to provide automatic access to archaeological and art collections. The prototype described in this paper uses, as study case, 3D models of archaeological objects belonging to Museo del Templo Mayor, a Mexican institution that preserves one of the largest collections of Aztec cultural heritage. Conclusions This work is part of an ongoing project focused on creating generic methodologies and user-friendly computational tools for shape analysis for the benefit of scholars and students interested in describing, interpreting and disseminating new knowledge about the morphology of cultural objects.

Highly efficient catalytic degradation of organic dyes using iron nanoparticles synthesized with Vernonia Amygdalina leaf extract

Today, nanoscience explores the potential of nanoparticles due to their extraordinary properties compared to bulk materials. The synthesis of metal nanoparticles using plant extracts is a very promising method for environmental remediation, which gets global attention due to pollution-led global warming. In the present study, iron nanoparticles (FeNPs) were successfully synthesized by the green method using Vernonia amygdalina plant leaf extract as a natural reducing and capping agent. Biosynthesized FeNPs were characterized with different analytical techniques such as UV–visible, FT-IR, XRD, and SEM. The analysis revealed the formation of amorphous FeNPs with an irregular morphology and non-uniform distribution in size and shape. The average particle size was approximately 2.31 µm. According to the catalytic degradation investigation, the FeNPs produced via the green approach are highly effective in breaking down both CV and MB into non-toxic products, with a maximum degradation efficiency of 97.47% and 94.22%, respectively, when the right conditions are met. The kinetics study exhibited a high correlation coefficient close to unity (0.999) and (0.995) for the degradation of MB and CV, respectively, for the zero-order pseudo-kinetics model, which describes the model as highly suitable for the degradation of both dyes by FeNPs compared to other models. The reusability and stability of biosynthesized nano-catalysts were studied and successfully used as efficient catalysts with a slight decrease in the degradation rate more than four times. The results from this study illustrate that green synthesized FeNPs offer a cost-effective, environmentally friendly, and efficient means for the catalytic degradation of organic dyes.