2,882 research outputs found
Research on the optimization formula performance and dust reduction effect of mine dust suppressant based on response surface method
In this study, sodium dodecyl benzene sulfonate, triton, guar gum and sodium polyacrylate are selected as the composite raw materials of dust suppressants through the determination of physical and chemical properties of single components. Design expert software is used to carry out the mixture design, the determination of experimental parameters and the response surface analysis of the sedimentation rate, evaporation resistance property, surface tension, contact angle of coal dust with the reagent. According to the response surface analysis results, the optimal ratio of the reagent has been determined, which is 39.8% for sodium dodecyl benzene sulfonate, 53% for triton, 3.9% for guar gum, and 3.3% for sodium polyacrylate. The results of infrared spectrum show that the dust suppressant had a significant effect on the content change of hydroxyl of hydrophilic functional groups of coal dust. The results of scanning electron microscope experiments show that the dust suppressor has good wetting and binding effects on coal dust. The toxicity test shows that the coal sample did not have the acute inhalation toxicity characteristics of hazardous waste. The dust reduction experiment in similar space shows that the dust reduction efficiency of this new dust suppressants is 95.3%, which is 28.1% and 10.2% higher than that of natural dust fall and water spray dust fall. The conclusions of this study are of great significance for improving the dust reduction efficiency of mine dust suppressants, the dust prevention technologies, the working environment of underground workers, and reducing the incidence of pneumoconiosis.Document Type: Original articleCited as: Gao, N., Zhou, T., Jin, L., Fan, J., Tong, L., Zhang, B. Research on the optimization formula performance and dust reduction effect of mine dust suppressant based on response surface method. Advances in Geo-Energy Research, 2024, 11(2): 115-131. https://doi.org/10.46690/ager.2024.02.0
Retinal vascular segmentation using superpixel-based line operator and its application to vascular topology estimation
Purpose: Automatic methods of analyzing of retinal vascular networks, such as retinal
blood vessel detection, vascular network topology estimation, and arteries / veins classi cation
are of great assistance to the ophthalmologist in terms of diagnosis and treatment of a wide
spectrum of diseases.
Methods: We propose a new framework for precisely segmenting retinal vasculatures,
constructing retinal vascular network topology, and separating the arteries and veins. A
non-local total variation inspired Retinex model is employed to remove the image intensity
inhomogeneities and relatively poor contrast. For better generalizability and segmentation
performance, a superpixel based line operator is proposed as to distinguish between lines and
the edges, thus allowing more tolerance in the position of the respective contours. The concept
of dominant sets clustering is adopted to estimate retinal vessel topology and classify the vessel
network into arteries and veins.
Results: The proposed segmentation method yields competitive results on three pub-
lic datasets (STARE, DRIVE, and IOSTAR), and it has superior performance when com-
pared with unsupervised segmentation methods, with accuracy of 0.954, 0.957, and 0.964,
respectively. The topology estimation approach has been applied to ve public databases
1
(DRIVE,STARE, INSPIRE, IOSTAR, and VICAVR) and achieved high accuracy of 0.830,
0.910, 0.915, 0.928, and 0.889, respectively. The accuracies of arteries / veins classi cation
based on the estimated vascular topology on three public databases (INSPIRE, DRIVE and
VICAVR) are 0.90.9, 0.910, and 0.907, respectively.
Conclusions: The experimental results show that the proposed framework has e ectively
addressed crossover problem, a bottleneck issue in segmentation and vascular topology recon-
struction. The vascular topology information signi cantly improves the accuracy on arteries
/ veins classi cation
Rethinking Human-like Translation Strategy: Integrating Drift-Diffusion Model with Large Language Models for Machine Translation
Large language models (LLMs) have demonstrated promising potential in various
downstream tasks, including machine translation. However, prior work on
LLM-based machine translation has mainly focused on better utilizing training
data, demonstrations, or pre-defined and universal knowledge to improve
performance, with a lack of consideration of decision-making like human
translators. In this paper, we incorporate Thinker with the Drift-Diffusion
Model (Thinker-DDM) to address this issue. We then redefine the Drift-Diffusion
process to emulate human translators' dynamic decision-making under constrained
resources. We conduct extensive experiments under the high-resource,
low-resource, and commonsense translation settings using the WMT22 and CommonMT
datasets, in which Thinker-DDM outperforms baselines in the first two
scenarios. We also perform additional analysis and evaluation on commonsense
translation to illustrate the high effectiveness and efficacy of the proposed
method.Comment: Under revie
The Study of Microwave and Electric Hybrid Sintering Process of AZO Target
We simulated the microwave sintering of ZnO by 3D modelling. A large-size Al-doped ZnO (AZO) green ceramic compact was prepared by slurry casting. Through studying the microwave and electric hybrid sintering of the green compact, a relative density of up to 98.1% could be obtained by starting microwave heating at 1200°C and increasing the power 20 min later to 4 kW for an AZO ceramic target measuring 120 × 240 × 12 mm. The resistivity of AZO targets sintered with microwave assistance was investigated. The energy consumption of sintering could be greatly reduced by this heating method. Until now, few studies have been reported on the microwave and electric hybrid sintering of large-size AZO ceramic targets. This research can aid in developing sintering technology for large-size high-quality oxide ceramic targets
The Current Progress in Research about the Effect of Phenolics from Brown Rice on the Digestibility of Starch
Chronic diseases inclding diabetes have been important public health problems worldwide. Starch intake is one of the main causes of postprandial blood glucose elevation. Recent studies have demonstrated that polyphenols can slow down the rate of starch digestion. Brown rice is rich in phenolics, and its nutritional health benefits are widely recognized around the world as an essential source of whole grains. The unique functional groups of phenolic substances in brown rice, such as phenolic hydroxyl, have a certain inhibitory effect on digestive enzymes. Changes in the structure of starch during processing also decrease the effect of digestive enzymes on it. This not only affects the digestion rate and digestibility of starch in an effective way, but also improves food quality. This paper reviews several aspects of phenolics in brown rice and their antioxidant activities, the process of starch digestion, the effects of brown rice polyphenols on starch digestive properties and their mechanisms of action. The aim of this review is to elucidate the scientific basis of whole grain brown rice polyphenols to retard starch digestion, and provide theoretical references for the development of whole grain brown rice-based and starch-based foods which are beneficial for populations of chronic disease, obesity, overweight, elderly, etc
AGT on the S-duality Wall
Three-dimensional gauge theory T[G] arises on a domain wall between
four-dimensional N=4 SYM theories with the gauge groups G and its S-dual G^L.
We argue that the N=2^* mass deformation of the bulk theory induces a
mass-deformation of the theory T[G] on the wall. The partition functions of the
theory T[SU(2)] and its mass-deformation on the three-sphere are shown to
coincide with the transformation coefficient of Liouville one-point conformal
block on torus under the S-duality.Comment: 14 pages, 3 figures. v2: Revised the analysis in sections 3.3 and 4.
Notes and references added. Version to appear in JHE
Polynomial Normal Transform Based on L-moments and Its Application to Structural Reliability
Information on the distribution of the basic random variable is essential for the accurate analysis of structural reliability. The usual method for determining the distributions is to fit a candidate distribution to the histogram of available statistical data of the variable. Generally, such candidate distribution would have parameters that may be evaluated from the statistical moments of the statistical data. Probability distributions are usually determined using one or two parameters evaluated from the mean and standard deviation of statistical data. However, these distributions are not flexible enough to represent the skewness and the kurtosis of statistical data. Normal transformation is often used in probabilistic analysis especially when multivariate non-normal random variables are involved. This study proposes a probability distribution based on polynomial normal transform, of which parameters are determined using the first four L-moments (L-mean, L-standard deviation, L-skewness and L-kurtosis) of the available data. The simplicity, generality, flexibility and advantages of this distribution in statistical data analysis are discussed. The results are found to better than two- and three-parameter distributions, and similar to cubic normal distribution based on central moments (C-moments). With the aiming at illustrate the stability of polynomial normal transform based on L-moments, several extreme values are added to data. The proposed distribution is demonstrated to provide significant stability and flexibility. Then this method is applied to reliability index calculation, and its significance in structural reliability evaluation is discussed. The calculation results are compared with Monte Carlo calculations. Several numerical examples are further presented to demonstrate the accuracy and efficacy of the distribution for conducting reliability analyses.The study is partially supported by the National Natural Science Foundation of China (Grant No.: 51820105014, 51738001). The support is gratefully acknowledged
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