Digital Image Art Style Transfer Algorithm and Simulation Based on Deep Learning Model

In order to solve the problems of poor region delineation and boundary artifacts in Indian style migration of images, an improved Variational Autoencoder (VAE) method for dress style migration is proposed. Firstly, the Yolo v3 model is used to quickly identify the dress localization of the input image, and then the classical semantic segmentation algorithm (FCN) is used to finely delineate the desired dress style migration region twice, and finally the trained VAE model is used to generate the migrated Indian style image using a decision support system. The results show that, compared with the traditional style migration model, the improved VAE style migration model can obtain finer synthetic images for dress style migration, and can adapt to different Indian traditional styles to meet the application requirements of dress style migration scenarios. We evaluated several deep learning based models and achieved BLEU value of 0.6 on average. The transformer-based model outperformed the other models, achieving a BLEU value of up to 0.72.

Model-Based Prediction of an Effective Adhesion Parameter Guiding Multi-Type Cell Segregation

The process of cell-sorting is essential for development and maintenance of tissues. Mathematical modeling can provide the means to analyze the consequences of different hypotheses about the underlying mechanisms. With the Differential Adhesion Hypothesis, Steinberg proposed that cell-sorting is determined by quantitative differences in cell-type-specific intercellular adhesion strengths. An implementation of the Differential Adhesion Hypothesis is the Differential Migration Model by Voss-Böhme and Deutsch. There, an effective adhesion parameter was derived analytically for systems with two cell types, which predicts the asymptotic sorting pattern. However, the existence and form of such a parameter for more than two cell types is unclear. Here, we generalize analytically the concept of an effective adhesion parameter to three and more cell types and demonstrate its existence numerically for three cell types based on in silico time-series data that is produced by a cellular-automaton implementation of the Differential Migration Model. Additionally, we classify the segregation behavior using statistical learning methods and show that the estimated effective adhesion parameter for three cell types matches our analytical prediction. Finally, we demonstrate that the effective adhesion parameter can resolve a recent dispute about the impact of interfacial adhesion, cortical tension and heterotypic repulsion on cell segregation.

Migration ethics in Genesis 47:1–12 as a limelight for Nigerian migrants

In Genesis 47, Jacob and his descendants were regularly migrants in Egypt. This article examines this text and its interest in the contemporary migrant crises affecting Nigerians. Findings reveal that Genesis 47 encourages regular migration and discourages irregular migration. The migration ethics in the pericope is contrary to the contemporary migration model adopted by Nigerians. This article concluded that the migrant crises affecting Nigerians occur as a result of the high level of irregular migration ethics adopted by Nigerian migrants. To find a solution to the problem, there should be the provision of adequate enlightenment and information to promote regular migration amongst Nigerians. Nigerian migrants should endeavour to present themselves to the authorities of their destination countries. This research employs the exegetical and phenomenological methods.Intra/interdisciplinary implications: This research is based on the misunderstood migration ethics in Genesis 47. Contrary to what is obtainable amongst Nigerian migrants, Genesis 47 encourages regular migration. Nigerians, just like Jacob and his descendants, migrated to other countries mainly for economic survival. However, it was discovered that most of the Nigerian migrants are irregular migrants. Disciplines implicated include Old Testament, Cultural Studies, and Sociology.

Soil moisture migration model based on Flux-concentration relation under steady rainfall

Moisture content distribution in soil is of great importance for understanding rainfall-induced slope failure and roadbed settlement. This study aims to develop a moisture migration model that improves the quantification of moisture content at an arbitrary point of the soil at any time for the whole process of infiltration under steady rainfall. The model was derived from the Richards' equation using the Flux-concentration relation, which was validated by numerical solutions calculated by Hydrus-1D software to evaluate the performance of the model. Results showed good accuracy and high adaptability for the moisture migration simulation of a wide range of soil types, and is applicable for short-duration and long-duration steady rainfall. Moreover, it can also reflect the stratification phenomenon for soil profile wetting by infiltration. Our analysis indicates that the flux and surface volumetric moisture content together can bound the boundary conditions of rainfall infiltration, which presents a shift from constant-flux to constant-concentration during a long-duration steady rainfall. The migration rate of the wetting front in the later stage of infiltration positively correlates with rainfall intensity under the constant-flux condition, while it finally stabilizes at Ks/(θs − θi) under the constant-concentration condition (i.e., Ks-saturated hydraulic conductivity, θs-saturated volumetric moisture content, θi-initial volumetric moisture content). HIGHLIGHT Moisture migration model was derived to improve the quantification of moisture content at an arbitrary point of the soil at any time for the whole process of infiltration under steady rainfall, which shows good accuracy and high adaptability for the moisture migration simulation of a wide range of soil types, and is applicable for short-duration and long-duration steady rainfall.

The Vertical Leaching Migration Research on 137Cs in Soil Around Shidaowan Plant of CAP1400

The risk of radioactive material leakage caused by nuclear accidents increased with the increasing of number of Nuclear Power Plants in China. One of the serious threat of radiation harm to the human body is believed to be 137Cs. It can exist in the environment for a long time, due to the half-life of which is as long as about 30 years. In this research, the brown soil and aeolian sandy soil were selected as two kinds of classic soil around the site of Shidaowan demonstration plant of CAP1400 to carry out the 137Cs migration model experiments. The source of radioactivity was put on the 16 of experiment columns that were filled by undisturbed soil, the simulated raining weather was according to the local rainfall amount with two sprinklers, and the sunlight was replaced by fluorescent lamp. The result showed that the vertical migration model of radionuclides in soil is one-dimensional convective dispersion equation. three-year experiments showed that most of 137Cs in soil were distributed in the range of 0–4cm. The simulation results using the Hydrus 1D with 10 years that most of 137Cs in soil were distributed in the range of 0–10cm, so the nuclear accident caused by the serious nuclides have little impact on groundwater.

Online Data Migration Model and ID3 Algorithm in Sports Competition Action Data Mining Application

The ID3 algorithm is a key and important method in existing data mining, and its rules are simple and easy to understand and have high application value. If the decision tree algorithm is applied to the online data migration of sports competition actions, it can grasp the sports competition rules in the relationship between massive data to guide sports competition. This paper analyzes the application performance of the traditional ID3 algorithm in online data migration of sports competition actions; realizes the application steps and data processing process of the traditional ID3 algorithm, including original data collection, original data preprocessing, data preparation, constructing a decision tree, data mining, and making a comprehensive evaluation of the traditional ID3 algorithm; and clarifies the problems of the traditional ID3 algorithm. Mainly, the problems of missing attributes and overfitting are clarified, which provide directions for the subsequent algorithm optimization. Then, this paper proposes a k -nearest neighbor-based ID3 optimization algorithm, which selects values similar to k -nearest neighbors to fill in the missing values for the attribute missing problem of the traditional ID3 algorithm. Based on this, the improved algorithm is applied to the online data migration of sports competition actions, and the application effect is evaluated. The results show that the performance of the k -nearest neighbor-based ID3 optimization algorithm is significantly improved, and it can also solve the overfitting problem existing in the traditional ID3 algorithm. For the overall classification problem of six types of samples of travel patterns, the experimental data samples have the characteristics of high data quality, a considerable number of samples, and obvious sample differentiation. Therefore, this paper also uses the deep factorization machine algorithm based on deep learning to classify the six classes of travel patterns of sports competition action data using the previously extracted relevant features. The research in this paper provides a more accurate method and a higher-performance online data migration model for sports competition action data mining.

Robust Quantification of Regional Patterns of Migration in Three-Dimensional Cell Culture Models

Wound healing assays is a common two-dimensional migration model, with the spheroid assay three-dimensional migration model recently emerging as being more representative of in vivo migration behaviours. These models provide insight to the overall migration of cells in response to various factors such as biological, chemotactic and molecular agents. However, currently available analysis techniques for these assays fall short on providing quantifiable means to measure regional migration patterns, , which is essential to allow more robust assessment of drug treatments on cell migration in a chemotactic fashion. Therefore, the aim of this study is to develop a finite element (FE) based pipeline that can objectively quantify regional migration patterns of cells. Here, we report that our FE based approach was able to accurately measure changes in overall migration areas compared to the standard ImageJ method. Furthermore, our regional migration analysis provided accurate and quantitative means to analyse the migration pattern seen in the phantom data and our experimental results, giving us confidence that it can be a robust tool for analysing cell migration patterns.

Research on data mining and prediction of large-scale competitions based on online data migration model

To improve the data mining effect of large-scale (sports) competitions and improve the results of competition prediction and analysis, based on the online data migration model, this paper establishes a system model for processing applications of transmitting nodes, relay nodes and receiving nodes in the competition network, and proposes an online distributed cost optimization control strategy to be responsible for the operation and processing of applications in the communication system. The control strategy realizes that while ensuring the stability of the application queue, the optimization target system overhead is infinitely close to the theoretical optimal value. In addition, according to the competition data mining and prediction requirements, this paper constructs a system structure model, and designs experiments to verify the system performance. The research results show that the performance of the data mining and prediction system of large-scale (sports) competition constructed in this paper meets actual needs.