Team-Scouter: Simulative Visual Analytics of Soccer Player Scouting.

In soccer, player scouting aims to find players suitable for a team to increase the winning chance in future matches. To scout suitable players, coaches and analysts need to consider whether the players will perform well in a new team, which is hard to learn directly from their historical performances. Match simulation methods have been introduced to scout players by estimating their expected contributions to a new team. However, they usually focus on the simulation of match results and hardly support interactive analysis to navigate potential target players and compare them in fine-grained simulated behaviors. In this work, we propose a visual analytics method to assist soccer player scouting based on match simulation. We construct a two-level match simulation framework for estimating both match results and player behaviors when a player comes to a new team. Based on the framework, we develop a visual analytics system, Team-Scouter, to facilitate the simulative-based soccer player scouting process through player navigation, comparison, and investigation. With our system, coaches and analysts can find potential players suitable for the team and compare them on historical and expected performances. For an in-depth investigation of the players' expected performances, the system provides a visual comparison between the simulated behaviors of the player and the actual ones. The usefulness and effectiveness of the system are demonstrated by two case studies on a real-world dataset and an expert interview.

Numerical Simulation and ANN Prediction of Crack Problems within Corrosion Defects.

Buried pipelines are widely used, so it is necessary to analyze and study their fracture characteristics. The locations of corrosion defects on the pipe are more susceptible to fracture under the influence of internal pressure generated during material transportation. In the open literature, a large number of studies have been conducted on the failure pressure or residual strength of corroded pipelines. On this basis, this study conducts a fracture analysis on buried pipelines with corrosion areas under seismic loads. The extended finite element method was used to model and analyze the buried pipeline under seismic load, and it was found that the stress value at the crack tip was maximum when the circumferential angle of the crack was near 5° in the corrosion area. The changes in the stress field at the crack tip in the corrosion zone of the pipeline under different loads were compared. Based on the BP algorithm, a neural network model that can predict the stress field at the pipe crack tip is established. The neural network is trained using numerical model data, and a prediction model with a prediction error of less than 10% is constructed. The crack tip characteristics were further studied using the BP neural network model, and it was determined that the tip stress fluctuation range is between 450 MPa and 500 MPa. The neural network model is optimized based on the GA algorithm, which solves the problem of convergence difficulties and improves the prediction accuracy. According to the prediction results, it is found that when the internal pressure increases, the corrosion depth will significantly affect the crack tip stress field. The maximum error of the optimized neural network is 5.32%. The calculation data of the optimized neural network model were compared with the calculation data of other models, and it was determined that GA-BPNN has better adaptability in this research problem.

An analysis of financial risk assessment of globally listed football clubs.

The global football market has grown in the past three decades, and football clubs' sustainable financial operations have gradually gained attention. This study aims to construct a financial risk assessment model applicable to the football industry, explore globally listed football clubs' overall financial operating characteristics, and analyse the leading causes of the club's financial crisis. We selected a sample of 24 currently listed football clubs worldwide and an exploratory factor analysis (EFA) model to construct the model of financial risk assessment for football clubs. The model identified and classified the financial risk components for listed football clubs, thus facilitating risk warning and prevention for modern professional clubs. This study found that football clubs are at higher financial risk overall, with the following general characteristics: (1) small amount of listed capital; (2) high asset-liability ratio; (3) low net profits and a large proportion of clubs make losses; and (4) weak asset liquidity. Finally, the study discussed the leading causes of the financial crises of football clubs in both external and internal dimensions, providing a reference for the self-sustainability of clubs and football authorities.

Determinants of international football performance: Empirical evidence from the 1994-2022 FIFA World Cup.

In the past 30 years, the global influence of the FIFA World Cup has continued to grow. According to statistics, the final match of the 2022 World Cup in Qatar attracted an audience of over 3 billion. Nowadays, nations (and regions) emphasize the correlation between overall social progress, football tradition, and national sporting prowess. This study aims to comprehend the dynamics of international football development and secure a competitive edge in the global arena. The study collected panel data from 68 countries (regions) participating in the final stage of the World Cup from 1994 to 2022. It modelled them using a generalized linear mixed model (GLMM) to reveal the macro determinants of success and winning patterns in international football performance. The findings show that (1) football tradition's "characteristic values" (e.g. World Cup host, the experience of hosting the World Cup and the number of all-time World Cup winners) and national comprehensive sporting strength (as represented by the Olympic Games results) have significantly contributed to the national team's World Cup performance; (2) the country's Human Development Index (HDI) has a significant negative impact on World Cup performance; (3) the history of football participation (e.g. the number of years of membership in the Intercontinental Football Association (IFA), history of professional leagues) will have little impact on World Cup performance; (4) two interactive variables: population scale × national comprehensive sporting strength (GPOP × CSOGMedals) and economic level × football tradition (lnGDP × PLHistory), have a negative and positive combined effect on World Cup performance, respectively.

Size Effect of a Piezoelectric Patch on a Rectangular Plate with the Neural Network Model.

Artificial neural networks have been widely used in many studies, such as the prediction of the piezoelectric effect of the plate of engineering structures in vibration and noise reduction. In this paper, an artificial neural network (ANN) model was employed to explore the piezoelectric patch size and thickness's effect on the first order natural frequency and displacement amplitude of a plate. With the finite element method (FEM), a rectangular plate actuated by a piezoelectric patch was analyzed with various patch sizes. The FEM data was later used to build an ANN model. The dynamic response of the plate was predicted by the ANN model and validated with FEM in terms of 1st order natural frequency and displacement amplitude. Results from case studies showed that with the input of patch length, width and thickness, ANN model can accurately predict both natural frequency and displacement amplitude. When the input of ANN model was simplified to patch size and thickness or the volume of the patch, the accuracy became worse and worse. The influence of the patch size and thickness on the first order natural frequency was coupled and the maximal and minimal values were predicted based on the ANN model.

Active Actuating of a Simply Supported Beam with the Flexoelectric Effect.

Piezoelectric materials with the electro-mechanical coupling effect have been widely utilized in sensors, dampers, actuators, and so on. Engineering structures with piezoelectric actuators and sensors have provided great improvement in terms of vibration and noise reduction. The flexoelectric effect-which describes the coupling effect between the polarization gradient and strain, and between the strain gradient and electric polarization in solids-has a fourth-rank order tensor electro-mechanical coupling coefficient, and in principle makes the flexoelectricity existing in all insulating materials and promises an even wider application potential in vibration and noise control. In the presented work, a flexoelectric actuator was designed to actuate a simply supported beam. The electric field gradient was generated by an atomic force microscopy probe. Flexoelectric control force and moment components could be induced within the flexoelectric control layer. As flexoelectricity is size-dependent, the key parameters that could affect the actuating effect were examined in case studies. Analytical results showed that the induced flexoelectric control moment was strongly concentrated at the probe location. The controllable transverse displacement of the simply supported beam was calculated with the modal expansion method. It was found that the controllable transverse displacement was dependent on the probe location as well.

[Apoptotic induction of human lung carcinoma A549 cells by DFMO through Fas/FasL pathway].

BACKGROUND & OBJECTIVE: Fas/FasL pathway play an important role in cell apoptosis. To investigate the role of Fas/FasL system in polyamine biosynthesis inhibition and malignant phenotype reversion of carcinoma cells, we examined the effect of DFMO (alpha-difluoromethylornithine), an inhibitor of polyamine biosynthesis, on cell growth and apoptosis of A549 cells, and their association with human lung carcinoma-associated antigen, ras P21 protein, and Fas/FasL. METHODS: MTT assay,flow cytometry,and DNA fragmentation analysis were used to determine cell growth and apoptosis,respectively. The gene and protein expression were determined by reverse transcription polymerase chain reaction (RT-PCR) and immunohistochemical staining, respectively. RESULTS: DFMO could inhibit the growth of A549 cells and induce their apoptosis, meanwhile the cells in G(1) phase were increased with (61.0+/-2.08)%, the cells in S phase were decreased with (21.2+/-0.88)%, and DNA ladder were observed. Simultaneously, the expression of human lung carcinoma-associated antigen and ras P21 protein were downregulated, but Fas mRNA and protein expression were upregulated. CONCLUSION: DFMO induce apoptosis of human lung carcinoma A549 cells through Fas/FasL pathway. It might be correlated with the expression of human lung carcinoma-associated antigen and ras P21 protein.

[Effect of alpha-difluoromethylornithine on growth characteristics and expression of ALT-04ag gene of human lung carcinoma cells].

OBJECTIVE: To study the effect of polyamine biosynthesis inhibition on growth characteristics of human lung carcinoma cells and its correlation with the expression of human lung carcinoma associated antigen ALT-04ag gene. METHODS: The gene expression was detected by RT-PCR and immunocytochemical tests. The cell growth characteristics were studied by cell growth curves, morphological observation, FCM analysis and DNA electrophoresis. RESULTS: Human lung squamous carcinoma cells L78 treated with 5 mmol/L alpha-difluoromethylornithine (DFMO) for 5 days showed significant growth inhibition and apoptosis induction. The mRNA and protein expressions of ALT-04ag gene in the cells were downregulated, while these changes resulted from DFMO treatment were prevented by provision of DFMO along with exogenous putrescine. CONCLUSION: The effect of polyamine biosynthesis inhibition induced by DFMO restrains the growth characteristics and promotes apoptosis of human lung carcinoma L78 cells, which is associated with down regulation of ALT-04ag gene expression.