Development of Models for Performance Index (PI) and Score Index(SI) of Individual players based on 5 European Soccer Leagues
Most football managers are not aware of the need for analysis of soccer data, which is one of the dynamic sports. In this study, we developed a statistical model with performance indicators and score indicators of individual soccer player based on various event data including dynamic features such as goal, assist, pass, etc. In this study, the correlation between the dependent variables and the explanatory variables, and each explanatory variable was confirmed through the correlation analysis to solve the problem of multiple communicability from the regression model and to analyze the statistically significant preliminary model. In addition, we analyzed the correlation between individual rating of the players and the data recorded in the soccer games, and found that there has been a problem with the rating of the soccer players evaluated by the reporters and the soccer statistics site. To solve this problem, we developed a model that best fit the performance indicators of individual soccer player using the linear regression model and the beta regression model. The performance index model of the athletes was developed by comparing the R-squared value and the mean absolute percentage error of two models, the linear regression model and the beta regression model, and found out the beta regression model is better model to use. By using the estimated regression coefficients of the regression model we made new PI model. Score Index, which is the attractive point of soccer, was developed by comparing Poisson regression model and negative binomial regression model based on AIC value, and the one using negative binomial regression model was found to be better. Through the model developed by this study, it is possible to collect the event data recorded by individual athletes for each soccer game, and obtain the PI & SI index which are the athlete performance index models. This allows us to evaluate each team's players objectively, analyze the team's deficiencies, and provide tools to find players, who can fill in the missing positions of the teams. This study can also be utilized to grasp the performance of athlete in real time by simulating the resultative model.
Novel Biotechnological Approach for Recognition and Purification of Antibody: Lectin Affinity Membranes
Immunoglobulin G is a glycoprotein structured molecule that is produced by the immune system and protects organism from harmful effects of antigens. Ig G amount in the blood plasma is an appropriate indicator of; infection, cancer, diabetes, cardiovascular diseases, Alzheimer and other autoimmune diseases. Besides, purification of Ig G used in the treatment of these diseases from naturel sources is carried out at high costs on the World market. It is hard to obtain Ig G in high amounts and without any decomposes, that’s why it is important to develop new systems that will help to recognize and purify Ig G antibody. In this project, my purpose was; recognizing Ig G antibody with efficient, high amounted, fast, easily, with less toxicity, economically and purifying Ig G in high ratios from its natural sources. For this purpose p(HEMA-EDMA) membranes are synthesized with free radical photo polymerization method and characterized according to SEM images, swelling behaviors FTIR analysis and elemental analysis. In order to adsorb Ig G to polymeric membranes; polymeric membranes are activated with silanization agent (IMEO) and derivatized with Con A which is a lectin affinity ligand. In the SEM results it is examined that membranes are in spherical structures. Highest swelling value is determined as 224.8%.Binding of IMEO was demonstrated with FTIR and Elemental Analysis. Optimum conditions for Ig G adsorption to membranes are; 1.5 mg/ml initial Ig G concentration, 30 minutes of adsorption time, pH 4 citrate buffer 37 0C and without any different ion strength. Optimum adsorption capacity is determined as 253.8 mg/cm2 and it is also determined that this value is 7 times higher than nonspecific Ig G adsorption to p(HEMA-EDMA) membranes. Ig G adsorption-desorption cycles (5 times) proved that product is reusable without losing its adsorption capacity. According to the electrophoresis, Ig G could be desorbed in pure form without any denaturation to its structure.
Utilization of Starch for production of plastic-like material
The research is based on the production of biodegradable plastic-like material by only using household materials. Also, it can be made at home and it causes no harm to the environment. The biodegradable plastic-like materials made by different ratio of amylose, amylopectin, glycerol and water has different use. The finished product has smooth surface, highly transparency and well flexibility. Also, it can support strong load and be able to be deformed under stress. Ratios of components are tested on: 1. Easy to injection mold 2. Flexibility 3. Tensile strength and ductility & 4. Water resistance. It is found that the ratio of tapioca starch: glycerol: water = 1.5: 0.5: 9 can withstand 13N of force and 1.5: 0.93: 9 with high ductility. To improve water resistance, more amylopectin should be added to amylose. The best water resistance ratio is glutinous rice flour: tapioca starch: glycerol: water = 0.6:0.91:0.5:9 can withstand 16N force, while 0.6:0.91: 0.93:9 and 1.35:0.16: 0.5:9 with high ductility. All materials are available in supermarkets. Higher ratio of tapioca starch can produce bookmark, with laminate effect. More tough, higher ratio of glutinous rice flour can make cups, spoons and dishes.
Understanding the Modern Diagnoses of Protein C Deficiency "Pcd" with Unknown Gene Plays a Critical Role in the Inherited Thrombophilia
Protein C deficiency (PCD) is found in 1 out of 200 to 500 persons in the general global population which is also one of the common conditions of Inherited thrombophilia, it’s characterized by an increased tendency of blood to clot in human blood vessels. It is caused by several factors including mutations in the genes involved in thrombin binding, protein c activation and numerous clotting factors. This includes F5 (Factor 5 Leiden) gene on chromosome 1q24.2, F7 (Prothrombin) gene on chromosome 13q34, SERPINC1 (serpin peptidase inhibitor C) on chromosome 1q25.2, SERPIND1 (serpin peptidase inhibitor D) on chromosome 22q11.21, HRG (Histidine Rich Glycoprotein) on chromosome 3q27.3, PLAT (Plasminogen Activator) on chromosome 8q11.21 and THBD (Thrombomodulin) gene on chromosome 20p11.21. In the current study, a three Saudi families with inherited thrombophilia has been recruited to identify the underlying cause of this special condition. Whole exome sequencing, targeting all coding exons of the human genome, was performed using Illumina Nextera library preparation kits followed by paired-end sequencing on Illumina NextSeq500 instrument. Reads quality control was performed and reads were aligned to the reference genome using BWA software. Variants calling and annotation was performed using GATK. All known genes involved in causing inherited thrombophilia All known genes involved in causing PCD were excluded by whole exome sequencing. The genes that were previously reported to be involved in inherited thrombophilia were checked for any causative variant. No mutation has been identified in known genes. identifying a novel gene underlying PCD. The Result of this study will hopefully pave the way to better understanding the disease pathophysiology and help in developing DNA based diagnosis, carrier screening and somatic gene therapy.