Results: The results showed that there was a significant difference between mean values of interleukin-8 (P < 0.05, F = 12.25) and the plasminogen activator inhibitor-1 (P < 0.05, P=0.10737) in four groups. A dose of 60 mg/ kg/day, a pure extract of Taxol was injected peritoneal Data were analyzed by t-test, One-way ANOVA and post hoc Bonferron's at the significant level P<0. The training group completed the endurance training protocol, which included 3 sessions per week, 50 minutes per session, at a speed of 14-18 m/s for six weeks. The implantation of cancerous tumors was performed under the skin of the upper pelvis. Material and method: In this experimental study, 40 female C57 mice, eight weeks old, were randomly divided into 4 groups: cancer, cancer-taxol complement, cancer-training and cancer-training - taxol complement with 10 mice in each group. Greedy layer-wise pretraining Procedia PDFīackground: The The purpose of this study was to evaluate the effect of six-week aerobic training and taxol consumption on interleukin 8 and Plasminogen Activator Inhibitor-1 (PAI-1) in mice with cervical cancer. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio with respect to the most efficient conversion. You will be able to generate the logical structure of this system and transform it into beautiful 3D animations.Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. You will be at the end of the course, capable of simulating complex system in many different industries including warehouses, supply chain networks, manufacturing facilities, people interactions and others. This course also touches databases with the SQL API, Excel API, GIS integration and many other things that use the powerful AnyLogic Software to create amazing 3D animation models, generate statistics and data representation through different kinds of graphs and plots. It's a good starting point to learn any programming language afterwards. This course will also teach you the basics of JAVA, of course not to become a JAVA expert, but to be able to be fluent with its basic tools in order to be an autonomous JAVA developer. This in order to stimulate this new ability in your brain and accelerate your progress. You will learn the grand majority of the tools required to model advanced scenarios to solve complicated business questions.Īfter the JAVA introduction, the course gets quite deep quite fast with assignments that are not easy to complete. On this course you will learn how to develop simulation models using AnyLogic, with the paradigms of discrete-events, agent-based and the combination of both as multi-method simulations. This course was developed for people who have zero or very little knowledge of JAVA and simulation modeling and for people who have used other simulation software and want to learn a new one from scratch. If you want a big discount for this course, find a way to contact me.
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