PENERAPAN PEMBELAJARAN KOOPERATIF PDEODE DENGAN BANTUAN SIMULASI KOMPUTER UNTUK MENGURANGI MISKONSEPSI SISWA SMA PADA MATERI LISTRIK DINAMIS

Berdasarkan studi literatur, cukup banyak siswa yang mengalami miskonsepsi. Miskonsepsi merupakan pemahaman suatu konsep yang diyakini secara kuat namun konsep yang diyakini tidak sesuai dengan konsep-konsep ilmiah para ahli. Miskonsepsi apabila tidak diperbaiki akan memahami salah konsep selamanya. Sehingga, miskonsepsi dipandang penting untuk diubah agar siswa memiliki pemahaman konsep yang benar. Untuk mengatasi miskonsepsi diperlukan pembelajaran yang mampu membuat siswa menggali konsep sendiri, dalam hal ini peneliti menggunakan pembelajaran kooperatif PDEODE menggunakan simulasi komputer . Tujuan penelitian ini adalah untuk melihat penerapan pembelajaran PDEODE dengan bantuan simulasi komputer dapat mengurangi miskonsepsi siswa pada materi listrik dinamis. Penelitian ini menggunakan metode quasi experiment jenis Pre test and Post test Group Design dengan sampel 27 siswa pada salah satu SMA Boarding di Kabupaten Bandung Barat secara purposive sample. Hasil penelitian mengungkapkan bahwa pembelajaran kooperatif PDEODE dapat menurunkan miskonsepsi siswa.;---Based on study of some literature, there are students who have misconceptions. The misconception is understanding a concept that is believed to be strong but inconsistent with the concepts of scientis. If it’s not corrected, student wouldn’t be understand on concept forever. Therefore, misconceptions is essential to be changed until they have true concepts. Cooperative learning PDEODE with computer simulations was used to overcome misconceptions required learning that makes the students explore own concept. The purpose of this study is to look at the application of cooperative learning PDEODE with the support of computer simulations can reduce misconceptions students on the dynamic electricity. This study uses quasi experimental test types Pre and Post Test Group Design with a sample of 27 students at one high school in West Bandung. Results of the study revealed that cooperative learning PDEODE can reduce misconceptions students

DriverGenePathway: Identifying driver genes and driver pathways in cancer based on MutSigCV and statistical methods

Although computational methods for driver gene identification have progressed rapidly, it is far from the goal of obtaining widely recognized driver genes for all cancer types. The driver gene lists predicted by these methods often lack consistency and stability across different studies or datasets. In addition to analytical performance, some tools may require further improvement regarding operability and system compatibility. Here, we developed a user-friendly R package (DriverGenePathway) integrating MutSigCV and statistical methods to identify cancer driver genes and pathways. The theoretical basis of the MutSigCV program is elaborated and integrated into DriverGenePathway, such as mutation categories discovery based on information entropy. Five methods of hypothesis testing, including the beta-binomial test, Fisher combined p-value test, likelihood ratio test, convolution test, and projection test, are used to identify the minimal core driver genes. Moreover, de novo methods, which can effectively overcome mutational heterogeneity, are introduced to identify driver pathways. Herein, we describe the computational structure and statistical fundamentals of the DriverGenePathway pipeline and demonstrate its performance using eight types of cancer from TCGA. DriverGenePathway correctly confirms many expected driver genes with high overlap with the Cancer Gene Census list and driver pathways associated with cancer development. The DriverGenePathway R package is freely available on GitHub: https://github.com/bioinformatics-xu/DriverGenePathway

Mg-MOF-74/MgF2 Composite Coating for Improving the Properties of Magnesium Alloy Implants: Hydrophilicity and Corrosion Resistance

Surface modification on Mg alloys is highly promising for their application in the field of bone repair. In this study, a new metal–organic framework/MgF2 (Mg-MOF-74/MgF2) composite coating was prepared on the surface of AZ31B Mg alloy via pre-treatment of hydrofluoric acid and in situ hydrothermal synthesis methods. The surface topography of the composite coating is compact and homogeneous, and Mg-MOF-74 has good crystallinity. The corrosion resistance of this composite coating was investigated through Tafel polarization test and immersion test in simulated body fluid at 37 °C. It was found that Mg-MOF-74/MgF2 composite coating significantly slowed down the corrosion rate of Mg alloy. Additionally, Mg-MOF-74/MgF2 composite coating expresses super-hydrophilicity with the water contact angle of nearly 0°. In conclusion, on the basis of MgF2 anticorrosive coating, the introduction of Mg-MOF-74 further improves the biological property of Mg alloys. At last, we propose that the hydrophilicity of the composite coating is mainly owing to the large number of hydroxyl groups, the high specific surface area of Mg-MOF-74, and the rough coating produced by Mg-MOF-74 particles. Hence, Mg-MOF-74 has a great advantage in enhancing the hydrophilicity of Mg alloy surface