Judul: Radioprotective Effect of Rosella Extract (Hibiscus sabdariffa L.) against Recurrent Radiodiagnostic Ionizing Radiation: Study of Leukocytes Differentiation in Mice (Mus musculus)
Abstrak: Tujuan penelitian ini adalah untuk mengetahui efek radioprotektif ekstrak tanaman rosela (Hibiscus sabdariffa L.) terhadap radiasi ionisasi radiodiagnostik berulang melalui studi differensiasi sel leukosit darah perifer pada mencit (Mus musculus). Mencit betina sebanyak 48 ekor dibagi kedalam 4 kelompok yaitu: K- (diberi NaCl fisiologis tanpa radiasi), K+ (diberi NaCl fisiologis dengan radiasi), R- (diberi Ekstrak rosela tanpa radiasi), R+ (diberi Ekstrak rosela dengan radiasi). Mencit diberi ekstrak rosela dengan dosis 50 mg/kg berat badan dan NaCl fisiologis dengan volume 0.2 ml/ekor/2 hari sebelum pemaparan radiasi. Radiasi ionisasi dilakukan dengan dosis 0,2 mSv/paparan/2 hari selama 4 & 8 minggu pada berkas sinar utama. Pengambilan darah perifer dilakukan pada setiap kelompok pada minggu ke-0 (sebelum perlakuan), 2, 4, 6 & 8. Pengambilan data pemulihan selama 30 hari setelah minggu 4 dan 8 tanpa paparan radiasi. Hasil penelitian menunjukkan paparan radiasi dapat meningkatkan persentase netrofil band meningkat, netrofil adult, migrasi limfoblas, dan mieloblas serta menurunkan persentase monosit dan limfosit pada jaringan darah perifer. Pemberian ekstrak rosela dapat meningkatkan persentase limfosit dan monosit serta menurunkan persentase netrofil band, netrofil adult, limfoblas, dan mieloblas. Dari hasil penelitian didapatkan bahwa ekstrak tanaman rosela (Hibibscus sabdariffa L.) memiliki efek radioprotektif terhadap radiodiagnostik berulang pada sel leukosit darah perifer mencit (Mus musculus)
Keyword: 

Judul: Studi In-vitro dan In-vivo Efek Radioprotektif Rosela (Hibiscus Sabdariffa Linn.) terhadap Radiasi Ionisasi Radiodiagnostik Berulang
Abstrak: The purpose of this study is to determine the natural radioprotective effect of ethanolic extract of roselle (Hibiscus sabdariffa L.) through the in-vitro and invivo study of mice that were exposed by ionizing radiation from recurrent radiodiagnostic. In in-vitro study, splenic lymphocytes were cultured in different concentration of ethanolic extract of roselle. Splenic lymphocytes were divided in two groups; with radiation exposure and without radiation exposure. The numbers of lymphocyte were calculated at 1, 2 and 3 days after radiation of each group. In in-vivo study, mice supplemented with ethanolic extract of roselle dose 50 mg/kg body weight prior to radiation for 60 days and 30 days after recovery for clinical and pathological evaluation. Radiation from radiodiagnostic radiography exposure performs repeated every 2 days. Forty eight adult mice were divided in 4 groups; control (K), radiation (P), roselle (R) and roselle with radiation (RP). Clinical data were collected for live survival, body weight, and peripheral blood characteristic. Pathological data were collected for relative organ weight and histopathological finding of bone marrow and spleen at 4 and 8 weeks after radiation; 8 and 12 weeks after 30 days recovery. The in-vitro study clearly showed that roselle enhances the splenic lymphocyte proliferation and maintained amount of cells (p<0.05). The in-vivo study showed that roselle maintained peripheral blood characteristic (p<0.05), however did not affect the mice live survival and body weight (p>0.05). Pathological evaluation showed that relative organ weight, hematopoietic bone marrow cells, and white pulpa area of spleen were significant different between groups (p<0.05).
Keyword: 

Judul: The Construction of Greedy SVP LLL Algorithm
Abstrak: A lattice is a set of all integer linear combination of a set of linearly independent vectors in ℝ𝑛���. The independent vectors are called bases of lattice. Any lattice can be generated from many bases, and these bases have the same cardinality. In the lattice, the most fundamental and renowned problem is the Shortest Vector Problem (SVP). SVP is a tracking problem of the shortest nonzero vector in a lattice with equivalent bases. In two dimensions, SVP problem has resolved exactly by Gauss’ algorithm. When the lattice dimension is higher than two, A.K. Lenstra, H.W. Lenstra and L. Lovasz gave a LLL algorithm to compute approximation of nonzero shortest vector in the lattice. Reduced bases solution obtained from LLL algorithm still be an approximation and has polynomial running time of arbitrary dimension which large enough. In 1994, Schnoor and Euchner modified this LLL algorithm as a new variant which later was named deep insertion LLL algorithm. This algorithm is a modified version of the LLL algorithm to the terms of the exchange step to improve the accuracy of output of LLL reduced bases and applying it to the subset sum problem. The purpose of this research are: (1) Reconstruct the LLL algorithm and deep insertion LLL algorithm using a geometric approach. (2) Construct a greedy SVP LLL algorithm. (3) Implement the three algorithms in a symbolic programming language, and evaluate them experimentally. A bases ℬ=[𝐛���1,𝐛���2,…,𝐛���𝑛���] in ℝ𝑚��� is called reduced LLL with parameter 𝛿��� if satisfies: (a) |𝜇���𝑗���𝑖���|≤12, for every integer 𝑖���,𝑗��� with 1≤𝑖���<𝑗���<𝑛���. (b)𝛿���‖𝜋���𝑗���(𝐛���𝑗���)‖2≤‖𝜋���𝑗���(𝐛���𝑗���+1)‖2, for 𝑗���=1,2,…,𝑛���−1,where 𝛿��� is a reduced parameter of real numbers with 14<𝛿���<1. The first requirement is the reduced basis 𝛿��� must “nearly orthogonal” and in its computation case, this requirement can be reached out by using the Gram-Schmidt’s orthogonalization. While the second requirement is called exchange step, or used to called as Lovasz condition. By using both of these requirements, then they establish the LLL algorithm. Then, Schnoor and Euchner modify the LLL algorithm based on the requirements of the exchange step called the deep insertion LLL algorithm, where the exchange step is based on the comparison of the projected vector in orthogonal complement [𝐛���1,𝐛���2,…,𝐛���𝑘���−1]⊥ after j-th reduction. To construct greedy SVP LLL algorithm, the requirements of the exchange step is based on purely by comparing norm of lattice 𝐛���𝑗��� with norm lattice 𝐛���𝑖��� for 𝑖���=1,2,3…,𝑗���−1. The process of insertion reduced vector after the exchange step also has done greedily. Then, we calculate the number of arithmetic operation in greedy SVP LLL algorithm for further analysis. The result of our exprimentation for three algorithms on the certain matrix size shows that the running time of the three algorithms increases propotional to the size of the matrix. The result also shows that by using 𝛿���=34 for the LLL algorithm and the deep insertion LLL algorithm, and the greedy SVP LLL algorithm which is a new variant made by using no parameter of 𝛿���, outperform of the other of two previous algorithm in terms of speed with the same output.
Keyword: LLL algorithm, LLL deep insertion algorithm, greedy SVP LLL algorithm