Judul: Tingkat kerusakan Babesia canis dengan pemberian ekstrak meniran, Phyllanthus sp. secara in vitro
Abstrak: Penelitian ini dilakukan dengan tujuan untuk mengetahui pengaruh pemberian ekstrak meniran dalam menghambat perkembangan Babesia canis berdasarkan perubahan morfologi B. canis pada pemupukan secara in vitro. Sampel darah yang digunakan dalam penelitian ini diambil dari dua ekor anjing betina yang bebas babesiosis sebagai donor serum dan satu ekor anjing jantan yang terinfeksi B. canis sebagai donor eritrosit berparasit. Hasil yang didapat menunjukan penurunan persentase B. canis pada semua perlakuan dan terjadi perubahan morfologi sel parasit. Perubahan yang terlihat yaitu bentuk limbik, inti pecah/rusak, inti mengecil sitoplasma hilang. Pada konsentrasi 1 µg/ml bentuk normal ditemukan dengan jumlah terbanyak (42.41 ± 38.17), sedangkan perubahan morfologi terbanyak adalah bentuk inti pecah/rusak (34.92 ± 13.61). Pada konsentrasi 10 µg/ml perubahan morfologi terbanyak adalah bentuk limbik (56.95 ± 40.28). Pada konsentrasi 100 µg/ml perubahan morfologi terbanyak adalah bentuk inti mengecil sitoplasma hilang (80.56 ± 22.15). Perubahan morfologi pada parasit merupakan indikasi adanya degenerasi parasit dan berkurangnya daya hidup parasit.
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Judul: Perkembangan Babesia canis in vitro pada konsentrasi serum 10
Abstrak: Babesia canis penyebab Babesiosis pada anjing didapatkan dari sel darah merah anjing lokal yang terinfeksi secara alami yang telah di splenektomi. Parasit ini dapat dikembangbiakkan secara in vitro dalam media RPMI 1640 dengan konsentrasi serum 10% yang diikubasikan pada suhu 37°C dengan kadar CO2 5%. Peningkatan jumlah eritrosit berparasit terjadi setelah dilakukannya subkultur pertama, peningkatan optimal terjadi pada subkultur keempat dengan jumlah eritrosit berparasit mencapai 5.28±0.19%, akan tetapi jumlah parasit mengalami penurunan pada subkultur kelima hingga mencapai 1.56 ± 0.22%. Bentuk morfologi B. canis dalam media kultur mempunyai kesamaan dengan yang ditemukan pada darah perifer.
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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