Judul: Fenomena Peradangan Kardio-Obesitas Pada Monyet Ekor Panjang (Macaca Fascicularis) Jantan Dewasa Dengan Induksi Diet Obsitogenik
Abstrak: Pola hidup masyarakat dengan konsumsi makanan tinggi kolesterol dan karbohidrat akan meningkatkan resiko sindrom metabolik, seperti obesitas. Obesitas adalah faktor utama penyebab penyakit kardiovaskular dan peradangan yang dapat menyebabkan aterosklerosis serta akumulasi sel-sel radang pada sekitar pembuluh darah. Respon peradangan yang disebabkan oleh kardio-obesitas pada pembuluh darah aorta diteliti pada monyet ekor panjang jantan dewasa (Macaca fascicularis) (n=11) menggunakan standar penilaian kuantitatif histologis. Respons peradangan ini diamati pada monyet obesitas yang disebabkan oleh asupan diet obesitogenik selama 15 bulan (n=9) dibandingkan dengan monyet obesitas yang disebabkan konsumsi pakan monyet dalam jumlah tak terbatas (ad-libitum) (n=2). Fenomena ini bisa digunakan sebagai gambaran mikroskopis kardio-obesitas pada monyet sebagai hewan model penyakit kardiovaskular. Respon peradangan lebih rendah pada monyet yang diberi asupan diet obsitogenik diikuti intervensi nikotin cair dosis rendah selama tiga bulan. Studi kasus ini menunjukkan bahwa nikotin cair dosis rendah memiliki efek hambat pada respon peradangan kardio-obesitas.
Keyword: Macaca fascicularis, obesitas, respon peradangan, nikotin cair dosis rendah

Judul: Hipertrofi Kordis pada Monyet Ekor Panjang (Macaca fasicularis) Pasca Obes Induksi Diet Obesitogenik Diikuti Asupan Nikotin
Abstrak: The aim of this study was to examine the evidence of left ventricular hypertrophy of male cynomolgus macaque (Macaca fascicularis) as animal model of human obesity and atherosclerosis. The animals were fed obesitogenic diet for 12 month and treated by per-oral nicotine liquid for 3 month. The objective of this study is exploring the macroscopic aspect of fatty heart enlargement and its compensation. Almost of fifteen samples of hearts showed varies level of fatty deposition and blunted apex. Heart muscle thickening was measured on distal transversal one centimeter’s cutting using caliper with two decimal precision. Relative Wall Thickness (RWT) was measured by calculating Septal Wall Thickness (SWT) that added by Posterior Wall Thickness (PWT) and divided by Left Ventricular Internal Diameter (LVID). All of the heart mostly have concentric type of hypertrophy with elevation of RWT (1.87 ± 1.47 centimeter) compare to the normal one (0,45 centimeter). This RWT has low relations to body weight (r = 0.060) and body mass index (r =0.054). This study refilled that cynomlgous macaque can be developed as animal model of ventricular hypertrophy as a part of alternative solution of ventricular hypertrophy in conjunction with endemic obesity on urban society. This study suggested that the study of nicotine effect on ventricular hypertrophy should be conducted microscopically.
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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