Judul: Analisis hematologi, nilai kecernaan dan tingkah laku monyet ekor panjang (Macaca fascicularis) jantan obes yang diintervensi nikotin
Abstrak: Penelitian ini dilakukan untuk memperoleh informasi tentang perkembangan nilai-nilai hematologi dan kecernaan, dan kondisi tingkah laku dari 15 monyet ekor panjang jantan obes, sebelum dan sesudah diintervensi dengan nikotin. Penelitian ini dilakukan dilakukan dalam dua tahap. Tahap pertama adalah pembentukan hewan model obes yang telah berlangsung selama satu tahun, tahap pertama dari penelitian ini berlangsung dari 23 Februari sampai dengan 11 Maret 2009. Tahap kedua, yakni intervensi nikotin dalam pakan (0,75 mg/kg bobot badan/12 jam) pada hewan coba obes tersebut dari 12 Maret sampai dengan 3 Juni 2009. Penelitian dilakukan dengan menggunakan Rancangan Acak Lengkap yang tersarang dalam waktu, dianalisa dengan perangkat lunak SAS versi 6,12 untuk mendapatkan korelasi antara tingkah laku dengan nilai-nilai hematologi dan kecernaan. Hasil penelitian ini menunjukkan bahwa ada penurunan yang sangat signifikan (P<0,01) pada nilai hematologi diantaranya adalah sel darah merah, hematokrit dan platelet selama intervensi nikotin, namun kadar hemoglobin masih menunjukkan kisaran normal dengan nilai indeks sel darah merah (MCV, MCH dan MCHC) menunjukkan peningkatan yang sangat signifikan (P<0,01). Sedangkan jumlah sel darah putih, persentase netrofil dan limfosit tidak menunjukkan adanya perubahan, namun terjadi penurunan persentase eosinofil dan monosit (P<0,01). Intervensi nikotin tampak menunjukkan adanya peningkatan nilai kecernaan dan penurunan rataan konsumsi pakan (P<0,01). Penelitian menunjukkan adanya tanda-tanda penurunan bobot badan dan IMT walaupun tidak signifikan. Intervensi nikotin menyebabkan monyet menjadi lebih aktif, yang dibuktikan dengan indikasi peningkatan aktivitas makan dan minum, self grooming dan frekuensi lokomosi. Analisis korelasi menunjukkan bahwa bobot badan mempunyai korelasi positif terhadap hemoglobin, netrofil dan tingkah laku minum, sedangkan hemoglobin memiliki korelasi positif terhadap kecernaan protein kasar, BETN, bahan kering dan energi yang menunjukkan korelasi yang sangat tinggi (P<0,01). Nilai kecernaan protein kasar, berkorelasi positif dengan tingkah laku self grooming serta tingkah laku kontak, sedangkan kecernaan lemak kasar memiliki korelasi positif (P<0,05) dengan tingkah laku menatap. Korelasi antara hematologi dan tingkah laku memberikan indikasi bahwa tingkah laku minum dan self grooming, (MCV dan MCH) mempunyai nilai korelasi positif (P<0,05).
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Judul: Analisis Bobot Badan, Indeks Massa Tubuh, serta Profil Lipid (Total Kolesterol dan HDL) Pada Monyet Ekor Panjang (Macaca fascicularis) dengan Diet Tinggi Lemak dan Intervensi Nikotin.
Abstrak: The aim of this study was to obtain information of body weight, BMI (Body Mass Index), lipid profile especially cholesterol total and HDL cholesterol related to intervention of nicotine. This research consisted of 15 long tailed macaques, divided into three groups based on the types of diet. There were diet type A with energy derived from tallow, diet type B with energy derived from tallow and yolk eggs, and diet type C with commercial diet of Monkey chow. Observation was done before and during the intervention of low dose nicotine with dosage 0.75 mg/kg BB/12 hours per oral. The results of blood lipid analysis showed that there was a significant increase in cholesterol level total during three months of nicotine intervention, especially in group B. However, we found HDL level (P<0.05) was increased in the second month of diet type B and in the third month of diet type A and C. There was no significant decrease in body weight and BMI (P>0.05) during the period of nicotine intervention.
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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