Judul: Testosterone Levels as a Function of Age and Origin in Cynomolgus Monkeys (Macaca fascicularis)
Abstrak: Macaca fascicularis yang dikenal sebagai monyet ekor panjang atau monyet cynomolgus banyak digunakan sebagai hewan laboratorium untuk menguji obatobatan dan hormon karena kesamaan fisiologis dan anatomi monyet tersebut dengan manusia. Tujuan penelitian ini adalah untuk mengetahui hubungan konsentrasi testosteron dengan umur dan asal hewan. Konsentrasi testosteron hewan diuji dengan uji ELISA. Hasil diolah menggunakan Univariate ANOVA dan menunjukkan bahwa konsentrasi testosteron paling tinggi pada Macaca fascicularis berumur 10-19 tahun. Pada monyet yang berasal dari penangkaran dan habitat alami tidak ada hasil konsentrasi testosteron yang signifikan dan tidak ada perbedaan nyata. Pada grafik konsentrasi testosteron pada monyet yang berasal dari penangkaran menunjukkan bahwa grafik konentrasi testosteron serupa dengan grafik testosteron berdasarkan umur. Berdasarkan uji ini, bisa dilihat bahwa ada korelasi antara umur dan konsentrasi testosteron dan asal hewan tidak berbeda nyata mungkin karena kualitas pemeliharaan monyet serta nutrisi seimbang.
Keyword: Macaca fascicularis, testosteron, tipe habitat, umur

Judul: Non-Invasive Hormone Monitoring: Faecal Androgen and Glucocorticoid in Male Crested Macaques (Macaca nigra) in Relation to Seasonal and Social Factors.
Abstrak: Monitoring hormon secara non-invasiv menggunakan sampel feses merupakan teknik yang semakin populer. Hal ini didasarkan pada prinsip bahwa selain dari darah, hormon juga bisa diukur dari feses, urin dan saliva. Feses mengandung hormon steroid seperti progesteron, estrogen, androgen dan glukokortikoid dalam bentuk metabolit. Meskipun koleksi sampel feses relatif mudah, tetapi analisis hormon tidaklah mudah. Oleh karena itu, uji validasi untuk menentukan jenis metabolit hormon merupakan hal yang perlu dan penting untuk dilakukan, sehingga akan diperoleh hasil yang valid. Teknik non-invasiv ini memberikan kemudahan bagi kita untuk mempelajari fisiologi dari hewan liar atau hewan terancam punah (endangered) seperti monyet hitam Sulawesi (Macaca nigra) dari habitat alaminya. Monyet hitam Sulawesi adalah monyet endemik dari Sulawesi dengan status kritis (critically endangered animal). Namun, informasi tentang biologi reproduksi, fisiologi dan tingkah laku pada monyet ini masih sangat terbatas.
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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