Judul: Kapang Endofit dari Mangrove Rhizophora mucronata dan Potensinya Sebagai Antidiare
Abstrak: Mangrove plants are known as source of traditional medicines. Endophytic fungi have important economic potential for antibacterial, enzyme and secondary metabolites that are useful especially in pharmaceutical industry. The purpose of this research was to determine the antibacterial activity of the endophytic fungi extract from mangrove Rhizophora mucronata against bacteria that cause diarrhea. This research included isolation, characterization, cultivation, extraction, and antibacterial activities test. The study yielded 5 types of endophytic fungi with different morphology. Endophytic fungus A was the selected isolate based on antagonism test. The growth patterns showed the stationary phase of isolate A was on the 15th day. The result of antibacterial test of culture broth extract showed considerable inhibition on Pseudomonas aeruginosa 18.5 mm ± 3.32. Extract of mycelium showed inhibition on Staphylococcus aureus 2 mm. The culture broth extract was more effective as antidiarrhoeal in comparison with the mycelium.
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Judul: Identifikasi Cendawan Endofit Asal Tanaman Obat dan Penapisan Potensinya sebagai Antibakteri
Abstrak: Endophytic fungi are microorganisms living in plant tissue without causing any harm to its host. The fungi can be found in all plants including medicinal plants. Endophytic fungi produced variety of bioactive compounds such as antibacterial substances. This research aimed to identify 3 isolates of endophytic fungi JBa8, JMa3, and SLbt3 which were isolated from medicinal plants and to screen their potency as source of antibacterial compounds. Identification of endophytic fungi was performed based on morphological characteristics and DNA barcode using ITS region. Antibacterial test was conducted against Bacillus subtilis, Staphylococcus aureus, Pseudomonas aeruginosa, Enteropathogenic Escherichia coli (EPEC) K1-1, and microflora E. coli by antagonism technique and agar diffusion method using mycelia extract with methanol solvent. The inhibition activity of fungal extract on bacterial tested was observed on the day 3rd, 7th, 10th, and 14th after incubation by measuring clear zone around the colonies. The 3 isolates were tentatively identified as Fusarium solani for JBa8, Fusarium sp. for JMa3, and Colletotrichum sp. for SLbt3. Antibacterial activities were observed in F. solani and Fusarium sp. which were isolated from jati belanda (Guazuma ulmifolia) and jahe merah (Zingiber officinale), respectively. F. solani inhibited the growth of EPEC K1-1, whereas Fusarium sp. suppressed P. aeruginosa with clear zone produced was 12 mm. Fusarium sp. had antibacterial activity similar with that of 8 μg/mL cefotaxime positive control. The F. solani antibacterial activity, however, was lower than the two positive control concentrations used. Colletotrichum sp. isolated from sambiloto (Andrographis paniculata) did not have any antibacterial to all bacteria tested.
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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