Judul: Studi Histopatologi Potensi Radioprotektif Ekstrak Kelopak Rosela (Hibiscus sabdariffa L) terhadap Duodenum Mencit (Mus musculus) dengan Radiasi Ionisasi Radiodiagnostik Berulang
Abstrak: This study was conducted to find out the potency of Roselle (Hibiscus sabdariffa L.) as radioprotective against recurrent effect of radiodiagnostic radiation on duodenum of mice (Mus musculus). This research was to observed histophatological changes on duodenum of mice treated with roselle calyx extracts and radiation. Twenty four male mice were used in this study. They were divided into 4 groups namely control group (K) treated with 0.2 ml of NaCl 0.9 % (saline); primary radiation group (P) treated with 0.2 ml of NaCl 0.9 % (saline) and radiation 0.2 mSv; roselle group (R) treated with 0.2 ml roselle calyx extract; and primary radiation-roselle group (RP) treated with 0.2 ml roselle calyx extract and radiation 0.2 mSv. All treatments were done orally every two days for 8 weeks. Afterwards, 3 mice from each group were euthanized for organ sampling. The rest of mice were took 4 weeks of recovery. Afterwards, all mice were euthanized for organ sampling. Duodenum were fixed in Buffered Neutral Formaline (BNF) 10%, embedded in paraffin, then stained with hematoxyline and eosin (HE) and periodic-acid schiff (PAS). The result showed that RP group had lower demage of intestinal villi and numbers of goblet cell than P group. Lieberkühn crypt number of P group was increased, whereas intestinal villi height was decreased compared to R and RP groups. Roselle calyx extract (Hibiscus sabdariffa L.) showed radioprotective potency after radiation treatment on duodenum of mice.
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Judul: Studi Histopatologi Potensi Radioprotektif Ekstrak Kelopak Bunga Rosela (Hibiscus sabdariffa L.) dalam Radiasi Ionisasi Radiodiagnostik Berulang pada Lambung Mencit (Mus musculus
Abstrak: The aim of this study was to determine the radioprotective effect of calyx Roselle (Hibiscus sabdariffa L.) extract in recurrent radiodiagnostic ionizing radiation on the gastric of mice (Mus musculus). Fourty eight adult males of mice were used and divided into 4 groups: control (K-), radiation (K+), roselle without radiation (R-) and roselle with radiation (R+). Mice were treated with 50 mg/kg of body weight orally of Roselle extract every two days prior to recurrent irradiation for 4 and 8 weeks. The mice were euthanized by overdose Ketamine and then necropsied followed gastric collection at various time points after irradiation. Sample of gastric were processed to prepare histopathology slides with Haematoxylin-Eosin stain. The changes on the gastric alterations were studied by count the amount of parietal, chief cells and infiltration of inflammatory cells after whole body irradiation. Quantitative data were analysed with ANOVA test and followed by Duncan test. Radiation during 4 week produce total radiation 2.9 mSv and 8 week produce 5.3 mSv. The result showed that Roselle extract was protect parietal and chief cells from radiation effect by recurrent radiodiagnostic ionizing radiation. Roselle extract also inhibiting inflammation process by decreasing necrosis in parietal and chief cells. Administration of Roselle extract significantly (p<0.05) reduced the bioeffects of radiation. Roselle could be useful as natural radioprotector against ionizing radiation
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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