Identifikasi dan Uji Toksisitas Ekstrak Metanol dari Daun Tanaman Sirsak (Annona Muricata L)

Soursoup (Annona muricata L) was used in herbal medicine. This Annonaceae familymember contains alkaloids, tannins, and several other chemical constituents, includingasetogenin that allegedly to have cytotoxic potential. The n-hexane and methanolmacerating method was applied to isolate the secondary metabolites from the stem barkof this plant. The separation was carried out by vacuum liquid chromatography (VLC),column chromatography, and gel chromatography respectively. Characterization of thefractions was established using UV-Vis and FTIR spectrophotometry. Toxicity assaywas conducted by Brine Shrimp Lethality Test (BSLT) method. The LC 50 of 3 rd to 11 thfractionts of the methanol extract wer 4481.25; 37; 11.46; 0.85; 3.02; 0.23; 10.97; 8.53and 4093 ppm, respectively. The 3 rd and 11 th fractionts were not toxic, whereas otherfractions were toxic and potential to be used as an anticancer

Rapid Assessment Terhadap Kerusakan Bangunan Akibat Erupsi Merapi Tahun 2010

Erupsi Gunungapi Merapi di tahun 2010 memberikan dampak salah satunya adalah kerusakan bangunan. Penelitian ini bertujuan untuk memetakan dan menginventarisasi kerugian bangunan serta memberikan rekomendasi kebijakan rehabilitasi dan rekonstruksi tempat tinggal dan fasilitas permukiman, khususnya di wilayah Kabupaten Sleman. Metode penelitian yang digunakan adalah analisis penginderaan jauh dan sistem informasi geografis serta survey lapangan. Data dasar menggunakan Citra IKONOS, Citra ASTER dan Citra Geo eye-1. Hasil penelitian menunjukkan 3245 buah bangunan mengalami kerusakan berat hingga hancur, semuanya di Kecamatan Cangkringan. Wilayah ini direkomendasikan PVMBG menjadi Kawasan Rawan Bencana III Merapi. Penelitian merekomendasikan Pemerintah Daerah Kabupaten Sleman untuk melakukan relokasi warga dengan pendekatan persuasif dan sistematis berbasis sosial budaya, dengan sistem bedol dusun/kampung, penyediaan wilayah tujuan relokasi yang sesuai dengan wilayah asal, sistem tukar lahan, dan penyediaan fasilitas yang memadai. Rehabilitasi dan rekonstruksi juga perlu memperhatikan penyediaan fasilitas lingkungan permukiman antara lain fasilitas air bersih, fasilitas air limbah dan MCK, fasilitas pengelolaan sampah, fasilitas ruang publik, serta fasilitas jalan dan drainase

Performance of the reconstruction algorithms of the FIRST experiment pixel sensors vertex detector

Hadrontherapy treatments use charged particles (e.g. protons and carbon ions) to treat tumors. During a therapeutic treatment with carbon ions, the beam undergoes nuclear fragmentation processes giving rise to significant yields of secondary charged particles. An accurate prediction of these production rates is necessary to estimate precisely the dose deposited into the tumours and the surrounding healthy tissues. Nowadays, a limited set of double differential carbon fragmentation cross-section is available. Experimental data are necessary to benchmark Monte Carlo simulations for their use in hadrontherapy. The purpose of the FIRST experiment is to study nuclear fragmentation processes of ions with kinetic energy in the range from 100 to 1000 MeV/u. Tracks are reconstructed using information from a pixel silicon detector based on the CMOS technology. The performances achieved using this device for hadrontherapy purpose are discussed. For each reconstruction step (clustering, tracking and vertexing), different methods are implemented. The algorithm performances and the accuracy on reconstructed observables are evaluated on the basis of simulated and experimental data

Learning to Communicate: A Machine Learning Framework for Heterogeneous Multi-Agent Robotic Systems

We present a machine learning framework for multi-agent systems to learn both the optimal policy for maximizing the rewards and the encoding of the high dimensional visual observation. The encoding is useful for sharing local visual observations with other agents under communication resource constraints. The actor-encoder encodes the raw images and chooses an action based on local observations and messages sent by the other agents. The machine learning agent generates not only an actuator command to the physical device, but also a communication message to the other agents. We formulate a reinforcement learning problem, which extends the action space to consider the communication action as well. The feasibility of the reinforcement learning framework is demonstrated using a 3D simulation environment with two collaborating agents. The environment provides realistic visual observations to be used and shared between the two agents.Comment: AIAA SciTech 201