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Abstract. Energy efficiency has become an important measurement of scheduling algorithm for private cloud. The challenge is trade-off between minimizing of energy consumption and satisfying Quality of Service (QoS) (e.g. performance or resource availability on time for reservation request). We consider resource needs in context of a private cloud system to provide resources for applications in teaching and researching. In which users request computing resources for laboratory classes at start times and non-interrupted duration in some hours in prior. Many previous works are based on migrating techniques to move online virtual machines (VMs) from low utilization hosts and turn these hosts off to reduce energy consumption. However, the techniques for migration of VMs could not use in our case. In this paper, a genetic algorithm for poweraware in scheduling of resource allocation (GAPA) has been proposed to solve the static virtual machine allocation problem (SVMAP). Due to limited resources (i.e. memory) for executing simulation, we created a workload that contains a sample of one-day timetable of lab hours in our university. We evaluate the GAPA and a baseline scheduling algorithm (BFD), which sorts list of virtual machines in start time (i.e. earliest start time first) and using best-fit decreasing (i.e. least increased power consumption) algorithm, for solving the same SVMAP. As a result, the GAPA algorithm obtains total energy consumption is lower than the baseline algorithm on simulated experimentation.

A new triterpene (1) and six known pentacyclic terpenoids (2-7) were isolated from the methanol extract of the dried leaves from Mallotus apelta. Based on the spectral and chemical evidence, their structures were determined to be 3alpha-hydroxyhop-22(29)-ene (1), hennadiol (2), friedelin (3), friedelanol (4), epifriedelanol (5), taraxerone (6), and epitaraxerol (7).

Paclitaxel is one of the most effective chemotherapeutic agents for treating various types of cancer. However, the clinical application of paclitaxel in cancer treatment is considerably limited due to its poor water solubility and low therapeutic index. Thus, it requires an urgent solution to improve therapeutic efficacy of paclitaxel. In this study, folate decorated paclitaxel loaded PLA-TPGS nanoparticles were prepared by a modified emulsification/solvent evaporation method. The obtained nanoparticles were characterized by Field Emission Scanning Electron Microscopy (FESEM), Fourier Transform Infrared (FTIR) and Dynamic Light Scattering (DLS) method. The spherical nanoparticles were around 50 nm in size with a narrow size distribution. Targeting effect of nanoparticles was investigated in vitro on cancer cell line and in vivo on tumor bearing nude mouse. The results indicated the effective targeting of folate decorated paclitaxel loaded copolymer nanoparticles on cancer cells both in vitro and in vivo.

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