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Reservoir and mixer constrained scheduling for sample preparation on digital microfluidic biochips

机译:数字微流控生物芯片上样品制备的储库和混合器约束调度

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In recent years, digital microfluidic biochips are being dominantly used for implementing a wide range of biochemical laboratory protocols (bioprotocols) on hand-held devices. Accurate preparation of fluid-samples is a fundamental preprocessing step that is needed in many bioprotocols. Oftentimes, the number of reservoirs built on-chip may be far less than that of the reactant fluids to be mixed. Hence, during the execution of an assay, several fluids are to be unloaded from the reservoirs to make room for loading new fluids stored off-line. Such unload-wash-load steps (switching) may be required several times, and these steps, being manual, significantly impact assay-completion time. In this paper, we propose a new scheduling scheme namely Reservoir and Mixer constrained Scheduling (RMS) that can schedule a mixing tree obtained by a mixing algorithm, while minimizing the number of switching such that the total completion time can be minimized. Simulation results over a large number of target ratios show that given the mixing trees obtained by standard mixing algorithms such as MinMix/RMA/CoDOS, RMS reduces switching steps (on average by 40.3%/41.9%/33%) at the cost of increasing mixing time (by only 3.5%/6.2%/4.8%), compared to an existing scheduling scheme invoked with reservoir constraints.
机译:近年来,数字微流控生物芯片主要用于在手持设备上实施各种生化实验室协议(生物协议)。流体样品的准确制备是许多生物协议所需的基本预处理步骤。通常,在芯片上建立的储存器的数量可能远远少于要混合的反应流体的数量。因此,在执行测定期间,要从储存器中卸载几种流体,以腾出空间来加载离线存储的新流体。这样的卸载-洗涤-加载步骤(切换)可能需要多次,并且这些步骤是手动的,极大地影响了测定的完成时间。在本文中,我们提出了一种新的调度方案,即水库和混合器约束调度(RMS),该方案可以调度通过混合算法获得的混合树,同时最小化切换次数,从而可以使总完成时间最小化。在大量目标比率上的仿真结果表明,给定通过标准混合算法(如MinMix / RMA / CoDOS)获得的混合树,RMS会以增加成本的方式减少切换步骤(平均减少40.3%/ 41.9%/ 33%)混合时间(仅3.5%/ 6.2%/ 4.8%),与受油藏约束调用的现有调度方案相比。

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