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Microfluidics-based biochips are soon expected to revolutionize clinical diagnosis, DNA sequencing, and other laboratory procedures involving molecular biology. Most microfluidic biochips today are based on the principle of contin...
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Microfluidics-based biochips are soon expected to revolutionize clinical diagnosis, DNA sequencing, and other laboratory procedures involving molecular biology. Most microfluidic biochips today are based on the principle of continuous fluid flow and they rely on permanently etched microchannels, micropumps, and microvalves. We focus here on the automated design of "digital" droplet-based microfluidic biochips. In contrast to conventional continuous-flow systems, digital microfluidics offers dynamic reconfigurability; groups of cells in a microfluidics array can be reconfigured to change their functionality during the concurrent execution of a set of bioassays. We present a simulated annealing-based technique for module placement in such biochips. The placement procedure not only addresses chip area, but also considers fault tolerance, which allows a microfluidic module to be relocated elsewhere in the system when a single cell is detected to be faulty. Simulation results are presented for case studies involving the polymerase chain reaction and multiplexed in vitro clinical diagnostics.
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Microfluidics-based biochips are revolutionizing high-throughput sequencing, parallel immunoassays, blood chemistry for clinical diagnostics, and drug discovery. These emerging devices enable the precise control of nanoliter volum...
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Microfluidics-based biochips are revolutionizing high-throughput sequencing, parallel immunoassays, blood chemistry for clinical diagnostics, and drug discovery. These emerging devices enable the precise control of nanoliter volumes of biochemical samples and reagents. They combine electronics with biology, and they integrate various bioassay operations, such as sample preparation, analysis, separation, and detection. Compared to conventional laboratory procedures, which are cumbersome and expensive, miniaturized biochips offer the advantages of higher sensitivity, lower cost due to smaller sample and reagent volumes, system integration, and less likelihood of human error. This chapter provides an overview of droplet-based "digital" microfluidic biochips. It describes emerging computer-aided design (CAD) tools for the automated synthesis and optimization of biochips from bioassay protocols. Recent advances in fluidic-operation scheduling, module placement, droplet routing, pin-constrained chip design, and testing are presented. These CAD techniques allow biochip users to concentrate on the development of nanoscale bioassays, leaving chip optimization and implementation details to design-automation tools.
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摘要 :
Microfluidics-based biochips are revolutionizing high-throughput sequencing, parallel immunoassays, blood chemistry for clinical diagnostics, and drug discovery. These emerging devices enable the precise control of nanoliter volum...
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Microfluidics-based biochips are revolutionizing high-throughput sequencing, parallel immunoassays, blood chemistry for clinical diagnostics, and drug discovery. These emerging devices enable the precise control of nanoliter volumes of biochemical samples and reagents. They combine electronics with biology, and they integrate various bioassay operations, such as sample preparation, analysis, separation, and detection. Compared to conventional laboratory procedures, which are cumbersome and expensive, miniaturized biochips offer the advantages of higher sensitivity, lower cost due to smaller sample and reagent volumes, system integration, and less likelihood of human error. This chapter provides an overview of droplet-based "digital" microfluidic biochips. It describes emerging computer-aided design (CAD) tools for the automated synthesis and optimization of biochips from bioassay protocols. Recent advances in fluidic-operation scheduling, module placement, droplet routing, pin-constrained chip design, and testing are presented. These CAD techniques allow biochip users to concentrate on the development of nanoscale bioassays, leaving chip optimization and implementation details to design-automation tools.
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Microfluidics-based biochips are soon expected to revolutionize laboratory procedures involving molecular biology. These composite microsystems, also known as lab-on-a-chip or bio-MEMS, automate highly repetitive laboratory tasks ...
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Microfluidics-based biochips are soon expected to revolutionize laboratory procedures involving molecular biology. These composite microsystems, also known as lab-on-a-chip or bio-MEMS, automate highly repetitive laboratory tasks by replacing cumbersome equipment with miniaturized and integrated systems, and they enable the handling of small amounts, e.g., micro- and nano-liters, of fluids. Thus they are able to provide ultra-sensitive detection at significantly lower cost than traditional methods.
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Sensor nodes in a distributed sensor network can fail due to a variety of reasons, e.g., harsh weather conditions, sabotage, battery failure, and component wear-out. Since many wireless sensor networks are intended to operate in a...
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Sensor nodes in a distributed sensor network can fail due to a variety of reasons, e.g., harsh weather conditions, sabotage, battery failure, and component wear-out. Since many wireless sensor networks are intended to operate in an unattended manner after deployment, failing nodes cannot be replaced or repaired during field operation. Therefore, by designing the network to be fault-tolerant, we can ensure that a wireless sensor network can perform its surveillance and tracking tasks even when some nodes in the network fail. In this paper, we describe a fault-tolerant self-organization scheme that designates a set of backup nodes to replace failed nodes and maintain a backbone for coverage and communication. This scheme has been implemented on top of an energy-efficient self-organization technique for sensor networks. The proposed fault-tolerance-node selection procedure can tolerate a large number of node failures, without losing either sensing coverage or communication connectivity.
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Sensor nodes in a distributed sensor network can fail due to a variety of reasons, e.g., harsh weather conditions, sabotage, battery failure, and component wear-out. Since many wireless sensor networks are intended to operate in a...
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Sensor nodes in a distributed sensor network can fail due to a variety of reasons, e.g., harsh weather conditions, sabotage, battery failure, and component wear-out. Since many wireless sensor networks are intended to operate in an unattended manner after deployment, failing nodes cannot be replaced or repaired during field operation. Therefore, by designing the network to be fault-tolerant, we can ensure that a wireless sensor network can perform its surveillance and tracking tasks even when some nodes in the network fail. In this paper, we describe a fault-tolerant self-organization scheme that designates a set of backup nodes to replace failed nodes and maintain a backbone for coverage and communication. This scheme has been implemented on top of an energy-efficient self-organization technique for sensor networks. The proposed fault-tolerance-node selection procedure can tolerate a large number of node failures, without losing either sensing coverage or communication connectivity.
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3D integrated circuits (3D ICs) based on through-silicon vias (TSVs) have emerged as a promising solution for overcoming interconnect and power bottlenecks in IC design. However, testing of 3D ICs remains a significant challenge, ...
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3D integrated circuits (3D ICs) based on through-silicon vias (TSVs) have emerged as a promising solution for overcoming interconnect and power bottlenecks in IC design. However, testing of 3D ICs remains a significant challenge, and breakthroughs in test technology are needed to make 3D integration commercially viable. This paper first presents an overview of TSV-related defects and the impact of TSVs in the form of new defects in devices and interconnects. The paper next describes recent advances in testing, diagnosis, and design-for-testability for 3D ICs and techniques for defect tolerance using redundancy and repair. Topics covered include various types of TSV defects, stress-induced mobility and threshold-voltage variation in devices, stress-induced electromigration in inter-connects, pre-bond and test-bond testing (including TSV probing), and optimization techniques for defect tolerance.
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Most contemporary real-time distributed systems minimize computation energy consumption to reduce total system energy. However, wireless sensor networks expend a significant portion of total energy consumption on communication ene...
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Most contemporary real-time distributed systems minimize computation energy consumption to reduce total system energy. However, wireless sensor networks expend a significant portion of total energy consumption on communication energy costs. Wireless transmission energy depends directly on the desired transmission distance, so the energy required for communication between neighboring nodes is less than that for distant ones. Mobile nodes can therefore reduce transmission energy costs by approaching one another before communicating. The penalty for energy reduction through locomotion is an increase in time consumed, thus care must be taken to meet system deadlines. We combine locomotion as a communication energy reduction strategy with well-known computation energy reduction schemes and demonstrate the resultant energy savings for representative systems.
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摘要 :
Most contemporary real-time distributed systems minimize computation energy consumption to reduce total system energy. However, wireless sensor networks expend a significant portion of total energy consumption on communication ene...
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Most contemporary real-time distributed systems minimize computation energy consumption to reduce total system energy. However, wireless sensor networks expend a significant portion of total energy consumption on communication energy costs. Wireless transmission energy depends directly on the desired transmission distance, so the energy required for communication between neighboring nodes is less than that for distant ones. Mobile nodes can therefore reduce transmission energy costs by approaching one another before communicating. The penalty for energy reduction through locomotion is an increase in time consumed, thus care must be taken to meet system deadlines. We combine locomotion as a communication energy reduction strategy with well-known computation energy reduction schemes and demonstrate the resultant energy savings for representative systems.
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We present and investigate a novel application domain for deep reinforcement learning (RL): droplet routing on digital microfluidic biochips (DMFBs). A DMFB, composed of a two-dimensional electrode array, manipulates discrete flui...
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We present and investigate a novel application domain for deep reinforcement learning (RL): droplet routing on digital microfluidic biochips (DMFBs). A DMFB, composed of a two-dimensional electrode array, manipulates discrete fluid droplets to automatically execute biochemical protocols such as point-of-care clinical diagnosis. However, a major concern associated with the use of DMFBs is that electrodes in a biochip can degrade over time. Droplet-transportation operations associated with the degraded electrodes can fail, thereby compromising the integrity of the bioassay outcome. We show that casting droplet transportation as an RL problem enables the training of deep network policies to capture the underlying health conditions of electrodes and provide reliable fluidic operations. We propose a new RL-based droplet-routing flow that can be used for various sizes of DMFBs, and demonstrate reliable execution of an epigenetic bioassay with the RL droplet router on a fabricated DMFB. To facilitate further research, we also present a simulation environment based on the OpenAI Gym Interface for RL-guided droplet-routing problems on DMFBs.
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