633 research outputs found

    Synthesis of biochemical applications on digital microfluidic biochips with operation variability

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    Abstract—Microfluidic-based biochips are replacing the con-ventional biochemical analyzers, and are able to integrate on-chip all the necessary functions for biochemical analysis using microfluidics. The digital microfluidic biochips are based on the manipulation of liquids not as a continuous flow, but as discrete droplets. Researchers have presented approaches for the synthesis of digital microfluidic biochips, which, starting from a biochemical application and a given biochip architecture, determine the allocation, resource binding, scheduling and place-ment of the operations in the application. Existing approaches consider that on-chip operations, such as splitting a droplet of liquid, are perfect. However, these operations have variability margins, which can impact the correctness of the biochemical application. We consider that a split operation, which goes beyond specified variability bounds, is faulty. The fault is detected using on-chip volume sensors. We have proposed an abstract model for a biochemical application, consisting of a sequencing graph, which can capture all the fault scenarios in the application. Starting from this model, we have proposed a synthesis approach that, for a given chip area and number of sensors, can derive a fault-tolerant implementation. Two fault-tolerant scheduling techniques have been proposed and compared. We show that, by taking into account fault-occurrence information, we can derive better quality implementations, which leads to shorter application completion times, even in the case of faults. The proposed synthesis approach under operation variability has been evaluated using several benchmarks. I

    Compilation and Synthesis for Fault-Tolerant Digital Microfluidic Biochips

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    A Framework for Automated Correctness Checking of Biochemical Protocol Realizations on Digital Microfluidic Biochips

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    Recent advances in digital microfluidic (DMF) technologies offer a promising platform for a wide variety of biochemical applications, such as DNA analysis, automated drug discovery, and toxicity monitoring. For on-chip implementation of complex bioassays, automated synthesis tools have been developed to meet the design challenges. Currently, the synthesis tools pass through a number of complex design steps to realize a given biochemical protocol on a target DMF architecture. Thus, design errors can arise during the synthesis steps. Before deploying a DMF biochip on a safety critical system, it is necessary to ensure that the desired biochemical protocol has been correctly implemented, i.e., the synthesized output (actuation sequences for the biochip) is free from any design or realization errors. We propose a symbolic constraint-based analysis framework for checking the correctness of a synthesized biochemical protocol with respect to the original design specification. The verification scheme based on this framework can detect several post-synthesis fluidic violations and realization errors in 2D-array based or pin-constrained biochips as well as in cyberphysical systems. It further generates diagnostic feedback for error localization. We present experimental results on the polymerase chain reaction (PCR) and in-vitro multiplexed bioassays to demonstrate the proposed verification approach

    Peptide functionalization of silicon for detection and classification of prostatic cells

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    The development of simple, rapid, and low costmethods for early detection, identification, andmeasurement ofmultiple biomarkers remains a challenge to improve diagnosis, treatment monitoring, and prognosis of cancer. Biosensing technology, combining the properties of biological systems with functional advanced materials, guarantees rapid, reproducible, and highly sensitive cell detection. In this study, we developed silicon-based biochips for prostate cancer PC3 cells detection by using cytokeratin 8/18 and Urotensin Receptor (UTR) as markers in order to obtain a biochip-based diagnostic system. Spectroscopic ellipsometry and fluorescence microscopy were used to characterize surface homogeneity and chemical properties. Cell detection was investigated by optical microscopy.Moreover, synthetic fluorescently labeled peptides were prepared and used for developing faster and lowercost identification assay compared with classic ELISA immunoassay. Results showed an effective immobilization of PC3 cells on silicon surface and the specific recognition of these cells by fluorescent Urotensin II (4-11). In conclusion, this strategy could be really useful as diagnostic system for prostate cancer

    Test analysis & fault simulation of microfluidic systems

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    This work presents a design, simulation and test methodology for microfluidic systems, with particular focus on simulation for test. A Microfluidic Fault Simulator (MFS) has been created based around COMSOL which allows a fault-free system model to undergo fault injection and provide test measurements. A post MFS test analysis procedure is also described.A range of fault-free system simulations have been cross-validated to experimental work to gauge the accuracy of the fundamental simulation approach prior to further investigation and development of the simulation and test procedure.A generic mechanism, termed a fault block, has been developed to provide fault injection and a method of describing a low abstraction behavioural fault model within the system. This technique has allowed the creation of a fault library containing a range of different microfluidic fault conditions. Each of the fault models has been cross-validated to experimental conditions or published results to determine their accuracy.Two test methods, namely, impedance spectroscopy and Levich electro-chemical sensors have been investigated as general methods of microfluidic test, each of which has been shown to be sensitive to a multitude of fault. Each method has successfully been implemented within the simulation environment and each cross-validated by first-hand experimentation or published work.A test analysis procedure based around the Neyman-Pearson criterion has been developed to allow a probabilistic metric for each test applied for a given fault condition, providing a quantitive assessment of each test. These metrics are used to analyse the sensitivity of each test method, useful when determining which tests to employ in the final system. Furthermore, these probabilistic metrics may be combined to provide a fault coverage metric for the complete system.The complete MFS method has been applied to two system cases studies; a hydrodynamic “Y” channel and a flow cytometry system for prognosing head and neck cancer.Decision trees are trained based on the test measurement data and fault conditions as a means of classifying the systems fault condition state. The classification rules created by the decision trees may be displayed graphically or as a set of rules which can be loaded into test instrumentation. During the course of this research a high voltage power supply instrument has been developed to aid electro-osmotic experimentation and an impedance spectrometer to provide embedded test

    Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

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    Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities
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