Reproducible Enhancement of Fluorescence by Bimetal Mediated Surface Plasmon Coupled Emission for Highly Sensitive Quantitative Diagnosis of Double‐Stranded DNA

Plasmonic enhancement of fluorescence from SYBR Green I conjugated with a double‐stranded DNA (dsDNA) amplicon is demonstrated on polymerase chain reaction (PCR) products. Theoretical computation leads to use of the bimetallic (Au 2 nm–Ag 50 nm) surface plasmons due to larger local fields (higher quality factors) than monometallic (Ag or Au) ones at both dye excitation and emission wavelengths simultaneously, optimizing fluorescence enhancement with surface plasmon coupled emission (SPCE). Two kinds of reverse Kretschmann configurations are used, which favor, in signal‐to‐noise ratio, a fluorescence assay that uses optically dense buffer such as blood plasma. The fluorescence enhancement (12.9 fold at maximum) with remarkably high reproducibility (coefficient of variation (CV) < 1%) is experimentally demonstrated. This facilitates credible quantitation of enhanced fluorescence, however unlikely to obtain by localized surface plasmons. The plasmon‐induced optical gain of 46 dB due to SPCE‐active dye molecules is also estimated. The fluorescence enhancement technologies with PCR enables LOD of the dsDNA template concentration of ≈400 fg µL^?1 (CV < 1%), the lowest ever reported in DNA fluorescence assay to date. SPCE also reduces photobleaching significantly. These technologies can be extended for a highly reproducible and sufficiently sensitive fluorescence assay with small volumes of analytes in multiplexed diagnostics.     

Algorithm for the extraction of page-formatted binary digital data

We present an algorithm for fast and reliable extraction of page-formatted binary digital data. The advantages of the algorithm include a low raw bit-error rate, fast extraction speed, the use of a simple and density-efficient coding scheme, and large tolerance to a change of the signal-to-noise ratio. We used this algorithm to analyze shot-noise-limited binary data that had large interpage and intrapage intensity variations and obtained an improvement in the bit-error rate of 3-4 orders of magnitude compared with that in a single-threshold-detection scheme. Implications of our results for the development of high-speed, high-density holographic memories are discussed.     

An efficient microfluidic sorter: implementation of double meandering micro striplines for magnetic particles switching

The ability to trap, manipulate, and separate magnetic beads has become one of the key requirements in realizing an integrated magnetic lab-on-chip biosensing system. In this article, we present the design and fabrication of an integrated magneto-fluidic device for sorting magnetic particles with a sorting efficiency of up to 95%. The actuation and manipulation of magnetic beads are realized using microfabricated square meandering current-carrying micro striplines. The current is alternated between two neighboring micro striplines to switch the magnetic beads to either one of the two outlets. We performed a series of parametric study to investigate the effect of applied current, flow rate, and switching frequency on the sorting efficiency. Experimental results reveal that the sorting efficiency is proportional to the square of current applied to the stripline, and decreases with increasing buffer flow rate and switching frequency. Such phenomena agree well with our theoretical analysis and simulation result. The fastest switching rate, which is limited by the microchannel geometry and bead velocity, is 2 Hz.     

Integratable non-clogging microconcentrator based on counter-flow principle for continuous enrichment of CaSki cells sample

This study addresses the need to reduce the risk of clogging when preparing samples for cell concentration, i.e., the CaSki Cell-lines (epidermoid cervical carcinoma cells). Aiming to develop a non-clogging microconcentrator, we proposed a new counter-flow concentration unit characterized by the directions of penetrating flows being at an obtuse angle to the main flow, due to employment of streamlined turbine blade-like micropillars. Based on the optimization results of the counter-flow unit profile, a fractal arrangement for the counter-flow concentration unit was developed. A counter-flow microconcentrator chip was then designed and fabricated, with both the processing layer and collecting layer arranged in terms of the honeycomb structure. Visualized experiments using CaSki cell samples on the microconcentrator chip demonstrated that no cell-clogging phenomena occurred during the test and that no cells were found in the final filtrate. The test results show an excellent concentration performance for the microconcentrator chip, while a concentrating ratio of >4 with the flow rate being below 1.0 ml/min. As only geometrical structure is employed in the passive device, the counter-flow microconcentrator can be easily integrated into advanced microfluidic systems. Owing to the merit of non-clogging and continuous processing ability, the counter-flow microconcentrator is not only suitable for the sample preparation within biomedical field, but also applicable in water-particle separation.     

Solving the Matrix Differential Riccati Equation: A Lyapunov Equation Approach

In this technical note, we investigate a solution of the matrix differential Riccati equation that plays an important role in the linear quadratic optimal control problem. Unlike many methods in the literature, the approach that we propose employs the negative definite anti-stabilizing solution of the matrix algebraic Riccati equation and the solution of the matrix differential Lyapunov equation. An illustrative numerical example is provided to show the efficiency of our approach.      

A framework for linguistic logic programming

Lawry's label semantics for modeling and computing with linguistic information in natural language provides a clear interpretation of linguistic expressions and thus a transparent model for real‐world applications. Meanwhile, annotated logic programs (ALPs) and its fuzzy extension AFLPs have been developed as an extension of classical logic programs offering a powerful computational framework for handling uncertain and imprecise data within logic programs. This paper proposes annotated linguistic logic programs (ALLPs) that embed Lawry's label semantics into the ALP/AFLP syntax, providing a linguistic logic programming formalism for development of automated reasoning systems involving soft data as vague and imprecise concepts occurring frequently in natural language. The syntax of ALLPs is introduced, and their declarative semantics is studied. The ALLP SLD‐style proof procedure is then defined and proved to be sound and complete with respect to the declarative semantics of ALLPs. © 2010 Wiley Periodicals, Inc.     

Design and implementation of look-ahead linear jerk filter for a computerized numerical controlled machine

In this study, an open programmable logic controller (PLC) from Fuji electric prescribed in the Structured Text program was applied to develop a look-ahead linear jerk filter (LALJF) for a computerized numerically controlled (CNC) machine. To ensure the smooth and accurate motion of a tool with a linear change in jerk during real-time machining, the proposed filter was formed by combining a look-ahead algorithm with three modified moving average filters (3MMAF). The look-ahead algorithm performed a single look-ahead step-change in the speed of the speed curve. Based on a step-changing speed profile, given maximal acceleration/deceleration and maximum jerk, the speed curve was modified before it was passed through a linear jerk filter to reduce machining time. The speed commands filtered by the proposed filter stabilize machine table at the beginning and end of its motion, and at any point at which its speed exhibits a step-change. The theoretical and computational aspects of the LALJF are presented together with experimental results of its implementation on an X–Y table. The multiple-step-changing speed curve of a CNC machine and the speed curve of a high-speed measurement system were constructed in order to verify the feasibility and precision of the proposed method.     

A study of Q-learning considering negative rewards

In the reinforcement learning system, the agent obtains a positive reward, such as 1, when it achieves its goal. Positive rewards are propagated around the goal area, and the agent gradually succeeds in reaching its goal. If you want to avoid certain situations, such as dangerous places or poison, you might want to give a negative reward to the agent. However, in conventional Q-learning, negative rewards are not propagated in more than one state. In this article, we propose a new way to propagate negative rewards. This is a very simple and efficient technique for Q-learning. Finally, we show the results of computer simulations and the effectiveness of the proposed method.     

Design of a sliding mode controller for an automatic guided vehicle and its implementation

In this paper, a control scheme that combines a kinematic controller and a sliding mode dynamic controller with external disturbances is proposed for an automatic guided vehicle to track a desired trajectory with a specified constant velocity. It provides a method of taking into account specific mobile robot dynamics to convert desired velocity control inputs into torques for the actual mobile robot. First, velocity control inputs are designed for the kinematic controller to make the tracking error vector asymptotically stable. Then, a sliding mode dynamic controller is designed such that the mobile robot’s velocities converge to the velocity control inputs. The control law is obtained based on the backstepping technique. System stability is proved using the Lyapunov stability theory. In addition, a scheme for measuring the errors using a USB camera is described. The simulation and experimental results are presented to illustrate the effectiveness of the proposed controller.