Optical sensing of biomolecules using microring resonators

A biosensor application of vertically coupled glass microring resonators with Q/spl sim/12 000 is introduced. Using balanced photodetection, very high signal to noise ratios, and thus high sensitivity to refractive index changes (limit of detection of 1.8/spl times/10/sup -5/ refractive index units), are achieved. Ellipsometry and X-ray photoelectron spectroscopy results indicate successful modification of biosensor surfaces. Experimental data obtained separately for a bulk change of refractive index of the medium and for avidin-biotin binding on the ring surface are reported. Excellent repeatability and close-to-complete surface regeneration after binding are experimentally demonstrated.     

SNR estimation in time-varying fading channels

Signal-to-noise ratio (SNR) estimation is considered for phase-shift keying communication systems in time-varying fading channels. Both data-aided (DA) estimation and nondata-aided (NDA) estimation are addressed. The time-varying fading channel is modeled as a polynomial-in-time. Inherent estimation accuracy limitations are examined via the Cramer-Rao lower bound, where it is shown that the effect of the channel's time variation on SNR estimation is negligible. A novel maximum-likelihood (ML) SNR estimator is derived for the time-varying channel model. In DA scenarios, where the estimator has a simple closed-form solution, the exact performance is evaluated both with correct and incorrect (i.e., mismatched) polynomial order. In NDA estimation, the unknown data symbols are modeled as random, and the marginal likelihood is used. The expectation-maximization algorithm is proposed to iteratively maximize this likelihood function. Simulation results show that the resulting estimator offers statistical efficiency over a wider range of scenarios than previously published methods.     

ATSC DTV Receiver Implementation

Receivers of broadcast digital television (DTV) service operate in an often difficult environment of electrical interference, multiple other TV signals in close frequency proximity, multipath, wide dynamic range input signals, and uncertain antenna choice and installation. Receivers must demodulate and decode the signal and optimize its processing for different display technologies-a process that can include format conversion between progressive and interlaced scanning and different screen pixel counts. Data that supports the new services enabled by digital transmission must be decoded and processed. Receiver designers must implement the required functions cost-effectively even as they strive to provide performance and feature differentiation from their competitors' products. This paper describes all of the DTV receiver functions and references the associated standards. Emphasis is given to the difficult areas of signal reception and demodulation and to sections of the receiver that enable attractive and recognizable consumer features.     

AN ASYMPTOTIC SECOND‐ORDER SMOOTH SLIDING MODE CONTROL

Presented is a method of smooth sliding mode control design to provide for an asymptotic second‐order sliding mode on the selected sliding surface. The control law is a nonlinear dynamic feedback that in absence of unknown disturbances provides for an asymptotic second‐order sliding mode. Application of the second‐order disturbance observer in a combination with the proposed continuous control law practically gives the second‐order sliding accuracy in presence of unknown disturbances and discrete‐time control update. The piecewise constant control feedback is “smooth” in the sense that its derivative numerically taken at sampling rate does not contain high frequency components. A numerical example is presented.     

Maximizing Reward in a Non-Stationary Mobile Robot Environment

The ability of a robot to improve its performance on a task can be critical, especially in poorly known and non-stationary environments where the best action or strategy is dependent upon the current state of the environment. In such systems, a good estimate of the current state of the environment is key to establishing high performance, however quantified. In this paper, we present an approach to state estimation in poorly known and non-stationary mobile robot environments, focusing on its application to a mine collection scenario, where performance is quantified using reward maximization. The approach is based on the use of augmented Markov models (AMMs), a sub-class of semi-Markov processes. We have developed an algorithm for incrementally constructing arbitrary-order AMMs on-line. It is used to capture the interaction dynamics between a robot and its environment in terms of behavior sequences executed during the performance of a task. For the purposes of reward maximization in a non-stationary environment, multiple AMMs monitor events at different timescales and provide statistics used to select the AMM likely to have a good estimate of the environmental state. AMMs with redundant or outdated information are discarded, while attempting to maintain sufficient data to reduce conformation to noise. This approach has been successfully implemented on a mobile robot performing a mine collection task. In the context of this task, we first present experimental results validating our reward maximization performance criterion. We then incorporate our algorithm for state estimation using multiple AMMs, allowing the robot to select appropriate actions based on the estimated state of the environment. The approach is tested first with a physical robot, in a non-stationary environment with an abrupt change, then with a simulation, in a gradually shifting environment.     

Analysis of flip-chip packaging challenges on copper/low-k interconnects

An interfacial-fracture-mechanics-based simulation methodology has been developed to study the flip-chip packaging effect on the copper/low-k structures. Multilevel submodeling techniques have been used to bridge the scale difference between the flip-chip packages and the metal/dielectric stacks. To achieve a smaller feature size and higher speed in future chips, SiO/sub 2/ can be replaced with low-k dielectric material in all via and trench layers or the number of metal layers can be increased. The effect of both packaging options has been evaluated. With either option, the future flip-chip copper/low-k packages are facing higher possibilities of adhesive or cohesive failure near the low-k interface. This paper provides a quantitative evaluation of the increased risk, thus providing guidelines to the next level of low-k flip-chip packages.     

Identification of Tone Duration, Line Length, and Letter Position: An Experimental Approach to Timing and Working Memory Deficits in Schizophrenia.

Patients with schizophrenia display numerous cognitive deficits, including problems in working memory, time estimation, and absolute identification of stimuli. Research in these fields has traditionally been conducted independently. We examined these cognitive processes using tasks that are structurally similar and that yield rich error data. Relative to healthy control participants (n = 20), patients with schizophrenia (n = 20) were impaired on a duration identification task and a probed-recall memory task but not on a line-length identification task. These findings do not support the notion of a global impairment in absolute identification in schizophrenia. However, the authors suggest that some aspect of temporal information processing is indeed disturbed in schizophrenia. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Molecular Alignment Induced by Ultrashort Laser Pulses and Its Impact on Molecular Motion

Spectroscopy aims at extracting information about matter through its interaction with light. However, when performed on gas and liquid phases as well as solid phases lacking long-range order, the extracted spectroscopic features are in fact averaged over the molecular isotropic angular distributions. The reason is that light–matter processes depend on the angle between the transitional molecular dipole and the polarization of the light interacting with it. This understanding gave birth to the constantly expanding field of “laser-induced molecular alignment”. In this paper, we attempt to guide the readers through our involvement (both experimental and theoretical) in this field in the last few years. We start with the basic phenomenon of molecular alignment induced by a single pulse, continue with selective alignment of close molecular species and unidirectional molecular rotation induced by two time-delayed pulses, and lead up to novel schemes for manipulating the spatial distributions of molecular samples through rotationally controlled scattering off inhomogeneous fields and surfaces.     

Enhancing Photovoltaic Performance Using an All‐Conjugated Random Copolymer to Tailor Bulk and Interfacial Morphology of the P3HT:ICBA Active Layer

Bulk heterojunction (BHJ) solar cells are fabricated using active material blends of poly(3‐hexylthiophene) (P3HT) donor, indene‐C₆₀ bisadduct (ICBA) acceptor, and an all‐conjugated random copolymer (RCP) additive. By optimizing RCP loading, power conversion efficiencies (PCEs) up to 20% higher than those of a binary P3HT:ICBA mixture are achieved. The improved device characteristics are rationalized in terms of the differences between the photoactive thin film morphologies. Energy‐filtered transmission electron micro­scopy reveals that incorporation of the RCP improves the degree of structural order of the BHJ fibrillar network and increases the extent of microphase separation between P3HT and ICBA. Additionally, a combination of atomic force microscopy and X‐ray photoelectron spectroscopy analysis indicates segregation of the RCP at the free interface, leading to a shift in the surface potentials measured by Kelvin probe force microscopy. These changes, both in the bulk morphology and in the interfacial composition/energetics, are correlated to improved carrier collection efficiency due to a reduction of non‐geminate recombination, which is measured by charge extraction of photo­generated carriers by linearly increasing voltage.     

The quest for a Quantum Neural Network

With the overwhelming success in the field of quantum information in the last decades, the ‘quest’ for a Quantum Neural Network (QNN) model began in order to combine quantum computing with the striking properties of neural computing. This article presents a systematic approach to QNN research, which so far consists of a conglomeration of ideas and proposals. Concentrating on Hopfield-type networks and the task of associative memory, it outlines the challenge of combining the nonlinear, dissipative dynamics of neural computing and the linear, unitary dynamics of quantum computing. It establishes requirements for a meaningful QNN and reviews existing literature against these requirements. It is found that none of the proposals for a potential QNN model fully exploits both the advantages of quantum physics and computing in neural networks. An outlook on possible ways forward is given, emphasizing the idea of Open Quantum Neural Networks based on dissipative quantum computing.