Pulsed Laser Activation of Carbene Bioadhesive Boosts Bonding Strength

Light‐activated tissue adhesives are limited to low light doses (50 J) and intensities (<1 W cm^?2) due to photo‐to‐thermal heat generation. Low intensities have the disadvantage of limited penetration depths with retarded crosslinking kinetics, which impairs carbene‐based crosslinking strategies that compete with nitrogen evolution and gas nucleation. These limitations are circumvented by a trade‐off between high‐intensity activation while reducing the exposure surface area. Continuous or pulsed activation by line scanning the carbene precursor adhesive allows curing a higher surface area/volume ratio while preventing localized heat generation. By optimizing irradiation with a pulsed laser scan, the adhesion strength is improved by 17‐fold over ultraviolet A (UVA) light emitting diodes (LEDs) and is on par with bioadhesive gold standard of topical cyanoacrylates. Overall, this improved method of photo‐activation applies to other industrial and clinical photocuring adhesives where limits on UVA dose constrain exposure intensities.     

Comparison of parameter estimation methods in stochastic chemical kinetic models: Examples in systems biology

Stochastic chemical kinetics has become a staple for mechanistically modeling various phenomena in systems biology. These models, even more so than their deterministic counterparts, pose a challenging problem in the estimation of kinetic parameters from experimental data. As a result of the inherent randomness involved in stochastic chemical kinetic models, the estimation methods tend to be statistical in nature. Three classes of estimation methods are implemented and compared in this paper. The first is the exact method, which uses the continuous‐time Markov chain representation of stochastic chemical kinetics and is tractable only for a very restricted class of problems. The next class of methods is based on Markov chain Monte Carlo (MCMC) techniques. The third method, termed conditional density importance sampling (CDIS), is a new method introduced in this paper. The use of these methods is demonstrated on two examples taken from systems biology, one of which is a new model of single‐cell viral infection. The applicability, strengths and weaknesses of the three classes of estimation methods are discussed. Using simulated data for the two examples, some guidelines are provided on experimental design to obtain more information from a limited number of measurements. © 2014 American Institute of Chemical Engineers AIChE J, 60: 1253–1268, 2014     

Improving the contrast ratio of OLED displays: An analysis of various techniques

Organic light emitting diode (OLED) based displays have matured into commercial products. However, while we consider OLED for a low-cost high-resolution and high-contrast displays with a long life span, still there are performance gaps. This review addresses various techniques used for increasing the ambient contrast ratio of OLED displays. There are techniques which are integral to the OLED device, such as black cathodes and absorbing transport layers. In contrast, anti-reflection (AR) coatings and circular polarizer are applied externally to the device. This review provides a brief overview of each technique along with a discussion on its merits and demerits. The choice of a particular contrast enhancement technique for a display depends on the ambient where the same is intended to be used. Accordingly, for indoor and outdoor applications, the best possible methods are suggested.     

Hybrid Lead Halide Perovskites for Ultrasensitive Photoactive Switching in Terahertz Metamaterial Devices

The recent meteoric rise in the field of photovoltaics with the discovery of highly efficient solar‐cell devices is inspired by solution‐processed organic–inorganic lead halide perovskites that exhibit unprecedented light‐to‐electricity conversion efficiencies. The stunning performance of perovskites is attributed to their strong photoresponsive properties that are thoroughly utilized in designing excellent perovskite solar cells, light‐emitting diodes, infrared lasers, and ultrafast photodetectors. However, optoelectronic application of halide perovskites in realizing highly efficient subwavelength photonic devices has remained a challenge. Here, the remarkable photoconductivity of organic–inorganic lead halide perovskites is exploited to demonstrate a hybrid perovskite–metamaterial device that shows extremely low power photoswitching of the metamaterial resonances in the terahertz part of the electromagnetic spectrum. Furthermore, a signature of a coupled phonon–metamaterial resonance is observed at higher pump powers, where the Fano resonance amplitude is extremely weak. In addition, a low threshold, dynamic control of the highly confined electric field intensity is also observed in the system, which could tremendously benefit the new generation of subwavelength photonic devices as active sensors, low threshold optically controlled lasers, and active nonlinear devices with enhanced functionalities in the infrared, optical, and the terahertz parts of the electromagnetic spectrum.     

The Extracellular Zn2+ Concentration Surrounding Excited Neurons Is High Enough to Bind Amyloid‐β Revealed by a Nanowire Transistor

The Zn²⁺ stored in the secretory vesicles of glutamatergic neurons is coreleased with glutamate upon stimulation, resulting in the elevation of extracellular Zn²⁺ concentration (). This elevation of regulates the neurotransmission and facilitates the fibrilization of amyloid‐β (Aβ). However, the exact surrounding neurons under (patho)physiological conditions is not clear and the connection between and the Aβ fibrilization remains obscure. Here, a silicon nanowire field‐effect transistor (SiNW‐FET) with the Zn²⁺‐sensitive fluorophore, FluoZin‐3 (FZ‐3), to quantify the in real time is modified. This FZ‐3/SiNW‐FET device has a dissociation constant of ≈12 × 10^?9m against Zn²⁺. By placing a coverslip seeded with cultured embryonic cortical neurons atop an FZ‐3/SiNW‐FET, the elevated to ≈110 × 10^?9m upon stimulation with α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid (AMPA). Blockers against the AMPA receptor or exocytosis greatly suppress this elevation, indicating that the Zn²⁺ stored in the synaptic vesicles is the major source responsible for this elevation of . In addition, a SiNW‐FET modified with Aβ could bind Zn²⁺ with a dissociation constant of ≈633 × 10^?9m and respond to the Zn²⁺ released from AMPA‐stimulated neurons. Therefore, the can reach a level high enough to bind Aβ and the Zn²⁺ homeostasis can be a therapeutic strategy to prevent neurodegeneration.     

Finite dimensional approximation and Newton-based algorithm for stochastic approximation in Hilbert space

This paper presents a finite dimensional approach to stochastic approximation in infinite dimensional Hilbert space. The problem was motivated by applications in the field of stochastic programming wherein we minimize a convex function defined on a Hilbert space. We define a finite dimensional approximation to the Hilbert space minimizer. A justification is provided for this finite dimensional approximation. Estimates of the dimensionality needed are also provided. The algorithm presented is a two time-scale Newton-based stochastic approximation scheme that lives in this finite dimensional space. Since the finite dimensional problem can be prohibitively large dimensional, we operate our Newton scheme in a projected, randomly chosen smaller dimensional subspace.     

Fast adaptive algorithms for abrupt change detection

We propose two fast algorithms for abrupt change detection in streaming data that can operate on arbitrary unknown data distributions before and after the change. The first algorithm, MB-GT\textsf{MB-GT} , computes efficiently the average Euclidean distance between all pairs of data points before and after the hypothesized change. The second algorithm, MB-CUSUM\textsf{MB-CUSUM} , computes the log-likelihood ratio statistic for the data distributions before and after the change, similarly to the classical CUSUM algorithm, but unlike that algorithm, MB-CUSUM\textsf{MB-CUSUM} does not need to know the exact distributions, and uses kernel density estimates instead. Although a straightforward computation of the two change statistics would have computational complexity of O(N ⁴) with respect to the size N of the streaming data buffer, the proposed algorithms are able to use the computational structure of these statistics to achieve a computational complexity of only O(N ²) and memory requirement of O(N). Furthermore, the algorithms perform surprisingly well on dependent observations generated by underlying dynamical systems, unlike traditional change detection algorithms.