An improved common-mode feedback loop for the differential-difference amplifier

Unconditional stability of the high-gain amplifiers is a mandatory requirement for a reliable steady-state condition of time-discrete systems, especially for all blocks designed to sample-and-hold (S/H) circuits. Compared to differential path, the common-mode feedback loop is often affected by poles and zeros shifting that degrades the large signal response of the amplifiers. This drawback is made worse in some well-known topologies as the difference-differential amplifier (DDA) that shows non-constant transconductance and poor linearity. This work proposes a body-driven positive-feedback frequency compensation technique (BD-PFFC) to improve the linearity for precision DDA-based S/H applications. Theoretical calculations and circuit simulations carried out in a 0.13 μm process are also given to demonstrate its validity.     

Adaptive transform skipping for improved coding of motion compensated residuals

New generations of video compression algorithms, such as those included in the under development High Efficiency Video Coding (HEVC) standard, provide substantially higher compression compared to their ancestors. The gain is achieved by improved prediction of pixels, both within a frame and between frames. Novel coding tools that contribute to the gain provide highly uncorrelated prediction residuals for which classical frequency decomposition methods, such as the discrete cosine transform, may not be able to supply a compact representation with few significant coefficients. To further increase the compression gains, this paper proposes transform skip modes which allow skipping one or both 1-D constituent transforms (i.e., vertical and horizontal), which is more suitable for sparse residuals. The proposed transform skip mode is tested in the HEVC codec and is able to provide bitrate reductions of up to 10% at the same objective quality when compared with the application of 2-D block transforms only. Moreover, the proposed transform skip mode outperforms the full transform skip currently investigated for possible adoption in the HEVC standard.     

A design methodology for high-order class-D audio amplifiers

This paper presents a design methodology for high-order class-D amplifiers, based on their similarity with sigma–delta ( $\Upsigma\Updelta$ ) modulators, for which established theory and toolboxes are available. The proposed methodology, which covers the entire design flow, from specifications to component sizing, is validated with three design examples, namely a second-order, a third-order, and a fourth-order class-D amplifier. Moreover, the third-order class-D amplifier has been integrated on silicon and characterized, further confirming the validity of the whole design flow. The achieved results demonstrate that high-order class-D amplifiers can achieve total-harmonic-distortion (THD) performance compatible with the specifications of high-end audio applications (THD  ≈ 90 dB), which would be unfeasible with conventional first-order class-D amplifiers.     

A new peak detector based on usage of second-generation current conveyors

A new precision peak detector (full-wave rectifier) of input sinusoidal signals, which employs four two second-generation current conveyors and five metal-oxide-semiconductor transistors, is presented in this paper. The circuit gives a dc output voltage that is the peak input voltage over a wide frequency range, with a very low ripple voltage and low harmonic distortion. The proposed circuits use an all-pass filter as a 90° phase shifter of the processed input signal. The results of the calculations are verified using SPICE simulations.     

Implementation of depth‐based routing and its enhancement in AquaSim–Next Generation for underwater wireless sensor networks

In the last decade, underwater wireless sensor networks have been widely studied because of their peculiar aspects that distinguish them from common terrestrial wireless networks. Their applications range from environmental monitoring to military defense. The definition of efficient routing protocols in underwater sensor networks is a challenging topic of research because of the intrinsic characteristics of these networks, such as the need of handling the node mobility and the difficulty in balancing the energy consumed by the nodes. Depth‐based routing protocol is an opportunistic routing protocol for underwater sensor networks, which provides good performance both under high and low node mobility scenarios. The main contribution of our work is presenting a novel simulator for studying depth‐based routing protocol and its variants as well as novel routing protocols. Our simulator is based on AquaSim–Next Generation, which is a specialized tool for studying underwater networks. With our work, we improve the state of the art of underwater routing protocol simulators by implementing, among other features, a detailed cross‐layer communication and an accurate model of the operational modes of acoustic modem and their energy consumption. The simulator is open source and freely downloadable. Moreover, we propose a novel and completely distributed routing protocol, named residual energy–depth‐based routing. It takes into account the residual energy at the nodes' batteries to select the forwarder nodes and improve the network lifetime by providing a more uniform energy consumption among them. We compare its performance with that of depth‐based routing protocol and a receiver‐based routing protocol implementing a probabilistic opportunistic forwarding scheme.     

Tunable Nanoparticle and Cell Assembly Using Combined Self‐Powered Microfluidics and Microcontact Printing

The combination of cell microenvironment control and real‐time monitoring of cell signaling events can provide key biological information. Through precise multipatterning of gold nanoparticles (GNPs) around cells, sensing and actuating elements can be introduced in the cells' microenviroment, providing a powerful substrate for cell studies. In this work, a combination of techniques are implemented to engineer complex substrates for cell studies. Alternating GNPs and bioactive areas are created with micrometer separation by means of a combination of vacumm soft‐lithography of GNPs and protein microcontract printing. Instead of conventional microfluidics that need syringe pumps to flow liquid in the microchannels, degas driven flow is used to fill dead‐end channels with GNP solutions, rendering the fabrication process straightforward and accessible. This new combined technique is called Printing and Vacuum lithography (PnV lithography). By using different GNPs with various organic coating ligands, different macroscale patterns are obtained, such as wires, supercrystals, and uniformly spread nanoparticle layers that can find different applications depending on the need of the user. The application of the system is tested to pattern a range of mammalian cell lines and obtain readouts on cell viability, cell morphology, and the presence of cell adhesive proteins.     

Selective Functionalization of Microstructured Surfaces by Laser‐Assisted Particle Transfer

Microcavity arrays represent millions of different reaction compartments to screen, for example, molecular interactions, exogenous factors for cells or enzymatic activity. A novel method is presented to selectively synthesize different compounds in arrays of microcavities with up to 1 000 000 cavities per cm². In this approach, polymer microparticles with embedded pre‐activated monomers are selectively transferred into microcavities with laser radiation. After particle patterning, heating of the particle matrix simultaneously leads to diffusion and coupling of the monomers inside each microcavity separately. This method exhibits flexibility, not only in the choice of compounds, but also in the choice of particle matrix material, which determines the chemical reaction environment. The laser‐assisted selective functionalization of microcavities can be easily combined with the intensively growing number of laser applications for patterning of molecules and cells, which is useful for the development of novel biological assays.     

Ultrathin PECVD epitaxial Si solar cells on glass via low‐temperature transfer process

Fabrication of high‐quality ultrathin monocrystalline silicon layers and their transfer to low‐cost substrates are key steps for flexible electronics and photovoltaics. In this work, we demonstrate a low‐temperature and low‐cost process for ultrathin silicon solar cells. By using standard plasma‐enhanced chemical vapor deposition (PECVD), we grow high‐quality epitaxial silicon layers (epi‐PECVD) from SiH₄/H₂ gas mixtures at 175 °C. Using secondary ion mass spectrometry and transmission electron microscopy, we show that the porosity of the epi‐PECVD/crystalline silicon interface can be tuned by controlling the hydrogen accumulation there. Moreover, we demonstrate that 13–14% porosity is a threshold above which the interface becomes fragile and can easily be cleaved. Taking advantage of the H‐rich interface fragility, we demonstrate the transfer of large areas (∽10 cm²) ultrathin epi‐PECVD layers (0.5–5.5 µm) onto glass substrates by anodic bonding and moderate annealing (275–350 °C). The structural properties of transferred layers are assessed, and the first PECVD epitaxial silicon solar cells transferred on glass are characterized. Copyright © 2016 John Wiley & Sons, Ltd.     

Detection of Structural Features in Biological Signals

In this article structures in biological signals are treated. The simpler—directly visible in the signals, which still demand serious methods and algorithms in the feature detection, similarity investigation and classification. The major actions in this domain are of geometric, thus simpler sort, though there are still hard problems related to simple situations. The other large class of less simple signals unsuitable for direct geometric or statistic approach, are signals with interesting frequency components and behavior, those suitable for spectroscopic analysis. Semantics of spectroscopy, spectroscopic structures and research demanded operations and transformations on spectra and time spectra are presented. The both classes of structures and related analysis methods and tools share a large common set of algorithms, all of which aiming to the full automatization. Some of the signal features present in the brain signal patterns are demonstrated, with the contexts relevant in BCI, brain computer interfaces. Mathematical representations, invariants and complete characterization of structures in broad variety of biological signals are in the central focus.