Protein engineering of alcohol dehydrogenases; effects of amino acid changes at positions 93 and 48 of yeast ADH1

By protein engineering we have investigated changes to two aminoacid residues (Trp93 and Ser48) in the substrate pocket of yeastalcohol dehydrogenase 1. Upon changing Thr48 to serine we producedan enzyme which has markedly greater activity towards aliphaticalcohols with chain length up to 8, together with a generalincrease in catalytic activity (V/K). Changes at position 93were less pronounced, with the Phe enzyme being more activethan the parent towards the range of alcohols but with the alanineenzyme showing very little difference from the wild-type. Enzymeswith the double changes at 48 and 93 showed increased activitytowards alcohols with 3–8 carbons but the increases werenot additive over the single changes. The enzymes with changesat the two positions would metabolize both stereoisomers of2-octanol whereas the parent ADH would attack only one of them.None of the engineered enzymes would attack cyclohexanol oraromatic alcohols. The results are in general agreement withthe prediction that reducing the size of amino acids in thesubstrate pocket would enhance the ability to oxidize alcoholslarger than ethanol.     

Midwavelength Infrared Avalanche Photodiode Using InAs–GaSb Strain Layer Superlattice

InAs-GaSb strain layer superlattice p⁺-n^--n avalanche photodiodes (APDs) are fabricated using a newly introduced electron-beam aided zinc sulfide deposition. Temperature-dependent measurements were performed on 300 times 300 mum² mesa etched APDs. The effect of passivation was also studied on the diode characteristics and APD performances. Temperature-dependent gain strongly correlates with avalanche mechanism.     

Challenges and opportunities for next-generation intracortically based neural prostheses

Neural prosthetic systems aim to help disabled patients by translating neural signals from the brain into control signals for guiding computer cursors, prosthetic arms, and other assistive devices. Intracortical electrode arrays measure action potentials and local field potentials from individual neurons, or small populations of neurons, in the motor cortices and can provide considerable information for controlling prostheses. Despite several compelling proof-of-concept laboratory animal experiments and an initial human clinical trial, at least three key challenges remain which, if left unaddressed, may hamper the translation of these systems into widespread clinical use. We review these challenges: achieving able-bodied levels of performance across tasks and across environments, achieving robustness across multiple decades, and restoring able-bodied quality proprioception and somatosensation. We also describe some emerging opportunities for meeting these challenges. If these challenges can be largely or fully met, intracortically based neural prostheses may achieve true clinical viability and help increasing numbers of disabled patients.     

Data analytics in wireless systems and IoT issues and challenges

The emergence of data engineering along with the support of Online Social Networks is growing by millions every day due to the introduction of wireless systems and Internet of Things. The rapid growth of usage of smart devices helps to create new generation knowledge sharing platforms. Data Analytics has a major role to play in the growth and success of wireless and IoT applications. The growth of data has become exponential and is difficult to analyze. Many researchers depend on the data available on Wireless Systems and IoT for developing new generation services and applications. With the opportunity of information and communication technologies like heterogeneous networking, cloud computing, web services, crowd sensing and data mining, ubiquitous and asynchronous information sharing is feasible. But this also brings out a lot of provocations with respect to conflicting standards, data portability, data aggregation, data distribution, differential context and communication overhead. The smart information and communication technology has changed many features of human lifestyle: personal and work places.     

On reducing delay in mobile data collection based wireless sensor networks

In a wireless sensor network, battery power is a limited resource on the sensor nodes. Hence, the amount of power consumption by the nodes determines the node and network lifetime. This in turn has an impact on the connectivity and coverage of the network. One way to reduce power consumed is to use a special mobile data collector (MDC) for data gathering, instead of multi-hop data transmission to the sink. The MDC collects the data from the nodes and transfers it to the sink. Various kinds of MDC approaches have been explored for different assumptions and constraints. But in all the models proposed, the data latency is usually high, due to the slow speed of the mobile nodes. In this paper, we propose a new model of mobile data collection that reduces the data latency significantly. Using a combination of a new touring strategy based on clustering and a data collection mechanism based on wireless communication, we show that the delay can be reduced significantly without compromising on the advantages of MDC based approach. Using extensive simulation studies, we analyze the performance of the proposed approach and show that the packet delay reduces by more than half when compared to other existing approaches.     

Contact-Barrier Free,High Mobility,Dual-Gated Junctionless Transistor Using Tellurium Nanowire

The gate-all-around nanowire transistor, due to its extremely tight electrostatic control and vertical integration capability, is a highly promising candidate for sub-5 nm technology nodes. In particular, the junctionless nanowire transistors are highly scalable with reduced variability due to avoidance of steep source/drain junction formation by ion implantation. Here a dual-gated junctionless nanowire p-type field effect transistor is demonstrated using tellurium nanowire as the channel. The dangling-bond-free surface due to the unique helical crystal structure of the nanowire, coupled with an integration of dangling-bond-free, high quality hBN gate dielectric, allows for a phonon-limited field effect hole mobility of 570 cm² V⁻¹ s⁻¹ at 270 K, which is well above state-of-the-art strained Si hole mobility. By lowering the temperature, the mobility increases to 1390 cm² V⁻¹ s⁻¹ and becomes primarily limited by Coulomb scattering. The combination of an electron affinity of ≈ 4 eV and a small bandgap of tellurium provides zero Schottky barrier height for hole injection at the metal-contact interface, which is remarkable for reduction of contact resistance in a highly scaled transistor. Exploiting these properties, coupled with the dual-gated operation, we achieve a high drive current of 216 μA μm⁻¹ while maintaining an on-off ratio in excess of 2 × 10⁴. The findings have intriguing prospects for alternate channel material based next-generation electronics.     

Growth of Epitaxial (110) 0.7Pb(Mg<Subscript>1/3</Subscript>Nb<Subscript>2/3</Subscript>)O<Subscript>3</Subscript>-0.3PbTiO<Subscript>3</Subscript> Thin Films on r-Plane Sapphire Substrates by RF Magnetron Sputtering

The role of substrate temperature and substrate surface geometry in determining the crystal structure and crystallinity of 0.7Pb(Mg_1/3Nb_2/3)O₃-0.3PbTiO₃ (PMN-PT) thin films grown on r-plane sapphire substrates is examined. A 30-nm-thick amorphous PMN-PT seed layer deposited at 250°C and subjected to rapid thermal annealing at 850°C results in the formation of an epitaxial (110) perovskite PMN-PT growth template that can be used for subsequent growth of single-crystal (110) perovskite PMN-PT films at elevated temperature. The data show that single-crystal perovskite is promoted when the films nucleate with the \( \langle \overline{1} 11 \rangle \) PMN-PT direction parallel to the \( \langle 0\bar{2}21 \rangle \) Al₂O₃ direction.     

Vector-extrapolated fast maximum likelihood estimation algorithms for emission tomography

A new class of fast maximum-likelihood estimation (MLE) algorithms for emission computed tomography (ECT) is developed. In these cyclic iterative algorithms, vector extrapolation techniques are integrated with the iterations in gradient-based MLE algorithms, with the objective of accelerating the convergence of the base iterations. This results in a substantial reduction in the effective number of base iterations required for obtaining an emission density estimate of specified quality. The mathematical theory behind the minimal polynomial and reduced rank vector extrapolation techniques, in the context of emission tomography, is presented. These extrapolation techniques are implemented in a positron emission tomography system. The new algorithms are evaluated using computer experiments, with measurements taken from simulated phantoms. It is shown that, with minimal additional computations, the proposed approach results in substantial improvement in reconstruction.     

A Visible and Near-Infrared Light-Fueled Omnidirectional Twist-Bend Crawling Robot

In recent years, although light-driven soft actuators have attracted intense scientific attention and achieved remarkable progress, the design and construction of an intelligent robotic system with maneuverability, self-adaptability, untethered control, and greater freedom of action, in particular the omnidirectional motion capability on a plane, remains challenging. Herein, four types of photo-thermal fillers and an unprecedented twist-bend actuation mode is introduced into a liquid crystal elastomer-based soft robot. The obtained twist-bend crawling robot not only exhibits in situ rotation, four-way turning, and four-way linear motion under light irradiation with four wavelength bands (520, 655, 808, and 980 nm), but also demonstrates the ability to avoid obstacles in complex geographical environments. This work may bring a new perspective for fabrication and development of soft robots that can adapt to dynamic and complex environmental conditions.