Synthesis of bacteriophage lytic proteins against Streptococcus pneumoniae in the chloroplast of Chlamydomonas reinhardtii.

There is a pressing need to develop novel antibacterial agents given the widespread antibiotic resistance among pathogenic bacteria and the low specificity of the drugs available. Endolysins are antibacterial proteins that are produced by bacteriophage-infected cells to digest the bacterial cell wall for phage progeny release at the end of the lytic cycle. These highly efficient enzymes show a considerable degree of specificity for the target bacterium of the phage. Furthermore, the emergence of resistance against endolysins appears to be rare as the enzymes have evolved to target molecules in the cell wall that are essential for bacterial viability. Taken together, these factors make recombinant endolysins promising novel antibacterial agents. The chloroplast of the green unicellular alga Chlamydomonas reinhardtii represents an attractive platform for production of therapeutic proteins in general, not least due to the availability of established techniques for foreign gene expression, a lack of endotoxins or potentially infectious agents in the algal host, and low cost of cultivation. The chloroplast is particularly well suited to the production of endolysins as it mimics the native bacterial expression environment of these proteins while being devoid of their cell wall target. In this study the endolysins Cpl-1 and Pal, specific to the major human pathogen Streptococcus pneumoniae, were produced in the C. reinhardtii chloroplast. The antibacterial activity of cell lysates and the isolated endolysins was demonstrated against different serotypes of S. pneumoniae, including clinical isolates and total recombinant protein yield was quantified at ~1.3 mg/g algal dry weight. This article is protected by copyright. All rights reserved

Gate stability of GaN-Based HEMTs with P-Type Gate

status: publishe

Finite element analysis of thermo-elastical modal damping of mems vibrations

The paper deals with finite element analysis of damped modal vibrations Q-factor values determined by thermal-elastic damping in micro-electrical-mechanical systems (MEMS). Mathematically the problem is formulated as a complex eigenvalue problem. Verification problems have been solved by using several computational environments and different presentations of model equations in order to comprehend and reduce the influence of rounding errors. The analysis of damped modal properties of selected real MEMS resonator revealed the main features of thermal-elastic damping by taking into account 3D geometry of the resonator and anchoring (clamping) structur

Multi-agent deep reinforcement learning with centralized training and decentralized execution for transportation infrastructure management

We present a multi-agent Deep Reinforcement Learning (DRL) framework for managing large transportation infrastructure systems over their life-cycle. Life-cycle management of such engineering systems is a computationally intensive task, requiring appropriate sequential inspection and maintenance decisions able to reduce long-term risks and costs, while dealing with different uncertainties and constraints that lie in high-dimensional spaces. To date, static age- or condition-based maintenance methods and risk-based or periodic inspection plans have mostly addressed this class of optimization problems. However, optimality, scalability, and uncertainty limitations are often manifested under such approaches. The optimization problem in this work is cast in the framework of constrained Partially Observable Markov Decision Processes (POMDPs), which provides a comprehensive mathematical basis for stochastic sequential decision settings with observation uncertainties, risk considerations, and limited resources. To address significantly large state and action spaces, a Deep Decentralized Multi-agent Actor-Critic (DDMAC) DRL method with Centralized Training and Decentralized Execution (CTDE), termed as DDMAC-CTDE is developed. The performance strengths of the DDMAC-CTDE method are demonstrated in a generally representative and realistic example application of an existing transportation network in Virginia, USA. The network includes several bridge and pavement components with nonstationary degradation, agency-imposed constraints, and traffic delay and risk considerations. Compared to traditional management policies for transportation networks, the proposed DDMAC-CTDE method vastly outperforms its counterparts. Overall, the proposed algorithmic framework provides near optimal solutions for transportation infrastructure management under real-world constraints and complexities

Modeling and simulation of bulk gallium nitride power semiconductor devices

Bulk gallium nitride (GaN) power semiconductor devices are gaining significant interest in recent years, creating the need for technology computer aided design (TCAD) simulation to accurately model and optimize these devices. This paper comprehensively reviews and compares different GaN physical models and model parameters in the literature, and discusses the appropriate selection of these models and parameters for TCAD simulation. 2-D drift-diffusion semi-classical simulation is carried out for 2.6 kV and 3.7 kV bulk GaN vertical PN diodes. The simulated forward current-voltage and reverse breakdown characteristics are in good agreement with the measurement data even over a wide temperature range

Green biologics: the algal chloroplast as a platform for making biopharmaceuticals

Most commercial production of recombinant pharmaceutical proteins involves the use of mammalian cell lines, E. coli or yeast as the expression host. However, recent work has demonstrated the potential of eukaryotic microalgae as platforms for light-driven synthesis of such proteins. Expression in the algal chloroplast is particularly attractive since this organelle contains a minimal genome suitable for rapid engineering using synthetic biology approaches; with transgenes precisely targeted to specific genomic loci and amenable to high-level, regulated and stable expression. Furthermore, proteins can be tightly contained and bio-encapsulated in the chloroplast allowing accumulation of proteins otherwise toxic to the host, and opening up possibilities for low-cost, oral delivery of biologics. In this commentary we illustrate the technology with recent examples of hormones, protein antibiotics and immunotoxins successfully produced in the algal chloroplast, and highlight possible future applications

Impact of the substrate and buffer design on the performance of GaN on Si power HEMTs

Abstract This paper presents an extensive analysis of the impact of substrate and buffer properties on the performance and breakdown voltage of E-mode power HEMTs. We investigated the impact of buffer thickness, substrate resistivity and substrate miscut angle, by characterizing several wafers by means of DC and pulsed measurement. The results demonstrate that: (i) the resistivity of the silicon substrate strongly impacts on the breakdown voltage and vertical leakage current. In fact, highly resistive substrates may partly deplete under high vertical bias, thus limiting the total potential drop on the epitaxial layers. As a consequence, the vertical I V plots show a "plateau", that limits the vertical leakage. (ii) the depletion of the substrate may worsen the dynamic performance of the devices, due to an enhancement of buffer trapping. (iii) Larger buffer thickness results in an increased robustness of the vertical stack, due to the thicker insulating region. (iv) the miscut angle (0°, 0.5°, and 1°) can significantly impact on both threshold voltage and the 2DEG density; devices with miscut substrate have higher current density. On the other hand, the dynamic on-resistance variation is comparable in the three cases

Analysis of threshold voltage instabilities in semi-vertical GaN-on-Si FETs

We present a first study of threshold voltage instabilities of semi-vertical GaN-on-Si trench-MOSFETs, based on double pulsed, threshold voltage transient, and UV-Assisted C-V analysis. Under positive gate stress, small negative V th shifts (low stress) and a positive V thshifts (high stress) are observed, ascribed to trapping within the insulator and at the metal/insulator interface. Trapping effects are eliminated through exposure to UV light; wavelength-dependent analysis extracts the threshold de-Trapping energy ≈2.95 eV. UV-Assisted CV measurements describe the distribution of states at the GaN/Al2O3 interface. The described methodology provides an understanding and assessment of trapping mechanisms in vertical GaN transistors