Exploring electron transfer in myoglobin-based transistors

Electron transfer in proteins is an issue of fundamental importance in biochemistry. This is especially true for proteins whose functionality relies on redox reactions, which by definition means that electron exchange must take place between the protein and another protein, a cofactor, or the external environment. An important example consists of proteins containing heme groups, where the iron ion in the protoporphyrin ring changes valence state depending on the whether an electron is accepted or given up by the protein. Much experimental work has been carried out since the late 1950s in order to develop an understanding of protein electron transfer mechanisms. This understanding is mainly based on the statistical average of protein ensembles measured by spectroscopic and electrochemical techniques.;Since the 1990s, electron transfer through individual molecules has been probed using electrochemical scanning tunneling microscopy (EC-STM) in aqueous solution at room temperature. Models that explain the behavior of electron transfer include the resonant tunneling model and two-step electron transfer model.;Recently, the fabrication of nanometer-gap electrodes by electromigration (break-junction) techniques has made it possible to study electron conductance through small single molecules that undergo redox reactions at cryogenic temperatures. By applying a bias voltage V between the electrodes, as well as a gate voltage VG to the sample, the molecular energy levels can be probed and characteristic single-electron transistor (SET) behavior, such as a Coulomb blockade or a Kondo resonance, can be observed under the right conditions. This has created the possibility of making devices that exploit the unique electronic properties of organic and biomolecular compounds, such as their small size, stability, and dependence on conformation.;Considering the successful results in molecular SETs, an interesting question is whether similar devices can be fabricated using proteins. In principle, protein-based SETs could be observed at moderate cryogenic temperatures for heme proteins. Ideally, proteins with localized, well-defined energy levels are necessary.;In this work, the mechanism of electron transfer by myoglobin using nanometer-gap platinum electrodes was investigated. The electrodes were fabricated by breaking a small junction by electromigration at cryogenic temperatures. Apomyoglobin (myoglobin without the heme group) was used as a reference. The experimental results suggest single electron transport behavior is mediated by resonance of the electronic levels of the heme group in the myoglobin protein. This demonstrates that myoglobin across nanometer-gap electrodes could be utilized to fabricate single electron transistors. The orientation and conformation of myoglobin in the gap of electrodes may significantly affect the conductance of these devices

Learning Convolutional Networks for Content-weighted Image Compression

Lossy image compression is generally formulated as a joint rate-distortion optimization to learn encoder, quantizer, and decoder. However, the quantizer is non-differentiable, and discrete entropy estimation usually is required for rate control. These make it very challenging to develop a convolutional network (CNN)-based image compression system. In this paper, motivated by that the local information content is spatially variant in an image, we suggest that the bit rate of the different parts of the image should be adapted to local content. And the content aware bit rate is allocated under the guidance of a content-weighted importance map. Thus, the sum of the importance map can serve as a continuous alternative of discrete entropy estimation to control compression rate. And binarizer is adopted to quantize the output of encoder due to the binarization scheme is also directly defined by the importance map. Furthermore, a proxy function is introduced for binary operation in backward propagation to make it differentiable. Therefore, the encoder, decoder, binarizer and importance map can be jointly optimized in an end-to-end manner by using a subset of the ImageNet database. In low bit rate image compression, experiments show that our system significantly outperforms JPEG and JPEG 2000 by structural similarity (SSIM) index, and can produce the much better visual result with sharp edges, rich textures, and fewer artifacts

Modeling correlation noise statistics at decoder for multi-view distributed video coding

Recently, multi-view distributed video coding (MDVC) receives more and more attention, as its low-complexity encoder and high-complexity decoder coding paradigm suits for many applications such as sensor networks, in which several view sequences are required to be coded by a few power-constraint encoders. Modeling the correlation noises between original frame and side information frame is a hot research issue in distributed video coding (DVC), since it is a vital factor affecting the coding efficiency. This paper firstly proposes a novel method to model the correlation noises in MDVC. And an algorithm to online estimate the model at decoder using the knowledge of adjacent views is also presented. Experiment results show that the proposed correlation model can significantly improve coding efficiency. ?2009 IEEE.EI

An investigation into the feasibility of myoglobin-based single-electron transistors

Myoglobin single-electron transistors were investigated using nanometer- gap platinum electrodes fabricated by electromigration at cryogenic temperatures. Apomyoglobin (myoglobin without heme group) was used as a reference. The results suggest single electron transport is mediated by resonant tunneling with the electronic and vibrational levels of the heme group in a single protein. They also represent a proof-of-principle that proteins with redox centers across nanometer-gap electrodes can be utilized to fabricate single-electron transistors. The protein orientation and conformation may significantly affect the conductance of these devices. Future improvements in device reproducibility and yield will require control of these factors

DV-Hop localization based on Distance Estimation using Multinode and Hop Loss in WSNs

Location awareness is a critical issue in wireless sensor network applications. For more accurate location estimation, the two issues should be considered extensively: 1) how to sufficiently utilize the connection information between multiple nodes and 2) how to select a suitable solution from multiple solutions obtained by the Euclidean distance loss. In this paper, a DV-Hop localization based on the distance estimation using multinode (DEMN) and the hop loss in WSNs is proposed to address the two issues. In DEMN, when multiple anchor nodes can detect an unknown node, the distance expectation between the unknown node and an anchor node is calculated using the cross-domain information and is considered as the expected distance between them, which narrows the search space. When minimizing the traditional Euclidean distance loss, multiple solutions may exist. To select a suitable solution, the hop loss is proposed, which minimizes the difference between the real and its predicted hops. Finally, the Euclidean distance loss calculated by the DEMN and the hop loss are embedded into the multi-objective optimization algorithm. The experimental results show that the proposed method gains 86.11\% location accuracy in the randomly distributed network, which is 6.05% better than the DEM-DV-Hop, while DEMN and the hop loss can contribute 2.46% and 3.41%, respectively

Probability-based Distance Estimation Model for 3D DV-Hop Localization in WSNs

Localization is one of the pivotal issues in wireless sensor network applications. In 3D localization studies, most algorithms focus on enhancing the location prediction process, lacking theoretical derivation of the detection distance of an anchor node at the varying hops, engenders a localization performance bottleneck. To address this issue, we propose a probability-based average distance estimation (PADE) model that utilizes the probability distribution of node distances detected by an anchor node. The aim is to mathematically derive the average distances of nodes detected by an anchor node at different hops. First, we develop a probability-based maximum distance estimation (PMDE) model to calculate the upper bound of the distance detected by an anchor node. Then, we present the PADE model, which relies on the upper bound obtained of the distance by the PMDE model. Finally, the obtained average distance is used to construct a distance loss function, and it is embedded with the traditional distance loss function into a multi-objective genetic algorithm to predict the locations of unknown nodes. The experimental results demonstrate that the proposed method achieves state-of-the-art performance in random and multimodal distributed sensor networks. The average localization accuracy is improved by 3.49\%-12.66\% and 3.99%-22.34%, respectively

Experimental investigation of immiscible water-alternating-gas injection in ultra-high water-cut stage reservoir

Water-alternating-gas (WAG) injection is recommended as a means of improving gas mobility control. This paper describes a series of coreflood tests conducted to investigate the potential for continuous gas injection and WAG injection in ultra-high water-cut saline reservoirs. The mechanisms of immiscible water-alternating-nitrogen injection on residual oil distribution are analyzed, and pore-scale analysis is conducted. The effect of injection parameters on residual oil distribution and recovery efficiency is also evaluated. Coreflood results show that tertiary oil recovery efficiency is significantly higher using WAG injection than continuous gas injection during the ultra-high water-cut period. Pore-scale visualization illustrates the movement of gas through the waterflooded channels into the pore space previously occupied by water and residual oil, which then becomes trapped. Injected gas breaks the force balance of microscopic residual oil and reduces residual oil saturation. This mobilizes the displaced/collected residual oil into large waterfilled pores and blocks several water channels. WAG flooding can decrease free-gas saturation and increase trapped-gas saturation significantly, resulting in decreased relative permeabilities of gas and water. The experimental results indicate that appropriate WAG design parameters could enhance recovery by 15.62% when the injected pore volume of water and gas in the cycle is 0.3 PV at a gas/water injection ratio of 2:1. The results from this study will allow researchers and reservoir engineers to understand and implement immiscible WAG injection as an enhanced oil recovery method in ultra-high water-cut stage reservoirs.Cited as: Kong, D., Gao, Y., Sarma, H., Li, Y., Guo, H., Zhu, W. Experimental investigation of immiscible water-alternating-gas injection in ultra-high water-cut stage reservoir. Advances in Geo-Energy Research, 2021, 5(2): 139-152, doi: 10.46690/ager.2021.02.0

Mitigating Access-Driven Timing Channels in Clouds using StopWatch

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