Novel carbon nanosheets as support for ultrahigh-resolution structural analysis of nanoparticles

The resolution in transmission electron microscopy (TEM) has reached values as low as 0.08 nm. However, these values are not accessible for very small objects in the size range of a few nanometers or lower, as they have to be placed on some support, which contributes to the overall electron-scattering signal, thereby blurring the contrast. Here, we report on the use of nanosheets made from cross-linked aromatic self-assembled monolayers as TEM sample supports. When transferred onto a copper grid, a single 1.6-nm-thick nanosheet can cover the grid and is free standing within the micron-sized openings. Despite its thinness, the sheet is stable under the impact of the electron beam. Micrographs taken from nanoclusters onto these nanosheets show highly increased contrast in comparison to the images taken from amorphous carbon supports. In scanning transmission electron microscopy with nanosheet support, a size analysis of sub-nanometer Au clusters was performed and single Au atoms were resolved.     

X‐Ray Writing of Metallic Conductivity and Oxygen Vacancies at Silicon/SrTiO3 Interfaces

Tunable electronic properties of transition metal oxides and their interfaces offer remarkable functionalities for future devices. The interest in these materials has been boosted with the discovery of a 2D electron gas (2DEG) at SrTiO₃ (STO)‐based interfaces. For the majority of these systems, oxygen vacancies play a crucial role in the emergence of interface conductivity, ferromagnetism, and high electron mobility. Despite its great importance, controlling the density and spatial distribution of oxygen vacancies in a dynamic way remains extremely challenging. Here, lithography‐like writing of a metallic state at the interface between SrTiO₃ and amorphous Si using X‐ray irradiation is reported. Using a combination of transport techniques and in operando photoemission spectroscopy, it is revealed in real time that the X‐ray radiation induces transfer of oxygen across the interface leading to the on‐demand formation of oxygen vacancies and a 2DEG in STO. The formed 2DEG stays stable in ambient conditions as the interface oxygen vacancies are stabilized by the capping of Si. The study provides a fundamental understanding of X‐ray‐induced redox reactions at the SrTiO₃‐based interfaces and in addition shows the potential of X‐ray radiation for patterning stabile conductive pathways for future oxide‐based electronic devices.     

Numerical analysis of electron optical system with microchannel plate

This paper describes a numerical development of image converters and intensifiers which incorporate an inverting electron optical system (EOS) and a microchannel plate (MCP) as an amplifier. The numerical design of the system includes calculation of the electrostatic field in the device, trajectories of electrons emitted from a photocathode, and determination of the modulation-transfer-function (MTF) which gives the objective estimation for the image quality.     

A Lightweight Approach (BL-DAC) to Secure Storage Sharing in Cloud-IoT Environments

The growing advent of the Internet of Things (IoT) users is driving the adoption of cloud computing technologies. The integration of IoT in the cloud enables storage and computational capabilities for IoT users. However, security has been one of the main concerns of cloud-integrated IoT. Existing work attempts to address the security concerns of cloud-integrated IoT through authentication, access control, and blockchain-based methods. However, existing frameworks are somewhat limited by scalability, privacy, and centralized structures. To mitigate the existing problems, we propose a blockchain-based distributed access control method for secure storage in the IoT cloud (BL-DAC). Initially, the BL-DAC performs decentralized authentication using the Quantum Neural Network Cryptography (QNNC) algorithm. IoT users and edge nodes are authenticated in the blockchain deployed by distributed Trusted Authorities (TAs) using multiple credentials. The user data is classified into sensitive and non-sensitive categories using the Enhanced Seagull Optimization (ESO) algorithm. Also, the authentication to access this data is performed by a decentralized access control method using smart contract policy. Sensitive user data is encrypted using the QNNC algorithm and stored in the private cloud. In contrast, non-sensitive data is stored in the public cloud, and IPFS is used to store data in a decentralized manner with high reliability. In addition, data security is improved by using a hierarchical blockchain which improves scalability by managing the multiple blockchains hierarchically and is lightweight using Proof of Authentication Consensus (PoAH). The BL-DAC is simulated and validated using the Network Simulator-3.26 simulation tool and validated. This work shows better results than the compared ones in terms of validation metrics such as throughput (26%), encryption time (19%), decryption time (16%), response time (15%), block validation time (31%), attack detection rate (16%), access control precision (13%), and scalability (28%).     

Wrinkling Captured Garments Using Space-Time Data-Driven Deformation

The presence of characteristic fine folds is important for modeling realistic looking virtual garments. While recent garment capture techniques are quite successful at capturing the low-frequency garment shape and motion over time, they often fail to capture the numerous high-frequency folds, reducing the realism of the reconstructed space-time models. In our work we propose a method for reintroducing fine folds into the captured models using data-driven dynamic wrinkling. We first estimate the shape and position of folds based on the original video footage used for capture and then wrinkle the surface based on those estimates using space-time deformation. Both steps utilize the unique geometric characteristics of garments in general, and garment folds specifically, to facilitate the modeling of believable folds. We demonstrate the effectiveness of our wrinkling method on a variety of garments that have been captured using several recent techniques.     

Deformation‐Driven Shape Correspondence

Non‐rigid 3D shape correspondence is a fundamental and difficult problem. Most applications which require a correspondence rely on manually selected markers. Without user assistance, the performances of existing automatic correspondence methods depend strongly on a good initial shape alignment or shape prior, and they generally do not tolerate large shape variations. We present an automatic feature correspondence algorithm capable of handling large, non‐rigid shape variations, as well as partial matching. This is made possible by leveraging the power of state‐of‐the‐art mesh deformation techniques and relying on a combinatorial tree traversal for correspondence search. The search is deformation‐driven, prioritized by a self‐distortion energy measured on meshes deformed according to a given correspondence. We demonstrate the ability of our approach to naturally match shapes which differ in pose, local scale, part decomposition, and geometric detail through numerous examples.     

Subpixel Deblurring of Anti-Aliased Raster Clip-Art

Artist generated clip-art images typically consist of a small number of distinct, uniformly colored regions with clear boundaries. Legacy artist created images are often stored in low-resolution (100x100px or less) anti-aliased raster form. Compared to anti-aliasing free rasterization, anti-aliasing blurs inter-region boundaries and obscures the artist's intended region topology and color palette; at the same time, it better preserves subpixel details. Recovering the underlying artist-intended images from their low-resolution anti-aliased rasterizations can facilitate resolution independent rendering, lossless vectorization, and other image processing applications. Unfortunately, while human observers can mentally deblur these low-resolution images and reconstruct region topology, color and subpixel details, existing algorithms applicable to this task fail to produce outputs consistent with human expectations when presented with such images. We recover these viewer perceived blur-free images at subpixel resolution, producing outputs where each input pixel is replaced by four corresponding (sub)pixels. Performing this task requires computing the size of the output image color palette, generating the palette itself, and associating each pixel in the output with one of the colors in the palette. We obtain these desired output components by leveraging a combination of perceptual and domain priors, and real world data. We use readily available data to train a network that predicts, for each anti-aliased image, a low-blur approximation of the blur-free double-resolution outputs we seek. The images obtained at this stage are perceptually closer to the desired outputs but typically still have hundreds of redundant differently colored regions with fuzzy boundaries. We convert these low-blur intermediate images into blur-free outputs consistent with viewer expectations using a discrete partitioning procedure guided by the characteristic properties of clip-art images, observations about the antialiasing process, and human perception of anti-aliased clip-art. This step dramatically reduces the size of the output color palettes, and the region counts bringing them in line with viewer expectations and enabling the image processing applications we target. We demonstrate the utility of our method by using our outputs for a number of image processing tasks, and validate it via extensive comparisons to prior art. In our comparative study, participants preferred our deblurred outputs over those produced by the best-performing alternative by a ratio of 75 to 8.5.     

Exploring a mnemonic debiasing account of the underconfidence-with-practice effect.

Judgments of learning (JOLs) underestimate the increase in recall that occurs with repeated study (the underconfidence-with-practice effect; UWP). The authors explore an account in terms of a foresight bias in which JOLs are inflated when the to-be-recalled target highlights aspects of the cue that are not transparent when the cue appears alone and the tendency of practice to alleviate bias by providing learners with cues pertinent to recall. In 3 experiments the UWP effect was strongest for items that induce a foresight bias, but delaying JOLs reduced the debiasing effects of practice, thereby moderating the UWP effect. This occurred when delayed JOLs were prompted by the cue alone (like during testing), not when prompted by the cue-target pair (like during study). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Tribological Properties of Finely-Dispersed Coatings with Electric-Spark Alloying of Materials of the System Ti ― Al ― N

Mass transfer, composition, structure, and also the tribological and corrosion properties of coatings prepared with electric-spark alloying (ESA) of titanium alloy VT6 and steels 45 and 40Kh with electrode materials of the systems Ti ― Al and TiN ― AlN with different component ratios are studied. In both cases a finely-dispersed island structure forms with high wear and corrosion resistance. The best results are obtained for ESA with intermetallics. The main phase of ESA-coatings prepared with intermetallics is Al₂O₃, and from the nitrides it is TiN. It is suggested that the difference in tribological behavior of “intermetallic” and “nitride” coatings is due to the difference in their roughness and phase composition.