Structural and Mechanistic Characterization of Carbon-Phosphorus Lyase Multi-Protein Complex and the Phosphotriesterase from Sphingobium sp. Strain TCM1

Phosphonates are a class of organophosphorus compounds with a characteristic carbon–phosphorus bond. The carbon–phosphorus lyase complex, encoded by the genes phnGHIJKLM, catalyzes the cleavage of the stable carbon–phosphorus bond of organophosphonates to the corresponding hydrocarbon and inorganic phosphate. Recently, complexes of this enzyme containing five subunits (PhnG-H-I-J-K), four subunits (PhnG-H-I-J), and two subunits (PhnG-I) were purified after expression in Escherichia coli. Here we used mass spectrometry, ultracentrifugation, chemical cross-linking, N-terminal protein sequencing and single-particle cryo-electron microscopy experiments, revealing subunits interactions and construct structural models for the PhnG2H2I2J2 and PhnG2H2I2J2K C–P lyase complexes from E. coli. The proposed stoichiometry, subunit interaction and structural model of PhnG2H2I2J2 complex agreed quite well with the crystal structure that was published later. PhnG2H2I2J2 is a two-fold symmetric hetero-octamer. Its two PhnJ subunits provide two identical binding sites for PhnK. Only one PhnK binds to PhnG2H2I2J2 due to steric hindrance. Moreover, binding of PhnK exposes the active site residue, Gly32 of PhnJ, located near the interface between PhnJ and PhnH. This structural information provides a basis for further deciphering of the reaction mechanism of the C-P lyase. A group of organophosphorus compounds, the phosphotriester plasticizers and flame retardants, has recently become widely used. This group of compounds lacks an easily hydrolyzable bond, rendering them inert to typical phosphotriesterases. A phosphotriesterase from Sphingobium sp. strain TCM1 (Sb-PTE) has recently been reported to catalyze the hydrolysis of organophosphorus flame retardants. This enzyme was expressed in Escherichia coli, and the activity with a wide variety of organophosphorus substrates has been characterized. Sb-PTE exhibits catalytic activity against flame retardants, plasticizers, and industrial solvents. In this study, we use mass spectrometry and peptide mapping experiments, revealing the active site residues and reaction mechanism for Sb-PTE. The proposed active site residues of Sb-PTE complex agreed quite well with the crystal structure that was published later. The enzyme catalyzes the hydrolysis of substrates by activation of a nucleophilic water molecule for direct attack at the phosphorus center

Masked Diffusion Models Are Fast and Privacy-Aware Learners

Diffusion models have emerged as the \emph{de-facto} technique for image generation, yet they entail significant computational overhead, hindering the technique's broader application in the research community. We propose a prior-based denoising training framework, the first to incorporate the pre-train and fine-tune paradigm into the diffusion model training process, which substantially improves training efficiency and shows potential in facilitating various downstream tasks. Our approach centers on masking a high proportion (e.g., up to 90\%) of the input image and employing masked denoising score matching to denoise the visible areas, thereby guiding the diffusion model to learn more salient features from training data as prior knowledge. By utilizing masked learning in a pre-training stage, we efficiently train the ViT-based diffusion model on CelebA-HQ $256 \times 256$ in the pixel space, achieving a 4x acceleration and enhancing the quality of generated images compared to denoising diffusion probabilistic model (DDPM). Moreover, our masked pre-training technique can be universally applied to various diffusion models that directly generate images in the pixel space, aiding in the learning of pre-trained models with superior generalizability. For instance, a diffusion model pre-trained on VGGFace2 attains a 46\% quality improvement through fine-tuning with merely 10\% data from a different distribution. Moreover, our method shows the potential to serve as a training paradigm for enhancing the privacy protection capabilities of diffusion models. Our code is available at \url{https://github.com/jiachenlei/maskdm}

A new graphical password scheme resistant to shoulder-surfing

Shoulder-surfing is a known risk where an attacker can capture a password by direct observation or by recording the authentication session. Due to the visual interface, this problem has become exacerbated in graphical passwords. There have been some graphical schemes resistant or immune to shoulder-surfing, but they have significant usability drawbacks, usually in the time and effort to log in. In this paper, we propose and evaluate a new shoulder-surfing resistant scheme which has a desirable usability for PDAs. Our inspiration comes from the drawing input method in DAS and the association mnemonics in Story for sequence retrieval. The new scheme requires users to draw a curve across their password images orderly rather than click directly on them. The drawing input trick along with the complementary measures, such as erasing the drawing trace, displaying degraded images, and starting and ending with randomly designated images provide a good resistance to shoulder-surfing. A preliminary user study showed that users were able to enter their passwords accurately and to remember them over time

Arylsilanes and siloxanes as optoelectronic materials for organic light-emitting diodes (OLEDs)

Organic light emitting diodes (OLEDs) are currently receiving much attention for applications in new generation full-colour flat-panel and flexible displays and as sources for low energy solid-state lighting. Arylsilanes and siloxanes have been extensively studied as components of OLEDs, mainly focusing on optimizing the physical and electronic properties of the light-emitting layer and other functional layers within the OLED architecture. Arylsilanes and siloxanes display the advantages of good solubility in common organic solvents and excellent resistance to thermal, chemical and irradiation degradations. In this review, we summarize the recent advances in the utilization of arylsilanes and siloxanes as fluorophore emitters, hosts for phosphor emitters, hole and exciton blocking materials, and as electron and hole transporting materials. Finally, perspectives and challenges related to arylsilanes and siloxanes for OLED applications are proposed based on the reported progress and our own opinions

The effect of baroque music on the PassPoints graphical password

Graphical passwords have been demonstrated to be the possible alternatives to traditional alphanumeric passwords. However, they still tend to follow predictable patterns that are easier to attack. The crux of the problem is users’ memory limitations. Users are the weakest link in password authentication mechanism. It shows that baroque music has positive effects on human memorizing and learning. We introduce baroque music to the PassPoints graphical password scheme and conduct a laboratory study in this paper. Results shown that there is no statistic difference between the music group and the control group without music in short-term recall experiments, both had high recall success rates. But in long-term recall, the music group performed significantly better. We also found that the music group tended to set significantly more complicated passwords, which are usually more resistant to dictionary and other guess attacks. But compared with the control group, the music group took more time to log in both in short-term and long-term tests. Besides, it appears that background music does not work in terms of hotspots

The effect of baroque music on the PassPoints graphical password

Graphical passwords have been demonstrated to be the possible alternatives to traditional alphanumeric passwords. However, they still tend to follow predictable patterns that are easier to attack. The crux of the problem is users’ memory limitations. Users are the weakest link in password authentication mechanism. It shows that baroque music has positive effects on human memorizing and learning. We introduce baroque music to the PassPoints graphical password scheme and conduct a laboratory study in this paper. Results shown that there is no statistic difference between the music group and the control group without music in short-term recall experiments, both had high recall success rates. But in long-term recall, the music group performed significantly better. We also found that the music group tended to set significantly more complicated passwords, which are usually more resistant to dictionary and other guess attacks. But compared with the control group, the music group took more time to log in both in short-term and long-term tests. Besides, it appears that background music does not work in terms of hotspots

Masked Autoencoders for Egocentric Video Understanding @ Ego4D Challenge 2022

In this report, we present our approach and empirical results of applying masked autoencoders in two egocentric video understanding tasks, namely, Object State Change Classification and PNR Temporal Localization, of Ego4D Challenge 2022. As team TheSSVL, we ranked 2nd place in both tasks. Our code will be made available.Comment: 5 page