Iron-Based Metal-Organic Frameworks as Platform for H2S Selective Conversion: Structure-Dependent Desulfurization Activity.

Three classical Fe-MOFs, viz., MIL-100(Fe), MIL-101(Fe), and MIL-53(Fe), were synthesized to serve as platforms for the investigation of structure-activity relationship and catalytic mechanism in the selective conversion of H2S to sulfur. The physicochemical properties of the Fe-MOFs were characterized by various techniques. It was disclosed that the desulfurization performances of Fe-MOFs with well-defined microstructures are obviously different. Among these, MIL-100(Fe) exhibits the highest catalytic performance (ca. 100% H2S conversion and 100% S selectivity at 100-180 °C) that is superior to that of commercial Fe2O3. Furthermore, the results of systematic characterization and DFT calculation reveal that the difference in catalytic performance is mainly because of discrepancy in the amount of Lewis acid sites. A plausible catalytic mechanism has been proposed for H2S selective conversion over Fe-MOFs. This work provides critical insights that are helpful for rational design of desulfurization catalysts.

SPREAD: A Fully Automated Toolkit for Single-Particle Cryogenic Electron Microscopy Data 3D Reconstruction with Image-Network-Aided Orientation Assignment.

For the past decade, cryogenic electron microscopy (cryo-EM) has become an important technology to determine three-dimensional (3D) structures of biomacromolecules. Many software tools have been developed for cryo-EM image processing and 3D reconstruction, covering various computational tasks in cryo-EM data analysis. Despite the recent progress, most of these software tools focus on a single task, such as automatic particle picking or image clustering, whereas software packages covering the whole pipeline of cryo-EM data processing are still few. In this study, we developed a fully automatic single-particle reconstruction and analysis toolkit for cryo-EM data, named SPREAD, which integrates 2D image classification, 3D initial model generation, model selection, and 3D refinement. In SPREAD, we adopt our previously proposed network-based clustering algorithm for 2D image classification, NCEM, and the reference-free resolution measurement method SRes to realize the automatic model ranking and selection procedure. Projection orientation assignment is one of the key steps in initial model generation and 3D refinement. In SPREAD, we use the network-based image similarity metric and introduce a new probabilistic-based orientation searching method, named peak finding, to enhance assignment of the projection orientations. For dealing with both the particle images and projection images in the 3D refinement using SPREAD, we build a mixture image network containing both of these types of images on the basis of the peak-finding results, and then similarities for node pairs are recomputed by a superposed random walk on the network. SPREAD achieves a fully automatic workflow in which nearly no expert domain knowledge and interactive manual operation are involved. Our software can accessed for free at http://www.csbio.sjtu.edu.cn/bioinf/SPREAD/ for academic use.

On-line smoothing for an integrated navigation system with low-cost MEMS inertial sensors.

The integration of the Inertial Navigation System (INS) and the Global Positioning System (GPS) is widely applied to seamlessly determine the time-variable position and orientation parameters of a system for navigation and mobile mapping applications. For optimal data fusion, the Kalman filter (KF) is often used for real-time applications. Backward smoothing is considered an optimal post-processing procedure. However, in current INS/GPS integration schemes, the KF and smoothing techniques still have some limitations. This article reviews the principles and analyzes the limitations of these estimators. In addition, an on-line smoothing method that overcomes the limitations of previous algorithms is proposed. For verification, an INS/GPS integrated architecture is implemented using a low-cost micro-electro-mechanical systems inertial measurement unit and a single-frequency GPS receiver. GPS signal outages are included in the testing trajectories to evaluate the effectiveness of the proposed method in comparison to conventional schemes.

The Influence of Guanxi Between Boundary Spanners on Opportunistic Behaviors Based on the Theory of Reasoned Action Model.

This study constructs a mechanism of the influence of Guanxi between boundary spanners on opportunistic behaviors in collaborative innovation projects based on the theory of reasoned action model. The study conducts a survey in the automobile industry in Changchun, Jilin Province, China, and analyzes the research data using the structural equation model. The findings show that Guanxi has a negative an significant influence on opportunistic behavior attitudes and subjective norms., Guanxi has the greater influence on subjective norms than attitudes. Then, opportunistic behavior attitudes and subjective norms positively influence intentions. The influence of subjective norms is stronger. The attitudes and subjective norms of opportunistic behaviors also play mediation roles. Furthermore, opportunistic behavior intentions have a positive and significant influence on behaviors. In short, the study's findings reveal a mechanism of Guanxi between boundary spanners influencing opportunistic behaviors of boundary spanners. It also provides a reference for corporate managers to govern opportunistic behaviors of collaborator while inhabiting opportunistic behaviors of their own boundary spanners.

The Influence of Corporate Boundary Personnel Guanxi and Organizational Loyalty on Opportunistic Intentions - Based on Theory of Reasoned Action Model.

To understand the mechanism of boundary personnel opportunistic behaviors in collaborative R&D projects to reduce the risk of companies suffering from opportunism in collaboration. This study is conducted based on the context of collaborative R&D in the equipment manufacturing industry in Northeast China. This research mainly explored the mechanism of boundary personnel opportunistic intentions. Drawing on the theory of reasoned action (TRA), this study investigated the relationship between boundary personnel Guanxi, organizational loyalty, opportunistic attitudes, subjective norms, and intentions. In addition, this research examined the moderating role of the degree of dependence on the collaborator. In total, 524 valid questionnaires were finally collected. The data analysis results suggested that Guanxi inhibits opportunistic attitudes and subjective norms. Organizational loyalty promotes opportunistic attitudes and subjective norms. Opportunistic attitudes and subjective norms positively predict intentions. Opportunistic attitudes mediate between organizational loyalty and opportunistic intentions. Opportunistic subjective norms mediate between Guanxi and opportunistic intentions. Opportunistic subjective norms also mediate between organizational loyalty and opportunistic intentions. Dependence on the collaborator positively moderates the relationship between opportunistic attitudes and intentions. Therefore, it can be argued that in collaborative R&D in the equipment manufacturing industry, the corporate could stimulate boundary personnel to build good Guanxi to eliminate opportunism. At the same time, companies should lead employees to show loyalty properly, which opportunism is not wise in collaborative R&D. Finally, enterprises should objectively understand and evaluate the dependence relationship between the two partners in collaborative R&D to adopt the right strategy.