Embedding Representation of Academic Heterogeneous Information Networks Based on Federated Learning

Academic networks in the real world can usually be portrayed as heterogeneous information networks (HINs) with multi-type, universally connected nodes and multi-relationships. Some existing studies for the representation learning of homogeneous information networks cannot be applicable to heterogeneous information networks because of the lack of ability to issue heterogeneity. At the same time, data has become a factor of production, playing an increasingly important role. Due to the closeness and blocking of businesses among different enterprises, there is a serious phenomenon of data islands. To solve the above challenges, aiming at the data information of scientific research teams closely related to science and technology, we proposed an academic heterogeneous information network embedding representation learning method based on federated learning (FedAHE), which utilizes node attention and meta path attention mechanism to learn low-dimensional, dense and real-valued vector representations while preserving the rich topological information and meta-path-based semantic information of nodes in network. Moreover, we combined federated learning with the representation learning of HINs composed of scientific research teams and put forward a federal training mechanism based on dynamic weighted aggregation of parameters (FedDWA) to optimize the node embeddings of HINs. Through sufficient experiments, the efficiency, accuracy and feasibility of our proposed framework are demonstrated

Correlation of electron delocalisation with pseudocapacitance in nanostructured carbon

The unique electronic structure - partial electron delocalisation (PED) -has been for the first time correlated with pseudocapacitance in graphene-based electrode materials in this study. Pseudocapacitive charge storage was observed on electrodes fabricated from graphene and related materials with different degrees of electron delocalisation (DED%), including graphene oxide (GO), partially oxidised graphene (POG) and polycrystalline monolayer graphene (PMG). GO working electrodes were electrochemically reduced (ECR) via different potential cycling controls to prepare POGs with different DED%. Raman spectroscopy and X-ray photoelectrons spectroscopy (XPS) were used to qualitatively correlate the DED% with the state of oxidation of GOs. It was found that when the ECR was increased from 0 to 1000 potential cycles, the DED% of GO improved from 12.5% to 60.4%. Electrochemical characterisations were used to monitor the charge storage of ECR-treated GOs, i.e. POGs, in 3.0 M KCl and 1.0 M H2SO4, respectively. Cyclic voltammetry (CV) results showed that as the DED of GO was improved, the specific capacitance (Cm) increased from 0.1 to 38.0 F/g in 3.0 M KCl and 0.2 to 62.0 F/g in 1.0 M H2SO4. Electrochemical impedance spectroscopy (EIS) indicated that the improvement of charge storage could be mainly attributed to pseudocapacitance. In the case of PMG, the CV results showed that the value of Cm was ca. 28.0 F/g in 3.0 M KCl and ca. 64.0 F/g in 3.0 M HCl, respectively, although the DED% of PMG was almost 95.0% as derived from the XPS results. The EIS analyses again indicated that the pseudocapacitive contribution predominated the total charge storage. The electronic structures of representative GO models with DED% varying from 0 to 100% were established based on the density functional theory (DFT) modelling. The results showed that extra electronic states only emerged around the Fermi level of POG species (0% < DED% < 100%), but not in fully oxidised graphene (DED% = 0%), nor in pure graphene (DED% = 100%). These states should have originated from the partially delocalised valence electrons rather than those localised electrons. A non-linear relationship between the charge storage capacity and the DED% was found with a peak at between 65.0 and 75.0% of the DED. Finally, by sorting the specific capacitance of the above mentioned graphene species in the order of their DED%, a non-linear relationship has been found again with a peak between 65.0 to 75.0% of the DED. Both the experimental observations and theoretical predictions have revealed a consistent correlation between the pseudocapacitance and the DED% in graphene oxide electrode materials

Faradaic processes beyond Nernst’s law: density functional theory assisted modelling of partial electron delocalisation and pseudocapacitance in graphene oxides

The study of electron delocalisation in oxygen atom segregated zones in graphene, aided by the first-principles density functional theory, has revealed extra energy bands of ≥ 2 eV wide around the Fermi level, predicting faradaic charge storage occurring in a wide range of potentials, which disagrees with Nernst’s Law but accounts well for the so called pseudocapacitance of heteroatommodified graphene based electrode materials in supercapacitors

Asynchronous Collaborative Autoscanning with Mode Switching for Multi-Robot Scene Reconstruction

When conducting autonomous scanning for the online reconstruction of unknown indoor environments, robots have to be competent at exploring scene structure and reconstructing objects with high quality. Our key observation is that different tasks demand specialized scanning properties of robots: rapid moving speed and far vision for global exploration and slow moving speed and narrow vision for local object reconstruction, which are referred as two different scanning modes: explorer and reconstructor, respectively. When requiring multiple robots to collaborate for efficient exploration and fine-grained reconstruction, the questions on when to generate and how to assign those tasks should be carefully answered. Therefore, we propose a novel asynchronous collaborative autoscanning method with mode switching, which generates two kinds of scanning tasks with associated scanning modes, i.e., exploration task with explorer mode and reconstruction task with reconstructor mode, and assign them to the robots to execute in an asynchronous collaborative manner to highly boost the scanning efficiency and reconstruction quality. The task assignment is optimized by solving a modified Multi-Depot Multiple Traveling Salesman Problem (MDMTSP). Moreover, to further enhance the collaboration and increase the efficiency, we propose a task-flow model that actives the task generation and assignment process immediately when any of the robots finish all its tasks with no need to wait for all other robots to complete the tasks assigned in the previous iteration. Extensive experiments have been conducted to show the importance of each key component of our method and the superiority over previous methods in scanning efficiency and reconstruction quality.Comment: 13pages, 12 figures, Conference: SIGGRAPH Asia 202

Structure Diagram Recognition in Financial Announcements

Accurately extracting structured data from structure diagrams in financial announcements is of great practical importance for building financial knowledge graphs and further improving the efficiency of various financial applications. First, we proposed a new method for recognizing structure diagrams in financial announcements, which can better detect and extract different types of connecting lines, including straight lines, curves, and polylines of different orientations and angles. Second, we developed a two-stage method to efficiently generate the industry's first benchmark of structure diagrams from Chinese financial announcements, where a large number of diagrams were synthesized and annotated using an automated tool to train a preliminary recognition model with fairly good performance, and then a high-quality benchmark can be obtained by automatically annotating the real-world structure diagrams using the preliminary model and then making few manual corrections. Finally, we experimentally verified the significant performance advantage of our structure diagram recognition method over previous methods

How to Achieve Efficiency and Accuracy in Discrete Element Simulation of Asphalt Mixture: A DRF-Based Equivalent Model for Asphalt Sand Mortar

The clump-based discrete element model is one of the asphalt mixture simulation methods, which has the potential to not only predict mixture performance but also simulate particle movement during compaction, transporting, and other situations. However, modelling of asphalt sand mortar in this method remains to be a problem due to computing capacity. Larger-sized balls (generally 2.0-2.36 mm) were usually used to model the smaller particles and asphalt binder, but this replacement may result in the mixture\u27s unrealistic volumetric features. More specifically, replacing original elements with equal volume but larger size particles will increase in buck volume and then different particle contacting states. The major objective of this research is to provide a solution to the dilemma situation through an improved equivalent model of the smaller particles and asphalt binders. The key parameter of the equivalent model is the diameter reduction factor (DRF), which was proposed in this research to minimize the effects of asphalt mortar\u27s particle replacement modelling. To determine DRF, the DEM-based analysis was conducted to evaluate several mixture features, including element overlap ratio, ball-wall contact number, and the average wall stress. Through this study, it was observed that when the original glued ball diameters are ranging from 2.00 mm and 2.36 mm, the diameter reduction factor changes from 0.82 to 0.86 for AC mixtures and 0.80 to 0.84 for SMA mixtures. The modelling method presented in this research is suitable not only for asphalt mixtures but also for the other particulate mix with multisize particles

Effect of Dextrose Equivalent on Maltodextrin/Whey Protein Spray-Dried Powder Microcapsules and Dynamic Release of Loaded Flavor during Storage and Powder Rehydration

peer reviewedThe preparation of powdered microcapsules of flavor substances should not only protect these substances from volatilization during storage but also improve their di usion during use. This study aimed to investigate the e ects of maltodextrin (MD) with di erent dextrose equivalent (DE) values on retention of flavor substances during storage, and the dynamic release of flavor substances during dissolution. MDs with three di erent DE values and whey protein isolate were mixed in a ratio of 4:1 as wall materials to encapsulate ethyl acetate, and powdered microcapsules were prepared by spray drying. It was proved that MD could reduce the di usion of flavor substances under di erent relative humidity conditions through the interaction between core material and wall material. During dissolution, MD released flavor substances quickly owing to its superior solubility. The reconstituted emulsion formed after the powder dissolved in water recaptured flavor substances and made the system reach equilibrium. This study explored the mechanism of flavor release during the storage and dissolution of powder microcapsules and should help us understand the application of powder microcapsules in food systems

Ligustrazine Inhibits the Migration and Invasion of Renal Cell Carcinoma

Ligustrazine is a Chinese herb (Chuanxiong) approved for use as a medical drug in China. Recent evidence suggests that ligustrazine has promising antitumor properties. Our preliminary results showed that ligustrazine could inhibit the growth of human renal cell carcinoma (RCC) cell lines. However, the complicated molecular mechanism has not been fully revealed. Therefore, the purpose of this study to investigate the mechanism of ligustrazine resistance in human RCC cells. Cell proliferation, migration, invasion, and colony-formation ability of RCC cells A498 were detected by MTT assay, clonal formation rates, and transwell chamber assay in vitro. The expression of epithelial–mesenchymal transition (EMT)–related proteins were analyzed using western blot test. The effect of ligustrazine on the growth of A498 cells in nude mice was investigated in vivo. Our results showed that ligustrazine could significantly inhibit the proliferation, migration, and invasion of A498 both in vivo and vitro. Western blot analysis showed that the expressions of EMT-related, N-cadherin, snail, and slug proteins were significantly decreased in A498 in the ligustrazine treatment group. This study indicated that ligustrazine could significantly inhibit the malignant biological behaviors of RCC cell lines, possibly by inhibiting the EMT process