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The purpose of this paper is to propose a type of hybrid bearing lubricated with supercritical carbon dioxide (S-CO₂) and to investigate the stiffness and damping characteristics of the bearing under hydrostatic status.

Established a test rig for radial bearings lubricated with S-CO₂ and used it to measure the dynamic coefficients by recording the relative and absolute displacements of bearing. Test bearing is mounted on a nonrotating, stiff shaft. Using static loading experiments to obtain structural stiffness. The dynamic coefficient regularities of the test bearing under hydrostatic status were revealed through dynamic loading experiments.

Experiment results indicate that test bearing displayed increased stiffness when subjected to high excitation frequencies and low excitation forces, as well as elevated damping when exposed to low excitation frequencies and low excitation forces. Additionally, an increase in either environmental pressure or hydrostatic recess pressure can elevate the dynamic coefficient. The effect of temperature on the dynamic coefficient is more pronounced around the critical temperature of S-CO₂.

Designed a type of hybrid bearing for use in the Brayton cycle that is lubricated with S-CO₂ and uses hydrostatic lubrication during start-stop and hydrodynamic lubrication during high-speed operation. The hybrid bearing reduces the wear and friction power consumption of gas bearing. However, few experimental analyses have been conducted by researchers in this field.

The purpose of this study is to reduce the cracks, pores and unfused defects in arc welding, improve the crystalline structure of the weld, refine its grains and improve the mechanical properties.

Taking E690 marine steel as the research object, the experiment adopts a new process method of laser forging coupled arc welding. Welding for comparative experiments. Experiments show that the “V”-shaped groove arc welding process has a larger fusion area, but has pores, the arc current is 168 A, the arc voltage is 28 V and the welding speed is 600 mm/min.

It can be seen from tensile tests that the coupling welding process has the highest tensile strength and yield strength, 872 MPa and 692 MPa, respectively, and the fracture elongation is 29.29%. The single-beam laser forging coupled arc welding process has a distance of laser and wire of 6–8 mm, a laser wavelength of 1,064 nm and the highest weld fusion ratio. The microhardness test shows that the average hardness of single-beam laser forging in the weld zone is 487.54 HV, which is 10.30% higher than that of arc welding. The average hardness in the fusion zone is 788.08 HV, which is 14.52% higher than that of the arc welding process.

The originality of the experiment: proposed a new process method of coupling arc repair for offshore steel forging; adopted a new process method of simultaneous coupling of single-beam short-pulse laser, double-beam short-pulse laser and arc welding; and obtained effect of pulsed laser and arc composite repair on porosity and fusion of E690 marine steel welds.

This paper aims to study passive control techniques for transonic flow over a backward-facing step (BFS) using square-lobed trailing edges. The study investigates the efficacy of upward and downward lobe patterns, different lobe widths and deflection angles on flow separation, aiming for a deeper understanding of the flow physics behind the passive flow control system.

Large Eddy Simulation and Reynolds-averaged Navier–Stokes were used to evaluate the results of the study. The research explores the impact of upward and downward patterns of lobes on flow separation through the effects of different lobe widths and deflection angles. Numerical methods are used to analyse the behaviour of transonic flow over BFS and compared it to existing experimental results.

The square-lobed trailing edges significantly enhance the reduction of mean reattachment length by up to 80%. At Ma = 0.8, the up-downward configuration demonstrates increased effectiveness in reducing the root mean square of pressure fluctuations at a proximity of 5-step height in the wake region, with a reduction of 50%, while the flat-downward configuration proves to be more efficient in reducing the root mean square of pressure fluctuations at a proximity of 1-step height in the near wake region, achieving a reduction of 71%. Furthermore, the study shows that the up-downward configuration triggers early spanwise velocity fluctuations, whereas the standalone flat-downward configuration displays less intense crosswise velocity fluctuations within the wake region.

The findings demonstrate the effectiveness of square-lobed trailing edges as passive control techniques, showing significant implications for improving efficiency, performance and safety of the design in aerospace and industrial systems.

This paper demonstrates that the square-lobed trailing edges are effective in reducing the mean reattachment length and pressure fluctuations in transonic conditions. The study evaluates the efficacy of different configurations, deflection angles and lobe widths on flow and provides insights into the flow physics of passive flow control systems.

A series of sulfate-based Gemini anionic surfactants were synthesized via etherification, ring opening and sulfation reactions using epichlorohydrin, fatty alcohol, ethylene glycol and chlorosulfonic acid as the main raw materials. Orthogonal experiments for 1,8-bisalkoxymethylene-3,6-dioxin-1,8-octane disulfate were performed on the sulfation reaction to determine the optimal reaction conditions.

A series of sulfate-based Gemini anionic surfactants were synthesized via etherification, ring opening and sulfation reactions using epichlorohydrin, fatty alcohol, ethylene glycol and chlorosulfonic acid as the main raw materials. Orthogonal experiments for 1,8-bisalkoxymethylene-3,6-dioxin-1,8-octane disulfate were performed on the sulfation reaction to determine the optimal reaction conditions. The structures of the intermediate and final products were characterized by FT-IR (Fourier transform infrared spectroscopy analysis), ¹H-NMR (proton nuclear magnetic resonance spectroscopy) methods. The thermal performance of surfactants was analyzed using thermogravimetric analysis (TGA). The thermogravimetric results showed that the sulfate-based Gemini surfactants had good heat resistance (the thermal decomposition temperature of which was in the range of 140∼170?). The Krafft point, surface tension, foaming, Hydrophile–Lipophile Balance Number (HLB), emulsifying, wetting, and lime-soap dispersing performance were measured by visual observation, hanging drop method, aqueous surfactant solution method and Borghetti–Bergman method, respectively. The results have shown that all the sulfate-based Gemini surfactants had good water solubility and lime-soap dispersing ability. When spacer group was -(CH2)2-, with the increase of the carbon chain length from C12 to C14, the micellar concentration critical micelle concentration and surface tension (CMC) gradually increased from 8.25 × 10^–4 mol/L to 8.75 × 10^–4 mol/L and 27.5 mN/m to 30.9 mN/m, respectively. Also, the sulfate-based Gemini surfactants with the different length of the spacer group had a different effect on their performance on foaming properties and foam properties, HLB and emulsifying ability and wetting ability.

In view of the important role of the spacer group and the general use of anionic surfactants in oil fields, this article considers the preparation of a series of sulfate-based Gemini surfactants by changing the spacer group and the chain length of the hydrophobic group and evaluating their surface activity, and finally its Kraffi, on the foam properties, HLB value, emulsifying performance, lime soap dispersing ability etc.

Sulfate-based Gemini surfactants have broad application prospects in the fields of oil and gas exploitation, environmental protection, chemistry and daily chemical industry and so on.

This study aims to examine foreign direct investment (FDI) factors and develops a rational framework for FDI inflow in Western European countries such as France, Germany, the Netherlands, Switzerland, Belgium and Austria.

Data for this study were collected from the World development indicators (WDI) database from 1995 to 2018. Factors such as economic growth, pollution, trade, domestic capital investment, gross value-added and the financial stability of the country that influence FDI decisions were selected through empirical literature. A framework was developed using interpretable machine learning (IML), decision trees and three-stage least squares simultaneous equation methods for FDI inflow in Western Europe.

The findings of this study show that there is a difference between the most important and trusted factors for FDI inflow. Additionally, this study shows that machine learning (ML) models can perform better than conventional linear regression models.

This research has several limitations. Ideally, classification accuracies should be higher, and the current scope of this research is limited to examining the performance of FDI determinants within Western Europe.

Through this framework, the national government can understand how investors make their capital allocation decisions in their country. The framework developed in this study can help policymakers better understand the rationality of FDI inflows.

An IML framework has not been developed in prior studies to analyze FDI inflows. Additionally, the author demonstrates the applicability of the IML framework for estimating FDI inflows in Western Europe.

The purpose of this study is, First, to leverage the limitation of annotated data and to identify the cognitive level of learning objectives efficiently, this study adopts transfer learning by using word2vec and a bidirectional gated recurrent units (GRU) that can fully take into account the context and improves the classification of the model. This study adds a layer based on attention mechanism (AM), which captures the context vector and gives keywords higher weight for text classification. Second, this study explains the authors’ model’s results with local interpretable model-agnostic explanations (LIME).

Bloom's taxonomy levels of cognition are commonly used as a reference standard for identifying e-learning contents. Many action verbs in Bloom's taxonomy, however, overlap at different levels of the hierarchy, causing uncertainty regarding the cognitive level expected. Some studies have looked into the cognitive classification of e-learning content but none has looked into learning objectives. On the other hand, most of these research papers just adopt classical machine learning algorithms. The main constraint of this study is the availability of annotated learning objectives data sets. This study managed to build a data set of 2,400 learning objectives, but this size remains limited.

This study’s experiments show that the proposed model achieves highest scores of accuracy: 90.62%, F1-score and loss. The proposed model succeeds in classifying learning objectives, which contain ambiguous verb from the Bloom’s taxonomy action verbs, while the same model without the attention layer fails. This study’s LIME explainer aids in visualizing the most essential features of the text, which contributes to justifying the final classification.

In this study, the main objective is to propose a model that outperforms the baseline models for learning objectives classification based on the six cognitive levels of Bloom's taxonomy. In this sense, this study builds the bidirectional GRU (BiGRU)-attention model based on the combination of the BiGRU algorithm with the AM. This study feeds the architecture with word2vec embeddings. To prove the effectiveness of the proposed model, this study compares it with four classical machine learning algorithms that are widely used for the cognitive classification of text: Bayes naive, logistic regression, support vector machine and K-nearest neighbors and with GRU. The main constraint related to this study is the absence of annotated data; there is no annotated learning objective data set based on Bloom’s taxonomy's cognitive levels. To overcome this problem, this study seemed to have no choice but to build the data set.

The study aims to carry out the production of a bulk heterojunction organic solar cell in a laboratory scale using a blend of poly (3-hexylthiopene) (P3HT) and [6, 6]-phenyl (C61) butyric acid methyl ether (PCBM).

Four inverted geometry organic solar cells were prepared based on 1:1 ratio of P3HT to PCBM and subjected to post annealing at different temperatures of 32, 120, 130 and 140°C. Solar cells were fabricated with structure glass/ITO/P3HT:PCBM/PEDOT:PSS/Au and characterized using Keithley 2400 series sourcemeter and a multimeter interfaced to a computer system with a LabVIEW software, which showed both dark and illumination current–voltage characteristic curves. Four reference cells were also fabricated with structure soda lime glass/P3HT:PCBM and annealed at different temperatures of 32, 120, 130 and 140°C.

The third organic solar cell prepared, Sample CITO, had the best performance with power conversion efficiency (PCE) of 2.0281 per cent, fill factor (FF) of 0.392, short circuit current of −0.0133 A and open circuit voltage of 0.389 V. Annealing of active layer was found to improve cell morphology, FF and PCE. Annealing of the active layer at 140°C resulted in a decrease of the PCE to 2.01 per cent.

These findings are in good agreement with previous investigation in literature which reported that best annealing temperature for a 1:1 ratio blend of active material is 130°C. Ultraviolet–visible spectra on reference cells showed that sample CITO had wider absorption spectra with peak absorbance at a wavelength of 508 nm.

This research is purely original.

Perforated composite beams are an increasingly popular choice in the construction of buildings because they can provide a structurally and materially efficient design solution while also facilitating the passage of services. The purpose of this paper is to examine the behaviour of restrained perforated beams, which act compositely with a profiled slab and are exposed to fire. The effect of surrounding structure on the composite perforated beam is incorporated in this study using a virtual hybrid simulation framework. The developed framework could also be used to analyse other structural components in fire.

A finite element model is developed using OpenSees and OpenFresco using a virtual hybrid simulation technique, and the accuracy of the model is validated using available fire test data. The validated model is used to investigate some of the most salient parameters such as the degree of axial and rotational restraint, arrangement of the openings and different types of fire on the overall fire behaviour of composite perforated beams.

It is shown that both axial and rotational restraint have a considerable effect on time-displacement behaviour and the fire performance of the composite perforated beam. It is observed that the rate of heating and the consequent development of elevated temperature in the section have a significant effect on the fire behaviour of composite perforated beams.

The paper will improve the knowledge of readers about modelling the whole system behaviour in structural fire engineering and the presented approach could also be used for analysing different types of structural components in fire conditions.

This paper aims to explore the development trend of OA articles and their advantages and disadvantages in the process of fighting the pandemic, and conduct a multi-level and multi-angle analysis of the relationship between publishing costs and the influence of OA articles.

This study first compares the total number of articles in Web of Science with the number of OA articles, and the total number of COVID-19 related articles with the total number of OA articles. Subsequently, using the methods of institutional cooperation co-occurrence network, keyword co-occurrence and multidimensional scale analysis, and using the literature on the topic of COVID-19 in CNKI (Chinese National Knowledge Infrastructure) as the data set, we generate visualized maps of research results distribution and keyword co-occurrence network with the help of the Statistical Analysis Toolkit for Infometrics (SATI)

The research results show that the citation frequency and use frequency of OA articles related to COVID-19 are significantly higher than that of non-OA articles. OA articles dominate in the anti-pandemic process, with a series of advantages such as short review cycle, timeliness, high social benefit, high participation and fast dissemination playing an important role. Under the model of author's non-payment for OA article, the degree of institutional cooperation and author cooperation is enhanced, which improves the fluidity of knowledge, strengthens close links between keywords and enhances significant academic influence; OA articles will continue to promote research in the field of COVID-19, but the lack of quality of some OA articles may hinder their development. Then OA articles will further focus on clinical medicine, and related results will continue to promote the development and communication of OA articles in this field.

Corresponding measures are also proposed for the existing problems of OA articles, to provide a reference for the publication and dissemination of OA articles in public health emergencies in the future.