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Graphene is a two-dimensional material. Its use has many advantages in gas sensing, but its long desorption process is problematic. The aim of this paper is to design a graphene-based gas sensor, study the response to NO₂ gas concentrations and find ways to accelerate the desorption process.

In one group, the sensor was placed in air to measure its initial resistance. Then, it was exposed to the NO₂ gas at a certain concentration. Finally, the sensor was exposed to light immediately after NO₂ gas exposure was ended. In another group, the sensor was heated using a heating plate at a stable temperature, before taking the measurements. Then the adsorption and desorption experiments were carried on.

Illumination and heating at a suitable temperature can expedite desorption of NO₂ molecules on graphene.

In the paper, two main methods are introduced to accelerate the desorption process when the NO₂ gas is absorbed on graphene. Through a series of experiments and analysis, the authors found that the recovery time could be reduced observably and the recovery performance of the graphene-based NO₂ sensor could be improved effectively.

The paper aims to transfer the item image of a given clothing product to a corresponding area of the user image. Existing classical methods suffer from unconstrained deformation of clothing and occlusion caused by hair or poses, which leads to loss of details in the try-on results. In this paper, the authors present a details-oriented virtual try-on network (DO-VTON), which allows synthesizing high-fidelity try-on images with preserved characteristics of target clothing.

The proposed try-on network consists of three modules. The fashion parsing module (FPM) is designed to generate the parsing map of a reference person image. The geometric matching module (GMM) warps the input clothing and matches it with the torso area of the reference person guided by the parsing map. The try-on module (TOM) generates the final try-on image. In both FPM and TOM, attention mechanism is introduced to obtain sufficient features, which enhances the performance of characteristics preservation. In GMM, a two-stage coarse-to-fine training strategy with a grid regularization loss (GR loss) is employed to optimize the clothing warping.

In this paper, the authors propose a three-stage image-based virtual try-on network, DO-VTON, that aims to generate realistic try-on images with extensive characteristics preserved.

The authors’ proposed algorithm can provide a promising tool for image based virtual try-on.

The authors’ proposed method is a technology for consumers to purchase favored clothes online and to reduce the return rate in e-commerce.

Therefore, the authors’ proposed algorithm can provide a promising tool for image based virtual try-on.

This chapter aims to answer whether foreign multinational corporations (MNCs) operating within the Chinese context differ from indigenous firms on several essential labor standards indicators: white- and blue-collar salaries, pension insurance, and working hours. In drawing upon neo-institutional and organizational imprinting theories and applying these to the Chinese context, the study addresses competing arguments regarding the expected effects of ownership type on these indicators. We employ seemingly unrelated regressions (SURs) to empirically examine a novel national survey of 1,268 firms in 12 Chinese cities. The regression results show that foreign MNCs do not provide uniquely beneficial labor practice packages to workers when compared with various indigenous firm types, including state-owned enterprises (SOEs), affiliate businesses of Hong Kong, Macau, and Taiwan, and domestic private enterprises (DPEs). Specifically, although MNCs provide relatively higher wage rates, they underperform relative to SOEs concerning social insurance. However, DPEs consistently underperform relative to MNCs across most indicators. The mixture of the results contributes important nuances to the application of neo-institutional and organizational imprinting theories to the Chinese context.

The purpose of this study is to establish an effective numerical simulation method to describe the flow pattern and optimize the strategy of noncontact mixing induced by alternating Gaussian light inside a nanofluid droplet and analyzing the influencing factors and flow mechanism of fluid mixing inside a droplet.

First, the heat converted by the alternating incident Gaussian light acting on the nanoparticles was considered as the bulk heat source distribution, and the equilibrium equation between the surface tension and the viscous force at the upper boundary force was established; then, the numerical simulation methods for multiple-physical-field coupling was established, and the mixing index was used to quantify the mixing degree inside a droplet. The effects of the incident position of alternating Gaussian light and the height of the droplet on the mixing characteristics inside a droplet were studied. Finally, the nondimensional Marangoni number was used to reveal the flow mechanism of the internal mixing of the droplet.

Noncontact alternating Gaussian light can induce asymmetric vortex motion inside a nanofluid droplet. The incident position of alternating Gaussian light is a significant factor affecting the mixing degree in the droplet. In addition, the heat transfer caused by the surface tension gradient promotes the convection effect, which significantly enhances the mixing of the fluid in the droplet.

This study demonstrates the possibility of the chaotic mixing phenomenon induced by noncontact Gaussian light that occurs within a tiny droplet and provides a feasible method to achieve efficient mixing inside droplets at the microscale.

The aim of this study is to investigate the horizontal displacement effects of foundation pit excavation on adjacent metro stations and shield tunnel composite structures. It seeks to develop a theoretical calculation method capable of accurately assessing these engineering impacts, aiming to provide practical assistance for engineering applications.

This study introduces a model for shield tunnel segments incorporating rotation and misalignment, considering the constraints of metro stations. It establishes a displacement model for tunnel-station combinations during foundation pit excavation, deriving a formula for calculating station-proximal tunnel horizontal displacements. The method's accuracy is validated against field data from three engineering cases. The research also explores variations in tunnel displacement, inter-ring shear force, misalignment and rotation angle under different spatial relationships between pits, tunnels and stations.

This study models uneven deformation between stations and tunnels due to bending stiffness and shear constraints. It enhances the misalignment model with station-induced shear effects and introduces coefficients for their mutual interaction. Results show varied responses based on pit-station-tunnel positioning: minimal displacement near pit edges (coefficients around 0.1) and significant effects near pit centers (coefficients from 0.4 to 0.5). “Whip effect” from station constraints affects tunnel displacement, shear force, misalignment and rotation, with fluctuations decreasing with distance from excavation areas.

This study demonstrates significant originality and value. It introduces a novel displacement model for tunnel-station combinations considering station constraints, addressing theoretical calculations of horizontal displacement effects from foundation pit excavation on metro stations and shield tunnel structures. Through validation with field data and parameter studies, the concept of influence coefficients is proposed, offering insights into variations in structural responses under different spatial relationships. This research provides crucial technical support and decision-making guidance for optimizing designs and facilitating practical construction in similar engineering projects.

This paper aims to study the effect of laser energy on the formability, microstructure and mechanical properties of AZ61D alloy to assist systematic study of laser additive manufacturing of magnesium alloys.

In this study, porous magnesium alloy samples were prepared by using different laser parameters. The changes of the formability and microstructure were observed by SEM, and the mechanical properties were tested. The above results were analyzed to obtain optimized laser parameters.

When the laser power is between 85 and 95 W (pulse width 3.0 ms, frequency 40 Hz), the surface morphology of the selective laser-melted (SLMed) porous samples are smooth and even. At 80 W, SLMed porous samples have a maximum relative density of 99.2 per cent. Because of the “solute capture” effect and the evaporization of magnesium, the fraction of ß-Mg17Al12 increases from 42.1 to 52.1 per cent when power rises from 80 to 105 W. The ultimate compressive strength of SLMed porous magnesium alloys is strengthened with the increase of laser power.

The effect of laser parameters on microstructure and mechanical properties of porous magnesium alloys prepared by SLM has not been reported.