What determines pension insurance participation in China?: triangulation and the intertwined relationship among employers, employees and the government

The current study draws on the Advocacy Coalition Framework to examine what determines employees’ pension participation in China. For the purpose of exploring which employees actually receive pension coverage and why, econometric analysis was conducted with China’s Employer–Employee Matched Survey data (N = 3412). A variety of both individual factors, ranging from age and Hukou status to job characteristics, and macro factors, including interprovincial migration and level of economic development, are all found to predict insurance coverage. Qualitative research results contextualize these findings by discussing the often ambivalent and triangulated relations among employers, employees and government. These three groups primarily use shared core policy beliefs to structure their interactions in the form of advocacy coalitions. Various types of cross-coalition interaction, including negotiation, cooperation and conflict, are examined. These findings carry both theoretical and policy implications

Development of Hypereutectic AlSi Alloy Powder Injection Molding Feedstocks by Rheological Analysis

The comprehensive properties of a feedstock have a critical influence on the powder injection molding process. Proper feedstock with homogeneous structure, favorable flow characteristic, and moldability is the prerequisite for obtaining a final part with excellent comprehensive properties. The objective of the present work was to develop an optimal feedstock for fabrication of hypereutectic AlSi (20 wt.%) alloy parts by the powder injection molding technique. For this purpose, micron-sized hypereutectic AlSi (20 wt.%) alloy powder was mixed with different amounts of a binder which consisted of 35 wt.% high-density polyethylene, 62 wt.% carnauba wax, and 3 wt.% stearic acid. The binder contents of the feedstocks were in the range from 13 wt.% to 21 wt.%. The influences of binder content, shear rate, and temperature on the rheological behaviors of feedstocks have been investigated via a capillary rheometer. The feedstock with 21 wt.% binder exhibited a variable flow behavior and was culled. The rest of the feedstocks showed a pseudoplastic behavior. Comprehensive analysis of rheological parameters such as the flow behavior index, yield stress, flow activation energy, and the general moldability index, the feedstock with 17 wt.% binder exhibited the best rheological performance and favorable moldability. The molded part with 17 wt.% binder had constant density, good shape retention, and stiffness as well as homogeneous distribution of the powder and binder. After solvent debinding, the debound item showed a homogeneous porous structure which is suitable for the subsequent thermal debinding and sintering processes

Debinding and Sintering of an Injection-Moulded Hypereutectic Al–Si Alloy

Hypereutectic Al–Si (20 wt.%) alloy parts were fabricated by employing a powder injection moulding (PIM) technique with a developed multi-component binder system composed of high-density polyethylene (35 wt.%), carnauba wax (62 wt.%) and stearic acid (3 wt.%). The feedstocks contained 83 wt.% metal powders. The debinding process was carried out by a combination of solvent extraction and thermal decomposition. The effects of solvent debinding variables such as kind of solvents, debinding temperatures and time, and the bulk surface area to volume ratios on the debinding process were investigated. Thermal debinding and the subsequent sintering process were carried out in a heating sequence under a nitrogen atmosphere. The influences of sintering temperature and sintering time on the mechanical properties and structure were considered. Under the optimal sintering condition, sintering at 550 °C for 3 h, the final sintering parts were free of distortion and exhibited good mechanical properties. Relative sintered density, Brinell hardness, and tensile strength were ~95.5%, 58 HBW and ~154, respectively

Multi-Frame Super-Resolution Algorithm Based on a WGAN

Image super-resolution reconstruction has been widely used in remote sensing, medicine and other fields. In recent years, due to the rise of deep learning research and the successful application of convolutional neural networks in the image field, the super-resolution reconstruction technology based on deep learning has also achieved great development. However, there are still some problems that need to be solved. For example, the current mainstream image super-resolution algorithms based on single or multiple frames pursue high performance indicators such as PSNR and SSIM, while the reconstructed image is relatively smooth and lacks many high-frequency details. It is not conducive to application in a real environment. To address such problem, this paper proposes a super-resolution reconstruction model of sequential images based on Generative Adversarial Networks (GAN). The proposed approach combines the registration module to fuse adjacent frames, effectively use the detailed information in multiple consecutive frames, and enhances the spatio-temporality of low-resolution images in sequential images. While the GAN was used to improve the effect of image high-frequency texture detail reconstruction, WGAN was introduced to optimize model training. The reconstruction results not only improved the PSNR and SSIM indexes but also reconstructed more high-frequency detail textures. Finally, in order to further improve the perception effect, an additional registration loss item RLT is introduced in the GAN network perception loss. Through extensive experiments, it shows that the model proposed in this paper effectively obtains the information between the sequence images. When the PSNR and SSIM indicators are improve, it can reconstruct better high-frequency texture details than the current advanced multi-frame algorithms

Single-Core Multiscale Residual Network for the Super Resolution of Liquid Metal Specimen Images

In a gravity-free or microgravity environment, liquid metals without crystalline nuclei achieve a deep undercooling state. The resulting melts exhibit unique properties, and the research of this phenomenon is critical for exploring new metastable materials. Owing to the rapid crystallization rates of deeply undercooled liquid metal droplets, as well as cost concerns, experimental systems meant for the study of liquid metal specimens usually use low-resolution, high-framerate, high-speed cameras, which result in low-resolution photographs. To facilitate subsequent studies by material scientists, it is necessary to use super-resolution techniques to increase the resolution of these photographs. However, existing super-resolution algorithms cannot quickly and accurately restore the details contained in images of deeply undercooled liquid metal specimens. To address this problem, we propose the single-core multiscale residual network (SCMSRN) algorithm for photographic images of liquid metal specimens. In this model, multiple cascaded filters are used to obtain feature information, and the multiscale features are then fused by a residual network. Compared to existing state-of-the-art artificial neural network super-resolution algorithms, such as SRCNN, VDSR and MSRN, our model was able to achieve higher PSNR and SSIM scores and reduce network size and training time

Force Analysis and Strength Determination of the Cemented Paste Backfill Roof in Underhand Drift Cut-and-Fill Stopping

The stability of the cemented paste backfill roof (CPB roof) is critical to safe production in mines using the underhand drift cut-and-fill stopping. To investigate the scientific and reasonable design method of key parameters (size and strength) of the CPB roof and the stress state of the CPB roof during the mining process, field measurements were carried out with Jinchuan Group’s third mining area as the engineering background. Based on the measurement results, a mechanics model was constructed based on the thick plate theory. The field measurement results show that the overlying load on the CPB roof tends to increase first and then decrease with the gradual mining of the stope, and the maximum overlying load values of the two CPB roofs measured are 0.240 MPa and 0.244 MPa, respectively. With the gradual mining of the stope, the deformation of the CPB roof shows a trend of increasing first and then stabilizing. Based on the thick plate theory, the stress model of the CPB roof is constructed, and the error between the calculation results of the model and the field measurement results does not exceed 5%. Applying the research results to the three mines of Jinchuan Group, the span of the stope can be expanded from 5 m to 6 m under the existing strength standard of the filling body, which can increase its mining capacity by 20%. This study is the first to measure the overlying load and the tensile stress value on the CPB roof, which is an important guideline for related theoretical research

Formation mechanism and thermal decomposition properties of hydration products of superfine tailings cemented paste backfill

Filling mining with solid waste resources as aggregates is an important development direction for cleaner production in mines. The hydration products have an important effect on the mechanical properties of superfine tailings cemented paste backfill (SCPB). This paper investigates the mechanism of hydration product formation and thermal decomposition properties of SCPB by a series of experiments combined with thermal decomposition kinetics. Also, to optimize the mechanical properties of SCPB, the effect of Nano SiO2 (NS) on the related properties of SCPB is investigated. The results show that there are two main stages of the thermal decomposition of SCPB, and the kinetic models of these two stages are both reaction order models. After adding NS, the kinetic model of the second stage of thermal decomposition of SCPB is changed to random nucleation and growth model. The substances that undergo thermal decomposition reactions in the first stage are mainly hydration products such as ettringite and C-S-H, while the substances that undergo thermal decomposition reactions in the second stage are carbonates. The activation energy E and pre-exponential factor A of the first stage of thermal decomposition of SCPB with NS added are significantly improved, which indicates a more stable structure of its hydration products. The microscopic test results show that NS can promote the hydrolysis of C3S and gypsum and increase the production of hydration products, which in turn improves the strength of SCPB. In addition, the addition of NS to SCPB decreases the Ca/Si and increases the average silica chain length of C-S-H gels, while the H2O/Si decreases and the silica group increases, resulting in the enhancement of the structure of C-S-H gels

Olanzapine Reverses MK-801-Induced Cognitive Deficits and Region-Specific Alterations of NMDA Receptor Subunits

Cognitive dysfunction constitutes an essential component in schizophrenia for its early presence in the pathophysiology of the disease and close relatedness to life quality of patients. To develop effective treatment of cognitive deficits, it is important to understand their neurobiological causes and to identify potential therapeutic targets. In this study, adopting repeated MK-801 treatment as an animal model of schizophrenia, we investigated whether antipsychotic drugs, olanzapine and haloperidol, can reverse MK-801-induced cognitive deficits and how the reversal processes recruited proteins involved in glutamate neurotransmission in rat medial prefrontal cortex (mPFC) and hippocampus. We found that low-dose chronic MK-801 treatment impaired object-in-context recognition memory and reversal learning in the Morris water maze, leaving reference memory relatively unaffected, and that these cognitive deficits can be partially reversed by olanzapine, not haloperidol, treatment. At the molecular level, chronic MK-801 treatment resulted in the reduction of multiple N-methyl-D-aspartate (NMDA) receptor subunits in rat mPFC and olanzapine, not haloperidol, treatment restored the levels of GluN1 and phosphorylated GluN2B in this region. Taken together, MK-801-induced cognitive deficits may be associated with region-specific changes in NMDA receptor subunits and the reversal of specific NMDA receptor subunits may underlie the cognition-enhancing effects of olanzapine