A Journey into the City. Migrant Workers' Relation with the Urban Space and Struggle for Existence in Xu Zechen's Early Jingpiao Fiction

In contemporary China, rural-urban migrants constitute a new urban subject with entirely new identity-related issues. This study aims at demonstrating how literature can be a valid field in investigating such evolving subjectivities, through an analysis of Xu Zechen’s early novellas depicting migrants’ vicissitudes in Beijing. Combining a close reading of the texts and a review of the main social problems characterising rural-urban migration in China, this paper focuses on the representation of the identity crisis within the migrant self in Xu’s stories, taking into account the network of meanings employed by the writer to signify the objective and subjective tension between the city and the countryside

Optimization of energy storage assisted peak regulation parameters based on PSS/E

The development and utilization of new energy is one of the biggest issues facing mankind. With the rapid development of new energy, its proportion in the power system is getting higher and higher, which will inevitably lead to the increase of the peak–valley difference of the power grid, resulting in a series of stability problems. The connection of energy storage devices to the power grid can not only effectively utilize the power equipment, reduce the power supply cost, but also promote the application of new energy, improve the stability of the system operation, reduce the peak–valley difference of the power grid, and play an important role in the power system. In this paper, the simulation is carried out in PSS/E, and the excitation model and energy storage model are established based on the user-defined function of PSS/E. The particle swarm optimization algorithm is used to optimize the parameters of the excitation system and the energy storage control system, and the performance difference of peak regulation before and after adding the energy storage model and parameter optimization is simulated and compared. Through simulation, the correctness of the user-defined model of excitation and energy storage and the feasibility and superiority of energy storage participating in peak regulation are verified

Double-Level Energy Absorption of 3D Printed TPMS Cellular Structures via Wall Thickness Gradient Design

This paper investigates the deformation mechanism and energy absorption behaviour of 316 L triply periodic minimal surface (TPMS) structures with uniform and graded wall thicknesses fabricated by the selective laser melting technique. The uniform P-surface TPMS structure presents a single-level stress plateau for energy absorption and a localized diagonal shear cell failure. A graded strategy was employed to break such localized geometrical deformation to improve the overall energy absorption and to provide a double-level function. Two segments with different wall thicknesses separated by a barrier layer were designed along the compression direction while keeping the same relative density as the uniform structure. The results show that the crushing of the cells of the graded P-surface TPMS structure occurs first within the thin segment and then propagates to the thick segment. The stress–strain response shows apparent double stress plateaus. The stress level and length of each plateau can be adjusted by changing the wall thickness and position of the barrier layer between the two segments. The total energy absorption of the gradient TPMS structure was also found slightly higher than that of the uniform TPMS counterparts. The gradient design of TPMS structures may find applications where the energy absorption requires a double-level feature or a warning function

APPLICATION OF SURFACE MODIFICATION IN BIOMEDICAL MATERIALS RESEARCH

In this paper, the applications and qualifications of biomedical materials are introduced. In regard to the hard tissue implants, the biocompatibility can be improved by preparing various bio-ceramic and bio-glass coatings. In view of this, the principles, characteristics, and applications of surface modification (plasma spraying, electrostatic spray deposition, micro-arc oxidation, pulsed laser deposition, sol–gel deposition, and magnetron sputtering) in biomedical materials are reviewed. In addition, the research direction of improving biocompatibility by surface modification is presented.Biomedical materials, biocompatibility, surface modification

Analyzing congestion surplus distribution based on social welfare optimization

The distribution of congestion surplus affects not only the short-term economic interests of stakeholders in the power spot market, but the improvement of social welfare in the long run. At present, the congestion surplus in mature electricity spot markets of developed countries is usually returned to the power users or power generation enterprises according to established proportions. Although this method helps achieve rational distribution of congestion surplus, it does not offer a solution to the congestion problem and cannot achieve maximized social welfare. In light of the principles of welfare economics, we propose in this paper injecting the congestion surplus into the capital pool of the power grid as a transmission line expansion fund to fundamentally solve the power transmission congestion problem. Modeling results and case studies presented in our work verified that our proposed distribution model could achieve Pareto optimization. Finally, combining the power transmission and distribution (PTD) pricing and supervision method, this paper puts forward the method for use and supervision of congestion surplus on the power spot market to reach optimal allocation of resources

Event-Sensitive Network: A Construction Algorithm of Agricultural Sensor Network Driven by Environmental Change

In a wireless sensor network, the sensor nodes transmit the acquired information to the server through the data transmission link. On the serverside, the data are processed, fused, and expressed to serve the user. Sensor deployment is a key factor related to the stability and security of wireless networks. This article uses environmental changes to drive related technologies to deploy wireless sensors. In this article, environmental change-driven means that through certain deployment cost model assumptions and problem descriptions, network deployment is artificially divided into two stages: initial deployment and redeployment. In the deployment phase, by referring to the idea of virtual force, a new sensor deployment algorithm is proposed in the redeployment phase, which can well solve the stability- and security-related issues encountered in agricultural wireless sensor networks. In this algorithm, the moving distance of the mobile receiver and the average coverage of the network are calculated based on the virtual force, the direction, and the number of adjacent clusters. Finally, the algorithm model was simulated in MATLAB, and the feasibility of the algorithm was verified by analyzing the event coverage and the moving distance of nodes. The final simulation results show that the algorithm proposed in this paper can achieve better performance than existing algorithms in terms of average coverage and moving distance

Research and Verification of Convolutional Neural Network Lightweight in BCI

With the increasing of depth and complexity of the convolutional neural network, parameter dimensionality and volume of computing have greatly restricted its applications. Based on the SqueezeNet network structure, this study introduces a block convolution and uses channel shuffle between blocks to alleviate the information jam. The method is aimed at reducing the dimensionality of parameters of in an original network structure and improving the efficiency of network operation. The verification performance of the ORL dataset shows that the classification accuracy and convergence efficiency are not reduced or even slightly improved when the network parameters are reduced, which supports the validity of block convolution in structure lightweight. Moreover, using a classic CIFAR-10 dataset, this network decreases parameter dimensionality while accelerating computational processing, with excellent convergence stability and efficiency when the network accuracy is only reduced by 1.3%

Energy absorption of gradient triply periodic minimal surface structure manufactured by stereolithography

Triply periodic minimal surface (TPMS) metamaterials possess exceptional properties not commonly found in natural materials. TPMS metamaterials are used in lightweight structures and impact energy absorption structures due to their surface geometry and mechanical properties. The quasi-static mechanic properties of resin-based homogeneous and gradient TPMS structures manufactured by stereolithography are investigated in this study. The results of both experimental and numerical simulations reveal that the gradient TPMS structures have superior energy absorption abilities compared to the homogeneous TPMS structures. Furthermore, the benefits of gradient TPMS structures can be further enhanced by changing the gradient variation interval of the relative density and cell thickness of TPMS. If the slope and intercept of the C value function of the TPMS structures remain constant, selecting a design where the gradient direction of the cell aligns with the direction of the load on the material can enhance the energy absorption capability of the TPMS structures

Identification of urinary volatile organic compounds as a potential non-invasive biomarker for esophageal cancer

Abstract Early diagnosis of esophageal cancer (EC) is extremely challenging. The study presented herein aimed to assess whether urinary volatile organic compounds (VOCs) may be emerging diagnostic biomarkers for EC. Urine samples were collected from EC patients and healthy controls (HCs). Gas chromatography-ion mobility spectrometry (GC-IMS) was next utilised for volatile organic compound detection and predictive models were constructed using machine learning algorithms. ROC curve analysis indicated that an 8-VOCs based machine learning model could aid the diagnosis of EC, with the Random Forests having a maximum AUC of 0.874 and sensitivities and specificities of 84.2% and 90.6%, respectively. Urine VOC analysis aids in the diagnosis of EC