The causes of internal habit formation among Chinese urban residents: a multi-layer model perspective

Economic growth faces serious challenges due to the COVID-19 pandemic. To promote swift economic recovery, the focus has turned to consumption’s role as a driver of economic growth. To explore the influence of external social environment variables on internal habits, this study improves Naik and Moore’s consumption model and constructs a multi-layer statistical model with habit-forming effects. The study shows, first, that internal habit effects are significantly present in all types of the population’s consumption expenditures, and there are significant crossregional differences. Second, we find significant moderating effects of inclusive digital finance, education levels, income disparities, and regional economic differences on internal habit formation. Furthermore, the internal habit effect is more influenced by inclusive digital finance and income disparity and less by education and regional economic disparity. Finally, the study proposes policy recommendations for building an inclusive digital financial services infrastructure, improving access to education, reducing income disparities, and balancing regional development. To a certain extent, this study reveals the intrinsic link between the external consumption environment and internal habit effects, providing a new perspective for the government’s use in formulating consumption policies that promote economic growth

A Synergetic Pattern Matching Method Based-on DHT Structure for Intrusion Detection in Large-scale Network

AbstractResearch in network security, with the attacks becoming more frequent, increasing complexity means, for the large-scale network intrusion detection, this paper presents a warning by analyzing the behavior of the log, the contents of the relevant association, through the DHT(Distributed Hash Table) distributed architecture, the Collabarative matching, fusion, and ultimately determine the method of attack paths. First, by improving the classical Apriori algorithm, greatly improving the efficiency of the association. At the same time, through the behavior pattern matching algorithms to extract information about the behavior of the alert and the behavior sequence elements to match the template, and through the right path to finally determine the value of the threat of the network path. After the design of a DHT network, the distributed collaborative match the path used to find complex network attacks. Finally, the overall algorithm flow, proposed a complete threat detection system architecture

Effects of ABT on the morphogenesis and inclusions of Taxus chinensis (Pilger) Rehd f. baokangsis cutting rooting

This study aims to explore the cutting propagation method of a novel variant on Taxus chinensis (Pilger) Rehd f. baokangsis (T. chinensis baokangsis). Different types of rooting powder and different concentrations were used to treat the cuttage seedlings of T. chinensis baokangsis, and then the external morphology and anatomical morphology of the roots were observed. The membership function evaluation method was used to evaluate the cutting effect. The physiological characteristics of T. chinensis baokangsis cuttings were studied by the correlation analysis of nutrient components and endogenous hormone content. The results showed that the T. chinensis baokangsis belonged to callus rooting type, and the adventitious roots differentiated at about 150 d. For rooting growth indexes, the optimal treatment was ABT-1+400 mg/L. The rooting rate of T. chinensis baokangsis was positively correlated with the content of soluble sugar, soluble starch, and IAA, while extremely significantly negatively correlated with MDA (P <0.01). Moreover, the rooting rate also was negatively correlated with ABA, ZR, and GA3, and significantly negatively correlated with GA3 (P <0.05). This study will provide some technical support and theoretical basis for the conservation and reproduction of T. chinensis baokangsis

Joint Optimization of Active and Passive Beamforming in Multi-IRS Aided mmWave Communications

Intelligent reflecting surface (IRS) has been considered as a promising technology to alleviate the blockage effect and enhance coverage in millimeter wave (mmWave) communication. To explore the impact of IRS on the performance of mmWave communication, we investigate a multi-IRS assisted mmWave communication network and formulate a sum rate maximization problem by jointly optimizing the active and passive beamforming and the set of IRSs for assistance. The optimization problem is intractable due to the lack of convexity of the objective function and the binary nature of the IRS selection variables. To tackle the complex non-convex problem, an alternating iterative approach is proposed. In particular, utilizing the fractional programming method to optimize the active and passive beamforming and the optimization of IRS selection is solved by enumerating. Simulation results demonstrate the performance gain of our proposed approach.Comment: 6 pages, 4 figures, accepted by IEEE GLOBECOM 202