Continuous Cluster Expansion for Field Theories

A new version of the cluster expansion is proposed without breaking the translation and rotation invariance. As an application of this technique, we construct the connected Schwinger functions of the regularized $\phi^4$ theory in a continuous way

Evaluation of Governance Risk in Industry-University-Research Collaborative Innovation Project: Based on BP Neural Networks

Funding: This research was funded by [Projects of the National Social Science Foundation of China] grant number [18BGL020] Abstract Effective evaluation of project governance risks is of great significance to the successful implementation of industry-university-research collaborative innovation project. By introducing the idea of project governance into risk management in industry-university-research collaborative innovation project, this paper analyzes governance risk sources from four aspects, based on the project characteristics, which include the background of participators, organizational structure, project objectives and the relationship of the main participators from the view of project governance. The governance risks are categorized as structure risk, morality risk and behavior risk. The evaluation system of governance risk in Industry-University-Research collaborative innovation project is established. The BP neural network model is applied to assess risk and the MATLAB is used to process data according to the features of project governance risk and theory analysis. Finally, the model is checked by empirical test. This model solves the problem that the risks are difficult to quantify. Scientific nature of the feasibility of the evaluation is improved by the model. At the same time, not only the research field of project governance risk but also risk research of industry-university-research collaborative innovation project is extended. Keywords: industry-university-research, collaborative innovation, project governance risk, risk origin, BP neural network

Synthesis, crystal structure of and DFT calculations on bisglycinato-bis[p-(hydroxymethyl)pyridine]nickel(II)

The main aim of this study was to investigate the relationship between mIn tA new Ni(II) complex of bisglycinato-bis[p-(hydroxylmethyl)py-ridine] was synthesized and characterized by elemental analysis, IR, UV–Vis spectroscopy and X-ray single crystal diffraction analysis. The thermal stability of the title complex was also determined. The complex adopts a distorted octahedral geometry and possesses inversion symmetry with the Ni(II) ion as the center of inversion. Density function theory (DFT) calculations of the structure, electronic absorption spectra, electron structure and natural population analysis (NPA) at the B3LYP/LANL2DZ level of theory were performed. The predicted geometric parameters and electronic spectra were compared with the experimental values and they supported each other. The NPA results indicate that the electronic transitions were mainly derived from the contribution of an intra-ligand (IL) transition, a ligand-to-metal charge transfer (LMCT) transition and a d-d transition. The electron structure calculations suggest that the central Ni(II) ion uses its 4s and 3d orbitals to form covalent bonds with coordinated N and O atoms. The calculated bond orders are also consistent with the thermal decomposition results. Based on vibrational analysis, the thermodynamic properties of the title complex were predicted and the correlative equations between these thermodynamic properties and temperature are also reported

Disentangling the Relationship between Portfolio Homogenization and Transaction of Non-fungible Tokens

There has been an explosion in the popularity of Non-Fungible Tokens (NFTs), drawing attention from practitioners and scholars alike since 2021. Each NFT denotes a digital asset in the likes of an artwork, a tweet, or a video that is recorded on the blockchain with a unique identifying code. In turn, the emergence of NFTs has transformed the digital asset landscape. With the rapid growth of the NFT market, there is a concern that the market is becoming increasingly homogenized due to readily available blockchain technologies and relatively low costs of NFT mints. To this end, this study attempts to elucidate how NFT portfolio homogenization affects transaction volume and variation in the marketplace. Particularly, we collected and analyzed a dataset of 2,004 collections comprising 7,151,515 NFTs from OpenSea, a leading NFT platform. We discovered significant inverted U-shaped relationships between NFT portfolio homogenization and transaction variation and transaction volume

Pay It Forward: Unraveling the Role of Cause-related Marketing in the Curvilinear Relationship between Price-oriented Function Usage and Consumer Satisfaction

Price-oriented functions have been prevalently used by sellers for attracting consumers on e-marketplace platforms. However, existing literature has mixed understandings about its influence on improving consumer satisfaction. Besides, few studies have considered how cause-related marketing moderates the impact of price-oriented function usage. Therefore, this paper firstly explores the curvilinear relationship between price-oriented function usage and consumer satisfaction by adopting the repertoire perspective, then further considers the moderating role of cause-related marketing. This study collected data on 29,506 products from one e-marketplace platform in China. By using fixed-effects regression models, it is found that price-oriented function usage (i.e., volume and heterogeneity) have inverted U-shaped relationships with consumer satisfaction. In addition, cause-related marketing weakens the impact of price-oriented function usage heterogeneity on consumer satisfaction. This study contributes to research about platform function usage and guides sellers in terms of using those functions to stimulate consumer satisfaction