The Legitimacy of Chinese Outward Investment in English News — A Cognitive Approach to Discursive Legitimation

Chinese Investment Oversea often face legitimacy crisis, and media plays a central role in staging legitimacy struggle. This research attempts to apply Proximization theory and the construals of Cognitive Linguistics to account for the discursive legitimation process in business discourse. The comparative analysis of two reports on a case of Chinese investment in America has shown how different discursive strategies can construe distinct conceptualizations of the same event, influencing the judgment among readership on the legitimacy of the deal. The analysis of this study shows that drawing on the construals of Cognitive Linguistics, the application of Proximization theory can be extended to legitimacy discourse in wider social domains

The Trouble with Trebles: What Violates G.S. 75-1.1?

At first glance the North Carolina Unfair and Deceptive Trade Practices Act appears to be a broad, almost unconstitutionally vague statute. Its federal counterpart, the Federal Trade Commission Act, evoked similar responses when it was first enforced. Like the FTC Act, North Carolina General Statute § 75-1.1 has taken shape through judicial interpretation and legislative modification. (North Carolina General Statutes hereinafter referred to as G.S.). As this process has proceeded over the last decade or so, many aspects of the scope and application of the statute have been determined. No general answer, however, has been given to the question of just what does violate the statute. The boundary between a simple breach of contract, rendering one liable for at most simple damages, and an unfair trade practice, rendering one liable for treble damages and attorney\u27s fees, remains ill-defined. The significance of the question is clear, both to the used car dealer and his customer arguing over an $800 automobile, and to the businessman whose$8,000,000 deal falls through. This problem is highlighted, but not illuminated, by the conflict of analytical processes between the Supreme Court of North Carolina and the U.S. Court of Appeals for the Fourth Circuit. This conflict is evidence of uncertainty in the objectives of the statute and uncertainty among the judiciary as to the basic desirability of the statutory remedy

A Correlation Information-based Spatiotemporal Network for Traffic Flow Forecasting

The technology of traffic flow forecasting plays an important role in intelligent transportation systems. Based on graph neural networks and attention mechanisms, most previous works utilize the transformer architecture to discover spatiotemporal dependencies and dynamic relationships. However, they have not considered correlation information among spatiotemporal sequences thoroughly. In this paper, based on the maximal information coefficient, we present two elaborate spatiotemporal representations, spatial correlation information (SCorr) and temporal correlation information (TCorr). Using SCorr, we propose a correlation information-based spatiotemporal network (CorrSTN) that includes a dynamic graph neural network component for integrating correlation information into spatial structure effectively and a multi-head attention component for modeling dynamic temporal dependencies accurately. Utilizing TCorr, we explore the correlation pattern among different periodic data to identify the most relevant data, and then design an efficient data selection scheme to further enhance model performance. The experimental results on the highway traffic flow (PEMS07 and PEMS08) and metro crowd flow (HZME inflow and outflow) datasets demonstrate that CorrSTN outperforms the state-of-the-art methods in terms of predictive performance. In particular, on the HZME (outflow) dataset, our model makes significant improvements compared with the ASTGNN model by 12.7%, 14.4% and 27.4% in the metrics of MAE, RMSE and MAPE, respectively.Comment: 19 pages, 13 figures, 5 table

Next-to-leading order corrections for gg→ZHgg \to ZH with top quark mass dependence

In this Letter, we present for the first time a calculation of the complete next-to-leading order corrections to the $gg \to ZH$ process. We use the method of small mass expansion to tackle the most challenging two-loop virtual amplitude, in which the top quark mass dependence is retained throughout the calculations. We show that our method provides reliable numeric results in all kinematic regions, and present phenomenological predictions for the total and differential cross sections at the Large Hadron Collider and its future upgrades. Our results are necessary ingredients towards reducing the theoretical uncertainties of the $pp \to ZH$ cross sections down to the percent-level, and provide important theoretical inputs for future precision experimental collider programs