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As the Western world’s policy towards China has been changing in recent years, the international public opinion, that China comes into contact with, is also deteriorating, which has a serious negative impact on forming the international image of China and on shaping soft power. In the context of the rapid development of modern information technology, sports events like the Winter Olympics are often accompanied by large-scale media coverage and propaganda, and it is important to deal with the negative coverage of the Olympics involving China in the Western media and to build a good national image through the Winter Olympics. This study focuses on the specific content of Western media reports on China during the 2022 Beijing Winter Olympics cycle, and summarizes and analyzes the characteristics of “distorted facts”, “far-fetched” and “prominent political demands” in the negative reports on China in the Western media during the Winter Olympics. Based on the importance of guiding international public opinion and covering by media of such large sporting events as the Olympic Games, it is urgent and necessary to improve China’s international public opinion crisis response mechanism and enhance national and international media capacity. In this regard, this paper proposes four specific response strategies: strengthening the international communication capacity of mainstream media, enhancing the role of the government in guiding and making decisions, strengthening cooperation with international media; and making full use of our own media platforms.

A New Concept to Study Substitute Structures in Economics and Operations Models In "S-Convexity and Gross Substitutability," Chen and Li propose a novel concept of S-convex functions defined on continuous spaces, which extends a key concept of M-natural-convex functions in discrete convex analysis. They develop a host of fundamental properties and characterizations of S-convex functions. In a parametric maximization model with a box constraint, they show that the set of optimal solutions is nonincreasing in the parameters if the objective function is S-concave and prove the necessity of S-concavity under some conditions. The monotonicity result finds notable inventory models. Interestingly, the authors show that S-concavity is the correct notion characterizing gross substitutability, an important concept in economics for markets with divisible goods. We propose a new concept of S-convex functions (and its variant, semistrictly quasi-S- (SSQS)-convex functions) to study substitute structures in economics and operations models with continuous variables. We develop a host of fundamental properties and characterizations of S-convex functions, including various preservation properties, conjugate relationships with submodular and convex functions, and characterizations using Hessians. For a divisible market, we show that the utility function satisfies gross substitutability if and only if it is S-concave under mild regularity conditions. In a parametric maximization model with a box constraint, we show that the set of optimal solutions is nonincreasing in the parameters if the objective function is (SSQS-) S-concave. Furthermore, we prove that S-convexity is necessary for the property of nonincreasing optimal solutions under some conditions. Our monotonicity result is applied to analyze two notable inventory models: a single-product inventory model with multiple unreliable suppliers and a classic multiproduct dynamic inventory model with lost sales. Funding: This work was supported by the National Science Foundation [Grants CMMI-1538451 and CMMI-1635160] and the gift fund from JD.com. Supplemental Material: The online companion is available at https://doi.org/10.1287/opre.2022.2394. [ABSTRACT FROM AUTHOR]

The accurate prediction of adverse drug reactions (ADRs) is essential for comprehensive drug safety evaluation. Pre-trained deep chemical language models have emerged as powerful tools capable of automatically learning molecular structural features from large-scale datasets, showing promising capabilities for the downstream prediction of molecular properties. However, the performance of pre-trained chemical language models in predicting ADRs, especially idiosyncratic ADRs induced by marketed drugs, remains largely unexplored. In this study, we propose MoLFormer-XL, a pre-trained model for encoding molecular features from canonical SMILES, in conjunction with a CNN-based model to predict drug-induced QT interval prolongation (DIQT), drug-induced teratogenicity (DIT), and drug-induced rhabdomyolysis (DIR). Our results demonstrate that the proposed model outperforms conventional models applied in previous studies for predicting DIQT, DIT, and DIR. Notably, an analysis of the learned linear attention maps highlights amines, alcohol, ethers, and aromatic halogen compounds as strongly associated with the three types of ADRs. These findings hold promise for enhancing drug discovery pipelines and reducing the drug attrition rate due to safety concerns. [ABSTRACT FROM AUTHOR]

[Objectives] The sortie generation capacity is an important index of the operational capability of an aircraft carrier and largely determined by the support operation scheduling of the carrier-based aircraft. Therefore a good scheduling of carrier-based aircrafts on the deck can effectively improve the operational capability of aircraft carrier. [Methods] This paper establishes the operation scheduling module by converting the carrier-based aircraft support operation scheduling into job-shop scheduling problem. And through improvement of initial solution, search strategy and tabu list length, an improved tabu search algorithm is proposed to solve the model, with the purpose of minimizing the makespan. [Results] The simulation test results show that the improved tabu search algorithm can solve the carrier-based aircraft support operation scheduling problem effectively, and it is better than the traditional tabu search algorithm in terms of speed calculation and result optimization. [Conclusions] The proposed algorithm provides an effective way to solve the carrier-based aircraft support operation scheduling problem.

A generic way to verify asymptotic optimality of semi-open-loop policies for a wide class of MDPs with large lead times. In many real-life inventory models, order lead times can result in uncertain effects of inventory decisions. However, as the lead time grows large, one would naturally postulate that the effect of the delayed order depends weakly on the current inventory level and, thus, intuit that decoupling the delayed order with the current inventory level may provide good heuristics. Motivated by these examples, in "Asymptotic Optimality of Semi-open-Loop Policies in Markov Decision Processes with Large Lead Times," Bai et al. consider a generic Markov decision process (MDP) with one delayed control and one immediate control. For MDPs defined on general spaces with uniformly bounded cost functions and a fast mixing property, they construct a periodic semi-open-loop policy for each lead time value and show that these policies are asymptotically optimal as the lead time goes to infinity. For MDPs defined on Euclidean spaces with linear dynamics and convex structures, they impose another set of conditions under which constant delayed-control policies are asymptotically optimal. We consider a generic Markov decision process (MDP) with two controls: one control taking effect immediately and the other control whose effect is delayed by a positive lead time. As the lead time grows, one naturally expects that the effect of the delayed action only weakly depends on the current state, and decoupling the delayed action from the current state could provide good controls. The purpose of this paper is to substantiate this decoupling intuition by establishing asymptotic optimality of semi-open-loop policies, which specify open-loop controls for the delayed action and closed-loop controls for the immediate action. For MDPs defined on general spaces with uniformly bounded cost functions and a fast mixing property, we construct a periodic semi-open-loop policy for each lead time value and show that these policies are asymptotically optimal as the lead time goes to infinity. For MDPs defined on Euclidean spaces with linear dynamics and convex structures (convex cost functions and constraint sets), we impose another set of conditions under which semi-open-loop policies (actually, constant delayed-control policies) are asymptotically optimal. Moreover, we verify that these conditions hold for a broad class of inventory models, in which there are multiple controls with nonidentical lead times. Funding: Research of the first three authors was partly supported by the National Science Foundation [Grant CMMI-1635160]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2021.0088. [ABSTRACT FROM AUTHOR]