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How to evaluate the carbon emission efficiency of multimodal transport is an important issue of public concern, and this article attempts to solve it with a network data envelopment analysis (DEA) model. DEA is a method to evaluate the efficiency of homogeneous decision-making units (DMUs). First, this article studies the efficiency decomposition and efficiency aggregation of the general network structure for DEA model. In efficiency decomposition, the relationship between system efficiency and division efficiency is discussed; whereas in efficiency aggregation, the division tendency brought about by the definition of weights is analyzed. Then, a reasonable and single compromise solution to division efficiency scores is investigated while the system efficiency remains optimal. Finally, a two-stage network DEA model of rail-water intermodal transport is established with carbon dioxide (CO2) emissions as an undesirable output. Based on this model, the rail-water intermodal transport efficiencies of 14 ports in China in 2015 are evaluated by the methods of efficiency decomposition, efficiency aggregation, and non-cooperation. The results show that Rizhao Port, Tangshan Port, Nanjing Port, and Zhuhai Port have set an example to other ports. Qinhuangdao Port, Ningbo-Zhoushan Port, Guangzhou Port, and Beiliang Port need to improve the efficiency of railway transportation. Beibu Gulf port, Zhanjiang Port, Dalian Port, Lianyungang Port, Yantai Port, and Yichang Port should optimize their intermodal system. In addition, Yantai Port and Yichang Port urgently need to improve the port efficiency in low-carbon operation. The network DEA model constructed in this article can be further applied to the efficiency evaluation of multi-link supply chains, and the empirical results can provide a reference for the efficiency evaluation of ports in China. [ABSTRACT FROM AUTHOR]

After reviewing the problems of supply disruption caused by worldwide public health events, a two-echelon dual-marketing-channel supply model is presented in this paper, whose participants are one pharmaceutical company with disruption risks, one pharmaceutical company without disruption risks (NDPC), and one pharmaceutical retailer (PR). Their marketing consists of online and offline marketing channels. The PR signs an option contract with the NDPC to secure an adaptive and continuous pharmaceutical supply. The model is divided into three sub-models: single coalition structure, double coalition structure, and multi-party coalition structure, whose coalitional strategies and profits are investigated respectively. Their optimal decisions under disruption risks also are compared, and their pharmaceutical quality and process resilience are discussed. The merit of the model is to combine option contracts, government double subsidies, and business interruption insurance in the supply chain. [ABSTRACT FROM AUTHOR]

Since December 2019, the COVID‐19 epidemic has been spreading continuously in China and many countries in the world, causing widespread concern among the whole society. To cope with the epidemic disaster, most provinces and cities in China have adopted prevention and control measures such as home isolation, blocking transportation, and extending the Spring Festival holiday, which has caused a serious impact on China's output of various sectors, international trade, and labor employment, ultimately generating great losses to the Chinese economic system in 2020. But how big is the loss? How can we assess this for a country? At present, there are few analyses based on quantitative models to answer these important questions. In the following, we describe a quantitative‐based approach of assessing the potential impact of the COVID‐19 epidemic on the economic system and the sectors taking China as the base case. The proposed approach can provide timely data and quantitative tools to support the complex decision‐making process that government agencies (and the private sector) need to manage to respond to this tragic epidemic and maintain stable economic development. Based on the available data, this article proposes a hypothetical scenario and then adopts the Computable General Equilibrium (CGE) model to calculate the comprehensive economic losses of the epidemic from the aspects of the direct shock on the output of seriously affected sectors, international trade, and labor force. The empirical results show that assuming a GDP growth rate of 4–8% in the absence of COVID‐19, GDP growth in 2020 would be ‐8.77 to ‐12.77% after the COVID‐19. Companies and activities associated with transportation and service sectors are among the most impacted, and companies and supply chains related to the manufacturing subsector lead the economic losses. Finally, according to the calculation results, the corresponding countermeasures and suggestions are put forward: disaster recovery for key sectors such as the labor force, transportation sector, and service sectors should be enhanced; disaster emergency rescue work in highly sensitive sectors should be carried out; in the long run, precise measures to strengthen the refined management of disaster risk with big data resources and means should be taken. [ABSTRACT FROM AUTHOR]

Abstract Background Trastuzumab is currently approved for the clinical treatment of breast and gastric cancer patients with HER-2 positive tumors, but not yet for the treatment of esophageal carcinoma patients, whose tumors typically show 5 ~ 35% HER-2 gene amplification and 0 ~ 56% HER-2 protein expression. This study aimed to investigate the therapeutic efficacy of Trastuzumab in patient-derived esophageal squamous cell carcinoma xenograft (PDECX) mouse models. Methods PDECX models were established by implanting patient esophageal squamous cell carcinoma (ESCC) tissues into immunodeficient (SCID/nude) mice. HER-2 gene copy number (GCN) and protein expression were determined in xenograft tissues and corresponding patient EC samples by FISH and IHC analysis. Trastuzumab anti-tumor efficacy was evaluated within these PDECX models (n = 8 animals/group). Furthermore, hotspot mutations of EGFR, K-ras, B-raf and PIK3CA genes were screened for in the PDECX models and their corresponding patient’s ESCC tissues. Similarity between the PDECX models and their corresponding patient’s ESCC tissue was confirmed by histology, morphology, HER-2 GCN and mutation. Results None of the PDECX models (or their corresponding patient’s ESCC tissues) harbored HER-2 gene amplification. IHC staining showed HER-2 positivity (IHC 2+) in 2 PDECX models and negativity in 3 PDECX models. Significant tumor regression was observed in the Trastuzumab-treated EC044 HER-2 positive model (IHC 2+). A second HER-2 positive (IHC 2+) model, EC039, harbored a known PIK3CA mutation and showed strong activation of the AKT signaling pathway and was insensitive to Trastuzumab treatment, but could be resensitised using a combination of Trastuzumab and AKT inhibitor AZD5363. In summary, we established 5 PDECX mouse models and demonstrated tumor regression in response to Trastuzumab treatment in a HER-2 IHC 2+ model, but resistance in a HER-2 IHC 2+/PIK3CA mutated model. Conclusions This study demonstrates Trastuzumab-induced tumor regressions in HER-2 positive tumors, and highlights PIK3CA mutation as a potential resistance mechanism to Trastuzumab treatment in pre-clinical patient-derived EC xenograft models.

A novel metal‐doped metal–organic framework (MOF) was developed by incorporating salen–Mg into NH2–MIL‐101(Cr) structure under ambient conditions. The Schiff base complex was successfully prepared by condensing salicylaldehyde with a free amino group and then coordinating metal ions. Such a structure can endow the sample with higher CO2 adsorption performance. At 0°C and 1 bar, the salen–Mg‐modified sample achieves the maximum adsorption capacity of 2.18 mmol g−1 for CO2, which was 5.8% higher than the pristine salen–MOF under the same conditions. Notably, the Freundlich model indicates that the CO2 adsorption process of all samples conforms to reversible adsorption. However, the correlation coefficients (R2) of the Mg‐doped sample are lower than that of the pristine sample. Besides, the CO2/N2 adsorption selectivity and isosteric heat also show a similar trend. These results indicate that the salen–Mg can enhance the interaction between the material and CO2 molecules. [ABSTRACT FROM AUTHOR]

As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co‐opetition matrices of Chinese provinces, then builds the co‐opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co‐opetition DEA cross‐efficiency model that integrates haze's feature of cross‐border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision‐making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co‐opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co‐opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results. [ABSTRACT FROM AUTHOR]

The cruise industry, which serves as a prominent exemplar of globalized business, is characterized by unique features that render its supply chain operations highly susceptible to various risk factors, thereby giving rise to significant consequences. Evaluating the risks associated with major disruptive events and enhancing the robustness of the cruise supply chain have become crucial issues of concern for various stakeholders. This study first develops an indicator evaluation system for assessing the risks of China's cruise supply chain, drawing upon relevant literature and expert interview opinions. Secondly, set pair analysis is utilized to identify the scores and trends of risk indicators in China's cruise supply chain. Thirdly, the Set pair analysis-Markov chain model is employed to forecast the future risk status of China's cruise supply chain system, and the influence of different weights on the prediction results is discussed. Finally, the risk evolution network of China's cruise supply chain is constructed to identify common risk consequences and visualize the evolution path of risk events, with the aim of providing reference for the formulation of prevention and control measures. The findings of this article have important consequences for improving risk mitigation strategies and enhancing the resilience of the cruise supply chain. [ABSTRACT FROM AUTHOR]

The transportation industry is the main source of carbon dioxide (CO 2) emissions, and the development of multimodal transport is conducive to reducing transportation carbon emissions. In order to evaluate the low carbon efficiency of multimodal transport, this article proposes a cross efficiency data envelopment analysis (DEA) method for complex network structures from the perspective of fairness, and takes China's rail-water intermodal transport as an example for research. The proposed method includes two secondary goal models that reduce the unreasonable differences between self-evaluation and peer-evaluation and treat all stages within the network system equally. Then, the improved entropy weight method is used to aggregate the cross efficiency. In addition, a numerical example is given to verify the effectiveness of the proposed method. The results of the case study show that the efficiency of Tangshan Port and Rizhao Port is relatively high, and others should learn from the successful experiences and develop improvement strategies based on their own characteristics. The conclusions can provide reference for transportation enterprise management and policy formulation, and the proposed method can be widely applied to the performance analysis of enterprise network, industrial chain, and supply chain. [Display omitted] • A novel cross efficiency DEA model is proposed. • The proposed approach includes two secondary goal models. • The low carbon efficiency of multimodal transport is evaluated. [ABSTRACT FROM AUTHOR]

As the division of work within the world economic system becomes increasingly complex, the impact of disturbing events on the economic system is expanding. Recently, Japan proposed to discharge nuclear wastewater into the Pacific Ocean, which will cause damage to marine fisheries, thereby seriously affecting fisheries and other industries in Japan and other countries and regions around the world. Considering different scenarios of final and intermediate demand shifting, this paper uses the Inoperability Input-Output Model (IIM) and Multi-Region Input-Output Model (MRIO) to simulate the economic consequences of nuclear wastewater discharge in Japan and calculate the economic changes of each industry and country (region). The results show that: In the short term, when only the final demand for Japanese fishery products decreases. (1) The ten countries (regions) with significant economic losses are Japan, the United States, Chinese Taipei, Canada, Chile, South Africa, Mexico, Peru, the United Kingdom, and Ireland. (2) The ten countries (regions) with a significant increase in total output due to demand shift are China (People's Republic of), the Rest of the World, India, Indonesia, Viet Nam, the Philippines, Brazil, Myanmar, the Russian Federation, and Malaysia. (3) A ranking of changes in the total output of different industries. In the long term, when both intermediate and final demand for Japanese fishery products decrease. (4) The change in value added in Japan. (5) The change in value added of 67 countries (regions) worldwide. The ten countries (regions) with the most significant increase in value-added are the Russian Federation, China (People's Republic of), the Rest of the World, the United States, Indonesia, Australia, Norway, Korea, Viet Nam, and Myanmar. The ten countries (regions) with the most significant decrease in value-added are Japan, Chinese Taipei, Chile, South Africa, Peru, Thailand, Mexico, Cambodia, Costa Rica, and Morocco. Changes in value added of 45 industrial sectors worldwide. • The impact of Japan's nuclear wastewater discharge on the global industrial economy was estimated. • Negative impacts of the shift of intermediate goods on the Japanese economy are more significant than that of final goods. • Economic losses of countries (regions) and industries caused by reduced demand for fishing products were ranked. • Economic growth of countries (regions) and industries driven by substitution of demand for fishing products were ranked. [ABSTRACT FROM AUTHOR]