Cooperation, Retaliation and Forgiveness in Revision Games

Revision game is a very new model formulating the real-time situation where players dynamically prepare and revise their actions in advance before a deadline when payoffs are realized. It is at the cutting edge of dynamic game theory and can be applied in many real-world scenarios, such as eBay auction, stock market, election, online games, crowdsourcing, etc. In this work, we novelly identify a class of strategies for revision games which are called Limited Retaliation strategies. An limited retaliation strategy stipulates that, (1) players first follow a recommended cooperative plan; (2) if anyone deviates from the plan, the limited retaliation player retaliates by using the defection action for a limited duration; (3) after the retaliation, the limited retaliation player returns to the cooperative plan. A limited retaliation strategy has three key features. It is cooperative, sustaining a high level of social welfare. It is vengeful, deterring the opponent from betrayal by threatening with a future retaliation. It is yet forgiving, since it resumes cooperation after a proper retaliation. The cooperativeness and vengefulness make it constitute cooperative subgame perfect equilibrium, while the forgiveness makes it tolerate occasional mistakes. limited retaliation strategies show significant advantages over Grim Trigger, which is currently the only known strategy for revision games. Besides its contribution as a new robust and welfare-optimizing equilibrium strategy, our results about limited retaliation strategy can also be used to explain how easy cooperation can happen, and why forgiveness emerges in real-world multi-agent interactions. In addition, limited retaliation strategies are simple to derive and computationally efficient, making it easy for algorithm design and implementation in many multi-agent systems

Supply network position and firm performance: evidence from Chinese listed manufacturing companies

The aim of this paper is to examine the relationship between supply network position and firm performance. A-share manufacturing companies listed from 2013 to 2015 are chosen as the initial samples, and large sample supply networks are constructed with relational embeddedness and structural embeddedness. The location of supply network is depicted by network centrality and structural hole with social network analysis, and the influence of supply network position on the corporate performance is examined with multiple OLS regression analysis. This paper observes that a firms’ supply network position is an important factor affecting its performance. The higher the network centrality is, the richer the structural holes are, and the worse the company’s performance is. The results suggest that firms that have a high level of centrality or rich structural holes in their supply networks will gain limited information, resource and control benefits and face great business risks that may negatively influence their performance

Scenario Analyses of Land Use Conversion in the North China Plain: An Econometric Approach

Scenario analysis and dynamic prediction of land use structure which involve many driving factors are helpful to investigate the mechanism of land use changes and even to optimize land use allocation for sustainable development. In this study, land use structure changes during 1988–2010 in North China Plain were discerned and the effects of various natural and socioeconomic driving factors on land use structure changes were quantitatively analyzed based on an econometric model. The key drivers of land use structure changes in the model are county-level net returns of land resource. In this research, we modified the net returns of each land use type for three scenarios, including business as usual (BAU) scenario, rapid economic growth (REG) scenario, and coordinated environmental sustainability (CES) scenario. The simulation results showed that, under different scenarios, future land use structures were different due to the competition among various land use types. The land use structure changes in North China Plain in the 40-year future will experience a transfer from cultivated land to built-up area, an increase of forestry, and decrease of grassland. The research will provide some significant references for land use management and planning in the study area

Pengetahuan, kemahiran dan amalan guru membina item kemahiran berfikir aras tinggi (KBAT) dalam instrumen pentaksiran pembelajaran

Kajian ini dijalankan bagi mengenal pasti tahap pengetahuan, kemahiran dan amalan guru membina item kemahiran berfikir aras tinggi (KBAT) dalam instrumen pentaksiran pembelajaran. Kajian ini juga melihat perbezaan tahap pengetahuan, kemahiran dan amalan guru membina item KBAT berdasarkan kepada kumpulan guru mengajar matapelajaran tingkatan 3 dan kumpulan guru mengajar matapelajaran tingkatan 5. Sebanyak enam persoalan kajian telah dibangunkan bagi mengkaji permasalahan kajian. Rekabentuk kajian ini melibatkan analisis deskriptif dan inferensi dalam bentuk tinjauan yang melibatkan data kuantitatif dengan menggunakan borang soal selidik berskala likert lima mata sebagai instrumen kajian. Seramai 161 sampel guru daripada 3 buah sekolah di daerah Muar, Johor terpilih menjadi responden dalam kajian ini. Model Pengukuran Rasch telah digunakan bagi menentukan kesahan dan kebolehpercayaan instrumen kajian yang telah dibina sendiri. Hasil analisis kajian menunjukkan tahap pengetahuan, kemahiran dan amalan guru membina item KBAT adalah berada pada tahap tinggi. Dapatan kajian juga menunjukkan tidak terdapat perbezaan yang signifikan di antara kumpulan guru mengajar matapelajaran tingkatan 3 dan kumpulan guru mengajar matapelajaran tingkatan 5 terhadap tahap pengetahuan, kemahiran dan amalan membina item KBAT. Hasil kajian ini dapat dijadikan sebagai satu garis panduan kepada guru-guru yang mengubal item pentaksiran dan program peningkatan profesionalisme guru di sekolah. Kajian lanjutan juga boleh dilaksanakan bagi memperbaiki kekurangan dalam kajian ini

Seasonal and Interannual Variation in Energy Balance in the Semiarid Grassland Area of China

Near surface energy budget changes have been proved to be induced by the land cover conversion through changing the surface physical properties, which can further impact the regional climate change. This study applies the DLS model to simulate the land cover under the business as usual (BAU) scenario and then analyses the seasonal and interannual variation of energy balance in the semiarid grassland area of China based on the simulated land cover with the Weather Research and Forecasting (WRF) model. The results indicate that the grassland will show a growing trend under the BAU scenario. Downward long wave radiation and downward short wave radiation will all have small-scale increase with time going by, while the surface net radiation will decrease from 2030 to 2050. However, there is obvious seasonal variation. Summer has the highest downward long wave radiation and downward short wave radiation, followed by spring and autumn. The lowest are in winter. As for the net surface radiation, there is obvious decrease in southeast of study area due to returning cropland to grassland. Those research conclusions can offer valuable information for the land use planning and relieving the effects of land cover change on climate change at the semiarid grassland area

Land Cover Mapping Based on Multisource Spatial Data Mining Approach for Climate Simulation: A Case Study in the Farming-Pastoral Ecotone of North China

The land use and land cover change (LUCC) is one of the prime driving forces of climate change. Most attention has been paid to the influence of accuracy of the land cover data in numerous climate simulation projects. The accuracy of the temporal land use data from Chinese Academy of Sciences (CAS) is higher than 90%, but the high-precision land cover data is absent. We overlaid land cover maps from different sources, and the grids with consistent classification were selected as the sample grids. By comparing the results obtained with different decision tree classifiers with the WEKA toolkit for data mining, it was found that the C4.5 algorithm was more suitable for converting land use data of CAS classification to land cover data of IGBP classification. We reset the decision rules with Net Primary Productivity (NPP) and Normalized Difference Vegetation Index (NDVI) as the indicators. The accuracy of the reclassified land cover data was proven to reach 83.14% through comparing with the Terrestrial Ecosystem Monitoring Sites and high resolution images. Therefore, it is feasible to produce the temporal land cover data with this method, which can be used as the parameters of dynamical downscaling in the regional climate simulation

Impacts of Cultivated Land Reclamation on the Climate and Grain Production in Northeast China in the Future 30 Years

China, as a large agricultural country as well as a major country with great demand for grain, has played a more and more important role in the international grain market. As Northeast China is one of the major commodity grain bases in China as well as one of the regions with the highest intensity of human activities, it plays an important role in influencing the global food security. This study first generally analyzed the cultivated land reclamation and the climate change of temperature and precipitation in Northeast China during 2000–2010. Then, on the basis of these data, the climatic effects of cultivated land reclamation in Northeast China during 2030–2040 were simulated by the weather research forecast (WRF) model. Finally, the possible effects of the climate change on the grain yield and the potential influence on the food security were analyzed. The simulation result indicated that the temperature in Northeast China would be increasing on the whole, while the precipitation would be decreasing. The result of this study can provide some theoretical support to the agricultural economic development in Northeast China and serve the national macropolicy and food security strategy of the whole China

Monitoring Prevalence and Persistence of Environmental Contamination by SARS-CoV-2 RNA in a Makeshift Hospital for Asymptomatic and Very Mild COVID-19 Patients

Objective: To investigate the details of environmental contamination status by SARS-CoV-2 in a makeshift COVID-19 hospital.Methods: Environmental samples were collected from a makeshift hospital. The extent of contamination was assessed by quantitative reverse transcription polymerase chain reaction (RT-qPCR) for SARS-CoV-2 RNA from various samples.Results: There was a wide range of total collected samples contaminated with SARS-CoV-2 RNA, ranging from 8.47% to 100%. Results revealed that 70.00% of sewage from the bathroom and 48.19% of air samples were positive. The highest rate of contamination was found from the no-touch surfaces (73.07%) and the lowest from frequently touched surfaces (33.40%). The most contaminated objects were the top surfaces of patient cubic partitions (100%). The median Ct values among strongly positive samples were 33.38 (IQR, 31.69–35.07) and 33.24 (IQR, 31.33–34.34) for ORF1ab and N genes, respectively. SARS-CoV-2 relic RNA can be detected on indoor surfaces for up to 20 days.Conclusion: The findings show a higher prevalence and persistence in detecting the presence of SARS-CoV-2 in the makeshift COVID-19 hospital setting. The contamination mode of droplet deposition may be more common than contaminated touches