Using an Improved SWAT Model to Simulate Karst Sinkholes: A Case Study in Southwest China

Hydrological simulation of the karst area is significant for assessing water resources accurately and exploring the relationship in the hydrologic cycle. However, the existence of sinkholes causes the spatial heterogeneity of aquifers and changes the distribution of surface water as well as groundwater, which makes the traditional hydrogeological model difficult to quantitatively characterize the hydrological processes of the sinkhole. Hence, improving the hydrological model for the karst area is a necessary direction at present. The soil and water assessment tool (SWAT) is one of the most widely used semi-distributed hydrological models right now in the world. In this study, we focused on the upper course of the South Panjiang River and used the pond module of the SWAT model to simulate karst sinkholes, modifying the source code to realize the rapid response to the recharge in karst sinkholes. After the improvement, the surface runoff, especially the peak value of the Xiqiao Hydrological Station at the outlet, has been reduced, while the baseflow of modified subbasins has been increased and the water yield is under a state of water balance. In addition, the model evaluation factor R2 was strengthened from 0.76 to 0.83 and NSE was strengthened from 0.66 to 0.79 of the Xiqiao Hydrological Station during the validation period. The improved model was used to analyze the spatial distribution of hydrological components. Also, it was found there are spatial relations between runoff modulus–slope and baseflow–surface runoff–land use types. The analysis demonstrated that the improved SWAT model could effectively change the hydrological components and simulate the rapid replenishment of karst sinkholes

Transcriptome profiling by RNA-Seq reveals differentially expressed genes related to fruit development and ripening characteristics in strawberries (Fragaria × ananassa)

Strawberry (Fragaria × ananassa) is an ideal plant for fruit development and ripening research due to the rapid substantial changes in fruit color, aroma, taste, and softening. To gain deeper insights into the genes that play a central regulatory role in strawberry fruit development and ripening characteristics, transcriptome profiling was performed for the large green fruit, white fruit, turning fruit, and red fruit stages of strawberry. A total of 6,608 differentially expressed genes (DEGs) with 2,643 up-regulated and 3,965 down-regulated genes were identified in the fruit development and ripening process. The DEGs related to fruit flavonoid biosynthesis, starch and sucrose biosynthesis, the citrate cycle, and cell-wall modification enzymes played important roles in the fruit development and ripening process. Particularly, some candidate genes related to the ubiquitin mediated proteolysis pathway and MADS-box were confirmed to be involved in fruit development and ripening according to their possible regulatory functions. A total of five ubiquitin-conjugating enzymes and 10 MADS-box transcription factors were differentially expressed between the four fruit ripening stages. The expression levels of DEGs relating to color, aroma, taste, and softening of fruit were confirmed by quantitative real-time polymerase chain reaction. Our study provides important insights into the complicated regulatory mechanism underlying the fruit ripening characteristics in Fragaria × ananassa

A Sensor-Based Visual Effect Evaluation of Chevron Alignment Signs’ Colors on Drivers through the Curves in Snow and Ice Environment

The ability to quantitatively evaluate the visual feedback of drivers has been considered as the primary research for reducing crashes in snow and ice environments. Different colored Chevron alignment signs cause diverse visual effect. However, the effect of Chevrons on visual feedback and on the driving reaction while navigating curves in SI environments has not been adequately evaluated. The objective of this study is twofold: (1) an effective and long-term experiment was designed and developed to test the effect of colored Chevrons on drivers’ vision and vehicle speed; (2) a new quantitative effect evaluation model is employed to measure the effect of different colors of the Chevrons. Fixation duration and pupil size were used to describe the driver’s visual response, and Cohen’s d was used to evaluate the colors’ psychological effect on drivers. The results showed the following: (1) after choosing the proper color for Chevrons, drivers reduced the speed of the vehicle while approaching the curves. (2) It was easier for drivers to identify the road alignment after setting the Chevrons. (3) Cohen’s d related to different colors of Chevrons have different effect sizes. The conclusions provide evident references for freeway warning products and the design of intelligent vehicles

Redefining cardiac biomarkers in predicting mortality and adverse outcomes of inpatients with COVID-19

The prognostic power of circulating cardiac biomarkers, their utility and pattern of release in coronavirus disease 2019 (COVID-19) patients have not been clearly defined. In this multi-centered retrospective study, we enrolled 3,219 patients with diagnosed COVID-19 admitted to 9 hospitals from December 31, 2019 to March 4, 2020, to estimate the associations and prognostic power of circulating cardiac injury markers with the poor outcomes of COVID-19. In the mixed-effect Cox model, after adjusting for age, gender and comorbidities, the adjusted hazard ratios of 28-day mortality for high-sensitivity cardiac troponin I (hs-cTnI) was 7.12 (95%CI, 4.60-11.03; P<0.001), NT-proB-type natriuretic peptide (NT-proBNP) was 5.11 (95%CI, 3.50-7.47; P<0.001), CK-MB was 4.86 (95%CI, 3.33-7.09; P<0.001), myoglobin was 4.50 (95%CI, 3.18-6.36; P < 0.001), and CK was 3.56 (95%CI, 2.53-5.02; P < 0.001). The cutoffs of those cardiac biomarkers for effective prognosis of 28-day mortality of COVID-19 were found to be much lower than for regular heart disease at about 49% of the currently recommended thresholds. Patients with elevated cardiac injury markers above the newly established cutoffs were associated with significantly increased risk of COVID-19 death. In conclusion, cardiac biomarker elevations are significantly associated with 28-day death in patients with COVID-19. The prognostic cutoffs for of these values might be much lower than the current reference standards. These findings can assist better management of COVID-19 patients to improve outcomes. Importantly, the newly established cutoff levels of COVID-19 associated cardiac biomarkers may serve as useful criteria for the future prospective studies and clinical trials

Redefining Cardiac Biomarkers in Predicting Mortality of Inpatients With COVID-19

The prognostic power of circulating cardiac biomarkers, their utility, and pattern of release in coronavirus disease 2019 (COVID-19) patients have not been clearly defined. In this multicentered retrospective study, we enrolled 3219 patients with diagnosed COVID-19 admitted to 9 hospitals from December 31, 2019 to March 4, 2020, to estimate the associations and prognostic power of circulating cardiac injury markers with the poor outcomes of COVID-19. In the mixed-effects Cox model, after adjusting for age, sex, and comorbidities, the adjusted hazard ratio of 28-day mortality for hs-cTnI (high-sensitivity cardiac troponin I) was 7.12 ([95% CI, 4.60-11.03] P\u3c0.001), (NT-pro)BNP (N-terminal pro-B-type natriuretic peptide or brain natriuretic peptide) was 5.11 ([95% CI, 3.50-7.47] P\u3c0.001), CK (creatine phosphokinase)-MB was 4.86 ([95% CI, 3.33-7.09] P\u3c0.001), MYO (myoglobin) was 4.50 ([95% CI, 3.18-6.36] P\u3c0.001), and CK was 3.56 ([95% CI, 2.53-5.02] P\u3c0.001). The cutoffs of those cardiac biomarkers for effective prognosis of 28-day mortality of COVID-19 were found to be much lower than for regular heart disease at about 19%-50% of the currently recommended thresholds. Patients with elevated cardiac injury markers above the newly established cutoffs were associated with significantly increased risk of COVID-19 death. In conclusion, cardiac biomarker elevations are significantly associated with 28-day death in patients with COVID-19. The prognostic cutoff values of these biomarkers might be much lower than the current reference standards. These findings can assist in better management of COVID-19 patients to improve outcomes. Importantly, the newly established cutoff levels of COVID-19-associated cardiac biomarkers may serve as useful criteria for the future prospective studies and clinical trials

Game Theoretic Analysis of Carbon Emission Abatement in Fashion Supply Chains Considering Vertical Incentives and Channel Structures

We study an emission-dependent dyadic fashion supply chain made up of a supplier and a manufacturer, both of which can reduce their own component/product emissions to serve the carbon-footprint sensitive consumers. With Carbon Tax regulation, we consider four scenarios resulting from two ways in form of adopting transfer price contract and/or introducing third-party emission-reduction service (TPERS) to enhance the efficiency of systematic emission reductions. We refine four models from these corresponding scenarios, which in turn constitute a decision-making framework composed of determining vertical incentives and choosing supply chain structures. By exploiting Stackelberg games in all models, we compare their emission reduction efficiencies and profitability for each pair of settings. Theoretic analysis and numerical studies show that adopting vertical transfer payment schemes can definitely benefit channel carbon footprint reduction and Pareto improvement of supply chain profitability, regardless of whether the emission-reduction service exists or not. However, whether introducing TPERS or not is heavily depending on systematic parameters when the transfer payment incentive is adopted there. We also provide insights on the sensitivity of carbon tax parameters with respect to the supply chain performance, overall carbon emission reduction, vertical incentive and TPERS adopting decision-makings

Carbon Emission Reduction with Capital Constraint under Greening Financing and Cost Sharing Contract

Motivated by the industrial practices, this work explores the carbon emission reductions for the manufacturer, while taking into account the capital constraint and the cap-and-trade regulation. To alleviate the capital constraint, two contracts are analyzed: greening financing and cost sharing. We use the Stackelberg game to model four cases as follows: (1) in Case A1, the manufacturer has no greening financing and no cost sharing; (2) in Case A2, the manufacturer has greening financing, but no cost sharing; (3) in Case B1, the manufacturer has no greening financing but has cost sharing; and, (4) in Case B2, the manufacturer has greening financing and cost sharing. Then, using the backward induction method, we derive and compare the equilibrium decisions and profits of the participants in the four cases. We find that the interest rate of green finance does not always negatively affect the carbon emission reduction of the manufacturer. Meanwhile, the cost sharing from the retailer does not always positively affect the carbon emission reduction of the manufacturer. When the cost sharing is low, both of the participants’ profits in Case B1 (under no greening finance) are not less than that in Case B2 (under greening finance). When the cost sharing is high, both of the participants’ profits in Case B1 (under no greening finance) are less than that in Case B2 (under greening finance)

Incentive Mechanism of R&D Firms’ Collaborative Innovation Based on Organisational Ambidexterity

From the perspective of organizational ambidexterity, we consider the choice of innovation strategy among R&D firms. By building on contractual arrangements and employing a dynamic game model, we focus on the incentive mechanism of R&D Firms’ collaborative innovation and analyze incentive contracts of benefits distribution and cost-sharing when two firms conduct market-driven innovation (exploitative innovation) strategy and technological research-driven innovation (exploratory innovation) strategy respectively, and collaborate for innovation with each other. We also discuss the influence of exploratory and exploitative innovation effects on decision-making of R&D firms regarding whether to choose collaborative innovation under different incentive contracts. The results show that the effects of exploratory innovation acts as the intrinsic motivation of collaborative innovation while exploratory innovation could be improved to some degree by exploitative innovation. In addition, both investment levels of exploratory and exploitative innovation would decrease (increase) when innovation cost (innovative efficiency) increases. Moreover, compared with a benefit-distribution contract, cost-sharing contracts would not only lead exploitative innovation to realize optimal revenue, but also provide incentives for exploratory innovation more effectively

Open or Not? Operation Strategies of Competitive eCommerce Platforms from an Ecosystem Perspective

According to the traditional theory of industrial organizations, differentiated competition leads to higher returns. However, Chinese eCommerce platforms tend to homogenize in the choice of operational strategies, which deviates from the principle of differentiated competition. Some competitive eCommerce platforms were described based on the hotelling model, and a sequential game model for the competition of ecosystems was built to analyze the choice of operation strategies. From the perspective of a business ecosystem, this paper studied the impact of the strategy choice of the core platform on the ecological profit. The results showed that an open strategy would always improve the performance of business ecosystems and could even benefit the competitive ecosystem because of its spillover effect. The equilibrium of the competitive platforms was related to the game strategies, independent of the distribution contracts of the suppliers. We found that the platforms’ positions deviated from the maximum difference principle due to network externalities, and differentiation did not improve the profits of platforms