Optimal strategies of automakers with demand and credit price disruptions under the dual-credit policy

In this paper, a production and pricing decision model for automakers under the dual-credit policy is formulated. Then, with consideration of demand and credit price disruptions, a nonlinear programming model that maximizes automakers’ profit and constrains the production of fuel vehicles (FVs) and new energy vehicles (NEVs) is investigated. Furthermore, four strategies that involve adjusting the production or price of FVs and NEVs are proposed, and four optimal solutions for each strategy are obtained. Finally, 16 scenarios are comprehensively analyzed, and a case study involving demand and credit price disruptions is conducted. The results show that the dual-credit policy has a positive impact on the development of NEVs, especially in early stages of NEV development. The FV credit coefficient has a significantly positive impact on the probability of automakers adopting adjustment strategies, while the NEV credit coefficient has almost no such impact. Moreover, automakers are inclined to adjust the prices of NEVs or the production of FVs to cope with demand and credit price disruptions

Direct rosiglitazone action on steroidogenesis and proinflammatory factor production in human granulosa-lutein cells

<p>Abstract</p> <p>Background</p> <p>Ovarian granulosa cells are the predominant source of estradiol and progesterone biosynthesis in vivo. Rosiglitazone, a synthetic agonist of the peroxisome proliferator-activated receptor gamma (PPAR gamma), is applied as the treatment of insulin resistance including women with PCOS. The aim of the study was to investigate the direct effects of rosiglitazone on steroidogenesis and proinflammatory factor production in human granulosa-lutein cells (GLCs).</p> <p>Methods</p> <p>Primary human GLCs were separated during in vitro fertilization and cultured in the presence of rosiglitazone, GW9662 (an antagonist of PPAR gamma) and hCG. The mRNA expression of key steroidogenic factors including 3beta- hydroxysteriod dehydrogenase (3beta-HSD), cytochrome P-450 scc (CYP11A1), cytochrome P-450 aromatase (CYP19A1), and steroidogenic acute regulatory protein (StAR) were detected by quantitative real-time PCR. Estradiol and progesterone levels in GLCs cultures were measured by chemiluminescence immunoassay, and the proinflammtory factors (TNFalpha and IL-6) in conditioned culture media were measured by ELISA.</p> <p>Results</p> <p>PPAR gamma mRNA levels increased up to 3.24 fold by rosiglitazone at the concentration of 30 microM compared to control (P < 0.05). hCG alone or hCG with rosiglitazone had no significant effects on PPAR gamma mRNA levels. The CYP19A1 mRNA level at exposure to rosiglitazone alone showed a drop, but was not significantly reduced comparing to control. The expression levels of enzymes 3beta-HSD and CYP11A1 in all treatments did not alter significantly. The StAR mRNA expression at exposure to rosiglitazone was significantly increased comparing to control (P < 0.05). The media concentrations of E2 and progesterone by rosiglitazone treatment showed a declining trend comparing to control or cotreatment with hCG, which did not reach significance. Most importantly, treatment with rosiglitazone decreased TNFalpha secretion in a statistically significant manner compared with control (P < 0.05). The concentration of IL-6 following rosiglitazone exposure did not significantly decrease comparing to control.</p> <p>Conclusion</p> <p>In cultured GLCs, rosiglitazone stimulated StAR expression, but did not significantly affect steroidogenic enzymes, as well as E2 and progesterone production. Moreover, rosiglitazone significantly decreased the production of TNFalpha in human GLCs, suggesting that PPAR gamma may play a role in the regulation of GLCs functions through inhibiting proinflammatory factors.</p

Novel multiple RIS-assisted communications for 6G networks

As an emerging technique, reconfigurable intelligent surface (RIS) has recently received extensive attention and can be considered as a key enabling technology for future sixth generation (6G) wireless communication networks. In this letter, we propose a novel multiple RIS-assisted single-input-single-output (SISO) wireless communication system working in a domino pattern when obscuration is severe. The upper bound of the ergodic capacity and the outage probability for the proposed system are analyzed and the corresponding closed-form expressions are provided under Nakagami-m fading channels. The general multiple RIS-assisted systems including two RISs and K RISs are analyzed. Numerical results indicate that the number of RISs, the number of RIS elements, and the communication environment can significantly affect the upper bound of the ergodic capacity and the outage probability performance of the proposed system. The feasibility of the proposed system and the accuracy of the upper bound of the ergodic capacity and the outage probability are also verified by the numerical results

Pushing the Limits of Machine Design: Automated CPU Design with AI

Design activity -- constructing an artifact description satisfying given goals and constraints -- distinguishes humanity from other animals and traditional machines, and endowing machines with design abilities at the human level or beyond has been a long-term pursuit. Though machines have already demonstrated their abilities in designing new materials, proteins, and computer programs with advanced artificial intelligence (AI) techniques, the search space for designing such objects is relatively small, and thus, "Can machines design like humans?" remains an open question. To explore the boundary of machine design, here we present a new AI approach to automatically design a central processing unit (CPU), the brain of a computer, and one of the world's most intricate devices humanity have ever designed. This approach generates the circuit logic, which is represented by a graph structure called Binary Speculation Diagram (BSD), of the CPU design from only external input-output observations instead of formal program code. During the generation of BSD, Monte Carlo-based expansion and the distance of Boolean functions are used to guarantee accuracy and efficiency, respectively. By efficiently exploring a search space of unprecedented size 10^{10^{540}}, which is the largest one of all machine-designed objects to our best knowledge, and thus pushing the limits of machine design, our approach generates an industrial-scale RISC-V CPU within only 5 hours. The taped-out CPU successfully runs the Linux operating system and performs comparably against the human-designed Intel 80486SX CPU. In addition to learning the world's first CPU only from input-output observations, which may reform the semiconductor industry by significantly reducing the design cycle, our approach even autonomously discovers human knowledge of the von Neumann architecture.Comment: 28 page

Gut Microbiota Aggravates Neutrophil Extracellular Traps-Induced Pancreatic Injury in Hypertriglyceridemic Pancreatitis

Hypertriglyceridemic pancreatitis (HTGP) is featured by higher incidence of complications and poor clinical outcomes. Gut microbiota dysbiosis is associated with pancreatic injury in HTGP and the mechanism remains unclear. Here, we observe lower diversity of gut microbiota and absence of beneficial bacteria in HTGP patients. In a fecal microbiota transplantation mouse model, the colonization of gut microbiota from HTGP patients recruits neutrophils and increases neutrophil extracellular traps (NETs) formation that exacerbates pancreatic injury and systemic inflammation. We find that decreased abundance of Bacteroides uniformis in gut microbiota impairs taurine production and increases IL-17 release in colon that triggers NETs formation. Moreover, Bacteroides uniformis or taurine inhibits the activation of NF-κB and IL-17 signaling pathways in neutrophils which harness NETs and alleviate pancreatic injury. Our findings establish roles of endogenous Bacteroides uniformis-derived metabolic and inflammatory products on suppressing NETs release, which provides potential insights of ameliorating HTGP through gut microbiota modulation

Live-Streaming Commerce in the Supply Chain with Equity Cooperation: Independent or Cooperative?

Live-streaming commerce (LSC) has been adopted by an increasing number of supply-chain enterprises to enhance their market competitiveness. However, the question of who will lead live-streaming e-commerce in the supply chain (SC-LSC) is a key issue, especially when there is equity cooperation between upstream and downstream enterprises. Three main SC-LSC models are examined: independent SC-LSC run by manufacturers, independent SC-LSC run by retailers, and cooperatively run SC-LSC. Then, a novel LSC demand function composed of online popularity, price discount and sales conversion rate is proposed. Furthermore, four scenarios have been comprehensively investigated considering whether there is an online-to-offline drainage effect and whether there is equity cooperation. Regardless of the scenario, having both parties reach an agreement on a given SC-LSC model is difficult, and even equity cooperation cannot promote SC-LSC cooperation. In most cases, manufacturers tend to offset the losses caused by the drainage effect by adopting high wholesale prices, which will in turn exacerbate retailers’ resistance to SC-LSC. These findings provide insight into how LSC is modeled and how LSC can be better implemented in various types of supply chains such as that of Gree Electric

Forecasting the delayed impact of energy price fluctuations on China's general prices based on a temporal input-output approach

The Chinese economy is facing the impact of soaring energy prices, including the prices of coal, electricity and oil. The impacts of energy price fluctuations on general prices have a significant delayed effect. A novel price-temporal input-output (I–O) method is proposed to measure these delayed effects. A series of time-delay functions caused by a single price fluctuation and continuous price fluctuations is obtained through polynomial fitting. Then, the impact of price regulation and price delay adjustment on the delayed effect is further examined. Finally, China's latest 2017 I–O table, 4186 listed companies, and actual oil price adjustment data for 2020 are used to conduct empirical research. The delayed effect of oil, coal, electricity and gas price fluctuations on general prices and price indices, such as the consumer price index (CPI) and producer price index (PPI), are comprehensively investigated, and a corresponding time-delay ratio table for rapid querying is provided. The results indicate that the delayed impact of energy price fluctuations on the prices of various sectors lasts for half a year or even longer; additionally, these effects are very different. Logistics prices and the PPI are the most affected by oil price fluctuations, while trade prices and the CPI are the least affected by oil price fluctuations. China's oil price adjustments in 2020 led to a decline in general prices, and prices rebounded at the end of the year. Price regulation, especially electricity price regulation, reduces the impact of energy price fluctuations on general prices, and price delay adjustments extend the length of the time delay. This study can help improve how governments and enterprises address the impact of energy price fluctuations

Optimal Production Strategies with Credit Sharing for Automakers under the Dual-Credit Policy

This paper investigates strategic production selections in scenarios of credit sharing between cooperative fuel vehicle (FV) automakers and new energy vehicle (NEV) automakers under the dual-credit policy. Three coopetition production strategies are formulated: the simultaneous production strategy, the FV priority production strategy, and the NEV priority production strategy. On the basis of these three production strategies, this study examines the optimal strategy for both parties in scenarios of no credit sharing, credit sharing dominated by the FV automaker, and credit sharing dominated by the NEV automaker. The simultaneous production strategy is the most conducive to both parties’ coexistence in the vehicle market, and the FV or NEV priority production strategy can be adopted to realize the Pareto optimization of their total profit in certain applicable intervals. Credit sharing will greatly change both parties’ applicable intervals and optimal strategy selections, and credit sharing dominated by FV automakers has been proven to effectively improve their social welfare with a low credit price. Interestingly, a high credit price is sometimes more important for the development of NEVs than the NEV cruising range and substitutability under the dual-credit policy. This study also demonstrates the impact of the credit coefficient, credit equilibrium, and NEV substitutability on both parties’ production decisions and credit sharing. Our study has important managerial implications and can be utilized as strategic guidance for FV/NEV automakers to pursue coopetition under the dual-credit policy

Mixed Carbon Policies Based on Cooperation of Carbon Emission Reduction in Supply Chain

This paper established cooperation decision model for a mixed carbon policy of carbon trading-carbon tax (environmental tax) in a two-stage S-M supply chain. For three different cooperative abatement situations, we considered the supplier driven model, the manufacturer driven model, and the equilibrium game model. We investigated the influence of mixed carbon policy with constraint of reduction targets on supply chain price, productivity, profits, carbon emissions reduction rate, and so on. The results showed that (1) high-strength carbon policies do not necessarily encourage enterprises to effectively reduce emissions, and increasing market acceptance of low carbon products or raising the price of carbon quota can promote the benign reduction; (2) perfect competitive carbon market has a higher carbon reduction efficiency than oligarch carbon market, but their optimal level of cooperation is the same and the realized reduction rate is in line with the intensity of carbon policy; (3) the policy sensitivity of the carbon trading mechanism is stronger than the carbon tax; “paid quota mechanism” can subsidize the cost of abatement and improve reduction initiative. Finally, we use a numerical example to solve the optimal decisions under different market situations, validating the effectiveness of model and the conclusions