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Aluminum nanoparticles (nAl) have received sustained interest due to their higher reactivity than micron aluminum particles (mAl). However, in practice, the densities of explosive formulations with nAl are far smaller than those with mAl, which greatly undercuts the energy release performance. To take advantages of both kinds of Al particles, in situ integration of mAl@nAl composites was proposed and evaluated. The mAl@nAl composites were prepared by in situ electrical explosion of Al wire. Their morphology, density, and specific surface area (SSA) were characterized by scanning electron microscope (SEM), densimetry, and Brunauer–Emmett–Teller (BET), respectively. SEM showed that nAl uniformly adhered to the surface of mAl. With the increase in voltage, the average diameter and density of the composites decreased, but the SSA of the composites increased. And the largest density of the composites was 1.13 g/cm3, comparable to that of the commercial graded Al product (1.25 g/cm3). Meanwhile, the highest SSA of the composites was 12.1192 m2/g. In addition, the combustion efficiency of mAl@nAl composites at 20 kV was 8.26% higher than that of physically graded counterparts. The constant-volume combustion test under zero oxygen balance revealed that the pressurization rate and peak pressure of mAl@nAl composites prepared at 20 kV were the highest of all. Furthermore, constant-volume combustion under constant heat showed that the combustion temperatures of mAl@nAl composites were 1.15–1.45 times higher than those of physically graded counterparts. Finally, the ignition delay of mAl@nAl composites was reduced with the increase in explosion voltage. [ABSTRACT FROM AUTHOR]

Online product pricing is an important research field in the platform economy, and a two‐stage mixed presale is a mainstream mode of online sales. In the process of online consumption, the payment method and presale mode have an important impact on consumer behaviour and product pricing. Based on the two‐stage mixed presale mode, this study considers the impact of anchoring and the payment pain reduction effect on consumer behaviour, establishes the corresponding product pricing model and obtains the optimal presale price, sales and profit. It sheds light on the influence mechanism of anchoring and the payment pain reduction effect on consumer behaviour and online product pricing. Theoretical and numerical analyses reveal that the payment pain reduction effect can help to raise the product price, stimulate market vitality and bring higher profits for online retailers, and the anchoring effect and consumers' loss aversion psychology can enhance the profits and sales of online retailers, but they will discourage setting high prices for products. The research results will further enrich the relevant research on customer behaviour and product pricing in the platform economy and will provide decision bases for platform enterprises and online retailers to participate in presale activities and formulate product pricing strategies. [ABSTRACT FROM AUTHOR]

Online product pricing is an important factor that affects the purchase of customers and the earnings of e‐commerce platform enterprises. It has an increasingly prominent influence on consumers' purchasing decisions. To study the influence of customers' anchoring psychology and product pricing on customers' purchasing behaviors, this paper proposes a pricing model that considers online consumers to be anchored by the product price and sales. The cognitive bias of online consumers is described by a utility function based on an anchoring‐adjustment heuristic, and consumer choice behavior and an online product pricing strategy are studied with a multinomial logit model. Then, it studies the influence of the anchoring point and anchoring degree on optimal pricing, sales and profit. In particular, when consumers are anchored only by sales of goods, the optimal solution is monotonic with respect to the anchoring degree. However, when consumers are anchored by both price and sales, both factors affect consumer behaviors and produce more complex results. This paper provides a flexible pricing mechanism for platform enterprises, and it can provide a theoretical basis and decision support for dynamic pricing of platform enterprises based on historical consumption data. [ABSTRACT FROM AUTHOR]

Two key issues are confronted by the Port Group when entering an inland-river market; namely, port acquisition selection at the strategic level and port service pricing at the operational level. This article identifies the multi-type game relationships among the Port Group and multiple ports and customers in the planning time-horizon, and proposes a three-level programming model based on repeated games for the inland-river port acquisition selection and service pricing collaborative optimization problem. According to the model characteristics, a three-level nested heuristic algorithm is developed by combining a genetic algorithm, game simulation algorithm and equilibrium allocation algorithm. A series of numerical experiments with partial real data in Jining City, Shandong Province, China, is conducted to validate the superiority and efficiency of the proposed model and method. This article also provides some valuable management suggestions for the inland-river Port Group in terms of investment scale, investment expectation, pricing mode and customer relationship. [ABSTRACT FROM AUTHOR]

This correction notice addresses an error in the original article titled "Silencing of CD147 inhibits cell proliferation, migration, invasion, lipid metabolism dysregulation and promotes apoptosis in lung adenocarcinoma via blocking the Rap1 signaling pathway." The authors identified that Figures 1 and 2 were inadvertently swapped. The correction provides the correct figures and captions, and assures readers that the corrections do not alter the interpretations or validity of the research. The error does not significantly impact the overall findings and conclusions of the paper. [Extracted from the article]