Data offloading through vehicular ad hoc networks (VANETs) is one of the most promising methods for overcoming the overload problem in cellular networks. As data delivery by service providers consumes resources such as bandwidth, storage and power, the incentive scheme with the optimal pricing strategy must be identified. In the literature, most incentive schemes focus on offloading through fixed nodes, such as roadside units (RSUs). It remains very challenging to motivate a moving vehicle to help other users deliver their data due to the high mobility of vehicles. Game theory is a widely adopted method for analyzing pricing issues in wireless networks. Therefore, this paper proposes an optimal pricing strategy that uses the Stackelberg game to model the interaction between a service provider and a service requester. Then, the Stackelberg equilibrium is derived under the corresponding conditions. Next, an algorithm is proposed for selecting the service provider that offers the lowest price based on the results of the Stackelberg equilibrium. Finally, the simulation results demonstrate that the proposed algorithm can effectively reduce the downloading time of a task while maximizing the utilities of both the service provider and the requester.
Objective. N6-Methyladenosine (m6A) is the most prevalent RNA epigenetic modulation in eukaryotic cells, which serves a critical role in diverse physiological processes. Emerging evidences indicate the prognostic significance of m6A regulator ZC3H13 in hepatocellular carcinoma (HCC). Herein, this study was conducted for revealing biological functions and mechanisms of ZC3H13 in HCC. Methods. Expression of ZC3H13 was examined in collected HCC and normal tissues, and its prognostic significance was investigated in a public database. Gain/loss of functional assays were presented for defining the roles of ZC3H13 in HCC progression. The specific interactions of ZC3H13 with PKM2 were validated in HCC cells via mRNA stability, RNA immunoprecipitation, and luciferase reporter and MeRIP‐qPCR assays. Moreover, rescue experiments were carried out for uncovering the mechanisms. Results. ZC3H13 expression was downregulated in HCC, and its loss was in relation to dismal survival outcomes. Functionally, overexpressed ZC3H13 suppressed proliferation, migration, and invasion and elevated apoptotic levels of HCC cells. Moreover, ZC3H13 overexpression sensitized to cisplatin and weakened metabolism reprogramming of HCC cells. Mechanically, ZC3H13-induced m6A modified patterns substantially abolished PKM2 mRNA stability. ZC3H13 facilitated malignant behaviors of HCC cells through PKM2-dependent glycolytic signaling. Conclusion. Collectively, ZC3H13 suppressed the progression of HCC through m6A-PKM2-mediated glycolysis and sensitized HCC cells to cisplatin, which offered a fresh insight into HCC therapy.
The standard algorithms of decision trees and their derived methods are usually constructed on the basis of the frequency information. However, they still suffer from a dilemma or multichotomous question for continuous attributes when two or more candidate cut points have the same or similar splitting performance with the optimal value, such as the maximal information gain ratio or the minimal Gini index. In this paper, we propose a unified framework model to deal with this question. We then design two algorithms based on Splitting Performance and the number of Expected Segments, called SPES1 and SPES2, which determine the optimal cut point, as follows. First, several candidate cut points are selected based on their splitting performances being the closest to the optimal. Second, we compute the number of expected segments for each candidate cut point. Finally, we combine these two measures by introducing a weighting factor α to determine the optimal one from several candidate cut points. To validate the effectiveness of our methods, we perform them on 25 benchmark datasets. The experimental results demonstrate that the classification accuracies of the proposed algorithms are superior to the current state-of-the-art methods in tackling the multichotomous question, about 5% in some cases. In particular, according to the proposed methods, the number of candidate cut points converges to a certain extent. INDEX TERMS Decision tree, classification, unified framework, split criteria.
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