Developing new energy vehicles is vital to promote green development and the harmonious coexistence of humans and nature. It is also the only way to help China move from a significant automobile ...country to a powerful automobile country. Based on the background of the "recession" of government subsidies and considering the importance of green credit in promoting green and low-carbon transformation, this paper constructs a four-party evolutionary game model that includes government, automotive companies, banks, and consumers to analyze the stability of the strategic choices of various parties in the development process of the new energy vehicle industry. It uses MATLAB simulation tools to analyze the impact of relevant factors on system stability. The research shows that: (1) The government's subsidy mechanism significantly promotes the development of the new energy vehicle industry. Still, there is a subsidy threshold, beyond which the effect will weaken and quickly bring financial pressure. (2) With the gradual decline of government subsidies, the bank's green credit policy has a specific policy complementary effect on the decline of government subsidies. (3) Considering that costs and benefits are the main influencing factors for automotive companies and consumers' strategic choices, the impact of factors such as the punishment of violations, adjustment of subsidy policies, and consumers' environmental awareness must also be paid attention to.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
The effective acquisition of clean water from atmospheric water offers a potential sustainable solution for increasing global water and energy shortages. In this study, an asymmetric ...amphiphilic surface incorporating self-driven triboelectric adsorption was developed to obtain clean water from the atmosphere. Inspired by cactus spines and beetle elytra, the asymmetric amphiphilic surface was constructed by synthesizing amphiphilic cellulose ester coatings followed by coating on laser-engraved spines of fluorinated ethylene propylene. Notably, the spontaneous interfacial triboelectric charge between the droplet and the collector was exploited for electrostatic adsorption. Additionally, the droplet triboelectric nanogenerator converts the mechanical energy generated by droplets falling into electrical energy through the volume effect, achieving an excellent output performance, and further enhancing the electrostatic adsorption by means of external charges, which achieved a water harvesting efficiency of 93.18 kg/m
2
h. This strategy provides insights for the design of water harvesting system.
Formaldehyde (HCHO) causes increasing concerns, because of its ubiquitous presence in the indoor environment and its irritating and carcinogenic nature, with regard to humans. The fast abatement of ...HCHO is of significant practical interest at room temperature. In this paper, we fabricate a three-dimensional manganese dioxide framework (3D-MnO2), which has interconnected network structures, low mass density (∼7.3 mg cm–3), and high absorption capacity for organic liquids. In particular, the 3D-MnO2 showed excellent activity and stability for HCHO oxidation at room temperature, achieving 45% of 100 ppm of HCHO mineralized into CO2 under high gas hourly space velocity (GHSV = 180 L gcat –1 h–1). The excellent performance of 3D-MnO2 catalysts in decomposing HCHO can be ascribed to their quick reversibility and high water content for replenishing the consumed surface hydroxyl groups during HCHO decomposition, and fully exposed active reaction sites. It is valuable to know that inexpensive metal oxides such as MnO2 can transform ppm-level HCHO into harmless CO2 in a timeframe as brief as a subsecond at room temperature.
Device-to-device (D2D) communications bring significant benefits to mobile multimedia services in local areas. However, these potential advantages hinge on intelligent resource sharing between ...potential D2D pairs and cellular users. In this paper, we study the problem of energy-efficient uplink resource sharing over mobile D2D multimedia communications underlaying cellular networks with multiple potential D2D pairs and cellular users. We first construct a novel analytical model of energy efficiency for different sharing modes, which takes into account quality-of-service (QoS) requirements and the spectrum utilization of each user. Then, we formulate the energy-efficient resource sharing problem as a nontransferable coalition formation game, with the characteristic function that accounts for the gains in terms of energy efficiency and the costs in terms of mutual interference. Moreover, we develop a distributed coalition formation algorithm based on the merge-and-split rule and the Pareto order. The distributed solution is characterized through novel stability notions and can be adapted to user mobility. From it, we obtain the energy-efficient sharing strategy on joint mode selection, uplink reusing allocation, and power management. Extensive simulation results are provided to demonstrate the effectiveness of our proposed game model and algorithm.
The Byzantine attack in cooperative spectrum sensing (CSS), also known as the spectrum sensing data falsification (SSDF) attack in the literature, is one of the key adversaries to the success of ...cognitive radio networks (CRNs). Over the past couple of years, the research on the Byzantine attack and defense strategies has gained worldwide increasing attention. In this paper, we provide a comprehensive survey and tutorial on the recent advances in the Byzantine attack and defense for CSS in CRNs. Specifically, we first briefly present the preliminaries of CSS for general readers, including signal detection techniques, hypothesis testing, and data fusion. Second, we propose a taxonomy of the existing Byzantine attack behaviors and elaborate on the corresponding attack parameters, which determine where, who, how, and when to launch attacks. Then, from the perspectives of homogeneous or heterogeneous scenarios, we classify the existing defense algorithms, and provide an in-depth tutorial on the state-of-the-art Byzantine defense schemes, commonly known as robust or secure CSS in the literature. Furthermore, we analyze the spear-and-shield relation between Byzantine attack and defense from an interactive game-theoretical perspective. Moreover, we highlight the unsolved research challenges and depict the future research directions.
This paper investigates the issue of spatial-temporal opportunity detection for spectrum-heterogeneous cognitive radio networks, where at a given time secondary users (SUs) at different locations may ...experience different spectrum access opportunities. Most prior studies address either spatial or temporal sensing in isolation and explicitly or implicitly assume that all SUs share the same spectrum opportunity. However, this assumption is not realistic and the traditional non-cooperative sensing (NCS) and cooperative sensing (CS) schemes are not very effective in a more realistic setting considering the heterogeneous spectrum availability among SUs. We define new performance metrics to guide the spatial-temporal opportunity detection and propose a two-dimensional sensing (TDS) framework to improve the opportunity detection performance, which exploits correlations in time and space simultaneously by effectively fusing sensing results in a spatial-temporal sensing window. Furthermore, in terms of maximum interference constrained transmission power (MICTP), we classify the spatial opportunities for SUs into three groups: black, grey, and white, and propose a TDS-based distributed power control scheme to further improve the spectrum utilization by exploiting both grey and white spectrum opportunities. The effectiveness of the proposed scheme is demonstrated through in-depth numerical simulations under a variety of scenarios.
Spectrum inference, also known as spectrum prediction in the literature, is a promising technique of inferring the occupied/free state of radio spectrum from already known/measured spectrum occupancy ...statistics by effectively exploiting the inherent correlations among them. In the past few years, spectrum inference has gained increasing attention owing to its wide applications in cognitive radio networks (CRNs), ranging from adaptive spectrum sensing, and predictive spectrum mobility, to dynamic spectrum access and smart topology control, to name just a few. In this paper, we provide a comprehensive survey and tutorial on the recent advances in spectrum inference. Specifically, we first present the preliminaries of spectrum inference, including the sources of spectrum occupancy statistics, the models of spectrum usage, and characterize the predictability of spectrum state evolution. By introducing the taxonomy of spectrum inference from a time-frequency-space perspective, we offer an in-depth tutorial on the existing algorithms. Furthermore, we provide a comparative analysis of various spectrum inference algorithms and discuss the metrics of evaluating the efficiency of spectrum inference. We also portray the various potential applications of spectrum inference in CRNs and beyond, with an outlook to the fifth-generation mobile communications and next generation high frequency communications systems. Last but not least, we highlight the critical research challenges and open issues ahead.
In this paper, we propose general-order transmit antenna selection to enhance the secrecy performance of multiple-input-multiple-output multieavesdropper channels with outdated channel state ...information (CSI) at the transmitter. To evaluate the effect of the outdated CSI on the secure transmission of the system, we investigate the secrecy performance for two practical scenarios, i.e., Scenarios I and II, where the eavesdropper's CSI is not available at the transmitter and is available at the transmitter, respectively. For Scenario I, we derive exact and asymptotic closed-form expressions for the secrecy outage probability in Nakagami-m fading channels. In addition, we also derive the probability of nonzero secrecy capacity and the ε-outage secrecy capacity, respectively. Simple asymptotic expressions for the secrecy outage probability reveal that the secrecy diversity order is reduced when the CSI is outdated at the transmitter, and it is independent of the number of antennas at each eavesdropper NE, the fading parameter of the eavesdropper's channel mE, and the number of eavesdroppers M. For Scenario II, we make a comprehensive analysis of the average secrecy capacity obtained by the system. Specifically, new closed-form expressions for the exact and asymptotic average secrecy capacity are derived, which are valid for general systems with an arbitrary number of antennas, number of eavesdroppers, and fading severity parameters. Resorting to these results, we also determine a high signal-to-noise ratio power offset to explicitly quantify the impact of the main channel and the eavesdropper's channel on the average secrecy capacity.
We investigate the problem of distributed channel selection using a game-theoretic stochastic learning solution in an opportunistic spectrum access (OSA) system where the channel availability ...statistics and the number of the secondary users are apriori unknown. We formulate the channel selection problem as a game which is proved to be an exact potential game. However, due to the lack of information about other users and the restriction that the spectrum is time-varying with unknown availability statistics, the task of achieving Nash equilibrium (NE) points of the game is challenging. Firstly, we propose a genie-aided algorithm to achieve the NE points under the assumption of perfect environment knowledge. Based on this, we investigate the achievable performance of the game in terms of system throughput and fairness. Then, we propose a stochastic learning automata (SLA) based channel selection algorithm, with which the secondary users learn from their individual action-reward history and adjust their behaviors towards a NE point. The proposed learning algorithm neither requires information exchange, nor needs prior information about the channel availability statistics and the number of secondary users. Simulation results show that the SLA based learning algorithm achieves high system throughput with good fairness.
•The MnOx particles assembled with nanosheets were uniformly coated on PET fibers.•The growth process of MnOx layer on PET is clearly clarified.•MnOx/PET showed good activity for HCHO decomposition ...at room temperature.•MnOx/PET material is promising for indoor air purification due to its light, flexible and low air-resistant properties.
Removal of low-level formaldehyde (HCHO) is of great interest for indoor air quality improvement. Supported materials especially those with low air pressure drop are of necessity for air purification. Manganese oxides (MnOx) was in situ deposited on the surface of fibers of a non-woven fabric made of polyethylene terephthalate (PET). As-synthesized MnOx/PET were characterized by SEM, XRD, TEM, ATR-FTIR and XPS analysis. The growth of MnOx layer on PET is thought to start with partial hydrolysis of PET, followed by surface oxidation by KMnO4 and then surface-deposition of MnOx particles from the bulk phase. The MnOx particles assembled with nanosheets were uniformly coated on the PET fibers. MnOx/PET showed good activity for HCHO decomposition at room temperature which followed the Mars–van Krevelen mechanism. The removal of HCHO was kept over 94% after 10h continuous reaction under the conditions of inlet HCHO concentration ∼0.6mg/m3, space velocity ∼17,000h−1 and relative humidity∼50%. This research provides a facile method to deposit active MnOx onto polymers with low air resistance, and composite MnOx/PET material is promising for indoor air purification.
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