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Fuzzy rough sets (FRSs) theory is an important granular computing method to deal with incomplete information systems, and the attribute reduction is a basic key issue in FRSs. In this article, we construct a novel framework for selecting the optimal reduct of FRSs with theoretical guarantees by considering the influence of granule size and incorporating the stability theory in machine learning. First, a granule-based soft-margin support vector machine (GSSVM) algorithm is proposed for classification tasks by introducing the $\lambda$-conditional entropy into the hinge loss function, which takes the impact of granule size on data loss into account. Then, according to stability theory, the generalization error bound of the GSSVM algorithm is derived as a theoretical guarantee for selecting the optimal reduct. Finally, an optimization attribute reduction algorithm (RDROAR) based on the relative discernibility relation is presented by removing the attributes with low importance in a reduct while ensuring the generalization ability of GSSVM. Numerical experiments prove the effectiveness of the improved algorithm as well as verify the rationality and effectiveness of the optimal reduct.

Targeting on the goal of carbon peaking and carbon neutralization, the transportation sector is facing the pressure of carbon reduction, emission reduction and energy transformation simultaneously. Building a green, flexible, self-consistent and sustainable road transportation energy integration system has become an inevitable trend for the future development in an area without power grid. This paper proposes a self-consistent micro grid system model for wind and solar power with hydrogen energy storage for a highway service area without power grid connection. On this basis, a micro grid optimal configuration model is proposed with the goal of minimizing the comprehensive cost of the micro grid in the service area, under the constraints of the battery, hydrogen energy storage system (ESS), and the power balance of the micro grid system. Particle Swarm Optimization (PSO) algorithm is employed to solve the problem for a case study to verify the effectiveness of the model and the method proposed. Experimental results show that the model proposed in this paper not only improves the renewable energy utilization rate of the system, but also improves the reliability of power supply, verifying the effectiveness of the micro grid configuration scheme for the highway service area containing hydrogen ESS.

Promoting the interconnection of highway system and the energy system electric-carbon market is the key to realizing the full integration and synergistic development of highway transportation and energy. To enhance the green energy transition of highway transportation in weak grid areas, this paper proposes an energy storage capacity planning method for highway self-consistent multi-microgrid system (HSC-MMS) and formulates an interconnection operation scheme for highway transportation multi-load aggregation scenarios. The planning method that considers the characteristics of electricity-hydrogen coupling within the microgrid and the synergistic interconnection between the microgrids can not only satisfy the relevant constraints but also ensure the reliable power supply of the system. By adding carbon trading between the highway system and energy system, the carbon tax of the highway system can be effectively reduced by $13,415.90, and the economic efficiency of the HSC-MMS can be improved by 7.30 %. Meanwhile, multiple weather typical scenarios are generated based on the K-means clustering algorithm, which ensures the scientificity and feasibility of the system planning scheme. The simulation results verify the effectiveness of the proposed planning method.

Purpose: Green energy as a transportation supply trend is irreversible. In this paper, a highway energy supply system (HESS) evolution model is proposed to provide highway transportation vehicles and service facilities with a clean electricity supply and form a new model of a source-grid-load-storage-charge synergistic highway-PV-WT integrated system (HPWIS). This paper aims to improve the flexibility index of highways and increase CO2emission reduction of highways. Design/methodology/approach: To maximize the integration potential, a new energy-generation, storage and information-integration station is established with a dynamic master–slave game model. The flexibility index is defined to evaluate the system ability to manage random fluctuations in power generation and load levels. Moreover, CO2emission reduction is also quantified. Finally, the Lianhuo Expressway is taken as an example to calculate emission reduction and flexibility. Findings: The results show that through the application of the scheduling strategy to the HPWIS, the flexibility index of the Lianhuo Expressway increased by 29.17%, promoting a corresponding decrease in CO2emissions. Originality/value: This paper proposed a new model to capture the evolution of the HESS, which provides highway transportation vehicles and service facilities with a clean electricity supply and achieves energy transfer aided by an energy storage system, thus forming a new model of a transportation energy system with source-grid-load-storage-charge synergy. An evaluation method is proposed to improve the air quality index through the coordination of new energy generation and environmental conditions, and dynamic configuration and dispatch are achieved with the master–slave game model.

Fabrication of air‐stable Pb‐free solar cells using the Ag2BiI5absorber has recently attracted extensive attention. 4‐tert‐Butylpyridine (tBP) is mainly used as an additive in the hole transport layer (HTL). However, tBP can strongly destroy Ag2BiI5perovskite structure due to the formation of the tBP‐BiI3complex. Herein, 2‐pentyl pyridine (2‐py) is selected to replace the tBP in the Spiro‐OMeTAD precursor solution, which will promote the dissolution of lithium bis(trifluoromethanesulphonyl)imide salt in the HTL precursor solution but not destroy the crystal structure due to more considerable steric hindrance. By judiciously choosing 2‐py as the additives, the best solar cell device achieves a power conversion efficiency (PCE) of 1.32% under standard one sun (AM1.5). The devices also show excellent long‐term air stability and maintain 95% of their initial PCE even after 840 h. The additive of 2‐py with a long alkyl chain is used to replace tBP, and 2‐py can promote the dissolution of lithium bis(trifluoromethanesulphonyl)imide salt in the hole transport layer precursor solution with no corrosion to the lead‐free Ag2BiI5perovskite film. Ag2BiI5perovskite solar cells based on 2‐py additive show enhanced stability and photoelectric performance.

To overcome the limited tribological properties of bismaleimide (BMI) resin, a kind of novel organic–inorganic hybrid silicon dioxide nanoparticles with terminal functional amidogen groups (SiO2–NH2) was prepared via a sol–gel process. The SiO2–NH2was chosen as raw materials to react with polyformaldehyde and aniline, and the silicon dioxide-containing benzoxazine-monomer (SiO2-BOZ) can be obtained via a solvent process. The new prepared SiO2-BOZ were then as modified phase to modify BMI to prepare the SiO2-BOZ/BMI composites. With 15.0 wt-% SiO2-BOZ, the flexural strength and impact strength of SiO2-BOZ/BMI composites can reached the maximum value of 166.12 MPa and 17.93 kJ m-2, respectively, while the wear rate of SiO2-BOZ/BMI composites is only 3.9?×?10-6mm3N-1m-1. The enhanced tribological properties of SiO2-BOZ/BMI can be attributed to the improvement of its heat resistance and mechanical properties, which can increase the capacity of the SiO2-BOZ/BMI to withstand external forces and heat during the friction process.

ABSTRACTTo overcome the limited tribological properties of bismaleimide (BMI) resin, a kind of novel organic–inorganic hybrid silicon dioxide nanoparticles with terminal functional amidogen groups (SiO2–NH2) was prepared via a sol–gel process. The SiO2–NH2was chosen as raw materials to react with polyformaldehyde and aniline, and the silicon dioxide-containing benzoxazine-monomer (SiO2-BOZ) can be obtained via a solvent process. The new prepared SiO2-BOZ were then as modified phase to modify BMI to prepare the SiO2-BOZ/BMI composites. With 15.0 wt-% SiO2-BOZ, the flexural strength and impact strength of SiO2-BOZ/BMI composites can reached the maximum value of 166.12 MPa and 17.93 kJ m−2, respectively, while the wear rate of SiO2-BOZ/BMI composites is only 3.9 × 10−6mm3 N−1 m−1. The enhanced tribological properties of SiO2-BOZ/BMI can be attributed to the improvement of its heat resistance and mechanical properties, which can increase the capacity of the SiO2-BOZ/BMI to withstand external forces and heat during the friction process.

The rail transit system plays a crucial role in modern transportation. With the increasing demand for clean and green energy in the transport sector, its energy system is expected to achieve low-carbon and highly efficient energy utilization in rail transit. However, the gradual development of the rail transport energy system has led to an increase in its complexity, and the rising difficulty of system assessment has faced the limitations of traditional assessment methods. Hence, it is essential to develop effective assessment methods. This paper begins by providing a systematic review of the development status of Reliability, Availability, Maintainability and Safety (RAMS) assessment and analyzing the shortcomings of traditional RAMS assessment technology in the context of rail transit energy systems. Subsequently, based on the four fundamental properties of RAMS, it summarizes the current state of key assessment technologies in the field of rail transit. Moreover, the paper delves into the challenges and potential solutions concerning the implementation of RAMS assessment technology for rail transit energy systems. Finally, the paper offers an outlook on the future development of RAMS assessment for rail transport energy systems. By comprehensively analyzing these aspects, the paper aims to contribute valuable insights into optimizing the rail transit energy system, promoting its sustainable and efficient operation in the context of clean and green energy utilization.

DNA damage response(DDR) is essential for maintaining genome stability and protecting cells from tumorigenesis. Ubiquitin and ubiquitin-like modifications play an important role in DDR, from signaling DNA damage to mediating DNA repair. In this report, we found that the E3 ligase ring finger protein 126 (RNF126) was recruited to UV laser micro-irradiation-induced stripes in a RNF8-dependent manner. RNF126 directly interacted with and ubiquitinated another E3 ligase, RNF168. Overexpression of wild type RNF126, but not catalytically-inactive mutant RNF126 (CC229/232AA), diminished ubiquitinationof H2A histone family member X (H2AX), and subsequent bleomycin-induced focus formation of total ubiquitin FK2, TP53-binding protein 1 (53BP1), and receptor-associated protein 80 (RAP80). Interestingly, both RNF126 overexpression and RNF126 downregulation compromised homologous recombination (HR)-mediated repair of DNA double-strand breaks (DSBs). Taken together, our findings demonstrate that RNF126 negatively regulates RNF168 function in DDR and its appropriate cellular expression levels are essential for HR-mediated DSB repair.

DNA damage response(DDR) is essential for maintaining genome stability and protecting cells from tumorigenesis. Ubiquitin and ubiquitin-like modifications play an important role in DDR, from signaling DNA damage to mediating DNA repair. In this report, we found that the E3 ligase ring finger protein 126 (RNF126) was recruited to UV laser micro-irradiation-induced stripes in a RNF8-dependent manner. RNF126 directly interacted with and ubiquitinated another E3 ligase, RNF168. Overexpression of wild type RNF126, but not catalytically-inactive mutant RNF126 (CC229/232AA), diminished ubiquitinationof H2A histone family member X (H2AX), and subsequent bleomycin-induced focus formation of total ubiquitin FK2, TP53-binding protein 1 (53BP1), and receptor-associated protein 80 (RAP80). Interestingly, both RNF126 overexpression and RNF126 downregulation compromised homologous recombination (HR)-mediated repair of DNA double-strand breaks (DSBs). Taken together, our findings demonstrate that RNF126 negatively regulates RNF168 function in DDR and its appropriate cellular expression levels are essential for HR-mediated DSB repair.

Increasing penetration of uncoordinated electric vehicles (EVs) and intermittent renewable energy generation in microgrid systems motivates us to explore an effective strategy for the safe and economic operation of such distributed generation (DG) systems. This paper presents a robust economic dispatch strategy for grid-connected microgrids. Uncertainty from wind power and EV charging loads is considered as an uncertain set of interval predictions. Considering the worst application scenario, the proposed strategy can help to schedule the EV charging behaviors and DG outputs in order to reduce operation cost under practical constraints. In addition, in order to facilitate the decision makers to make decision strategies from the perspective of economy, this paper explores the relationship between the volatility of uncertain parameters and economy based on the theory of interval forecast. Numerical case study shows the feasibility of the proposed dispatch strategy.

During the past decade, energy imbalance problem between supply and demand, together with the integration of renewable energy, have drawn much attention. Vehicle-to-Grid (V2G) technology, which aims at storing the electric power in the load valley period and supporting the grid at the load peak time, is considered as one of the most promising way to solve the energy imbalance problem. However, due to the random distribution characteristics of electric vehicles (EVs), the scale of interconnection may cause threat to the safety and economy of the power grid operation. A time-of-day price incentive mechanism is employed in this paper to address the problem, which helps to guide the EV users to shift their charging/discharging behaviors during the valley/peak period to achieve a reasonable scheduling strategy based on the dynamic discharging electricity price. Besides, mathematical analysis has been carried out to demonstrate the convergence of the proposed coordination strategy, and a case study shows that the strategy is effective.

The utilization of organic amine salt treatment for the formation of 2D/3D heterojunctions has emerged as a highly effective strategy for achieving both efficient and stable halide perovskite solar cells. The creation of a 2D phase necessitates specific structural attributes within the amine molecules. While previous reports have predominantly focused on amine molecules containing linear alkyl chains, benzene rings, and heterocyclic rings to fulfill these requirements, the exploration of amine molecules incorporating cycloalkane moieties remains limited. In light of this, we introduce cyclopentanethylamine hydroiodate (CPEAI) as an innovative amine salt for the in situ growth of 2D passivation layers on 3D perovskite surfaces. Through the application of the 2D perovskite treatment, nonradiative recombination processes are effectively suppressed, leading to an extension of the carrier lifetime. This treatment also rationalizes the energy-level architecture. Consequently, devices treated with CPEAI exhibit an elevated open-circuit voltage and filling factor. Notably, the champion efficiency reaches 23.2%, surpassing the control device efficiency of 20.8%. Furthermore, we conducted a prolonged environmental stability assessment, subjecting the devices to 1000 h of exposure to air with approximately 40% relative humidity. Remarkably, the CPEAI-treated devices sustained an initial efficiency of 89.5%, whereas the control group maintained an efficiency of only 76.1%. This stark contrast underscores the substantial enhancement in environmental robustness facilitated by the CPEAI treatment. Our work unequivocally demonstrates the promising potential of cycloalkane-containing amine molecules in advancing the efficiency and stability of 2D/3D halide perovskite solar cells.

During the past two decades, electrification of the transportation sector is gradually becoming a global trend due to the environmental benefits from electric vehicle (EV). Although EV charging post plays as a primary energy supply, public EV Fast Charging Station (FCS) is definitely an important backup energy supply system to the EV customers in case of urgent need. Based on current existing FCS system and the prediction of the EV charging need in the future, this paper proposes a multi-objective EV FCS layout re-planning optimization problem, which simultaneously takes the economic issue and the customers’ satisfaction into consideration. To solve the problem a popular multi-objective evolutionary algorithm, Strengthen Pareto Evolutionary Algorithm-II (SPEA-II), is employed in this study. Numerical case studies shows that the SPEA-II can successfully address the balance between different objectives during the re-planning FCS procedure by contrast to that of a single-objective optimization method (Improved Genetic Algorithm).

Evolutionary computations are kinds of random searching algorithms derived from natural selection and biological genetic evolution behavior. Evaluating the performance of an algorithm is a fundamental task to track and find the way to improve the algorithm, while visualization technique may play an important act during the process. Based on current existing algorithm performance evaluation criteria and methods, a Python-based programming tracking strategy, which employs 2-D graphical library of python matplotlib for online algorithm performance evaluation, is proposed in this paper. Tracking and displaying the performance of genetic algorithm (GA) and particle swarm optimization (PSO) optimizing two typical numerical benchmark problems are employed for verification and validation. Results show that the tracking strategy based on Python language for online performance evaluation of evolutionary algorithms is valid, and can be used to help researchers on algorithms’ performance evaluation and finding ways to improve it.

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