Numerical investigation on transverse flow of helical cruciform fuel rod assembly in a lead-bismuth cooled fast reactor

The helical cruciform fuel (HCF) rod assembly is a new type of fuel for the lead-bismuth (LBE) fast reactor. It can be self-positioned and realize a coolant mixing without wrapped wire or grid spacer. This kind of fuel assembly can not only realize the function of the traditional wire-wrapped fuel assembly, but also omit the wire -wrapped structure, which provides a satisfactory prospect for the development of LBE reactor. In this study, the coolant mixing in the LBE cooled reactor with HCF assembly was analyzed numerically. The influence of the Reynolds number and different coolant mediums were investigated. Advantages and disadvantages of the HCF assembly were analyzed and compared with the wire-wrapped fuel

Multiwinner Voting for Energy-Efficient Mobile Sink Rendezvous Selection in Wireless Sensor Network

Recent studies have demonstrated the advantage of applying mobile sink to prevent the energy-hole problem and prolong network lifetime in wireless sensor network. However, most researches treat the touring length constraint simply as the termination indicator of rendezvous point selection, which leads to a suboptimal solution. In this paper, we notice that the optimal set of rendezvous points is unknown but deterministic and propose to elect the set of rendezvous points directly with the multiwinner voting-based method instead of step-by-step selection. A weighted heuristic voter generation method is introduced to choose the representative voters, and a scoring rule is also well designed to obtain a satisfying solution. We also employ an iterative schema for the voting score update to refine the solution. We have conducted extensive experiments, and the results show that the proposed method can effectively prolong the network lifetime and achieve the competitive performance with other SOTA methods. Compared to the methods based on step-by-step selection, the proposed method increases the network lifetime by 23.2% and 10.5% on average under the balanced-distribution and unbalanced-distribution scenarios, respectively

Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein–Protein Interaction Network

High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein–protein interaction (PPI) networks. In this study, based on penalized matrix decomposition (PMD), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMDpc) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMDpc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR)

Pure thiophene–sulfur doped reduced graphene oxide: synthesis, structure, and electrical properties

Here we propose, for the first time, a new and green ethanol-thermal reaction method to synthesize highquality and pure thiophene–sulfur doped reduced graphene oxide (rGO), which establishes an excellent platform for studying sulfur (S) doping effects on the physical/chemical properties of this material. We have quantitatively demonstrated that the conductivity enhancement of thiophene–S doped rGO is not only caused by the more effective reduction induced by S doping, but also by the doped S atoms, themselves. Furthermore, we demonstrate that the S doping is more effective in enhancing conductivity of rGO than nitrogen (N) doping due to its stronger electron donor ability. Finally, the dye-sensitized solar cell (DSCC) employing the S-doped rGO/TiO₂ photoanode exhibits much better performance than undoped rGO/TiO₂, N-doped rGO/TiO₂ and TiO₂ photoanodes. It therefore seems promising for thiophene–S doped rGO to be widely used in electronic and optoelectronic devices

Ultrafast ammonia-driven, microwave-assisted synthesis of nitrogen-doped graphene quantum dots and their optical properties

For the first time, a facile, ultrafast, ammonia-driven microwave-assisted synthesis of high-quality nitrogen-doped graphene quantum dots (NGQDs) at room temperature and atmospheric pressure is presented. This one-step method is very cheap, environment friendly, and suitable for large-scale production. The as-synthesized NGQDs consisting of one to three graphene monolayers exhibit highly crystalline quality with an average size of 5.3 nm. A new fluorescence (FL) emission peak at 390 nm is observed, which might be attributed to the doped nitrogen atoms into the GQDs. An interesting red-shift is observed by comparing the FL excitation spectra to the UV-visible absorption spectra. Based on the optical properties, the detailed Jablonski diagram representing the energy level structure of NGQDs is derived

Assessing climate/air quality synergies and cost-effectiveness for Beijing transportation:Insights into sustainable development

CO2 emission reduction policies can simultaneously reduce air pollutant emissions in the transport sector, but the extent of their cost-effective is under-evaluated. To explore sustainable transportation in a mega-city, the potential synergies and cost-effectiveness of CO2 and air pollutant emission reductions in Beijing transportation are quantitatively evaluated by radar chart analysis, total cost of ownership (TCO) and marginal abatement cost curves (MACC) under various mitigation measures. The findings show that the adoption of electric light-duty vehicles can achieve a significant synergistic effect and cost-effectiveness of emission reductions, and would be implemented as a high priority. Moreover, improving emission standards and fuel economy have an obvious cost-effectiveness and effective mitigation for air pollutants, but with poor synergies due to low CO2 mitigation. In contrast, the clean energy for large and heavy vehicles, and bio-fuel for aviation are essential measures for achieving carbon neutrality, but with high costs. Furthermore, changes of transport modes have good cost-effectiveness, but there are no synergies due to the emission increments of PM2.5 and NOx. Given that transportation plays a crucial role in achieving carbon neutrality and enhancing air quality, more stringent and effective environmental policies targeting emission reduction can expedite the sustainable transition in Beijing transportation