Modeling Spacing Distribution of Queuing Vehicles in Front of a Signalized Junction Using Random-Matrix Theory

Modeling of headway/spacing between two consecutive vehicles has many applications in traffic flow theory and transport practice. Most known approaches only study the vehicles running on freeways. In this paper, we propose a model to explain the spacing distribution of queuing vehicles in front of a signalized junction based on random-matrix theory. We show that the recently measured spacing distribution data well fit the spacing distribution of a Gaussian symplectic ensemble (GSE). These results are also compared with the spacing distribution observed for car parking problem. Why vehicle-stationary-queuing and vehicle-parking have different spacing distributions (GSE vs GUE) seems to lie in the difference of driving patterns

Parameter Solving of Probability Integral Method Based on Improved Genetic Algorithm

The probability integral method (PIM) is the main method for mining subsidence prediction in China. Parameter errors and model errors are the main sources of error in the application of the probability integral method. There are many surface subsidence problems caused by coal mining. In order to improve the accuracy and operating efficiency of the genetic algorithm (GA) in calculating the parameters of the PIM, this paper proposes an improved genetic algorithm (IGA) by adding the dynamic crossover and mutation rate to the traditional GA. Made improvements to the shortcomings of random crossover and mutation rate of all individuals in the population in the original algorithm.Through simulation experiments, it is confirmed that the IGA improves the calculation efficiency and accuracy of the traditional GA under the same conditions.The IGA has higher accuracy, reliability, resistance to gross interference and resistance to missing observation points. This method is obviously superior to direct inversion and conventional optimization inversion algorithms, and effectively avoids the dependence on the initial value of the probabilistic integral method parameter

A Markov Process Inspired Cellular Automata Model of Road Traffic

To provide a more accurate description of the driving behaviors in vehicle queues, a namely Markov-Gap cellular automata model is proposed in this paper. It views the variation of the gap between two consequent vehicles as a Markov process whose stationary distribution corresponds to the observed distribution of practical gaps. The multiformity of this Markov process provides the model enough flexibility to describe various driving behaviors. Two examples are given to show how to specialize it for different scenarios: usually mentioned flows on freeways and start-up flows at signalized intersections. The agreement between the empirical observations and the simulation results suggests the soundness of this new approach.Comment: revised according to the helpful comments from the anonymous reviewer

Archaeological Soybean (Glycine max) in East Asia: Does Size Matter?

The recently acquired archaeological record for soybean from Japan, China and Korea is shedding light on the context in which this important economic plant became associated with people and was domesticated. This paper examines archaeological (charred) soybean seed size variation to determine what insight can be gained from a comprehensive comparison of 949 specimens from 22 sites. Seed length alone appears to represent seed size change through time, although the length×width×thickness product has the potential to provide better size change resolution. A widespread early association of small seeded soybean is as old as 9000–8600 cal BP in northern China and 7000 cal BP in Japan. Direct AMS radiocarbon dates on charred soybean seeds indicate selection resulted in large seed sizes in Japan by 5000 cal BP (Middle Jomon) and in Korea by 3000 cal BP (Early Mumun). Soybean seeds recovered in China from the Shang through Han periods are similar in length to the large Korean and Japanese specimens, but the overall size of the large Middle and Late Jomon, Early Mumun through Three Kingdom seeds is significantly larger than any of the Chinese specimens. The archaeological record appears to disconfirm the hypothesis of a single domestication of soybean and supports the view informed by recent phyologenetic research that soybean was domesticated in several locations in East Asia

Sulforaphane Mediates Glutathione Depletion via Polymeric Nanoparticles to Restore Cisplatin Chemosensitivity

Platinum (Pt)-based chemotherapy is a widely used therapeutic regimen against various cancers. However, the insufficient cellular uptake, deactivation by thiol-containing species and nonspecific distribution of cisplatin (CDDP) result in its low chemosensitivity as well as systemic side effects, which can largely constrain the employment of CDDP in clinical treatment. To circumvent these problems, in this study, polymeric nanoparticles were utilized to co-deliver a water-soluble CDDP derivative, poly (γ, L-glutamic acid)-CDDP conjugate, and a naturally occurring compound derived from broccoli, sulforaphane, which can achieve efficient glutathione (GSH) depletion, to enhance the accumulation of CDDP in cancer cells. Results show that compared with combinational treatment of CDDP and SFN, the nanoparticles were more effectively internalized and could significantly reduce GSH content in breast cancer cells, leading to a notable increase in DNA-bound Pt and DNA damage-induced apoptosis. Moreover, in an orthotopic breast cancer model, the nanoparticles achieved a significantly higher tumor accumulation and exhibited a more powerful anti-tumor activity. Finally, this nano-enhanced chemotherapy was further confirmed in a liver cancer model with high-expression of GSH. Taken together, this sulforaphane-based nano-strategy holds great promise to enhance the sensitivity and therapeutic efficacy of Pt-based chemotherapy

Research on the Effect of the Rural Wealth-Leader on Poverty Reduction of Farmers—Based on the Questionnaire Survey in China

The rural wealth-leader is one of the 10 projects of targeted poverty alleviation in the period of poverty alleviation. As the “leading wild goose” in rural areas, the personal characteristics of the rural wealth-leader directly affect the effect of stabilizing poverty and increasing income of poor farmers. Based on the survey of the rural wealth-leader in 10 cities and 21 counties, this paper systematically analyzes the path of poverty reduction by the rural wealth-leader, combs out the key individual characteristics that affect farmers’ poverty reduction, and puts forward a research hypothesis. Through empirical analysis, the research hypothesis is tested and the influencing mechanism is analyzed. The model results show that: The rural wealth-leader has a significant effect on increasing farmers’ income and eliminating poverty. The rural wealth-leader with high education level and engaged in e-commerce has a significant effect on increasing farmers’ income. Party members and the skilled rural wealth-leaders have a significant impact on rural households’ poverty alleviation. The income increasing effect of culture and education is negatively affected by corporate loans, and the income increasing effect of e-commerce is negatively affected by corporate profits. Therefore, we should improve the profit distribution mode of e-commerce related enterprises to avoid farmers being marginalized in the process of e-commerce development. The skills, management and financial knowledge training of the rural wealth-leaders should be strengthened to improve their knowledge and skills. Meanwhile, supporting fiscal, financial and tax policies should be improved

ResE: A Fast and Efficient Neural Network-Based Method for Link Prediction

In this study, we present a novel embedding model, named ResE, for predicting links in knowledge graphs. ResE employs depth-separable convolution and residual blocks, integrated with channel attention mechanisms. ResE surpasses previously published models, including the closely related TransE model, by achieving the satisfactory mean rank (MR) and the excellent Hits@10 scores on both WN18RR and FB15K-237 benchmarks. ResE is a promising model for knowledge graph completion tasks, with potential for further investigation and extension to new applications such as user-oriented relationship modeling. Although comparatively shallow compared to computer vision convolutional architectures, future work may explore deeper convolutional models. ResE exhibits remarkable performance and outperforms existing approaches, thus setting a new benchmark for knowledge graph completion. The outcomes of our study illustrate the effectiveness of incorporating depth-separable convolution and residual blocks, accompanied by channel attention mechanisms, in modeling knowledge graphs. These findings highlight ResE’s potential to push the boundaries of cutting-edge in this domain

A turn-on fluorescent chemodosimeter based on detelluration for detecting ferrous iron (Fe2+) in living cells

A turn-on fluorescent probe for the detection of Fe2+ is facilely synthesized via a nucleophile substitution reaction. The fluorescent probe, N-butyl-4-phenyltellanyl-1,8-naphthalimide (Naph-Te), shows excellent selectivity to Fe2+ in a mixed solution of acetonitrile and phosphate buffer under aerobic conditions. The coexistence of biological abundant metal ions such as Na+, K+, Ca2+ and Mg2+ has little effect on the fluorescence signal. This turn-on response is achieved via a redox-involved reaction triggered by Fe2+ at neutral pH and room temperature, which removes the heavy-atom effect of the tellurium atom on the naphthalimide fluorophore to afford a fluorescent product (N-butyl-4-hydroxyl-1,8-naphthalimide). The probe has excellent cell membrane permeability and is further applied successfully to monitor supplementary Fe2+ in live HL-7702 cells using a laser confocal fluorescence microscope