Nowadays, autonomous driving cars have become commercially available. However, the safety of a self-driving car is still a challenging problem that has not been well studied. Motion prediction is one of the core functions of an autonomous driving car. In this paper, we propose a novel scheme called GRIP which is designed to predict trajectories for traffic agents around an autonomous car efficiently. GRIP uses a graph to represent the interactions of close objects, applies several graph convolutional blocks to extract features, and subsequently uses an encoder-decoder long short-term memory (LSTM) model to make predictions. The experimental results on two wellknown public datasets show that our proposed model improves the prediction accuracy of the state-of-the-art solution by 30%. The prediction error of GRIP is one meter shorter than existing schemes. Such an improvement can help autonomous driving cars avoid many traffic accidents. In addition, the proposed GRIP runs 5x faster than the state-of-the-art schemes.

The reaction-diffusion Holling-Tanner predator-prey model with Neumann boundary condition is considered. We perform a detailed stability and Hopf bifurcation analysis and derive conditions for determining the direction of bifurcation and the stability of the bifurcating periodic solution. For partial differential equation (PDE), we consider the Turing instability of the equilibrium solutions and the bifurcating periodic solutions. Through both theoretical analysis and numerical simulations, we show the bistability of a stable equilibrium solution and a stable periodic solution for ordinary differential equation and the phenomenon that a periodic solution becomes Turing unstable for PDE.

No abstract

We collected data from Kailuan cohort study from 2006 to 2011 to examine whether short-term effects of ambient temperature on heart rate (HR) and blood pressure (BP) are non-linear or linear, and their potential modifying factors. The HR, BP and individual information, including basic characteristics, life style, socio-economic characteristics and other characteristics, were collected for each participant. Daily mean temperature and relative humidity were collected. A regression model was used to evaluate associations of temperature with HR and BP, with a non-linear function for temperature. We also stratified the analyses in different groups divided by individual characteristics. 47,591 residents were recruited. The relationships of temperature with HR and BP were “V” shaped with thresholds ranging from 22 °C to 28 °C. Both cold and hot effects were observed on HR and BP. The differences of effect estimates were observed among the strata of individual characteristics. The effect estimate of temperature was higher among older people. The cold effect estimate was higher among people with lower Body Mass Index. However, the differences of effect estimates among other groups were inconsistent. These findings suggest both cold and hot temperatures may have short-term impacts on HR and BP. The individual characteristics could modify these relationships.

No abstract

Sustainable development (SD) evaluations have attracted considerable attention from governments and scientific communities around the world. The objective and quantitative calculation of the importance of sustainable assessment indicators is a key problem in the accurate evaluation of SD. Traditional methods fail to quantify the coupling effects among indicators. This paper presents a weight determination approach based on the global sensitivity analysis algorithm known as the extended Fourier amplitude sensitivity test (EFAST). This method is efficient and robust and is not only able to quantify the sensitivity of the evaluation indictors to the target, but can also quantitatively describe the uncertainties among the indictors. In this paper, we analyze the sensitivity of 18 indicators in a multi-index comprehensive evaluation model and weigh the indicators in the system according to their importance. To verify the feasibility and advantages of this new method, we compare the evaluation result with the traditional entropy method. The comparison shows that the EFAST algorithm can provide greater detail in an SD evaluation. Additionally, the EFAST algorithm is more specific in terms of quantitative analysis and comprehensive aspects and can more effectively distinguish the importance of indicators.

No abstract

Guangxi is one of the provinces of Southern China with the highest incidence of alpha-thalassemia (thal). Liuzhou is the second biggest city in Guangxi. To find out the incidence of the various alpha-thal genotypes, and their distribution in the Liuzhou area, an F820 Blood Cell Analysis System was used to measure the parameters of red blood cells. A SPIFE Rapid Auto-Electrophoresis System was used to analyze the normal and abnormal hemoglobins (Hbs). Multiplex polymerase chain reaction (mPCR) was used to detect the alpha-globin genotypes. Thirty-two (2.05%) out of 7805 young couples undergoing pre-marriage counseling, were diagnosed as having an Hb H (beta4) disease. The study of 1228 cord blood samples revealed 138 newborn children carrying an alpha-thal determinant with nine different genotypes, thus making the total incidence of alpha-thal 11.24%. Among 185 cases of Hb H, 119 (64.1%) were confirmed as being deletional, and 66 cases (35.7%) nondeletional types. The severity of the Hb H diseases could be classified in the following order: alphaCSalpha/--SEA (alphaConstant (Spring)alpha/--Southeast Asia); alpha(-4.2)/--SEA; alpha(-3.7)/--SEA. Ten cases of alpha-thal determinants were found in combination with beta-thal. The mPCR technique can detect all kinds of combinations of the three common large deletions (--SEA, alpha(-4.2) and alpha(-3.7)) accurately and conveniently.