ALBERT

Description: Previous studies of transportation network design problem (NDP) always consider one peak-hour origin-destination (O-D) demand distribution. However, the NDP based on one peak-hour O-D demand matrix might be unable to model the real traffic patterns due to diverse traffic characteristics in the morning and evening peaks and impacts of network structure and link sensitivity. This paper proposes an NDP model simultaneously considering both morning and evening peak-hour demands. The NDP problem is formulated as a bilevel programming model, where the upper level is to minimize the weighted sum of total travel time for network users travelling in both morning and evening commute peaks, and the lower level is to characterize user equilibrium choice behaviors of the travelers in two peaks. The proposed NDP model is transformed into an equivalent mixed integer linear programming (MILP), which can be efficiently solved by optimization solvers. Numerical examples are finally performed to demonstrate the effectiveness of the developed model. It is shown that the proposed NDP model has more promising design effect of improving network efficiency than the traditional NDP model considering one peak-hour demand and avoids the misleading selection of improved links.

Description: Introduction. Limited comparative studies have reported the safety and efficacy of tirofiban in acute ischemic stroke (AIS) patients after mechanical thrombectomy (MT). Additionally, the available studies are inconsistent with each other, which makes application of tirofiban unclear in neuro-intervention. Here, we performed a comparative retrospective study to investigate whether tirofiban combined with MT improves short- and long-term prognosis in AIS patients and whether its use is associated with complications. Method. Retrospective data were collected for AIS patients admitted between January 2013 and January 2019 at three stroke centers. According to whether tirofiban was used during the operation, patients were divided into tirofiban group and control group. Multivariate and COX regression analyses were performed to determine the association of tirofiban treatment with safety and efficiency in subjects treated with MT. Result. A total of 174 patients were analyzed, of whom 89 (51.1%) were treated with tirofiban. There were no differences in the incidence of symptomatic intracerebral hemorrhage (10.2% vs. 10.6%, p=0.918), parenchymal hemorrhage type 2 (18.0% vs. 16.5%, p=0.793), and reocclusion at 24 h (3.4% vs. 10.6%, p=0.060) between the tirofiban group and control group. Multivariate regression showed that tirofiban was not associated with intracerebral hemorrhage, early neurological deterioration, neurological improvement at 7 days, functional independence at 3-month and 9-month follow-up, or death at 9-month follow-up (adjusted p〉0.05 for all). However, AIS patients treated with MT + tirofiban showed a trend towards acquiring faster functional independence, with a median time to acquire functional independence of 4.0 months compared with 6.5 months in the control group (risk ratio = 1.49, 95% confidence interval 0.98–2.27; long rank p=0.066). Conclusion. Tirofiban may help AIS patients given MT to gain functional independence faster, without increasing the risk of complications.

Description: Nonnegative sparsity-constrained optimization problem arises in many fields, such as the linear compressing sensing problem and the regularized logistic regression cost function. In this paper, we introduce a new stepsize rule and establish a gradient projection algorithm. We also obtain some convergence results under milder conditions.

Description: The measured diffusion coefficient and soil-water characteristic curve (SWCC) of remolded loess were used to modify the Mualem model for increasing its accuracy. The obtained results show that the goodness of fit between the Mualem model and the variable parameter-modified Mualem method comparing with the test results was not high. The saturation of 0.65 was introduced as the boundary to divide the curve of the measured diffusion coefficient into two segments. When the segmentation method combined with the variable parameter method was used to modify the Mualem model, the fitting correlation coefficient was increased to 0.921–0.998. The modified parameters Ko and L corresponding to remolded loess were calculated for different dry densities. Based on the exponential function between Ko and dry density and the linear relation between L and dry density, the segmentally modified Mualem model was established for remolded loess by considering variation in dry density. The results of the study can be used for directly determining the unsaturated infiltration coefficient and for indirectly determining the SWCC through diffusion coefficient.

Description: The interpolation-reconstruction of local underwater terrain using the underwater digital terrain map (UDTM) is an important step for building an underwater terrain matching unit and directly affects the accuracy of underwater terrain matching navigation. The Kriging method is often used in terrain interpolation, but, with this method, the local terrain features are often lost. Therefore, the accuracy cannot meet the requirements of practical application. Analysis of the geographical features is performed on the basis of the randomness and self-similarity of underwater terrain. We extract the fractal features of local underwater terrain with the fractal Brownian motion model, compensating for the possible errors of the Kriging method with fractal theory. We then put forward an improved Kriging interpolation method based on this fractal compensation. Interpolation-reconstruction tests show that the method can simulate the real underwater terrain features well and that it has good usability.

Description: In this study, the failure behaviors of debris flows were studied by flume model tests with artificial rainfall and numerical simulations (PFC3D). Model tests revealed that grain sizes distribution had profound effects on failure mode, and the failure in slope of medium sand started with cracks at crest and took the form of retrogressive toe sliding failure. With the increase of fine particles in soil, the failure mode of the slopes changed to fluidized flow. The discrete element methodPFC3Dcan overcome the hypothesis of the traditional continuous medium mechanic and consider the simple characteristics of particle. Thus, a numerical simulations model considering liquid-solid coupled method has been developed to simulate the debris flow. Comparing the experimental results, the numerical simulation result indicated that the failure mode of the failure of medium sand slope was retrogressive toe sliding, and the failure of fine sand slope was fluidized sliding. The simulation result is consistent with the model test and theoretical analysis, and grain sizes distribution caused different failure behavior of granular debris flows. This research should be a guide to explore the theory of debris flow and to improve the prevention and reduction of debris flow.

Description: Aimed at the multidimensional and complex characteristic of airport competitiveness, a new algorithm is proposed in which BP neural network is optimized by improved double chains quantum genetic algorithm (IDCQGA-BP). The new algorithm is better than existing algorithms in convergence and the diversity of quantum chromosomes. The empirical data of eight airports in Yangtze River Delta in 2011 and 2012 is applied to verify the feasibility of the new algorithm, and then the competitiveness of the eight airports from 2013 to 2015 is gotten through the algorithm. The results show the following. (1) The new algorithm is better than the existing optimization algorithms in the aspects of error accuracy and run time. (2) The gaps of the airports in Yangtze River Delta are narrowing; the competition and cooperation are getting stronger and stronger. (3) The main increase reason of airport competitiveness is the increase of own investment.

Description: As railroad infrastructure becomes older and older and rail transportation is developing towards higher speed and heavier axle, the risk to safe rail transport and the expenses for railroad maintenance are increasing. The railroad infrastructure deterioration (prediction) model is vital to reducing the risk and the expenses. A short-range track condition prediction method was developed in our previous research on railroad track deterioration analysis. It is intended to provide track maintenance managers with two or three months of track condition in advance to schedule track maintenance activities more smartly. Recent comparison analyses on track geometrical exceptions calculated from track condition measured with track geometry cars and those predicted by the method showed that the method fails to provide reliable condition for some analysis sections. This paper presented the enhancement to the method. One year of track geometry data for the Jiulong-Beijing railroad from track geometry cars was used to conduct error analyses and comparison analyses. Analysis results imply that the enhanced model is robust to make reliable predictions. Our in-process work on applying those predicted conditions for optimal track maintenance scheduling is discussed in brief as well.

Description: Previous studies of transportation network design problem (NDP) always consider one peak-hour origin-destination (O-D) demand distribution. However, the NDP based on one peak-hour O-D demand matrix might be unable to model the real traffic patterns due to diverse traffic characteristics in the morning and evening peaks and impacts of network structure and link sensitivity. This paper proposes an NDP model simultaneously considering both morning and evening peak-hour demands. The NDP problem is formulated as a bilevel programming model, where the upper level is to minimize the weighted sum of total travel time for network users travelling in both morning and evening commute peaks, and the lower level is to characterize user equilibrium choice behaviors of the travelers in two peaks. The proposed NDP model is transformed into an equivalent mixed integer linear programming (MILP), which can be efficiently solved by optimization solvers. Numerical examples are finally performed to demonstrate the effectiveness of the developed model. It is shown that the proposed NDP model has more promising design effect of improving network efficiency than the traditional NDP model considering one peak-hour demand and avoids the misleading selection of improved links.

Description: Hypertension is a highly prevalent risk factor for cardiovascular disease and it can also lead to other diseases which seriously harm the human health. Screening the risks and finding a clinical model for estimating the risk of onset, maintenance, or the prognosis of hypertension are of great importance to the prevention or treatment of the disease, especially if the indicator can be derived from simple health profile. In this study, we investigate a chronic disease questionnaire data set of 6563 rural citizens in East China and find out a clinical signature that can assess the risk of hypertension easily and accurately. The signature achieves an accuracy of about 83% on the external test dataset, with an AUC of 0.91. Our study demonstrates that a combination of simple lifestyle features can sufficiently reflect the risk of hypertension onset. This finding provides potential guidance for disease prevention and control as well as development of home care and home-care technologies.