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Coronary chronic total occlusion (CTO) contributes to the progression of heart failure in patients with ischemic cardiomyopathy. Randomized controlled trials demonstrated that percutaneous coronary intervention (PCI) for CTO significantly improves angina symptoms and quality of life but fails to reduce clinical events compared with optimal medical therapy. Even so, intervening physicians strongly support CTO-PCI. Cardiac regeneration therapy after CTO-PCI should be a promising approach to improving the prognosis of ischemic cardiomyopathy. However, the relationship between CTO revascularization and cardiac regeneration has rarely been studied, and experimental studies on cardiac regeneration usually employ rodent models with permanent ligation of the coronary artery rather than reopening of the occlusive artery. Limited early-stage clinical trials demonstrated that cell therapy for cardiac regeneration in ischemic cardiomyopathy reduces scar size, reverses cardiac remodeling, and promotes angiogenesis. This review focuses on the status quo of CTO-PCI in ischemic cardiomyopathy and the clinical prospect of cardiac regeneration in this setting.

The importance of understanding human mobility patterns has led many studies to examine their spatial-temporal scaling laws. These studies mainly reveal that human travel can be highly non-homogeneous with power-law scaling distributions of distances and times. However, investigating and quantifying the extent of variability in time and space when traveling the same air distance has not been addressed so far. Using taxi data from five large cities, we focus on several novel measures of distance and time to explore the spatio-temporal variations of taxi travel routes relative to their typical routes during peak and nonpeak periods. To compare all trips using a single measure, we calculate the distributions of the ratios between actual travel distances and the average travel distance as well as between actual travel times and the average travel time for all origin destinations (OD) during peak and nonpeak periods. In this way, we measure the scaling of the distribution of all single trip paths with respect to their mean trip path. Our results surprisingly demonstrate very broad distributions for both the distance ratio and time ratio, characterized by a long-tail power-law distribution. Moreover, all analyzed cities have larger exponents in peak hours than in nonpeak hours. We suggest that the interesting results of shorter trip lengths and times, characterized by larger exponents during rush hours, are due to the higher availability of travelers in rush hours compared to non-rush hours...

Background: Both clotrimazole and ketoconazole have been verified to have an inhibitory effect on CYP3A4. hCE2 is an enzyme closely related to the side effects of several anti-cancer drugs. However, the interactions between hCE2, clotrimazole, and ketoconazole remain unclear. Objective: The objective of this study was to investigate and compare the inhibition behaviors of the two antifungal agents, ketoconazole and clotrimazole, on the human liver microsome hCE2 and to explore their underlying mechanism. Methods: The inhibitory effects were investigated in human liver microsomes (HLMs) using fluorescein diacetate (FD), N-(2-butyl-1,3-dioxo-2,3-dihydro-1H-phenalen-6-yl)-2-chloroacetamide (NCEN) and irinotecan (CPT- 11) as substrates of hCE2. Results: Clotrimazole significantly inhibited the hCE2 activity, which was manifested by attenuated fluorescence when the substrates were FD and NCEN. The inhibitory effect of clotrimazole towards hCE2 was much stronger than that of ketoconazole, and the inhibitory behaviors displayed substrate-dependent inhibition. The IC50 value of clotrimazole, with CPT-11 as the substate, increased by 5 and 37 times more than that with FD and NCEN, respectively. Furthermore, the inhibitions of clotrimazole towards hCE2-mediated hydrolysis of FD, NCEN, and CPT-11 were all in competitive mode with the Ki values of 0.483 μM, 8.63 μM, and 29.0 μM, respectively. Molecular docking result of clotrimazole binding to hCE2 illustrated that clotrimazole could efficiently orient itself in the Z site cavity of hCE2. Conclusion: Clotrimazole displayed a strong inhibitory effect against hCE2, which might be used as a potential combined agent co-administrated with CPT-11 to alleviate the hCE2-mediated severe side effects.

A novel three-dimensional cellular automata evacuation model was proposed based on stairs factor for paired effect and variety velocities in pedestrian evacuation. In the model pedestrians' moving probability of target position at the next moment was defined based on distance profit and repulsive force profit, and evacuation strategy was elaborated in detail through analyzing variety velocities and repulsive phenomenon in moving process. At last, experiments with the simulation platform were conducted to study the relationships of evacuation time, average velocity and pedestrian velocity. The results showed that when the ratio of single pedestrian was higher in the system, the shortest route strategy was good for improving evacuation efficiency; in turn, if ratio of paired pedestrians was higher, it is good for improving evacuation efficiency to adopt strategy that avoided conflicts, and priority should be given to scattered evacuation.

Finding the influence of traffic accident on the road is helpful to analyze the characteristics of traffic flow, and take reasonable and effective control measures. Here, the detrended fluctuation analysis method is applied to investigate the complexity of time series in mixed traffic flow with a blockage induced by an accident. As a parameter to depict the long-term evolutionary behavior of the time series in traffic flow, the scaling exponent is analyzed. According to the scaling exponent, it is shown that the traffic flow time series can display long-range correlation characteristics, short-range correlation characteristics, and non-power-law relation in the long-range correlation characteristics, which is strongly dependent on the entering probability of vehicle, the ratio of slow vehicle and the blockage duration time.

SUMMARY This paper investigates the optimal transit fare in a simple bimodal transportation system that comprises public transport and private car. We consider two new factors: demand uncertainty and bounded rationality. With demand uncertainty, travelers are assumed to consider both the mean travel cost and travel cost variability in their mode choice decision. Under bounded rationality, travelers do not necessarily choose the travel mode of which perceived travel cost is absolutely lower than the one of the other mode. To determine the optimal transit fare, a bi-level programming is proposed. The upper-level objective function is to minimize the mean of total travel cost, whereas the lower-level programming adopts the logit-based model to describe users' mode choice behaviors. Then a heuristic algorithm based on a sensitivity analysis approach is designed to solve the bi-level programming. Numerical examples are presented to illustrate the effect of demand uncertainty and bounded rationality on the modal share, optimal transit fare and system performance. Copyright © 2013 John Wiley & Sons, Ltd.

In production market, the decision-making patterns of firms producing a homogeneous kind of products are different. Some are under the control of a dominant firm called centralized pattern. In this case, there is only one decision maker who takes charge of all the firms and attempts to maximize the total utility of the system. Another is decentralized pattern, in which firms plan by themselves. In reality, there always exists a third pattern, where the centralized pattern and decentralized pattern firms are in the same market. This article deals with the last case and studies the effects of decentralized pattern firms’ decisions on centralized pattern firms in the same market, which is described as a Stackelberg game. It is supposed that centralized pattern firms are the leaders who affect the whole market by adjusting the production of each firm. Decentralized pattern firms are the followers who determine their productions in a manner of competitive equilibrium against the given centralized firm’s strategy. This game in this article is formulated as a bilevel programming model. Solution algorithm based on the sensitivity analysis is adopted to solve the model, and a numerical example is given to illustrate the model and algorithm.

SUMMARY This study developed a methodology to model the passenger flow stochastic assignment in urban railway network (URN) with the considerations of risk attitude. Through the network augmentation technique, the urban railway system is represented by an augmented network in which the common traffic assignment method can be used directly similar to a generalized network form. Using the analysis of different cases including deterministic travel state, emergent event, peak travel, and completely stochastic state, we developed a stochastic equilibrium formulation to capture these stochastic considerations and give effects of risk aversion level on the URN performance, the passenger flow at transfer stations through numerical studies. Copyright © 2012 John Wiley & Sons, Ltd.

In this paper, by considering benefits of customers and logistics planning departments, a bi-level programming model is presented to seek the optimal location for logistics distribution centers. The upper-level model is to determine the optimal location by minimizing the planners’ cost, and the lower gives an equilibrium demand distribution by minimizing the customers’ cost. Based on the special form of constraints, a simple heuristic algorithm is proposed. Finally, a numerical example is used to illustrate the application of the method, which shows that the algorithm is feasible and advantageous.

The origin and destination (O-D) matrix estimation is an important problem in traffic networks. We apply the gravitation model to express the preference attachment and to analyse the statistical characteristics of the traffic flow in each O-D pair in theory. It is found that the distribution of the future O-D matrix decays as a power law. Additionally, different exponents are obtained for both the constant and variable link cost.

In this paper, based on the utility preferential attachment, we propose a new unified model to generate different network topologies such as scale-free, small-world and random networks. Moreover, a new network structure named super scale network is found, which has monopoly characteristic in our simulation experiments. Finally, the characteristics of this new network are given.

A new model for network generation is proposed by considering both the preferential and random attachments with aging. The connectivity distribution is obtained with the mean-field theory. The simulation results show that the model can be used to generate such networks with different topology structures as random and scale-free ones. The networks with different densities (i.e., the average connectivity degrees) can also be generated by the model.

Sharing market information has been recognized as an effective approach to reduce demand distortion and improve supply chain performance. This paper proposes a bilevel model to solve the location problem by considering information sharing effects. The upper level is to determine the optimal location of logistics centers, and the lower is to obtain the demand assignments among different centers with a fixed-point problem. The Chaotic Optimization Algorithm (COA) is used to solve the model. And a simple example is given to illustrate the method.

In this paper, the author used the full-wave electromagnetic simulation to research the narrowband low-loss miniaturization HTS diplexer. The diplexer is manufactured on the double-sided HTS YBCO film on a LaAlO3 substrate of 0.5 mm. The miniaturization and low insertion loss of electron devices are realized using the advantage that the quality factor of HTS film is 1~3 orders higher than normal metals.

The detrended fluctuation analysis method is applied to analyse the complexity of traffic flow time series and the scale index is obtained, which is a parameter to depict the long term evolutionary behaviour of the mixed traffic flow time series. According to the changes of the scale index, it is shown that the traffic flow time series has long-range correlation characteristics or short-range correlation characteristics. It is found that the traffic flow series shows long-range correlation when the density ρ12; and when ρ1 or ρ>ρ2, the time series displays short-range correlation. That is to say, the vehicle density plays an important role in the changes of the scale index. Additionally, we also found that the ratio of slow vehicles have influence on the changes of the scale index.