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The purpose of this paper is to uncover the relationship between flows and real estate investment at open-ended real estate funds (OEREFs).

The study employs fixed-effects panel regressions, relying on data from the Hungarian fund managers’ trade association. First, the effect of lagged flows on allocation to real estate is assessed. Second, the paper studies how this relationship changes as the cyclical position of CRE market advances using two proxies.

Flows are found to affect funds’ real estate holdings if they occurred 12–18 months earlier. Inflows (outflows) in the preceding six months demonstrably lower (increase) funds’ real estate holdings ratio. Beyond this relationship, findings do not suggest that less funds are channelled to real estate as “CRE heat” intensifies.

In an environment marked by strong cash inflows, the investment lag can translate into a significant drop in funds’ exposure to real estate. The share of real estate at Hungarian funds in the sample, for example, fell from 79 to 50 per cent on average over the period of 2011–2017. Measures designed to limit inflows are in the interest of those existing investors who wish to avoid a dilution of the core investment strategy.

The paper adds to the literature on OEREFs which has been particularly scarce on liquidity transformation during non-crisis times and on non-German funds.

Urban networks are usually divided into several open or closed sub‐networks. Signal coordination has been recognized as one of the most efficient methods of controlling sub‐networks that have independently optimized timing plans. However, coordinating adjacent intersections in a network is a basic prerequisite to optimizing signal‐timing plans for sub‐networks. This paper aims to develop a linear model to support decisions regarding coordination of adjacent signals.

This paper aims to develop a linear model to support decisions regarding coordination of adjacent signals. The tests of this model which using the field data differ from those for calibration from various roadways, indicating that the model has transferability. Evaluations using microscopic simulation show that the model can objectively determine whether or not to interconnect adjacent signals depending on various traffic demands.

The model was calibrated by stepwise regression analysis with a total of 195 field samples. This model consists of the dependent variable critical block length (CL) between adjacent intersections, and the independent variables original platoon size (OPS) and platoon completeness ratio (PCR). The calibrated model is shown as following: CL = 689.97 + 6.86 OPS−7.15 PCR.

The proposed model appears to be a viable solution for determining whether to coordinate adjacent signals according to various traffic demands for variously configured roadways. The model shows that a larger OPS or a smaller PCR implies a larger CL. The model also indicates that adjacent signals must be interconnected if they are separated by 690 meters or less. The results also suggest that OPS from 10 to 30 fully disperse at about 800 meters downstream of a stop line. The results support the CL for effectively coordinating adjacent signals, similar to that recommended in the Manual on Uniform Traffic Control Devices. These results may be useful for the effective management of traffic signal networks.

Nowadays, transportation authorities in various countries are in tension as to whether to invest in railroads or roads. There are arguments for each side, and in the end, each transportation authority reaches a kind of balance between the investments. This study aims to anticipate how autonomous vehicles will influence this decision.

The roads' capacity in the era of autonomous vehicles is assessed and research has concluded that the anticipated increase in road capacity will encourage transportation authorities to invest much more in roads than in railroads.

The appearance of the autonomous vehicles will significantly change the balance in favor of the roads, because the roads' capacity will be increased substantially so the roads will be able to accommodate many more vehicles.

Currently, autonomous vehicles are still very rare.

The impact of autonomous vehicles on the decision whether to build more roads is explained.

The study explained why the transportation authorities in the various countries will be more inclined to switch to road construction and why the transition to more roads and fewer railroads will likely be done gradually as more autonomous vehicles enter service.

This study aims to provide resiliency against earthquakes to the framework of an urban road network and to construct a comprehensive model with sufficient computational detail to assist metropolitan managers as a decision support tool in emergency situations via parametric analysis (model behaviour analysis with parameter changes) to quantify the consequences of decisions.

Performed stages are: developing existing resilience assessment frameworks for use against earthquakes in urban road networks, identifying earthquake scenarios and estimating the weight of components using AHP, including an example modelling of Tehran; and developing modelling software (using Matlab®).

This study produced a software that performs three-dimensional (3D) graphical modelling, resiliency index measurements and its parametric analyses for the road networks against earthquakes. Based on this model, a prioritized list of upgrades is also introduced. The developed tool also addresses issues regarding the allocation of limited resources between the network components.

Because of the novelty of the study, there is limited literature on this topic.

The developed model provides urban managers with a comprehensive list of upgrades and empowering them to graphically and numerically evaluate the resiliency changes as they alter the parameters of these measures and balance their decisions based on available funding.

In contrast to previous studies, this study has focused on all of these three keywords: resiliency, earthquake and road networks, and not only two of them.

This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane (CLL) intersections.

The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness. The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique.

The proposed model has a promising control effect under different geometric controlled conditions. Moreover, the proposed model performs robustly under various safety time headways, lengths of the CLL and green times of the main signal.

This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections. The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness

The purpose of this paper is to develop a general numerical solution for the wetting fluid spread into porous media that can be used in solving of droplet spread into soils, printing applications, fuel cells, composite processing.

A discrete capillary network model based on micro‐force balance is numerically implemented and the flow for an arbitrary capillary number can be solved. At the fluid interface, the boundary condition that accounts for the capillary pressure jump is used.

The wetting fluid spread into porous medium starts as a single‐phase flow, and after some particular number of the porous medium characteristic length scales, the multi‐phase flow pattern occurs. Hence, in the principal flow direction, the phase content (saturation) decreases, and in the lower limit for the capillary number sufficiently small, the saturation should become constant. This qualitative saturation behavior is observed irrespective of the flow dimensionality, whereas the quantitative results vary for different flow systems.

The numerical solution has to be expanded to solve the spread of the fluid in the porous medium after there is no free fluid left at the porous medium surface.

It is shown that the multi‐phase flow can develop even on a small domain due to the porous medium heterogeneity. Neglecting the medium heterogeneity and flow type can lead to a large error as shown for the droplet spread time in the porous medium.

This is believe to be the only paper relating to solving the droplet spread into porous medium as a multi‐phase flow problem.

This paper aims to present an efficient IMPES algorithm based on a global model order reduction method, proper orthogonal decomposition (POD), to achieve the fast solution and prediction of two-phase flows in porous media.

The key point of the proposed algorithm is to establish an accurate POD reduced-order model (ROM) for two-phase porous flows. To this end, two projection methods including projecting the original governing equations (Method I) and projecting the discrete form of original governing equations (Method II) are respectively applied to construct the POD-ROM, and their distinctions are compared and analyzed in detail. It is found the POD-ROM established by Method I is inapplicable to multiphase porous flows due to its failed introduction of fluid saturation and permeability that locate on the edge of grid cell, which would lead to unphysical results.

By using Method II, an efficient IMPES algorithm that can substantially speed up the simulation of two-phase porous flows is developed based on the POD-ROM. The computational efficiency and numerical accuracy of the proposed algorithm are validated through three numerical examples, and simulation results illustrate that the proposed algorithm displays satisfactory computational speed-up (one to two orders of magnitude) without sacrificing numerical accuracy obviously when comparing to the standard IMPES algorithm that without any acceleration technique. In addition, the determination of POD modes number, the relative errors of wetting phase pressure and saturation, and the influence of POD modes number on the overall performances of the proposed algorithm, are investigated.

1. Two projection methods are applied to establish the POD-ROM for two-phase porous flows and their distinctions are analyzed. The reason why POD-ROM is difficult to be applied to multiphase porous flows is clarified firstly in this study. 2. A highly efficient IMPES algorithm based on the POD-ROM is proposed to accelerate the simulation of two-phase porous flows. 3. Satisfactory computational speed-up (one to two orders of magnitude) and prediction accuracy of the proposed algorithm are observed under different conditions.