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WeChat is the largest acquaintance social networking platform in China, in which users can view and reshare web pages shared by friends. This paper aims to analyze the spatio-temporal dynamics of web pages diffused in WeChat and advice on commercials.

A large number of web pages diffused in WeChat are collected and exclusively divided into four categories according to their titles, including advertisements, news bulletins, holiday greetings and emotional essays. For each web page, an information cascade (tree structure) is constructed to describe the diffusion trace. Based on the categories, the spatio-temporal popularity is characterized; the topological, temporal and spatial properties are examined; and the spatio-temporal diffusion velocity is explored.

Through comparative analysis, different categories of pages show diversity. For spatio-temporal popularity, there is no significant difference in cascade size; holiday greetings usually last for a relatively short time on average; emotional essays are more likely to spread to more provinces. For topological, temporal and spatial characteristics, the diffusion process of advertisements is more likely to be broadcasting than other categories; news bulletins and holiday greetings have an obvious bursty; the number of viewing behavior decreases from east to west in general. For spatio-temporal diffusion velocity, emotional essays diffuse the fastest in topological and spatio-temporal dimensions.

These findings contribute to promoting products and providing support for data driven modeling of information diffusion and human activity in spatio-temporal dimensions.

The purpose of this paper is to analyze the characteristics of spatio-temporal dynamics and the evolution of land use change is essential for understanding and assessing the status and transition of ecosystems. Such analysis, when applied to Horqin sandy land, can also provide basic information for appropriate decision-making.

By integrating long time series Landsat imageries and geographic information system (GIS) technology, this paper explored the spatio-temporal dynamics and evolution-induced land use change of the largest sandy land in China from 1983 to 2016. Accurate and consistent land use information and land use change information was first extracted by using the maximum likelihood classifier and the post-classification change detection method, respectively. The spatio-temporal dynamics and evolution were then analyzed using three kinds of index models: the dynamic degree model to analyze the change of regional land resources, the dynamic change transfer matrix and flow direction rate to analyze the change direction, and the barycenter transfer model to analyze the spatial pattern of land use change.

The results indicated that land use in Horqin sandy land during the study period changed dramatically. Vegetation and sandy land showed fluctuating changes, cropland and construction land steadily increased, water body decreased continuously, and the spatial distribution patterns of land use were generally unbalanced. Vegetation, sandy land and cropland were transferred frequently. The amount of vegetation loss was the largest. Water body loss was 473.6 km², which accounted for 41.7 per cent of the total water body. The loss amount of construction land was only 1.0 km². Considerable differences were noted in the rate of gravity center migration among the land use types in different periods, and the overall rate of construction land migration was the smallest. Moreover, the gravity center migration rates of the water body and sandy land were relatively high and were related to the fragile ecological environment of Horqin sandy land.

The results not only confirmed the applicability and effectiveness of the combined method of remote sensing and GIS technology but also revealed notable spatio-temporal dynamics and evolution-induced land use change throughout the different time periods (1983-1990, 1990-2000, 2000-2010, 2010-2014, 2014-2016 and 1983-2016).

This paper aims to describe two Web-based technologies of geographic information systems (GIS) to be used in monitoring and analysis of environmental processes, proposed by the authors. The technologies analyze the temporal aspect of the process together with the spatial aspect, which defers them from most other works on environmental processes, as these are usually limited either to spatial statistics or to temporal statistics. The approach is instrumental in dynamically finding the relationships between the processes and predicting critical incidents.

Often, the study of natural processes is limited to the analysis of their spatial properties presented by individual time series. The principal idea of this approach consists in supplementing this traditional analysis with the analysis of time fields. In this way, the authors are able to analyze temporal and spatial properties of environmental processes together.

The paper presents two technologies which provide the analysis of spatial and temporal data obtained in natural environment monitoring. The discussed spatio-temporal data mining methods are shown to enable the research into environmental processes, and the solution of practical issues of critical situation forecasts.

The paper discussed Web-based GIS technologies for the analysis of the temporal aspect of the environmental process together with the spatial aspect. Application examples demonstrate the ability of this approach to find the relationships in dynamics of the processes and to predict critical incidents.

This study aims to investigate the cross-sectional reshaping in transitioning/starting rectangular jets of aspect ratio 2 under various inlet perturbation conditions at the Reynolds number of Re = UD_h/v = 17,750.

Large eddy simulation results compared with the phase-locked particle image velocimetry data exhibit the cross-sectional jet deformations from rectangular to rounder shapes. Inflow velocity oscillations are introduced at the fundamental frequency associated with the Kelvin–Helmholtz instability characterized by the spectral analysis of the hotwire data and the linear stability predictions.

The initially rectangular cross-section of the jet reshapes into the rounder geometries with increased downstream distance while the edges of the jet become distorted due to the shear layer instability more significantly observed near the high curvature corners. The different expansion rates in the longer and shorter edges of the jet and the consequent cross-sectional reshaping are found to be sensitive to small levels of random inlet perturbations. In addition, introducing controlled sinusoidal oscillations results in the formation of more organized trailing shear layer where the stronger vortex rings go through the curvature-induced deformations.

Spatio-temporal study of vortex dynamics in transitioning rectangular jets reveals important information about the effect of the controlled jet forcing on local entrainment. Dynamics of the leading vortex dominates the entrainment in transitioning jets which are commonly used in practical applications. Near-field entrainment is also promoted proportional to the amplitude of the controlled inlet oscillations within the trailing vortex rings.

The purpose of this paper is twofold: first is to examine the changing spatio-temporal patterns and regional trends in residential fires; and second is to investigate the likely association of fire risk with seasons, calendar events and socio-economic disadvantage.

Using spatial analytic and predictive techniques, 11 years of fire incident data supplied by the Queensland Fire and Emergency Services are mapped and analysed.

The results show significant spatial and temporal variability in the distribution of residential fires. Residential fire incidents are more likely to occur in the inner city and across more disadvantaged areas. Mapped outputs show some areas in Brisbane at a higher risk of fire than others and that the risk of fire escalates at specific times of the year, in neighbourhoods with a higher disadvantage, during major sporting events and school holidays. The residential fires showed strong seasonal periodicity. There is a continuous yet gradual increase in the number of fire incidents recorded for all five sub-regions within SEQ. Sunshine Coast experienced the highest upward trend whereas Toowoomba and West Moreton show the lowest increase.

This study provides an empirical basis to guide future operational strategies through targeting high fire risk areas at particular times. This, in turn, will help utilise finite resources in areas where and when they need and thus enable minimise emergency management costs.

The purpose of this paper is to model housing price temporal variations and to predict price trends within the context of land use–transportation interactions using machine learning methods based on longitudinal observation of housing transaction prices.

This paper examines three machine learning algorithms (linear regression machine learning (ML), random forest and decision trees) applied to housing price trends from 2001 to 2016 in the Greater Toronto and Hamilton Area, with particular interests in the role of accessibility in modelling housing price. It compares the performance of the ML algorithms with traditional temporal lagged regression models.

The empirical results show that the ML algorithms achieve good accuracy (R² of 0.873 after cross-validation), and the temporal regression produces competitive results (R² of 0.876). Temporal lag effects are found to play a key role in housing price modelling, along with physical conditions and socio-economic factors. Differences in accessibility effects on housing prices differ by mode and activity type.

Housing prices have been extensively modelled through hedonic-based spatio-temporal regression and ML approaches. However, the mutually dependent relationship between transportation and land use makes price determination a complex process, and the comparison of different longitudinal analysis methods is rarely considered. The finding presents the longitudinal dynamics of housing market variation to housing planners.

With the development of global food markets, the structural properties of supply chain networks have become key factors affecting the ability to evaluate and control infectious diseases and food contamination. The purpose of this paper is to describe and characterize the nationwide pork supply chain networks (PSCNs) in China and to demonstrate the potential of using social network analysis (SNA) methods for accessing outbreaks of diseases and contaminations.

A large-scale PSCN with 17,582 nodes and 49,554 edges is constructed, using the pork trade data collected by the National Important Products Traceability System (NIPTS) in China. A network analysis is applied to investigate the static and dynamic characteristics of the annual network and monthly networks. Then, the metric maximum spreading capacity (MSC) is proposed to quantify the spreading capacity of farms and estimate the potential maximum epidemic size. The structure of the network with the spatio-temporal pattern of the African swine fever (ASF) outbreak in China in 2018 was also analysed.

The results indicate that the out-degree distribution of farms approximately followed a power law. The pork supply market in China was active during April to July and December to January. The MSC is capable of estimating the potential maximum epidemic size of an outbreak, and the spreading of ASF was positively correlated with the effective distance from the origin city infected by ASF, rather than the geographical distance.

Empirical research on PSCNs in China is scarce due to the lack of comprehensive supply chain data. This study fills this gap by systematically examining the nationwide PSCN of China with large-scale reliable empirical data. The usage of MSC and effective distance can inform the implementation of risk-based control programmes for diseases and contaminations on PSCNs.

The purpose of this paper is to quantify the relative importance of the multiphase model for the simulation of a gas bubble impacted by a normal shock wave in water. Both the free-field case and the collapse near a wall are investigated. Simulations are performed on both two- and three-dimensional configurations. The main phenomena involved in the bubble collapse are illustrated. A focus on the maximum pressure reached during the collapse is proposed.

Simulations are performed using an inviscid compressible homogeneous solver based on different systems of equations. It consists in solving different mixture or phasic conservation laws and a transport-equation for the gas volume fraction. Three-dimensional configurations are considered for which an efficient massively parallel strategy was developed. The code is based on a finite volume discretization for which numerical fluxes are computed with a Harten, Lax, Van Leer, Contact (HLLC) scheme.

The comparison of three multiphase models is proposed. It is shown that a simple four-equation model is well-suited to simulate such strong shock-bubble interaction. The three-dimensional collapse near a wall is investigated. It is shown that the intensity of pressure peaks on the wall is drastically increased (more than 200 per cent) in comparison with the cylindrical case.

The study of bubble collapse is a key point to understand the physical mechanism involved in cavitation erosion. The bubble collapse close to the wall has been addressed as the fundamental mechanism producing damage. Its general behavior is characterized by the formation of a water jet that penetrates through the bubble and the generation of a blast wave during the induced collapse. Both the jet and the blast wave are possible damaging mechanisms. However, the high-speed dynamics, the small spatio-temporal scales and the complicated physics involved in these processes make any theoretical and experimental approach a challenge.

Cavitation erosion is a major problem for hydraulic and marine applications. It is a limiting point for the conception and design of such components.

Such a comparison of multiphase models in the case of a strong shock-induced bubble collapse is clearly original. Usually models are tested separately leading to a large dispersion of results. Moreover, simulations of a three-dimensional bubble collapse are scarce in the literature using such fine grids.

System dynamics is a whole-system modelling and learning approach, useful for tackling non-linear problems, such as sustainable urban development. The purpose of this paper is to review system dynamics applications in the simulation of sustainable urban development over a period from 2005 to 2017.

The analysis reveals that the number of applications of system dynamics modelling in the area of urban sustainable development increased in the analysed period. Research has changed its focus from the modelling of environmental problems to more complex models, portraying the multidimensional socio-economic processes that have an impact on the sustainability of urban development. Analysed case studies most often use the behaviour reproduction test for model validation, but without a unified approach. In most cases, modelling has been done in China, Germany and the USA, while urban development in the Eastern European countries, Africa and Latin America has not often been investigated. This paper indicates the knowledge gaps and suggests future research directions.

Papers that report the use of system dynamics modelling reveal a wide range of applications in urban sustainability. The analysis shows significant emphasis on environmental problems, while the interest for modelling social problems has been increasing during the last several years. Most of the modelled problems examine the sustainability of resources (land, water) and waste management, which are used for insights into the reasons for the system behaviour, forecasting future behaviour and policy testing.

The presented models were developed in most cases for the purpose of understanding the phenomena examined, as well as the future use of the models in policy planning. This brings us back to the need for greater stakeholder involvement, not only in the initial phase, but also during the whole modelling process, which could increase understanding, use and ownership of the models in the future, and thus increase their practical application.

The purpose of this paper is to extend an analysis presented in earlier work which investigated the dynamical behavior of a network of oscillatory units described by the amplitude of and phase of oscillations, and to present an objective function that can be successfully applied to multi‐layer networks.

In this paper, an objective function is presented that can be successfully applied to multi‐layer networks. The behavior of the objective function is explained through its ability to achieve a sparse representation of the inputs in complex‐valued space.

It is found that if the activity of each network unit is represented by a phasor in the complex plane, then sparsity is achieved when there is maximal phase separation in the complex plane. Increasing the spread of feedback connections is shown to improve segmentation performance significantly but does not affect separation performance. This enables a quantitative approach to characterizing and understanding cortical function.

The formulation of the multi‐layer objective function and the interpretation of its behavior through sparsity in complex space are novel contributions of this paper.