Search Results (675)

With societal progress, urban brownfields have become restrictive, and redevelopment studies have become an important part of urban renewal. In this work, we developed a two-step model for urban brownfield redevelopment, while considering the Wangping brownfield as the study area. Site suitability evaluation models for brownfield parks, agricultural picking gardens, and creative industrial centers were developed based on the elevation, slope, and surface runoff, and the evaluation results were categorized into five levels. The redevelopment plan was formulated based on these evaluation results. To study the effect of the plan, a transition matrix of land use was assessed using satellite images and the cellular automata (CA)–Markov model; based on the analysis, we predicted the land use situation of the Wangping brownfield, with respect to natural development, for 2030. A comparison of the redevelopment planning with the forecasted results revealed that the proportions of grassland, construction, and unused land decreased by 25.68, 3.12, and 2.38% and those of plowland and forest land increased by 6.61 and 24.57%. This confirms the advantages of redevelopment planning for restoring plowland and increasing biological carbon sinks. Notably, our two-step urban brownfield redevelopment model can enrich the current research on urban brownfields and guide similar urban renewal projects. Full article

The agro-pastoral ecotone of Inner Mongolia, one of China’s most ecologically vulnerable regions, requires careful evaluation and prediction of landscape ecological risks to improve its environment and support sustainable development. Our study built a model to assess the landscape ecological risks from 1990 to 2020 using land use data from Google Earth Engine. We examined the changes in landscape ecological risks and their driving factors through spatial autocorrelation analysis and geographic detectors. Future ecological risks from 2025 to 2040 were predicted using the multi-criteria evaluation-cellular automata-Markov model. Results revealed a declining trend in both disturbance and loss intensity across land use types, with the overall ecological risk index also decreasing. Higher risk areas were concentrated in the east and southwest, while lower risks were observed in the north and center. Temperature and precipitation are key natural factors, while the impact of Gross Domestic Product (GDP), a human factor, on ecological risk is increasing and surpassed natural influences in 2015 and 2020. In the future, the highest risk areas will remain in the southwest and northeast. This study provides detailed evidence and guidance for ecological safety and sustainable development in the agro-pastoral ecotone of Inner Mongolia. Full article

Traffic emissions pose a substantial challenge for contemporary societies, particularly at roundabouts, where high levels of vehicle interaction and the associated emission dynamics are prevalent. Building upon this, a cellular automata model was developed to simulate traffic characteristics, including fuel consumption, emissions (CO, HC, and NO_x), and vehicle speed at a large roundabout. The model examines critical parameters, such as interaction, stop-and-go behavior, density, speed, and spacing, to identify the factors influencing fuel consumption and emissions in roundabout traffic. Numerical verification confirmed the model’s effectiveness in replicating complex traffic flows at large roundabouts, while also revealing that driving behavior, particularly during lane entry, is a critical factor influencing fuel consumption and emissions. Therefore, we proposed four optimization strategies—two space-based and two behavior-based—aimed at reducing emissions and enhancing traffic efficiency. Simulation results demonstrated that the behavior-based strategies achieved reductions of up to 18.40%, 43.20%, 28.98%, and 30.02% in fuel consumption and emissions, along with an 8.88% increase in traffic efficiency. In contrast, the space-based strategies improved traffic efficiency by 10.26%, while reducing fuel consumption and emissions by 8.25%, 32.64%, 18.48%, and 18.09%. While the space-based strategies enhanced traffic efficiency more, their overall optimization effects were relatively modest. Thus, integrating these strategies can enhance roundabout traffic efficiency across varying conditions, while reducing fuel consumption and emissions. These findings can enhance our understanding of the traffic parameters affecting vehicular emissions, offering crucial insights for urban planners and policymakers to optimize roundabout design and management toward greater sustainability and environmental benefits. Full article

Rapid urbanization has further expanded the scale of construction land in urban agglomerations. The encroachment of urban land on ecological land has led to severe ecological problems and threatened the stability of ecological security in urban agglomerations. Analyzing the characteristics of future urban multi-scenario expansion and its impacts on ecological security patterns (ESP) can provide guidance for formulating ecologically sustainable management and control Policies. Our study focuses on Changsha-Zhuzhou-Xiangtan (CZX) urban agglomeration as the study area and establishes an ESP. Additionally, a cellular automata (CA) was used to simulate future urban expansion patterns under three scenarios (i.e., natural development scenario, urban development scenario, and ecological conservation scenario). The subsequent analysis evaluates their impact on the ESP. The simulation results indicate that from 2020 to 2030, the CZX urban agglomeration will undergo rapid urban expansion under the natural development scenario and urban development scenario, characterized by outward growth surrounding the existing construction land. In the natural development scenario, urban expansion is primarily concentrated in the northwest and south directions of construction land, the proportion of construction land increased by 2.78%; in the urban development scenario, it is concentrated in the southeast direction of construction land, the proportion of construction land increased by 3.24%. Ecological conflicts in the aforementioned development scenarios primarily arise in the southwestern region of Changsha County, as well as the southern areas of Kaifu District and Furong District. Conversely, under the ecological conservation scenario, the rate of urban expansion has significantly decreased, environmental preservation is upheld at its highest level, and the proportion of construction land only increased by 0.04%. Based on the simulation results, we present targeted recommendations for urban land planning and growth management, as well as the protection, restoration, monitoring, and development of ecological land. These suggestions provide effective guidance for improving the stability of ESP in urban agglomerations and promoting high-quality development in Chinese urban agglomerations. Full article

The Greater Amanzule Peatlands (GAP) in Ghana is an important biodiversity hotspot facing increasing pressure from anthropogenic land-use activities driven by rapid agricultural plantation expansion, urbanisation, and the burgeoning oil and gas industry. Accurate measurement of how these pressures alter land cover over time, along with the projection of future changes, is crucial for sustainable management. This study aims to analyse these changes from 2010 to 2020 and predict future scenarios up to 2040 using multi-source remote sensing and machine learning techniques. Optical, radar, and topographical remote sensing data from Landsat-7, Landsat-8, ALOS/PALSAR, and Shuttle Radar Topography Mission derived digital elevation models (DEMs) were integrated to perform land cover change analysis using Random Forest (RF), while Cellular Automata Artificial Neural Networks (CA-ANNs) were employed for predictive modelling. The classification model achieved overall accuracies of 93% in 2010 and 94% in both 2015 and 2020, with weighted F1 scores of 80.0%, 75.8%, and 75.7%, respectively. Validation of the predictive model yielded a Kappa value of 0.70, with an overall accuracy rate of 80%, ensuring reliable spatial predictions of future land cover dynamics. Findings reveal a 12% expansion in peatland cover, equivalent to approximately 6570 ± 308.59 hectares, despite declines in specific peatland types. Concurrently, anthropogenic land uses have increased, evidenced by an 85% rise in rubber plantations (from 30,530 ± 110.96 hectares to 56,617 ± 220.90 hectares) and a 6% reduction in natural forest cover (5965 ± 353.72 hectares). Sparse vegetation, including smallholder farms, decreased by 35% from 45,064 ± 163.79 hectares to 29,424 ± 114.81 hectares. Projections for 2030 and 2040 indicate minimal changes based on current trends; however, they do not consider potential impacts from climate change, large-scale development projects, and demographic shifts, necessitating cautious interpretation. The results highlight areas of stability and vulnerability within the understudied GAP region, offering critical insights for developing targeted conservation strategies. Additionally, the methodological framework, which combines optical, radar, and topographical data with machine learning, provides a robust approach for accurate and detailed landscape-scale monitoring of tropical peatlands that is applicable to other regions facing similar environmental challenges. Full article

The elementary cellular automata (ECAs) under the chaotic rule possess long periodicity and are widely used in pseudo-random number generators. However, their period is limited, related to the rule and the number of cells. Meanwhile, the Boolean functions of some ECAs are linear and vulnerable to linear analysis. Thus, the ECA cannot be directly implemented in the stream cipher. In this paper, a hybrid ECA (HECA) with dynamic mask (HECA-M) is designed. The HECA-M consists of two parts: the driving and mask parts. The driving part based on a HECA is used in generating the keystream, and the mask part based on a chaotic ECA is utilized to determine the iterative rule of the driving part. Subsequently, a stream cipher based on the HECA-M and SHA-512 is proposed. The statistic and secure analyses indicate that the proposed stream cipher possesses good randomness and can resist stream cipher analyses, such as exhaustive search, Berlekamp–Massey synthesis, guess and determine attack, time–memory–data tradeoff attack, etc. Hence, the proposed scheme can meet security requirements. Moreover, the time and space consumption of the proposed stream cipher is qualified. Full article

Lightning-induced forest fires frequently inflict substantial damage on forest ecosystems, with the Daxing’anling region in northern China recognized as a high-incidence region for such phenomena. To elucidate the occurrence patterns of forest fires caused by lightning and to prevent such fires, this study employs a multifaceted approach, including statistical analysis, kernel density estimation, and spatial autocorrelation analysis, to conduct a comprehensive examination of the spatiotemporal distribution patterns of lightning-induced forest fires in the Greater Khingan Mountains region from 2016–2020. Additionally, the geographical detector method is utilized to assess the explanatory power of three main factors: climate, topography, and fuel characteristics associated with these fires, encompassing both univariate and interaction detections. Furthermore, a mixed-methods approach is adopted, integrating the Zhengfei Wang model with a three-dimensional cellular automaton to simulate the spread of lightning-induced forest fire events, which is further validated through rigorous quantitative verification. The principal findings are as follows: (1) Spatiotemporal Distribution of Lightning-Induced Forest Fires: Interannual variability reveals pronounced fluctuations in the incidence of lightning-induced forest fires. The monthly concentration of incidents is most significant in May, July, and August, demonstrating an upward trajectory. In terms of temporal distribution, fire occurrences are predominantly concentrated between 1:00 PM and 5:00 PM, conforming to a normal distribution pattern. Spatially, higher incidences of fires are observed in the western and northwestern regions, while the eastern and southeastern areas exhibit reduced rates. At the township level, significant spatial autocorrelation indicates that Xing’an Town represents a prominent hotspot (p = 0.001), whereas Oupu Town is identified as a significant cold spot (p = 0.05). (2) Determinants of the Spatiotemporal Distribution of Lightning-Induced Forest Fires: The spatiotemporal distribution of lightning-induced forest fires is influenced by a multitude of factors. Univariate analysis reveals that the explanatory power of these factors varies significantly, with climatic factors exerting the most substantial influence, followed by topographic and fuel characteristics. Interaction factor analysis indicates that the interactive effects of climatic variables are notably more pronounced than those of fuel and topographical factors. (3) Three-Dimensional Cellular Automaton Fire Simulation Based on the Zhengfei Wang Model: This investigation integrates the fire spread principles from the Zhengfei Wang model into a three-dimensional cellular automaton framework to simulate the dynamic behavior of lightning-induced forest fires. Through quantitative validation against empirical fire events, the model demonstrates an accuracy rate of 83.54% in forecasting the affected fire zones. Full article

Cable-stayed bridges have become the preferred bridge type for large-span bridges due to their unique advantages, and the long-term performance of the cable under the extreme conditions has been facing great challenges. An accelerated corrosion test was carried out using in-service cable, and the evolution model of the etch pit was established based on cellular automata to study the evolution law of corrosion damage to steel wire. This study showed that with the increase in the number of dry-wet cycles in the electrified accelerated corrosion, the macro- and micromorphology of the steel wire showed more serious corrosion damage, the tensile strength decreased, the ductility index decreased, and the tensile strength of the steel wire after corrosion decreased by nearly 5%; the geometric dimension of the steel wire etch pits all met a right-skewed distribution with a broader range of etch pit depth, mainly consisting of shallow spherical etch pits and deep ellipsoidal etch pits. The length, width, and depth sizes were mainly distributed in the range of 0.005 mm to 0.015 mm, 0.005 mm to 0.02 mm, and 0 mm to 0.04 mm; at the early stage of corrosion, the etch pits were first developed along the longitudinal direction. As the corrosion process progressed, the iron matrix participated in the electrochemical reaction, leading to the rapid expansion of the etch pits’ dimensions. The stress concentration effect at the bottom of the etch pit caused the maximum stress to approach 1800 MPa, with a stress concentration coefficient of more than 3.0; when the cable anchorage system was located in the connecting sleeve and the threaded splice seam, where corrosion protection was prone to failure, the outer steel wire bore most of the corrosive effects, and the internal cable was less eroded by the corrosive medium. Full article

This paper aims to extend a previously developed probabilistic model for simulating extreme response scenarios to include congested traffic flow on long-span bridges, addressing the challenge of accurately modeling traffic loads under changing conditions. While the model was initially designed for free-flow traffic, this study demonstrates how it can be adapted for congested conditions, with the objective of improving the accuracy of traffic load models. To overcome the limitation of traditional Weigh-in-Motion (WIM) systems in capturing congested traffic, congested flow characteristics were inferred from available free-flow data. The cellular automata (CA) method was applied to generate realistic congested traffic scenarios, which were used as input for the probabilistic model. Key simulation parameters, such as cell length and vehicle weight distribution, were adjusted to reflect congested conditions. The results validate the model’s flexibility, showing how, with the adaptation of some parameters, it can simulate both free-flow and congested traffic patterns effectively. This research provides a basis for improving traffic load models used in the design and assessment of long-span bridges, addressing the current limitations in existing codes and standards. Full article

The expanding cropland profoundly affects stream water quality. However, the relationships between landscape patterns and stream water quality in different cropland composition classes remain unclear. We observed total nitrogen (TN), total phosphorus (TP) concentrations, and landscape patterns changed in 78 sub-watersheds of the Taihu Lake Basin’s Jiangsu segment from 2005 to 2020. The results showed that cropland area was positively correlated with TN and TP concentrations. The 21.10% reduction in cropland area, coupled with a 41.00% increase in building land, has led to an escalation in cropland fragmentation. Meanwhile, TN and TP concentrations declined by 26.67% and 28.57%, respectively. Partial least squares suggested that forest interspersion and juxtaposition metrics and forest area percentage were dominant factors influencing water quality in high- and medium-density cropland zones, respectively. The Cellular Automata–Markov Model shows reasonable distribution of forests. Scenarios with enhanced forest interspersion and juxtaposition metrics (75.28 to 91.12) showed reductions in TP (26.92% to 34.61%) and TN (18.45% to 25.89%) concentrations by 2025 compared to a natural economic development scenario. Landscape configuration optimization could assist managers in improving water quality. Full article

The effects of quantum mechanics dominate nanoscale devices, where Moore’s law no longer holds true. Additionally, with the recent rapid development of quantum computers, the development of reversible gates to overcome the problems of energy and information loss and the nano-level quantum-dot cellular automata (QCA) technology to efficiently implement them are in the spotlight. In this study, a full adder-subtractor, a core operation of the arithmetic and logic unit (ALU), the most important hardware device in computer operations, is implemented as a circuit capable of reversible operation using QCA-based reversible gates. The proposed circuit consists of one reversible QCA gate and two Feynman gates and is designed as a multi-layer structure for efficient use of area and minimization of delay. The proposed circuit is tested on QCADesigner 2.0.3 and QCADesigner-E 2.2 and shows the best performance and lowest energy dissipation. In particular, it shows tremendous improvement rates of 180% and 562% in two representative standard design cost indicators compared to the best existing studies, and also shows the highest circuit average output polarization. Full article

This article is largely oriented towards the theoretical foundations of the rational design of molecular cells for quantum cellular automata (QCA) devices with optimized properties. We apply the vibronic approach to the analysis of the two key properties of such molecular cells, namely the cell–cell response and energy dissipation in the course of the non-adiabatic switching of the electric field acting on the cell. We consider two kinds of square planar cells, namely cells represented by a two-electron tetrameric mixed valence (MV) cluster and bidimeric cells composed of two one-electron MV dimeric half-cells. The model includes vibronic coupling of the excess electrons with the breathing modes of the redox sites, electron transfer, intracell interelectronic Coulomb repulsion, and also the interaction of the cell with the electric field of polarized neighboring cells. For both kinds of cells, the heat release is shown to be minimal in the case of strong delocalization of excess electrons (weak vibronic coupling and/or strong electron transfer) exposed to a weak electric field. On the other hand, such a parametric regime proves to be incompatible with a strong nonlinear cell–cell response. To reach a compromise between low energy dissipation and a strong cell–cell response, we suggest using weakly interacting MV molecules with weak electron delocalization as cells. From this point of view, bidimeric cells are advantageous over tetrameric ones due to their smaller number of electron transfer pathways, resulting in a lower extent of electron delocalization. The distinct features of bidimeric cells, such as their two possible mutual arrangements (“side-by-side” and “head-to-tail”), are discussed as well. Finally, we briefly discuss some relevant results from a recent ab initio study on electron transfer and vibronic coupling from the perspective of the possibility of controlling the key parameters of molecular QCA cells. Full article

Due to the flammable and explosive nature of explosives, there are significant potential hazards and risks during transportation. During the operation of explosive transport vehicles, there are often situations where the vehicles around them approach or change lanes abnormally, resulting in insufficient avoidance and collision, leading to serious consequences such as explosions and fires. Therefore, in response to the above issues, this article has developed an explosive transport vehicle driving warning system based on object detection algorithms. Consumer-level cameras are flexibly arranged around the vehicle body to monitor surrounding vehicles. Using the YOLOv4 object detection algorithm to identify and distance surrounding vehicles, using a game theory-based cellular automaton model to simulate the actual operation of vehicles, simulating the driver’s decision-making behavior when encountering other vehicles approaching or changing lanes abnormally during actual driving. The cellular automaton model was used to simulate two scenarios of explosive transport vehicles equipped with and without warning systems. The results show that when explosive transport vehicles encounter the above-mentioned dangerous situations, the warning system can timely issue warnings, remind drivers to make decisions, avoid risks, ensure the safety of vehicle operation, and verify the effectiveness of the warning system. Full article

When dealing with complex models in real situations, many optimization problems require the use of more than one objective function to adequately represent the relevant characteristics of the system under consideration. Multi-objective optimization algorithms that can deal with several objective functions are necessary in order to obtain reasonable results within an adequate processing time. This paper presents the multi-objective version of a recent metaheuristic algorithm that optimizes a single objective function, known as the Majority–minority Cellular Automata Algorithm (MmCAA), inspired by cellular automata operations. The algorithm presented here is known as the Multi-objective Majority–minority Cellular Automata Algorithm (MOMmCAA). The MOMmCAA adds repository management and multi-objective search space density control to complement the performance of the MmCAA and make it capable of optimizing multi-objective problems. To evaluate the performance of the MOMmCAA, results on benchmark test sets (DTLZ, quadratic, and CEC-2020) and real-world engineering design problems were compared against other multi-objective algorithms recognized for their performance (MOLAPO, GS, MOPSO, NSGA-II, and MNMA). The results obtained in this work show that the MOMmCA achieves comparable performance with the other metaheuristic methods, demonstrating its competitiveness for use in multi-objective problems. The MOMmCAA was implemented in MATLAB and its source code can be consulted in GitHub. Full article

To provide accurate and efficient forecasting of fluvial flooding assessment in the river basin, the present study links the well-known CA-based urban inundation modeling (2D-OFM-CA) with a one-dimensional river flow model (1D-RFM) as a coupled 1D-2D river–overland modeling. Rules to delineate the geometric linking between the 1D-RFM and 2D-OFM-CA along embankments are developed. The corresponding exchanged water volume across an embankment is then computed by using the free and submerged weir flow formulas. The applicability of the proposed coupled model on fluvial flooding assessment is then assessed and compared with a well-recognized commercial software (HEC-RAS model) through an idealized fluvial case and an extensively studied real-scale fluvial case in the Severn River Basin. Based on the simulated results concerning the numerical accuracy, the coupled model is found to give similar results in the aspects of the river flow and overland flow modeling in both two study cases, which demonstrates the effectiveness of the linking methodology between the 1D-RFM and 2D-OFM-CA. From the viewpoint of numerical efficiency, the coupled model is 47% and 41% faster than the HEC-RAS model in the two cases, respectively. The above results indicate that the coupled model can reach almost the same accuracy as the HEC-RAS model with an obvious reduction in its computational time. Hence, it is concluded that the coupled model has considerable potential to be an effective alternative for fluvial flooding assessment in the river basin. Full article