Search

With the increasing consumer focus on automotive safety, Autonomous Emergency Braking (AEB) systems, recognized as effective active safety technologies for collision avoidance and the mitigation of collision-related injuries, are gaining wider application in the automotive industry. To address the issues of the insufficient working reliability of AEB systems and their unsatisfactory level of accordance with the psychological expectations of drivers, this study proposes an optimized second-order Time to Collision (TTC) safety time algorithm based on the motion state of the preceding vehicle. Additionally, the study introduces a safety distance algorithm derived from an analysis of the braking process of the main vehicle. The safety time algorithm focusing on comfort and the safety distance algorithm focusing on safety are effectively integrated in the time domain and the space domain to obtain the safety time–safety distance fusion algorithm. A MATLAB/Simulink–Carsim joint simulation platform has been established to validate the AEB control strategy in terms of safety, comfort, and system responsiveness. The simulation results show that the proposed safety time–safety distance fusion algorithm consistently achieves complete collision avoidance, indicating a higher safety level for the AEB system. Furthermore, the application of active hierarchical braking minimizes the distance error, at under 0.37 m, which meets psychological expectations of drivers and improves the comfort of the AEB system.

The natural color of biological specimens plays a crucial role in body protection, signaling, physiological adaptations, etc. Full-color optical sectioning structured illumination microscopy (OS-SIM) color is a promising approach that can reconstruct biological specimens in three-dimension meanwhile maintaining their natural color. Full-color OS-SIM takes the advantages of rapid imaging speed, compatibility with fluorescence and non-fluorescence samples, compact configuration, and low cost. However, the commonly used HSV-RMS reconstruction algorithm for full-color OS-SIM faces two issues to be improved. One is the RMS (root-mean-square) OS reconstruction algorithm is prone to background noise, and the other is the reconstruction is bound in RGB and HSV color spaces, consuming more reconstructing time. In this paper, we propose a full-color Fourier-OS-SIM method that allows for the OS reconstruction using the high-frequency spectrum of the sample and thus is immune to the low-frequency background noise. The full-color Fourier-OS-SIM directly runs in the RGB color space, providing an easy way to restore the color information. Simulation and experiments with various samples (pollen grains and tiny animals) demonstrate that the full-color Fourier-OS-SIM method is superior to the HSV-RMS method regarding background noise suppression. Moreover, benefiting from the background noise suppression merit, the quantitative morphological height map analysis with the full-color Fourier-OS-SIM method is more accurate. The proposed full-color Fourier-OS-SIM method is expected to find broad applications in biological and industrial fields where the 3D morphology and the color information of objects both need to be recovered.

As a branch of 3D microscopy, optical sectioning structured illumination microscopy (OS-SIM) has the advantages of fast imaging speed, weak photobleaching and phototoxicity, and flexible and compatible configuration. Although the method of using the one-dimensional periodic fringe pattern projected on the sample can remove the out-of-focus background from the in-focus signal, the axial resolution of the final reconstructed 3D image is not improved. Here, we propose a three-beam interference OS-SIM, namely TBOS, instead of the common-used dual-beam interference OS-SIM (DBOS). The three-beam interference scheme has been adopted in 3D super-resolution SIM (3D-SR-SIM), where the fringe phase shifting needs to be along each of the three orientations. In contrast, TBOS applies phase shifting only in one arbitrary direction. We built a TBOS SIM microscope and performed the 3D imaging experiments with 46 nm diameter fluorescent microspheres and a mouse kidney section. The axial resolution of the 3D image obtained with TBOS was enhanced by a factor of 1.36 compared to the DBOS method, consistent with the theoretical analysis and simulation. The OS-SIM with enhanced axial resolution for 3D imaging may find a wide range of applications in the biomedical field.

A new 3D cellular automata-lattice Boltzmann method (CA-LBM) coupling model is proposed to simulate the formation of facet and facet dendrites in directional solidification. In this model, the CA method is used to simulate the crystal growth process and the LBM method is used to simulate the physical field in the calculation area. A new three-dimensional anisotropic function is introduced, and the model is modified by interpolation and neighborhood restriction. We add the remelting calculation model. The interaction between interface energy anisotropy and dynamic anisotropy is solved reasonably. The growth process and morphology of small plane and small plane dendrites were simulated.

Silicon facet formation during directional solidification is simulated by cellular automaton (CA) modeling in which anisotropic interfacial energy and kinetics are considered. Numerical simulations were performed with different anisotropy strengths of interfacial energy and they show good agreement with analytical equilibrium shapes obtained by the Gibbs-Thomson equation. We also compare our results of anisotropic kinetics with in situ observation experiments and the results of the phase model to verify the accuracy of our model. Simulation results of facet formation show that perturbation is promoted to the corner by the negative temperature gradient of the interface and the heat accumulation location leads to the disappearance of small corners.

Simulating and predicting carbon storage under different development scenarios is crucial for formulating effective carbon management strategies and achieving carbon neutrality goals. However, studies that focus on specific regions and incorporate local policy context require further investigation. Taking Fujian Province as a case study, this research developed four policy-driven scenarios—natural development, farmland protection, urban development, and ecological protection—based on local policy frameworks. Using the PLUS (Patch-generating Land Use Simulation) and InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) models, the study simulated and predicted the carbon storage dynamics under each scenario. The results show that carbon storage declined from 1995 to 2020, mainly due to the conversion of forests and agricultural land into construction areas. The ecological protection scenario demonstrated the highest potential for carbon storage recovery, projecting an increase to 2.02 billion tons by 2030, driven by afforestation and conservation initiatives. Conversely, the urban development scenario posed the greatest risks, leading to substantial losses. Key conservation areas, including 12 priority districts, were identified in the western and northwestern regions, while coastal urban areas, comprising 31 vulnerable districts, face significant carbon storage losses. These findings emphasize the need for balanced land use policies that prioritize both urban development and ecological protection to achieve sustainable carbon management.

The interactions between economic development, environmental sustainability, population growth, and urbanization are vital in assessing the ecological dynamics of urban agglomerations. This study explores the relationship between economic development, environmental sustainability, population growth, and urbanization within the Xia-Zhang-Quan urban agglomeration in Fujian Province from 1989 to 2022. Utilizing Landsat remote sensing images, we calculated the Remote Sensing Ecological Index (RSEI) to evaluate changes in ecological quality. The results show that the average RSEI values for 1989, 2000, 2010, and 2022 were 0.5829, 0.5607, 0.5827, and 0.6195, respectively, indicating an initial decline followed by a significant increase, culminating in an overall upward trend. The spatial distribution of RSEI classification shows that the study area has the largest proportion of mainly “good” ecological quality. The proportion of areas with “excellent” ecological environmental quality has increased (13.41% in 1989 and 25.12% in 2022), while those with “general” quality has decreased (28.03% in 1989 and 21.21% in 2022). Over the past three decades, Xiamen experienced substantial ecological degradation (RSEI change of −0.0897), Zhangzhou showed marked improvement (RSEI change of 0.0519), and Quanzhou exhibited slight deterioration (RSEI change of −0.0396). Central urban areas typically had poorer ecological conditions but showed signs of improvement, whereas non-central urban regions demonstrated significant environmental enhancement. The factor detector analysis identified land use as the dominant factor influencing ecological environmental quality, with precipitation having a relatively minor impact. Interaction analysis revealed that all other factors demonstrated bi-variable enhancement or nonlinear enhancement, suggesting that the interactive effects of these factors are greater than the effects of individual factors alone. Land use consistently showed solid explanatory power. Temperature also exhibited significant influence in 2022 when interacting with other factors. Due to urban planning that can plan for land use, these findings suggest that effective urban planning can harmonize economic development with ecological protection within the Xia-Zhang-Quan urban agglomeration.

Identifying the spatial changes in farming–pastoral ecotone (FPE) is of utmost importance for the development of strategies for ecological protection in ecologically fragile areas. This study employed spatial autocorrelation and spatial clustering techniques to map FPE at the pixel scale using CLCD data with a spatial resolution of 30 × 30 m in the years 1985, 2000, and 2021, and then analyzed the changes of the FPE in northern China. The results showed that the FPE is mainly located at the border between the Inner Mongolia Autonomous Region and the adjacent provinces, which is along the Hu-line and the 400-mm isohyetal line. The area of the FPE was 63.94 × 104 km2, 62.90 × 104 km2, and 53.81 × 104 km2 in 1985, 2000, and 2021, respectively, accounting for 6.7%, 6.6%, 5.6% of the total land area in China. The FPE boundary moved northwestward during 1985–2021, demonstrating retreating, fragmenting, and shrinking tendencies. The decreased areas and the moving distances of the gravity center are six times and four times greater during 2000–2021 than that during 1985–2000, respectively. Moreover, the discontinuous change in FPE was mainly due to the increase in forest land, especially for the conversion of grassland to forest land. Our findings provide guidance for the construction of ecological civilization and the optimization of ecosystem structure in the farming–pastoral ecotone.

The stable operating region of a photovoltaic (PV) cascaded H-bridge (CHB) grid-tied module level inverter is extended by adopting the hybrid modulation strategy. However, the traditional single hybrid modulation method is unable to regulate the DC-side voltage of each module precisely, which may aggravate the fluctuation of modules’ DC-side voltages or even cause the deviation of modules’ DC-side voltages under some fault conditions and, thus, degrade the energy harvesting of PV panels. To tackle this problem, a switching modulation strategy for PV CHB inverter is proposed in this paper. When the CHB inverter is operating in normal mode, the hybrid modulation strategy containing the zero state is adopted to suppress DC-side voltage fluctuation, thereby, improving the output power of PV modules. When the CHB inverter is operating in fault mode owing to failing solar panels, the hybrid modulation strategy without the zero state is utilized to make the DC-side voltages reach the references and, thus, maintain a higher energy yield under fault conditions. Experimental results achieved by a laboratory prototype of a single-phase eleven-level CHB inverter demonstrate both the feasibility and effectiveness of the proposed method.

The spatiotemporal distribution pattern of the surface temperatures of urban forest canopies (STUFC) is influenced by many environmental factors, and the identification of interactions between these factors can improve simulations and predictions of spatial patterns of urban cool islands. This quantitative research uses an integrated method that combines remote sensing, ground surveys, and spatial statistical models to elucidate the mechanisms that influence the STUFC and considers the interaction of multiple environmental factors. This case study uses Jinjiang, China as a representative of a city experiencing rapid urbanization. We build up a multisource database (forest inventory, digital elevation models, population, and remote sensing imagery) on a uniform coordinate system to support research into the interactions that influence the STUFC. Landsat-5/8 Thermal Mapper images and meteorological data were used to retrieve the temporal and spatial distributions of land surface temperature. Ground observations, which included the forest management planning inventory and population density data, provided the factors that determine the STUFC spatial distribution on an urban scale. The use of a spatial statistical model (GeogDetector model) reveals the interaction mechanisms of STUFC. Although different environmental factors exert different influences on STUFC, in two periods with different hot spots and cold spots, the patch area and dominant tree species proved to be the main factors contributing to STUFC. The interaction between multiple environmental factors increased the STUFC, both linearly and nonlinearly. Strong interactions tended to occur between elevation and dominant species and were prevalent in either hot or cold spots in different years. In conclusion, the combining of multidisciplinary methods (e.g., remote sensing images, ground observations, and spatial statistical models) helps reveal the mechanism of STUFC on an urban scale.

Integration of Landsat images and multisource data using spatial statistical analysis and geographical detector models can reveal the individual and interactive influences of anthropogenic activities and ecological factors on concentrations of atmospheric particulate matter less than 2.5 microns in diameter (PM2.5). This approach has been used in many studies to estimate biomass and forest disturbance patterns and to monitor carbon sinks. However, the approach has rarely been used to comprehensively analyze the individual and interactive influences of anthropogenic factors (e.g., population density, impervious surface percentage) and ecological factors (e.g., canopy density, stand age, and elevation) on PM2.5 concentrations. To do this, we used Landsat-8 images and meteorological data to retrieve quantitative data on the concentrations of particulates (PM2.5), then integrated a forest management planning inventory (FMPI), population density distribution data, meteorological data, and topographic data in a Geographic Information System database, and applied a spatial statistical analysis model to identify aggregated areas (hot spots and cold spots) of particulates in the urban area of Jinjiang city, China. A geographical detector model was used to analyze the individual and interactive influences of anthropogenic and ecological factors on PM2.5 concentrations. We found that particulate concentration hot spots are mainly distributed in urban centers and suburbs, while cold spots are mainly distributed in the suburbs and exurban region. Elevation was the dominant individual factor affecting PM2.5 concentrations, followed by dominant tree species and meteorological factors. A combination of human activities (e.g., population density, impervious surface percentage) and multiple ecological factors caused the dominant interactive effects, resulting in increased PM2.5 concentrations. Our study suggests that human activities and multiple ecological factors effect PM2.5 concentrations both individually and interactively. We conclude that in order to reveal the direct and indirect effects of human activities and multiple factors on PM2.5 concentrations in urban forests, quantification of fusion satellite data and spatial statistical methods should be conducted in urban areas.

The propose of this review was to summarize the advances in multi-scale surface technology of titanium implants to accelerate the osseointegration process. The several multi-scaled methods used for improving wettability, roughness, and bioactivity of implant surfaces are reviewed. In addition, macro-scale methods (e.g., 3D printing (3DP) and laser surface texturing (LST)), micro-scale (e.g., grit-blasting, acid-etching, and Sand-blasted, Large-grit, and Acid-etching (SLA)) and nano-scale methods (e.g., plasma-spraying and anodization) are also discussed, and these surfaces are known to have favorable properties in clinical applications. Functionalized coatings with organic and non-organic loadings suggest good prospects for the future of modern biotechnology. Nevertheless, because of high cost and low clinical validation, these partial coatings have not been commercially available so far. A large number of in vitro and in vivo investigations are necessary in order to obtain in-depth exploration about the efficiency of functional implant surfaces. The prospective titanium implants should possess the optimum chemistry, bionic characteristics, and standardized modern topographies to achieve rapid osseointegration.

Anthocyanin contributes to the coloration of pear fruit and enhances plant defenses. Members of the ethylene response factor (ERF) family play vital roles in hormone and stress signaling and are involved in anthocyanin biosynthesis. Here, PbERF22 was identified from the lanolin-induced red fruit of ‘Zaosu’ pear (Pyrus bretschneideri Rehd.) using a comparative transcriptome analysis. Its expression level was up- and down-regulated by methyl jasmonate and 1-methylcyclopropene plus lanolin treatments, respectively, which indicated that PbERF22 responded to the jasmonate- and ethylene-signaling pathways. In addition, transiently overexpressed PbERF22 induced anthocyanin biosynthesis in ‘Zaosu’ fruit, and a quantitative PCR analysis further confirmed that PbERF22 facilitated the expression of anthocyanin biosynthetic structural and regulatory genes. Moreover, a dual luciferase assay showed that PbERF22 enhanced the activation effects of PbMYB10 and PbMYB10b on the PbUFGT promoter. Therefore, PbERF22 responses to jasmonate and ethylene signals and regulates anthocyanin biosynthesis. This provides a new perspective on the correlation between jasmonate−ethylene crosstalk and anthocyanin biosynthesis.