During the past several decades, soil heavy metal contamination has emerged as an environmental affliction and subject of study. Soil heavy metal contamination in peri-urban areas is more severe and intricate. The western region of Laizhou City, as a typical industrial city exhibiting vigorous factory, agricultural, and extraction activities, possesses substantial research merit and can offer a noteworthy example for the analysis of heavy metal contamination in the peri-urban areas of industrial cities. We procured 271 surface soil samples (0–20 cm) from the western peri-urban areas of Laizhou City. Through statistical scrutiny, it was discerned that the concentrations of As, Cd, Hg, and Pb surpassed the local baseline concentrations, with the ranking of the coefficient of variation being Hg > 1 > Cd > 0.5 > Pb > Cu > As > Ni > Zn > Cr. Subsequently, we investigated the potential origins of heavy metals through correlation analysis, principal component analysis, and geostatistical analysis and elucidated the primary origins of heavy metals based on the existing land-use scenario: PC1 (As, Cd, Cu, Pb, and Zn) predominantly originated from agricultural pursuits, transportation, and industrial production; PC2 (Cr and Ni) was correlated with soil parent materials; and PC3 (Hg) was attributed to industrial production and open-pit mining of minerals. According to the analysis of the Nemero comprehensive index and potential ecological risk index, the soil environmental risk in the study area was within a controllable range. However, the continuous enrichment of heavy metals in the soil should receive sufficient attention, and continuous monitoring of the site is recommended. This study attempts to use a combination of existing land-use scenarios and statistical analysis methods to analyze the heavy metal pollution conditions in peri-urban industrial cities. Although this study has shortcomings, it provides valuable information for the study of heavy metal sources and environmental risks in typical industrial city suburbs. Full article

This study aims to carry out a comparative analysis between the level of digitization of the Romanian public administration compared to that existing in the most digitally developed states at the European level. Our study identifies the extent to which Romanian citizens have access to non-bureaucratic and transparent public services that support social inclusion and non-discrimination, compared to European citizens from states with the best digitalization of public services. Also, our research studies the relationship between the level of digitalization quantified by the DESI indicator and the level of income for the states considered in the analysis, as well as the relationship between digitalization and bureaucracy, the corruption index, and the digital skills of citizens. Based on the 486 statistical data collected and centralized on the corruption index (CPI), as well as the values for DESI and GNI per capita, for the period 2017–2022 for the 27 EU member states, we performed a statistical analysis using SPSS 28 regarding the existence of a DESI relationship and level of income (GNI per capita) and/or CPI (Corruption Perceptions Index). Our study is on a current issue, as it addresses the issue of digitalization of public administration, in the new post-pandemic and geostrategic context. It has theoretical applicability, by determining a model that can be used to study the relationship between digitalization and the standard of living and corruption, and also practical application, because it can contribute to the awareness of the government in taking measures and adopting strategies to reduce gaps as compared to the most developed digital states. Full article

This paper examines the outward foreign direct investment events of Chinese manufacturing firms from 2008 to 2022. It explores how sunk cost and performance feedback drive firms’ foreign exit strategies based on the behavioral theory of the firm. Additionally, it also examines the contextual factor that may affect the focal relationship. We adopt a panel logistic estimation to test the hypotheses. The conclusions show that firms are more likely to exit overseas markets when faced with sunk costs and negative performance feedback. Conversely, positive performance feedback significantly decreases the probability of firms exiting foreign markets. Additionally, environmental munificence and complexity can weaken the strength of the focal nexus to some extent. These findings hold both theoretical and practical significance for multinational enterprises and the government in the context of the ‘dual-circulation strategy’. Full article

This study investigates the relationship between cultural heritage and climate change, assessing the global implementation of advanced technologies in line with UNESCO’s Thematic Indicators for Cultural Sustainability. Few studies have been conducted on this topic; hence, theoretical background examines the keywords related to cultural heritage preservation, conservation, restoration, climate change mitigation, and adaptation, as well as the intersection of culture and climate change. It also analyses the definitions provided by leading global organizations and explores the use of advanced technologies in protecting cultural heritage. The research methodology is based on an analytical method consisting of a bibliometric assessment and a scientometric assessment The bibliometric and scientometric analyses map occurrences, frequencies, and intercorrelations of these keywords with UNESCO Thematic Indicators and advanced technology utilization. The findings reveal a predominance of conservation-related Thematic Indicators, suggesting a conservative approach to cultural sustainability, particularly for environmental resilience, wealth, and livelihoods. In terms of advanced technologies, laser scanning and photogrammetry are used for both conservation and restoration purposes, while chromatography and virtual tours are mainly applied to conservation and preservation practices. Otherwise, infrared thermography, X-ray imaging, and online platforms are used, respectively, for heritage preservation, restoration, and conservation. On the other hand, ground-penetrating radar and remote sensing exhibit fewer connections to heritage protection. The mapping of culture and climate change also highlights the importance of conservation in responding to changing climate conditions. Climate adaptation is closely linked to both conservation and preservation efforts, highlighting the critical role of cultural heritage in fostering climate resilience. Full article

The Xiaojiang Basin ranks among the global regions with the highest density of geological hazards. Landslides, avalanches, and debris flows represent significant threats to the safety of residents and their properties, impeding sustainable development. This study utilized three InSAR techniques to monitor surface deformations in the basin, using the standard deviation of these measurements as a stability threshold to identify potential landslides. A systematic analysis of landslide development characteristics was then conducted. Key findings include the following: (1) The annual average deformation velocity in the basin from 2018 to 2021 ranged from −25.36 to 24.40 mm/year, identifying 212 potential landslides. (2) Deformation analysis of a typical landslide in Caizishan showed consistent detection of significant surface changes by all three InSAR methods. Seasonal deformation linked to summer rainfall exacerbates the movement in elevated landslides. (3) Landslides predominantly occur in fragile geological formations such as sandstone, mudstone, and kamacite on slopes of 20° to 40°. These landslides, typically covering less than 0.1 km², are mostly found on barren and grassland terrains adjacent to lower debris gullies, with a relative elevation difference of under 300 m and an aspect range of 90° to 270°. A high kernel density value of 0.3 or higher was noted, with 86.8% influenced by regional tectonic activities, including fault zones. The results demonstrate that natural environmental factors primarily drive landslides in the Xiaojiang Basin, which pose significant threats to the safety of nearby residents. This study’s insights and outcomes provide valuable references for safeguarding local populations, disaster prevention, and promoting regional sustainable development. Full article

Sustainable development is implemented not only at the global level, but primarily in local environments. Shaping the space of river valleys becomes particularly important in the face of climate change and growing water deficit. The article therefore addresses the issue of the social perception of water management in the context of climate change. The aim was to answer the questions: what is the social awareness of water management in the face of climate change, and what sustainable solutions are socially accepted? The research was carried out in the south-eastern part of Poland, in the Podkarpackie and Lublin voivodeships. The diagnostic survey method, an original survey form, and the CAWI technique were used. The study group analyzed the perception of global, negative megatrends, and challenges related to water retention in the context of climate change. The task was to identify respondents’ awareness of new sustainable management methods in river valleys. Due to the fact that the studied area is largely agricultural, differences in the perception of the studied items were sought, depending on the place of residence. It was assumed that inhabitants of rural areas have greater contact with nature, which may change their perception, and differences were looked for depending on the region of residence. Differences in the perceptions of the studied phenomena were also searched for, depending on the respondent’s sex. The calculations show that the place of residence (urban–rural) and the regions (Podkarpackie–Lublin voivodeships) do not differentiate the perceptions of most of the examined items. However, sex primarily affects the perception of global megatrends and the perception of climate change. The results indicate the respondents’ lack of awareness about natural forms of water retention. Respondents expected the implementation of outdated technical forms of flood protection. Expectations focused mainly on flood embankments and large dam reservoirs. There was strong belief among respondents regarding global megatrends and their impacts on social and economic life. A knowledge deficit was identified in relation to sustainable management methods in river valleys that favor water retention. Full article

Combining the Intangible Cultural Heritage and sustainable development has been an important effort of UNESCO since the new century. This study discusses the suitability of educational tourism development of intangible cultural heritage. On the one hand, it was beneficial to improve the comprehensive quality of students; on the other hand, it was conducive to protecting and rationally developing the cultural heritage and avoiding its loss. In this study, an evaluation index system was established according to the analytic hierarchy process, which included two aspects (i.e., intrinsic value and extrinsic conditions) and 16 indices from four criterion layers (e.g., educational value, recreational value, environmental conditions, and relevant facilities and services). Furthermore, we calculated the development suitability and spatial distribution patterns of intangible cultural heritage for educational tourism. At the same time, using the obstacle degree model, the obstacle degrees of each indicator factor were screened and identified to explore the source of obstacles that restrict the suitability of educational tourism development of ICH. Results showed that: (1) The development suitability of intangible cultural heritage for educational tourism was divided into high suitability, middle suitability, and low suitability. A total of 186 intangible cultural heritages were found in Shandong Province, China. Among these intangible cultural heritages, 60 of 186 (32.26%) were low suitability, with values ranging from 0.326 to 0.460; 86 of 186 (46.24%) were middle suitability, with values of 0.460–0.543, and 40 of 186 (21.50%) were high suitability with a range of 0.543–0.689. (2) The spatial distribution patterns of suitability showed that the development suitability of intangible cultural heritage for educational tourism in Shandong Province exhibited a significantly positive spatial correlation that projects with similar suitability levels were clustered into a group and generally distributed with a direction of “southwest to the northeast”. (3) According to the diagnostic results of obstacle factor analysis, from the perspective of the first level indicator, the obstacle degree of the intrinsic value (A1) of the three levels of suitability of ICH was the highest. Among the second-level indicators, educational value (B1) has always been the biggest obstacle factor affecting the educational tourism of ICH, and the relevance of cultural content (C2), representativeness and typicality of the phenomenon (C3), applicability of teaching cases (C4), and uniqueness or rarity (C5) were the greatest among the three suitability factors. Full article

This study aims to fill in a gap by examining how physical activities (PAs), feeling good about oneself physically, and academic performance (ACD_PRF) all work together to influence the overall quality of life (QoL) for vulnerable students. We examined data from 400 vulnerable students studying in various universities and major specializations. We employed the Partial Least Squares–Structural Equation Modeling (PLS-SEM) data-analysis technique to test the validity and reliability of the outer model and to test the hypotheses used in the inner model. The research findings indicate that physical activities and physical self-esteem (PHS) can directly and indirectly improve vulnerable students’ QoL. However, among vulnerable students, ACD_PRF can only strengthen their QoL indirectly through improving their PHS. These findings help us to understand how physical activities, feeling good about one’s body, and ACD_PRF all contribute to these students having a better overall QoL. This knowledge can help us to develop better ways to support vulnerable students and to improve their well-being in all aspects of their lives, bodies, and ACD_PRF, which contributes to these students having a better overall QoL. This knowledge can help us to develop better ways to support students with disabilities (SwDs) and to improve their well-being in all aspects of their lives. Full article

Investigating the influence of human activities and climate change on streamflow and sediment load is of great significance for understanding the hydrological cycle, addressing climate change, and ensuring sustainable water resource management. Based on observed data of precipitation, streamflow, and sediment load from 1990 to 2021 in the Xiliugou Basin, trend and abrupt change analyses of streamflow and sediment load were conducted using the coefficient of variation and Bayesian change point detection method. The effects of climate change and human activities on streamflow and sediment load were further examined through the double mass curve method, with a focus on the impact of land use changes on streamflow and sediment load dynamics. The results indicated that: (1) During the study period, there was a consistent decreasing trend in streamflow, sediment load, and precipitation, with respective rates of −77.76 × 10⁴ m³/year, −55.97 × 10⁴ Mt/year, and −0.84 mm/year. The distribution of annual streamflow and sediment load in the basin was uneven, with 61.05% of precipitation occurring during the wet season and the peak sediment discharge month being July, accounting for 58.90% of the total annual sediment load. (2) The variations in streamflow and sediment load in the Xiliugou Basin exhibited distinct stage characteristics, with abrupt changes occurring around 1997. Both streamflow and sediment load showed significant fluctuations from the reference period to the changing period, decreasing by 45.54% and 82.85%, respectively. (3) A positive correlation between precipitation and streamflow was observed in the Xiliugou Basin, with correlation coefficients (R) of 0.62 and 0.49, indicating a stimulating effect of precipitation on streamflow and sediment load. Human activities significantly reduced sediment load in the Xiliugou Basin from 1998 to 2021, contributing to a reduction of 115.08%. (4) An increase in cropland, water, and barren areas would lead to higher streamflow and sediment load, while an increase in grassland, forest, and impervious areas would decrease both streamflow and sediment load. Full article

Understanding the mechanisms by which the combination of green marketing components fosters local sustainable development is crucial for global regions in achieving the United Nations’ sustainable development goals. Utilizing panel data from China’s provinces from 2011 to 2022, this study employs the DEA model to assess both the static and dynamic efficiencies of sustainable development across China’s 31 provinces. Subsequently, drawing on the 6P theory of marketing element combination, this study selects human input, capital input, energy input, technological output, economic output, and ecological output as causal variables, with the local sustainable development index serving as the outcome variable. By integrating the fsQCA method, the study identifies four distinct configurations: a “single input–multiple output” model, a “multiple input–single output” model, an “input–output” linkage model, and an “input-driven” model. This conclusion can enhance the comprehension of the dynamics through which various combinations of green marketing components contribute to local sustainable development from a regional macroeconomic perspective, offering a theoretical foundation for achieving sustainable development globally. Full article

Accurate and stable prediction of atmospheric PM_2.5 concentrations is crucial for air pollution prevention and control. Existing studies usually rely on a single model or use a single evaluation criterion in multi-model ensemble weighted forecasts, neglecting the dual needs for accuracy and stability in PM_2.5 forecast. In this study, a novel ensemble forecast model is proposed that overcomes these drawbacks by simultaneously taking into account both forecast accuracy and stability. Specifically, four advanced deep learning models—Long Short-Term Memory Network (LSTM), Graph Convolutional Network (GCN), Transformer, and Graph Sample and Aggregation Network (GraphSAGE)—are firstly introduced. And then, two combined models are constructed as predictors, namely LSTM–GCN and Transformer–GraphSAGE. Finally, a combined weighting strategy is adopted to assign weights to these two combined models using a multi-objective optimization algorithm (MOO), so as to carry out more accurate and stable predictions. The experiments are conducted on the dataset from 36 air quality monitoring stations in Beijing, and results show that the proposed model achieves more accurate and stable predictions than other benchmark models. It is hoped that this proposed ensemble forecast model will provide effective support for PM_2.5 pollution forecast and early warning in the future. Full article

Driver behavior plays a pivotal role in ensuring road safety as it is a significant factor in preventing traffic crashes. Although extensive research has been conducted on this topic in developed countries, there is a notable gap in understanding driver behavior in developing countries, such as Pakistan. It is essential to recognize that the cultural nuances, law enforcement practices, and government investments in traffic safety in Pakistan are significantly different from those in other regions. Recognizing this disparity, this study aims to comprehensively understand risky driving behaviors in Peshawar, Pakistan. To achieve this goal, a Driver Behavior Questionnaire was designed, and responses were collected using Google Forms, resulting in 306 valid responses. The study employs a Fuzzy Analytical Hierarchy Process framework to evaluate driver behavior’s ranking criteria and weight factors. This framework assigns relative weights to different criteria and captures the uncertainty of driving thought patterns. Additionally, machine learning techniques, including support vector machine, decision tree, Naïve Bayes, Random Forest, and ensemble model, were used to predict driver behavior, enhancing the reliability and accuracy of the predictions. The results showed that the ensemble machine learning approach outperformed others with a prediction accuracy of 0.84. In addition, the findings revealed that the three most significant risky driving attributes were violations, errors, and lapses. Certain factors, such as clear road signage and driver attention, were identified as important factors in improving drivers’ risk perception. This study serves as a benchmark for policymakers, offering valuable insights to formulate effective policies for improving traffic safety. Full article

The harvesting of herbs from urban and peri-urban areas requires systematic monitoring of soils and plants, especially of trace element concentrations. The aim of the study was to assess the phytoaccumulation of selected trace elements (Zn, Cu, Fe, and Mn) in elderberry flowers from the Kuyavian-Pomeranian province (Poland). The enzymatic activity of soils was also assessed in the context of the impact of metals on the biological properties of soils at risk of contamination with trace elements. Soil and plant samples were taken from seven locations with different anthropopressures. Flowers from sites with a high frequency of road traffic were characterized by a greater number of elements (location 1, 3–7) than from areas away from busy roads (location 2). The correlation analysis showed that Cu and Zn contents were highly correlated in the flowers of elderberry as compared to the corresponding soils seven locations with different anthropopressures Regarding the Zn content, only flowers from habitats 1, 2, 7 met the conditions specified in the WHO standard for herbs used in herbal medicine (<50 mg·kg⁻¹). Based on the conducted research, it was found that the level of soil enzymatic activity in the tested soils varied within wide limits but clearly depended on their location. The highest enzyme activity in the soil was found in soil from town center 1 (location 3), where high DHA dehydrogenase DHA (114.5 mg TPF·g⁻¹·24 h⁻¹), fluorescein diacetate hydrolysis FDA (51.26 μg F·g⁻¹·h⁻¹), and β-glucosidases GLUC activity (4.833 μg pNP·g⁻¹·h⁻¹) were determined, as well as in soil from residential area 2 (location 3), where high DHA (165.9 mg TPF·g⁻¹·24 h⁻¹) and FDA (48.23 μg F·g⁻¹·h⁻¹) activity were determined. Analyzing the soil properties, it can be concluded that the content of Cu_t and Zn_t in the soil and their forms available for plants, as well as DHA activity, correlates most closely with the content of organic matter. Full article

Rural industrial integration refers to the process of relying on technological innovation and industrial model innovation to promote the optimal allocation of factors such as land, capital, and labor in rural areas, promote the optimization of a rural industrial structure, rural property rights stability, agricultural and rural development, and ultimately achieve the extension of the agricultural industry chain and improvements in farmers’ income levels. In order to grasp the mechanism of digital economy and rural land certification on rural industrial integration, this paper analyzes the impact of digital economy development and rural land certification on rural industrial integration based on the 2011–2021 panel data of the Yangtze River Economic Belt at the municipal level. Research has shown the following. (1) The early development of the digital economy significantly promoted the integration of rural industries. After overcoming the turning point of the digital economy, the digital economy has a restraining effect on the integration of rural industries; in terms of controlling variables, the education level of rural residents, regional economic development level, per capita disposable income of rural residents, and rural power generation all significantly promote the process of rural industrial integration. (2) Rural land certification has played a positive transmission role by confirming, reviewing, and registering land ownership in accordance with the law, clarifying the ownership of land rights, providing a stable property rights foundation for rural industrial integration, and effectively promoting rural industrial integration. (3) The impact of the digital economy on rural industrial integration has a single threshold effect, and after crossing the threshold value of a rural population, the positive impact of the digital economy on industrial integration is more significant. (4) The development of the digital economy has significantly improved the integration level of rural industries in this region and neighboring areas. The above conclusions have important policy implications for further leveraging the digital economy to promote the integration of rural industries and the modernization of agriculture and rural areas. Full article

Human actions that modify terrestrial and aquatic environments contribute to unsustainability, influencing the economy and human health. Urban environments are responsible for the dispersion of pollution and nanoparticles (NPs), which can potentially harm the health of human populations and contaminate the fauna and flora of aquatic ecosystems on a global scale. The objective of this study is to analyze the dissemination of nanoparticles in Cartagena Bay, Colombia, during the strong winds/low runoff season of January 2020 and the weak winds/high runoff season of October 2021. This was accomplished using images from the Sentinel-3B OLCI (Ocean Land Color Instrument) satellite in conjunction with an analytical chemical analysis of sediments collected in the study area in a laboratory with advanced electron microscopy. It was possible to obtain, on average, a sample of suspended sediments (SSs) every 1000 m in the areas of Bocagrande, Isla de Tierra Bomba, and Playa Blanca, which were analyzed in the laboratory with X-ray diffraction (XRD) and electron transmission and scanning microscopies. Images obtained in the summer of 2020 and winter of 2021 by the Sentinel 3B OLCI satellite were selected at a distance of 1 km from each other and analyzed for the following variables: chlorophyll (CHL_NN), water turbidity (TSM_NN), and suspended pollution potential (ADG443_NN). In addition to of evaluating georeferenced maps, they were subjected to an analysis within the statistical and K-Means clustering model. The laboratory analysis of SSs showed the presence of potentially toxic NPs, responsible for contamination that may harm the health of the local population and marine ecosystems. The K-Means and satellite image analysis corroborated the laboratory analyses, revealing the source of the pollution and contamination of Cartagena Bay as the estuary located close to its center. Full article

The scarcity of water resources, climate change, and water-wasting behavior have contributed to a worsening water crisis in many countries. This has raised concerns among farmers and increased pressure on governments. Digital technologies provide effective solutions to reduce resource waste; therefore, exploring farmers’ willingness to implement water-smart farming technologies to reduce waste, especially in developing countries, requires further analysis. To address this gap, this paper aims to investigate the factors that influence farmers’ intention to minimize water waste in Algeria. The theory of planned behavior was extended with the constructs of perceived usefulness of water-smart farming and knowledge of water waste reduction. Primary data were collected from 202 farmers to test the model. The empirical evidence suggests that attitudes, knowledge about water waste reduction, perceived usefulness, and perceived behavioral control significantly predict farmers’ intention to reduce waste. These factors explained 54.6% of the variation in intention. However, social influence was not found to be a significant antecedent of intentions. This paper’s findings can provide useful insights for various stakeholders on how to encourage farmers to reduce water waste and offer guidance on strategies for achieving sustainability in agriculture. Full article

Although micro- and nanoplastics (MNPs) represent one of the main environmental emergencies worldwide, citizens are not always aware of their active role in contributing to such contamination. In this study, the perception, level of knowledge, and behaviours towards MNPs were assessed in young citizens in Modena (Italy), represented by science-oriented Bachelor’s students (n = 220) enrolled at the university, through the administration of a voluntary-based questionnaire. No differences in knowledge and in students’ attitudes were observed according to gender and the undergraduate program. Students seem to be aware of MNPs’ global distribution and effects on ecosystems but were less advised about MNP types and their potential effects on human health. A positive correlation between the students’ level of concern and their knowledge or their behaviour was found. Differently, no correlation between students’ knowledge and behaviour towards plastic and MNP contamination was observed. Thus, having a good knowledge of the issue does not always translate into effective actions planned to mitigate the problem. As a first step forward, more environmental education programs should be promoted to increase knowledge and awareness in young citizen as well as pro-environmental behaviours to pursue future mitigation strategies. Full article

In this paper, we prove the existence of at least two weak solutions to a class of singular two-phase problems with variable exponents involving a $\psi$-Hilfer fractional operator and Dirichlet-type boundary conditions when the term source is dependent on one parameter. Here, we use the fiber method and the Nehari manifold to prove our results. Full article

An efficient obstacle detection system is one of the most important guarantees for improving the active safety performance of autonomous vehicles. This paper proposes an obstacle detection method based on high-precision positioning applied to blocked zones to solve the problems of the high complexity of detection results, low computational efficiency, and high load in traditional obstacle detection methods. Firstly, an NDT registration method which uses the likelihood function as the optimal value of the registration score function to calculate the registration parameters is designed to match the scanning point cloud and the target point cloud. Secondly, a target reduction method combined with threshold judgment and the binary tree search algorithm is designed to filter the point cloud of non-road obstacles to improve the processing speed of the computing platform. Meanwhile, KD-tree is used to speed up the clustering process. Finally, a vehicle remote control simulation platform with the combination of a cloud platform and mobile terminal is designed to verify the effectiveness of the strategy in practical application. The results prove that the proposed obstacle detection method can improve the efficiency and accuracy of detection. Full article

Pan–tilt–zoom cameras are commonly used for surveillance applications. Their automation could reduce the workload of human operators and increase the safety of airports by tracking anomalous objects such as drones. Reinforcement learning is an artificial intelligence method that outperforms humans on certain specific tasks. However, there exists a lack of data and benchmarks for pan–tilt–zoom control mechanisms in tracking airborne objects. Here, we show a simulated environment that contains a pan–tilt–zoom camera being used to train and evaluate a reinforcement learning agent. We found that the agent can learn to track the drone in our basic tracking scenario, outperforming a solved scenario benchmark value. The agent is also tested on more complex scenarios, where the drone is occluded behind obstacles. While the agent does not quantitatively outperform the optimal human model, it shows qualitative signs of learning to solve the complex, occluded non-linear trajectory scenario. Given further training, investigation, and different algorithms, we believe a reinforcement learning agent could be used to solve such scenarios consistently. Our results demonstrate how complex drone surveillance tracking scenarios may be solved and fully autonomized by reinforcement learning agents. We hope our environment becomes a starting point for more sophisticated autonomy in control of pan–tilt–zoom cameras tracking of drones and surveilling airspace for anomalous objects. For example, distributed, multi-agent systems of pan–tilt–zoom cameras combined with other sensors could lead towards fully autonomous surveillance, challenging experienced human operators. Full article

To determine a vertical cooperation strategy and address the optimal pricing problem of the electric vehicle (EV) supply chain, a supply chain system consisting of two competing EV manufacturers (M₁ and M₂) and a battery supplier is studied. Firstly, three cooperation strategy models were constructed for the battery supplier and the EV manufacturers, namely: Strategy N (neither the battery supplier nor the two manufacturers cooperate with each other); Strategy I (M₁ cooperates with the battery supplier); and Strategy II (M₂ cooperates with the battery supplier). Then, the Stackelberg solution method was used to obtain the optimal equilibrium decisions under the three strategic models. Finally, the effect of the preference coefficient of consumers for leasing EVs per unit on the optimal equilibrium decision was analyzed. We found that: (1) The wholesale price of batteries provided by the battery supplier to M₁ is always greater than to M₂. (2) Strategies I and II prompt M₁ and M₂ to reduce the unit and fixed rental prices of EVs to some extent, while intensifying the competition between the two manufacturers in terms of EV lease prices. (3) When the consumer preference coefficient (θ) for leasing EVs per unit provided by manufacturer M₁ is relatively small, the cooperation alliance S₂ and the supply chain achieve the maximum profit under Strategy II; however, while θ is large, M₁, cooperative alliance S₁, and the entire supply chain could benefit the most under Strategy I. Full article

In order to investigate the impact of moisture content on energy evolution, three types of rock samples with varying moisture contents were subjected to uniaxial compression tests. The study aimed to analyze the reasons behind the differences in energy during the deformation process of rocks with different moisture contents. The findings indicate that with increasing moisture content, the peak strength and elastic modulus of the samples decrease. However, the ratio of crack initiation strength σ_ci to peak strength σ_f shows little effect, primarily because the characteristic strength ratio σ_ci/σ_f is determined by external loads. The growth rate of elastic energy reaches its maximum value in the early stage of yield, while the proportion of elastic energy reaches its peak value in the later stage of yield. In the deformation and failure process of rocks with varying moisture contents, the increment in elastic performance is smallest in the initial compaction stage for saturated rocks, whereas it is the largest in the yield stage for dry rocks. Additionally, a damage evolution equation based on energy dissipation was established and validated. Full article