bluuebunny/crossref_metadata_2025 huggingface dataset:
Neural Signature and Decoding of Unmanned Aerial Vehicle Operators in Emergency Scenarios Using Electroencephalography
Authors: Liu Manyu , Liu Ying , Feleke Aberham Genetu , Fei Weijie , Bi Luzheng
Published: September 2024

Brain–computer interface (BCI) offers a novel means of communication and control for individuals with disabilities and can also enhance the interactions between humans and machines for the broader population. This paper explores the brain neural signatures of unmanned aerial vehicle (UAV) operators in emergencies and develops an operator’s electroencephalography (EEG) signals-based detection method for UAV emergencies. We found regularity characteristics similar to classic event-related potential (ERP) components like visual mismatch negativity (vMMN) and contingent negative variation (CNV). Source analysis revealed a sequential activation of the occipital, temporal, and frontal lobes following the onset of emergencies, corresponding to the processing of attention, emotion, and motor intention triggered by visual stimuli. Furthermore, an online detection system was implemented and tested. Experimental results showed that the system achieved an average accuracy of over 88% in detecting emergencies with a detection latency of 431.95 ms from the emergency onset. This work lays a foundation for understanding the brain activities of operators in emergencies and developing an EEG-based detection method for emergencies to assist UAV operations.
Hyperspectral Prediction Models of Chlorophyll Content in Paulownia Leaves under Drought Stress
Authors: Zhang Yamei , Ru Guangxin , Zhao Zhenli , Wang Decai
Published: September 2024

This study explored the quantitative inversion of the chlorophyll content in Paulownia seedling leaves under drought stress and analyzed the factors influencing the chlorophyll content from multiple perspectives to obtain the optimal model. Paulownia seedlings were selected as the experimental materials for the potted water control experiments. Four drought stress treatments were set up to obtain four types of Paulownia seedlings: one pair of top leaves (T1), two pairs of leaves (T2), three pairs of leaves (T3), and four pairs of leaves (T4). In total, 23 spectral transformations were selected, and the following four methods were adopted to construct the prediction model, select the best spectral preprocessing method, and explore the influence of water bands: partial least squares modeling with all spectral bands (all-band partial least squares, AB-PLS), principal component analysis partial least squares (PCA-PLS), correlation analysis partial least squares (CA-PLS), correlation analysis (water band) partial least squares, ([CA(W)-PLS]), and vegetation index modeling. Based on the prediction accuracy and the uniformity of different leaf positions, the optimal model was systematically explored. The results of the analysis of spectral reflectance showed significant differences at different leaf positions. The sensitive bands of chlorophyll were located near 550 nm, whereas the sensitive bands of water were located near 1440 and 1920 nm. The results of the vegetation index models indicate that the multiple-index models outperformed the single-index models. Accuracy decreased as the number of indicators decreased. We found that different model construction methods matched different optimal spectral preprocessing methods. First derivative spectra (R′) was the best preprocessing method for the AB-PLS, PCA-PLS, and CA-PLS models, whereas the inverse log spectra (log(1/R)) was the best preprocessing method for the CA(W)-PLS model. Among the 14 indices, the green normalized difference vegetation index (GNDVI) was most correlated with the chlorophyll content sensitivity indices, and the water index (WI) was most correlated with the water sensitive indices. At the same time, the water band affected the cross validation accuracy. When characteristic bands were used for modeling, the cross validation accuracy was significantly increased. In contrast, when vegetation indices were used for modeling, the accuracy of the cross validation increased slightly but its predictive ability was reduced; thus, these changes could be ignored. We found that leaf position also affected the prediction accuracy, with the first pair of top leaves exhibiting the worst predictive ability. This was a bottleneck that limited predictive capability. Finally, we found that the CA(W)-PLS model was optimal. The model was based on 23 spectral transformations, four PLS construction methods, water bands, and different leaf positions to ensure systematicity, stability, and applicability.
A Respiratory Sensor-Based Study of the Relationship between Voluntary Breathing Patterns and Aerobic and Anerobic Exercise Capacity—An Exploratory Applied Study
Authors: Du Yinling , Jiang Kai , Li Haojie
Published: September 2024

(1) Background: Exploring the relationship between spontaneous breathing patterns and aerobic and anerobic running exercise performance can greatly improve our understanding of optimizing physical fitness. Spontaneous breathing patterns refer to how the rhythm and depth of breathing affect performance and physical adaptation during exercise. (2) Methods: This study aimed to investigate this relationship by enrolling 240 college students (120 males and 120 females, aged 18–22). We evaluated their resting respiratory rate (RR), the combined total of abdominal and thoracic movements (AM+TM), the proportion of abdominal movement to the overall respiratory movement (AM/(AM+TM)), and the inhalation to exhalation ratio (I/E ratio). Additionally, their performance in a 50 m sprint (measuring anerobic capability), an 800- or 1000 m run (assessing mixed aerobic and anerobic capacity), and a 12 min distance run (evaluating aerobic capacity) was recorded. (3) Results: Our findings, through both correlational and comparative analyses, indicate that a larger AM+TM is predictive of a greater distance covered in the 12 min run, suggesting enhanced aerobic capacity. Interestingly, among female participants, a lower body mass index (BMI) coupled with a higher proportion of abdominal movement (AM/(AM+TM)) was linked to better performance in the 800 m run, indicative of superior mixed aerobic and anerobic capacities. These results imply that women with a larger tidal volume and those with a lower BMI but higher abdominal contribution to breathing at rest may exhibit better aerobic and mixed exercise capacities, respectively. (4) Conclusions: Based on these findings, we recommend that healthcare professionals and physical education instructors incorporate respiratory pattern assessments into their practices to potentially improve the physical health of their clients and students, with a particular emphasis on female populations. This study underscores the importance of understanding the intricate relationship between spontaneous respiratory patterns and exercise capabilities in enhancing overall physical fitness and health.
Machine Learning Applied to Edge Computing and Wearable Devices for Healthcare: Systematic Mapping of the Literature
Authors: Pereira Carlos Vinicius Fernandes , de Oliveira Edvard Martins , de Souza Adler Diniz
Published: September 2024

The integration of machine learning (ML) with edge computing and wearable devices is rapidly advancing healthcare applications. This study systematically maps the literature in this emerging field, analyzing 171 studies and focusing on 28 key articles after rigorous selection. The research explores the key concepts, techniques, and architectures used in healthcare applications involving ML, edge computing, and wearable devices. The analysis reveals a significant increase in research over the past six years, particularly in the last three years, covering applications such as fall detection, cardiovascular monitoring, and disease prediction. The findings highlight a strong focus on neural network models, especially Convolutional Neural Networks (CNNs) and Long Short-Term Memory Networks (LSTMs), and diverse edge computing platforms like Raspberry Pi and smartphones. Despite the diversity in approaches, the field is still nascent, indicating considerable opportunities for future research. The study emphasizes the need for standardized architectures and the further exploration of both hardware and software to enhance the effectiveness of ML-driven healthcare solutions. The authors conclude by identifying potential research directions that could contribute to continued innovation in healthcare technologies.
Performance of Soil Moisture Sensors at Different Salinity Levels: Comparative Analysis and Calibration
Authors: Qi Qiuju , Yang Hai , Zhou Quanping , Han Xiaole , Jia Zhengyang , Jiang Yuehua , Chen Zi , Hou Lili , Mei Shijia
Published: September 2024

Soil dielectric sensors have been widely used to obtain real-time soil moisture data, which are important for water resource management. However, soluble salts in the soil significantly affect the accuracy of these sensor measurements. Therefore, it is crucial to select suitable soil dielectric sensors for soil moisture measurements at different salinity levels. Eight mainstream sensors (EC-5, 5TE, Teros12, Hydra-probe II, TDR315L, TDR315H, TDR305H, and CS655) were selected and tested at four different soil salinity levels (EC1:5 = 3.0, 1.5, 1.0, and 0.75 dS·m−1). The measured values using the factory calibration formulas were compared at six soil moisture levels. The results showed that the measured soil moisture values from various sensors exhibited varying degrees of overestimation, which increased with increasing salinity. Only EC-5 did not exhibit distortion at high-salinity levels, with the measured values showing a good linear trend compared to the standard values. Mutational distortion of the measured apparent dielectric permittivity occurred in TDR315L, TDR315H, Hydra-probe II, and 5TE at EC1:5 = 3.0 dS·m−1. Insensitive distortion of the measured apparent dielectric permittivity occurred in Teros12 and TDR305H at EC1:5 = 3.0 dS·m−1 as well as in Teros12, TDR305H, 5TE and Hydra-probe II at EC1:5 = 1.5 dS·m−1. All tested sensors performed reasonably well at EC1:5 ≤ 1.0 dS·m−1. Seven sensors (excluding CS655) were calibrated within the distortion threshold. The soil moisture accuracy using the calibrated formulas could reach ±0.02 cm3·cm−3. At EC1:5 ≤ 1.0 dS·m−1, most sensors in this study could be applied with the factory calibration formulas. TDR series, EC-5, 5TE and Teros12 were recommended after calibration for EC1:5 > 1.0 dS·m−1. For extremely high soil salinity levels, the TDR series and EC-5 may be the best choices.
Fuzzy Petri Nets for Traffic Node Reliability
Authors: Kiss Gabor , Bakucz Peter
Published: September 2024

Self-driving cars are one of the main areas of research today, but it has to be acknowledged that the information from the sensors (the perceptron) is a huge amount of data, which is now unmanageable even when projected onto a single traffic junction. In the case of self-driving, the nodes have to be sequenced and organized according to the planned route. A self-driving car in Hungary would have to be able to interpret more than 70,000 traffic junctions to be able to drive all over the country. Besides the huge amount of data, another problem is the issue of validation and verification. For self-driving cars, this implies a level of complexity using traditional methods that calls into question the economics of the already existing system. Fuzzy Petri nets provide an alternative solution to both problems. They allow us to obtain a model that accurately describes the reliability of a node through its dynamics, which is essential in perception since the more reliable a node is, the smaller the deep learning mesh required. In this paper, we outline the analysis of a traffic node’s safety using Petri nets and fuzzy analysis to gain information on the reliability of the node, which is essential for the modeling of self-driving cars, due to the deep learning model of perception. The reliability of the dynamics of the node is determined by using the modified fuzzy Petri net procedure. The need for a fuzzy extension of the Petri net was developed by knowledge of real traffic databases.
A Driving Warning System for Explosive Transport Vehicles Based on Object Detection Algorithm
Authors: Sun Jinshan , Zheng Ronghuan , Liu Xuan , Jiang Weitao , Jia Mutian
Published: September 2024

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.
A ROS2-Based Gateway for Modular Hardware Usage in Heterogeneous Environments
Authors: Carreira Rúben , Costa Nuno , Ramos João , Frazão Luís , Pereira António
Published: September 2024

The rise of robotics and the Internet of Things (IoT) could potentially represent a significant shift towards a more integrated and automated future, where the physical and digital domains may merge. However, the integration of these technologies presents certain challenges, including compatibility issues with existing systems and the need for greater interoperability between different devices. It would seem that the rigidity of traditional robotic designs may inadvertently make these difficulties worse, which in turn highlights the potential benefits of modular solutions. Furthermore, the mastery of new technologies may introduce additional complexity due to the varying approaches taken by robot manufacturers. In order to address these issues, this research proposes a Robot Operating System (ROS2)-based middleware, called the “ROS2-based gateway”, which aims to simplify the integration of robots in different environments. By focusing on the payload layer and enabling external communication, this middleware has the potential to enhance modularity and interoperability, thus accelerating the integration process. It offers users the option of selecting payloads and communication methods via a shell interface, which the middleware then configures, ensuring adaptability. The solution proposed in this article, based on the gateway concept, offers users and programmers the flexibility to specify which payloads they want to activate depending on the task at hand and the high-level protocols they wish to use to interact with the activated payloads. This approach allows for the optimisation of hardware resources (only the necessary payloads are activated), as well as enabling the programmer/user to utilise high-level communication protocols (such as RESTful, Kafka, etc.) to interact with the activated payloads, rather than low-level programming.
An Eco-Driving Strategy at Multiple Fixed-Time Signalized Intersections Considering Traffic Flow Effects
Authors: Wang Huinian , Guo Junbin , Wang Jingyao , Guo Jinghua
Published: September 2024

To encourage energy saving and emission reduction and improve traffic efficiency in the multiple signalized intersections area, an eco-driving strategy for connected and automated vehicles (CAVs) considering the effects of traffic flow is proposed for the mixed traffic environment. Firstly, the formation and dissipation process of signalized intersection queues are analyzed based on traffic wave theory, and a traffic flow situation estimation model is constructed, which can estimate intersection queue length and rear obstructed fleet length. Secondly, a feasible speed set calculation method for multiple signalized intersections is proposed to enable vehicles to pass through intersections without stopping and obstructing the following vehicles, adopting a trigonometric profile to generate smooth speed trajectory to ensure good riding comfort, and the speed trajectory is optimized with comprehensive consideration of fuel consumption, emissions, and traffic efficiency costs. Finally, the effectiveness of the strategy is verified. The results show that traffic performance and fuel consumption benefits increase as the penetration rate of CAVs increases. When all vehicles on the road are CAVs, the proposed strategy can increase the average speed by 9.5%, reduce the number of stops by 78.2%, reduce the stopped delay by 82.0%, and reduce the fuel consumption, NOx, and HC emissions by 20.4%, 39.4%, and 46.6%, respectively.
Hyphenated Techniques and NMR Methods for Possible Organochlorinated Pesticides Occurrence in Human and Animal Milk
Authors: Thanou Eleni D. , Tsiafoulis Constantinos G.
Published: September 2024

Although not expected to be used due to restrictions raised on their usage, Persisted Organic Pollutants (POP) such as organochlorinated pesticides (OCPs) can be found in several matrices, even nowadays. The lack of biodegradation and, furthermore, their persistence in the environment result in the possible occurrence of these lipophilic toxins in several matrices, from environmental samples and foods to human milk. The current review focuses on the usage of hyphenated techniques for the determination and monitoring of OCPs in several matrices, such as milk—both animal and human milk. The lipid matrix of milk and dairy products favors the possible bioaccumulation of the above pollutants, and the complex matrix of the dairy products is a challenge for method development. Additionally, spectroscopic methods—mainly Nuclear Magnetic Resonance (NMR)-based metabolomics—for biomonitoring of OCPs persistence, bioaccumulation, and effect of possible exposure, along with NMR usage in several methods developed, are also presented and discussed. Finally, we introduce and present the metabolomic approach for OCPs and other POPs in lipid matrices.
Surveillance, Disinformation, and Legislative Measures in the 21st Century: AI, Social Media, and the Future of Democracies
Authors: Azgin Bilge , Kiralp Sevki
Published: September 2024

In contemporary society, the internet, particularly social media, has become a significant area where individuals spend considerable amounts of time engaging in various activities. Concurrently, the growing utilization of artificial intelligence (AI) has emerged as a critical component of the propaganda that is disseminated online within economic, social, and political spheres. AI encompasses a broad range of applications, including data collection for microtargeting and the dissemination of diverse forms of disinformation. Additionally, AI can be effectively employed to detect and remove content from social media platforms that contradicts democratic principles, such as disinformation or hate speech. This study reviews the existing literature on the use of AI in political propaganda, examining not only how AI has become an integral part of propaganda strategies, but also how it is utilized to counter propaganda that violates democratic values. It explores the legislation in various countries that enables (and mandates) the removal of propaganda content contrary to democratic principles from social media platforms with the assistance of AI, and it discusses perspectives that highlight the potential conflict between these practices and the principle of freedom of expression.
Omitting the Application of Nitrogen or Potassium Reduced the Growth of Young Chestnut (Castanea sativa) Trees, While a Lack of Boron Decreased Fruit Yield
Authors: Arrobas Margarida , Raimundo Soraia , Correia Carlos Manuel , Rodrigues Manuel Ângelo
Published: September 2024

The chestnut tree (Castanea sativa Mill.) is gaining importance in the mountainous regions of southern Europe due to the high value of its fruits. It is essential to establish effective cultivation protocols, considering that this species is still relatively understudied. In this study, we present the outcomes of the initial establishment of a chestnut orchard conducted through a nutrient omission trial for four years. The treatments included a fertilization plan with nitrogen, phosphorus, potassium, and boron (NPKB), the control, and four other treatments corresponding to the omission of each nutrient (-NPKB, N-PKB, NP-KB, NPK-B). The -NPKB and NP-KB treatments showed significantly lower trunk circumferences and canopy volumes compared to the other treatments. The NPK-B treatment resulted in the lowest fruit production, with a total accumulated yield (2020–2022) of 0.56 kg tree–1, a value significantly lower than that of NPKB (1.12 kg tree–1) and N-PKB (1.19 kg tree–1). The assessment of nutrient concentrations in the leaves revealed plants with deficient levels of B and K in treatments that did not receive these nutrients. Conversely, N levels in the leaves in the -NPKB treatment fell within the sufficiency range (20 to 28 g kg–1). This suggests that the sufficiency range should be adjusted to higher values, given the treatment’s effect on tree growth. It was also observed that the -NPKB treatment led to lower soil organic matter compared to the other treatments, likely due to reduced herbaceous vegetation development under the canopy, leading to decreased organic substrate deposition in the soil. The main findings of this study are that N and K were crucial elements for the optimal growth of chestnut trees, while B played a significant role in fruit production.
Decoding Jakarta Women’s Non-Working Travel-Mode Choice: Insights from Interpretable Machine-Learning Models
Authors: Hermaputi Roosmayri Lovina , Hua Chen
Published: September 2024

Using survey data from three dwelling types in Jakarta, we examine how dwelling type, socioeconomic identity, and commuting distance affect women’s travel-mode choices and motivations behind women’s choices for nearby and distant non-working trips. We compared the performance of the multinomial logit (MNL) model with two machine-learning classifiers, random forest (RF) and XGBoost, using Shapley additive explanations (SHAP) for interpretation. The models’ efficacy varies across different datasets, with XGBoost mostly outperforming other models. The women’s preferred commuting modes varied by dwelling type and trip purpose, but their motives for choosing the nearest activity were similar. Over half of the women rely on private motorized vehicles, with women living in the gated community heavily relying on private cars. For nearby shopping trips, low income and young age discourage women in urban villages (kampungs) and apartment complexes from walking. Women living in gated communities often choose private cars to fulfill household responsibilities, enabling them to access distant options. For nearby leisure, longer commutes discourage walking except for residents of apartment complexes. Car ownership and household responsibilities increase private car use for distant options. SHAP analysis offers practitioners insights into identifying key variables affecting travel-mode choice to design effective targeted interventions that address women’s mobility needs.
Prediction Method of Rock Uniaxial Compressive Strength Based on Feature Optimization and SSA-XGBoost
Authors: Xie Huihui , Lin Peng , Kang Jintao , Zhai Chenyu , Du Yuchao
Published: September 2024

In order to establish an optimal model for reasonably predicting the uniaxial compressive strength (UCS) of rocks, a method based on feature optimization and SSA-XGBoost was proposed. Firstly, the UCS predictor system of rocks, considering petrographic and physical parameters, was determined based on the systematic discussion of the factors affecting the UCS of rocks. Then, a feature selection method combining the RReliefF algorithm and Pearson correlation coefficient was proposed to further determine the optional input features. The XGBoost algorithm was used to establish the prediction model for rock UCS. In the process of model training, the Sparrow Search Algorithm (SSA) was used to optimize the hyperparameters. Finally, model evaluation was carried out to test the performance of the UCS prediction model. The method was applied and validated in a granitic tunnel. The results show that the proposed UCS prediction model can effectively predict the UCS of granitic rocks. Compared with simply adopting petrographic or physical parameters as the input features of the model, the UCS predictor considering petrographic and physical characteristics can improve the generalization ability of the SSA-XGBoost UCS prediction model effectively. The prediction method proposed in this study is reasonable and can provide some reference for establishing a universal method for accurately and quickly predicting the UCS of rocks.
Ecological Security Evaluation and Prediction for Coal Resource Cities Based on the PSR Model: A Case Study of Xuzhou, China
Authors: Song Zhihui , Zhu Nan , Yang Dejun , He Dan
Published: September 2024

The rapid development of urbanization has led to population growth, increased resource consumption, and intensified environmental pollution. Consequently, urban ecological security has increasingly become a key factor constraining the sustainable development of socio-economic systems. This study constructed an urban ecological security evaluation system based on the Pressure-State-Response (PSR) model and used Xuzhou, a typical coal resource city, as a case study to apply and validate the model. Specifically, the analytic hierarchy process and entropy weight method were used to determine the index weights, and the ecological security index was used to evaluate the ecological security status of each system in Xuzhou from 2006 to 2022. Finally, the grey prediction GM (1,1) model was used to predict the ecological security status of Xuzhou in the next five years. The results show that the “disposal capacity of waste gas treatment facilities”, “per capita disposable income”, and “agricultural fertilizer application intensity” occupy a large weight in the whole evaluation system. The pressure index generally showed a fluctuating upward trend, and the state index fluctuated around 0.12. There is a simultaneous upward trend in the response index and the composite index. The ecological security level of the composite index has increased from “unsafe” in 2006 to “relatively safe” in 2022 and will continue to improve to “ideal security” in the future. This study provides a scientific basis for the formulation of sustainable development policies in Xuzhou and also provides a reference for the ecological safety management and assessment of other similar cities.
The Coupling Coordination Degree and Its Driving Factors for Water–Energy–Food Resources in the Yellow River Irrigation Area of Shandong Province
Authors: Zhang Wei , Liu Chang , Li Lingqi , Jiang Enhui , Zhao Hongjun
Published: September 2024

Water resources, energy, and food are essential for the development of society, and they are strongly interdependent. The coupling and coordination relationships of the water–energy–food (WEF) system are important for regional resource security and high-quality development. The Yellow River Irrigation Area in Shandong Province, China, is a grain production base and has a substantial impact on national food security. To examine the water, energy, and food subsystem dynamics in this area, an evaluation system for the WEF system was established. A comprehensive weighting method based on game theory was employed to determine index weights. TOPSIS was used to assess the development level of the WEF system. A coupling coordination degree model was used to analyze the evolution of the coupling coordination degree of the WEF system from 2000 to 2020, and a GWR model was constructed to explore the spatial heterogeneity of its driving factors. The findings indicated that the development level of the WEF system in the study area was moderate, with a gradual upward trend. The coupling coordination degree fluctuated between 0.62 and 0.739. The GWR model revealed that temperature had an overall negative effect on the coupling coordination degree, with the greatest impact on the central irrigation area; the slope and NDVI had a negative effect, with increasing intensity from the southwest to the northeast; and rainfall had an overall positive effect, with the greatest impact on the irrigation area near the estuary in the northeast. Overall, the building area ratio had a negative effect on the coupling coordination degree, with exceptions in some areas. These research outcomes provide theoretical support for sustainable agricultural development in the Yellow River irrigation areas of Shandong Province and methodological reference data for studying collaborative resource utilization in irrigation regions.
Evaluation of the Impacts of On-Demand Bus Services Using Traffic Simulation
Authors: Liyanage Sohani , Dia Hussein , Duncan Gordon , Abduljabbar Rusul
Published: September 2024

This paper uses smart card data from Melbourne’s public transport network to model and evaluate the impacts of a flexible on-demand transport system. On-demand transport is an emerging mode of urban passenger transport that relies on meeting passenger demand for travel using dynamic and flexible scheduling using shared vehicles. Initially, a simulation model was developed to replicate existing fixed-schedule bus performance and was then extended to incorporate on-demand transport services within the same network. The simulation results were used to undertake a comparative analysis which included reliability, service quality, operational efficiency, network-wide effectiveness, and environmental impacts. The results showed that on-demand buses reduced average passenger trip time by 30%, increased vehicle occupancy rates from 8% to over 50%, and reduced emissions per passenger by over 70% on an average weekday compared to fixed-schedule buses. This study also offers insights for successful on-demand transport implementation, promoting urban sustainability. It also outlines future research directions, particularly the need for accurate short-term passenger demand prediction to improve service provision and passenger experience.
Modelling the Influence of Management Practices on Sustainable Market Performance in Serbian Enterprises
Authors: Mazić Mina , Terek Stojanović Edit , Stanisavljev Sanja , Bakator Mihalj
Published: September 2024

In the evolving global market, new business conditions necessitate that enterprises adapt and construct organizational structures grounded in new principles and the implementation of contemporary management methods. This is particularly crucial for enterprises in transitional economies, which need to be highly flexible and innovative to meet the increasing demands of users swiftly, employ modern management techniques, and gain a competitive edge. The modern business environment assumes that there are very few products, technologies, services, knowledge areas, or procedures unavailable to interested groups worldwide. This study examines the influence of modern management methods and techniques (MMMTs), human resource management (HRM), quality management (QM), and intellectual capital management (ICM) on the sustainable market performance (SMPC) of these enterprises. A structured survey was conducted among 146 managers from various Serbian industrial enterprises, and the data were analyzed using descriptive statistics, Pearson correlation analysis, linear regression, and multicollinearity tests. The results revealed significant positive correlations between MMMTs, HRM, QM, ICM, and SMPC, with quality management having the highest impact. These findings provide valuable insights for improving business competitiveness in Serbia’s industrial sector. The results also support the development of an integrated model for sustainable management practices in transitional economies.
Composite Intake Ports Interference Mechanism and Application in Dual Intake Channels of the Opposed-Piston Diesel Engine
Authors: Liang Yongsen , Wang Wenxiao , Zuo Zhengxing , Jia Boru , Wang Wei , Xu Yonghong
Published: September 2024

With the development of control technology, the uniflow scavenging opposed-piston (USOP) diesel engine has shown unique advantages in energy savings and emission reductions. Due to the uniflow scavenging process, unstable scavenging performance has become the key problem in the development process of the USOP diesel engine, and the intake structure is an effective method for regulating scavenging performance. This study verifies the simulation model based on experimental data and then analyzes the influence of the intake port structure through simulations. On the one hand, this study explores the interference mechanism and application rules of two structures: composite intake ports and dual independent intake ports. The results show that the external alignment structure should be used under all operating conditions for composite intake ports. For dual independent intake ports, the internal alignment structure should be used at high swirl strength, and the external alignment structure should be used at low swirl strength. On the other hand, the dual independent intake ports matching the dual intake channels can improve scavenging performance while reducing supply power. The conclusion provides a reference for the design of the intake structure of the USOP diesel engine from many aspects.
Public Food Trees’ Usage and Perception, and Their Potential for Participatory Edible Cities: A Case Study in Birjand, Iran
Authors: Colinas Juliette , Ugolini Francesca , Khalilnezhad Mohammad Reza
Published: September 2024

Public food trees are increasingly popular among researchers, urban planners, and citizens for their diversity of social, provisional, and environmental benefits. However, more research is needed to determine how to overcome their barriers. Here we used a qualitative approach to explore the usage and perception of public fruit trees and attitudes towards public usage and participation in two urban green spaces harboring fruit trees in Birjand, Iran: Tohid Park and Akbarieh Garden. Semi-structured interviews were conducted with twelve visitors to both spaces, four administrators, and eight workers. Almost all visitors had great personal experience and interest in picking fruit; nevertheless, usage in these green spaces was low, partly due to social norms. Almost all visitors appreciated the public fruit trees for the diverse pleasures that they provide (sensory, emotional, cognitive, experiential, social). Ten also had a high interest in participating in their management, especially in Tohid Park due to its greater social impact. Education and access limitation were suggested by some as important to reduce tree damage and maximize production. Our findings expand our understanding of how citizens relate to public urban fruit trees and can be involved in co-management schemes, thereby contributing to building smart and participatory edible cities.
Comparative Analysis of Sustainable Seafarers’ Employment and Welfare Systems in South Korea and China: Contemporary Issues and Improvements
Authors: Choi Junghwan , Lim Sangseop , Lee Changhee
Published: September 2024

Seafarers are recognized as essential workers responsible for maintaining the national logistics supply chain. This study analyzes the sustainable seafarers’ employment and welfare systems in South Korea and China using the comparative case study approach and presents relevant implications. In the era of the “New Normal” after the coronavirus disease 2019 pandemic, which is marked by hyper-personalization, seafarers have become increasingly resistant to acquiring maritime education and performing onboard duties. Even though South Korea has recognized seafarers as key agents of national economic growth, the participation of the new generation in the shipping industry has recently been declining. Meanwhile, China has been developing its shipping industry since the Deng Xiaoping reforms and fosters skilled seafarers by providing rigorous maritime education. However, both countries have been experiencing difficulties in ensuring the legal and social protection of seafarers; hence, the challenge of providing sustainable employment and welfare to seafarers remains. In conclusion, this study proposes the establishment of the “Asia Maritime Education, Employment, and Welfare Support Center” to support seafarers’ employment and welfare with the cooperation of other countries in the Asian region.
Impact of the COVID-19 Pandemic on the Financial Situation of Rural and Urban Households in Poland
Authors: Głowicka-Wołoszyn Romana , Wołoszyn Andrzej , Stanisławska Joanna , Oliveira Amílcar , Oliveira Teresa
Published: September 2024

The COVID-19 pandemic not only caused a global health crisis but also had a huge impact on household finances. This research aimed to examine the financial situation of rural and urban households in Poland between 2018 and 2022 from a multidimensional perspective. In a unidimensional approach, the financial situation of households was analyzed separately for their income, expenditures, savings rate, and shares of fixed expenses. In a multidimensional approach, the analysis used a synthetic index constructed for all these variables combined, employing the TOPSIS method and drawing on microdata from the Polish Central Statistical Office that totaled approximately 150,000 households. It was found that despite the pandemic outbreak, which led to major changes in the labor market, government-introduced organizational and legal measures protected the income of Polish households from decline. Indeed, income was increasing up until 2021, with a modest fall in 2022, which was less severe in rural households (by about 2%) than in urban ones (by 6%). A more immediate response to the outbreak was observed in consumer spending, which fell sharply, while the food share in consumption increased at similar levels in rural and urban areas. Regression analysis showed that compared to 2019, the pandemic worsened the financial situation of Polish households, but only in 2020 and 2022 were these changes statistically significant. In 2021, the financial situation improved slightly, but the change was not statistically significant. Before the pandemic, the synthetic assessment of the financial situation in rural areas was lower than in urban ones, and the pandemic period did not reduce these differences, showing no convergence between poorer rural areas and richer urban ones. Diagnosing and monitoring the household financial situation are crucial steps for achieving the social dimension goals of sustainable development. Research on the pandemic’s effects on household finances provides valuable information that can help develop effective strategies to counter future crises while supporting the social dimension of the sustainable development strategy.
Digital Escape Rooms: A Resource for Environmental Education
Authors: Repetto Manuela , Bianco Prevot Alessandra , Brizio Adelina , Boldi Arianna , Talarico Melania , Stanchi Silvia , Palma Davide , Acquadro Maran Daniela
Published: September 2024

Today’s adolescents represent an elective target in addressing environmental challenges. Education is a key factor in achieving a sustainable future for them. However, formal education can represent a challenge when youths are its target, as they are considered the “interactive generation”. Game-based learning, and, in particular, Digital Educational Escape Rooms (DERs), have emerged as innovative methods in education, with promising applications in environmental sustainability studies. In this study, we developed 14 Digital Escape Rooms using the Social Cognitive Theory of Bandura as a theoretical framework. These were focused on environmental education and we tested them on a sample of 411 students (aged 12–18 years; 158 female, 38.4%). A one-group quasi-experimental research design was adopted, carrying out a pre-test post-test analysis. Each participant completed assessments at two time points: before engaging in the escape rooms (T0) and after (T1). The assessment tools included the Goal Assessment Scale (GAS) and the Perceived Climate Self-Efficacy Scale. Our findings revealed no significant gender differences in goal achievement. However, at T0, females exhibited higher levels of perceived climate self-efficacy in both individual and collective dimensions. Instead, the Digital Escape Rooms appeared particularly effective in increasing self-efficacy among male participants. These results suggest that Digital Escape Rooms hold potential for enhancing environmental self-efficacy, although gender differences in baseline efficacy levels warrant further exploration.
Dynamic Analysis and Temporal Governance of Safety Risks: Evidence from Underground Construction Accident Reports
Authors: Wu Xiuyu , Sun Pengkai
Published: September 2024

Due to the complexity and dynamics of underground construction projects, safety risk management has experienced significant challenges restricting the sustainable development of underground space. The research on risk causal chains and risk coupling has yet to reveal the dynamic interactive characteristics of these risk factors and their temporal relationships over time. This study utilized a complex system view for safety risk analysis, using 37 accident investigation reports of underground construction projects. Combined with two novel and emerging analytical methods, temporal qualitative comparative analysis and crisp-set qualitative comparative analysis, this study discusses the temporal relationship of risk factors to the cause of accidents and explores the multi-actor coupling characteristics of management risk. The findings indicate that (1) compared with general construction projects, underground construction should pay more attention to management safety risks because they have an obvious time lag effect expressed in all accident causation paths, namely, preceding management risk, management risk, and machine/material risk cross-concurrently, and management risk initiation and (2) underground construction project management risks have three key main paths, namely, single-actor-dominated management deficiency (supervisors, owners, and subcontractors that cause management risks as a single-core actor) and dual-actor-dominated management deficiency (owner and subcontractor as dual core actors of management risk). Multi-actor-dominated management deficiency (owners, subcontractors, and supervisors are the multiple core actors of management risk). This study thus developed a temporal governance framework of underground construction safety risks based on the synergy of multi-actors and proposed risk governance strategies, such as synergistic multi-actor governance, to consider the temporal relationship of safety risk. This study further reveals the temporal and coupling characteristics of safety risks to enrich the risk casual chain theory and risk coupling theory and establish a systematic risk analysis framework for new guidance for safety and risk management for underground construction projects.
The Rise and Transfer of the River Chief System: A Review of Chinese Water Governance and Its Potential to Transfer to the Global Community
Authors: Dolowitz David Peter
Published: September 2024

As a result of water sustainability issues, China has enacted a range of policies to improve its water ecosystem since the middle of the 20th century. These measures include the creation of the Seven River Conservancy Commissions, the development (combination and recombination) of ministries and departments to address environmental pollution and degradation, and recently, the implementation of the river chief system. Considering the importance of global water sustainability and the positive impact Chinese measures have had in this area, the author will examine if the river chief can be transferred to other political jurisdictions. To do this, the author gathered data using keyword searches of the Web of Science and Google Scholar, official government sites, media sites and key international organizations. Based on this, the author reviews the development of the river chief system in the context of broader ecological reforms, places the rise of the river chief in the context of potential lessons for future improvement, and speculates on the possibility that China could transfer the river chief to countries facing similar challenges in their water governance regimes.
Upcycling PVC and PET as Volume-Enhancing Functional Fillers for the Development of High-Performance Bio-Based Rigid Polyurethane Foams
Authors: Ochigue Princess Claire D. , Dingcong Roger G. , Bondaug John Christian S. , Magalong Brian Christian G. , Dumancas Gerard G. , Gutierrez Carlo S. , Alguno Arnold C. , Malaluan Roberto M. , Lubguban Arnold A. , Bacosa Hernando P.
Published: September 2024

Polyvinyl chloride (PVC) and polyethylene terephthalate (PET) contribute significantly to global plastic waste, with only 9% recycled in recent years. In this work, these plastic wastes were upcycled as functional fillers to improve the rigid polyurethane foam (RPUF) properties. To attain this target, we leveraged the intrinsic polarity of the C=O and C-Cl groups of PVC and PET to induce intermolecular attractions with the N-H groups of the polyurethane matrix, evidenced by the observed IR peak shifts. This enhanced the nucleating effect during foaming, increasing the foams’ compressive strengths by 77% and 22% with the addition of 10% PVC and 5% PET filler, respectively. Furthermore, the addition of PVC and PET fillers increased the foam volume. Thus, the collective utilization of PPW and its corresponding impact on the CO-based RPUF’s properties signifies a reduction in carbon dioxide emissions by 14.15% and 17.52% for PVC and PET, respectively. Moreover, thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) revealed improved thermal stability and degradation profiles of the produced RPUFs. Overall, this work highlights potential advancement in environmentally responsible upcycling strategies for common end-of-life plastic wastes, while enhancing rigid foam properties.
The Psychological Mechanism of Moral Leadership Influencing Responsible Subordinate Behavior
Authors: Zhang Zonghe , Mao Yuxi , Liu Weichen
Published: September 2024

As China’s anti-corruption campaign intensifies, several of those involved in various capacities in the public sector are demonstrating slackness, a lack of moral awareness, and a weakened sense of responsibility. This study analyzes the multiple mechanisms influencing the responsible behavior of public sector personnel by combining certain key factors, such as managers’ moral leadership style, psychological security, and the notion of interactive justice. Based on social information processing theory and social exchange theory, this study constructs a dual mediation model (psychological security and interactive justice) to explore the mediating psychological mechanism of moral leadership influencing employees’ responsible behavior. The results of a two-stage paired survey and structural equation modeling analysis of civil servants from 48 departments and eight units in Shandong and Henan provinces show that moral leadership positively impacts responsible behavior. Moreover, psychological security and interactive justice play a mediating role between them. Furthermore, this study elaborates upon the mechanism of moral leadership affecting the responsible behavior of employees, which is of great value for improving the efficiency of government management and guiding civil servants to behave more responsibly.