bluuebunny/crossref_metadata_2025 huggingface dataset:
Fault Diagnostics Based on the Analysis of Probability Distributions Estimated Using a Particle Filter
Authors: Darányi András , Abonyi János
Published: January 2024

This paper proposes a monitoring procedure based on characterizing state probability distributions estimated using particle filters. The work highlights what types of information can be obtained during state estimation and how the revealed information helps to solve fault diagnosis tasks. If a failure is present in the system, the output predicted by the model is inconsistent with the actual output, which affects the operation of the estimator. The heterogeneity of the probability distribution of states increases, and a large proportion of the particles lose their information content. The correlation structure of the posterior probability density can also be altered by failures. The proposed method uses various indicators that characterize the heterogeneity and correlation structure of the state distribution, as well as the consistency between model predictions and observed behavior, to identify the effects of failures.The applicability of the utilized measures is demonstrated through a dynamic vehicle model, where actuator and sensor failure scenarios are investigated.
Live Cell Imaging by Single-Shot Common-Path Wide Field-of-View Reflective Digital Holographic Microscope
Authors: Kumar Manoj , Murata Takashi , Matoba Osamu
Published: January 2024

Quantitative phase imaging by digital holographic microscopy (DHM) is a nondestructive and label-free technique that has been playing an indispensable role in the fields of science, technology, and biomedical imaging. The technique is competent in imaging and analyzing label-free living cells and investigating reflective surfaces. Herein, we introduce a new configuration of a wide field-of-view single-shot common-path off-axis reflective DHM for the quantitative phase imaging of biological cells that leverages several advantages, including being less-vibration sensitive to external perturbations due to its common-path configuration, also being compact in size, simple in optical design, highly stable, and cost-effective. A detailed description of the proposed DHM system, including its optical design, working principle, and capability for phase imaging, is presented. The applications of the proposed system are demonstrated through quantitative phase imaging results obtained from the reflective surface (USAF resolution test target) as well as transparent samples (living plant cells). The proposed system could find its applications in the investigation of several biological specimens and the optical metrology of micro-surfaces.
Design of Optical System for Ultra-Large Range Line-Sweep Spectral Confocal Displacement Sensor
Authors: Yang Weiguang , Du Jian , Qi Meijie , Yan Jiayue , Cheng Mohan , Zhang Zhoufeng
Published: January 2024

The spectrum confocal displacement sensor is an innovative type of photoelectric sensor. The non-contact advantages of this method include the capacity to obtain highly accurate measurements without inflicting any harm as well as the ability to determine the object’s surface contour recovery by reconstructing the measurement data. Consequently, it has been widely used in the field of three-dimensional topographic measuring. The spectral confocal displacement sensor consists of a light source, a dispersive objective, and an imaging spectrometer. The scanning mode can be categorized into point scanning and line scanning. Point scanning is inherently present when the scanning efficiency is low, resulting in a slower measurement speed. Further improvements are necessary in the research on the line-scanning type. It is crucial to expand the measurement range of existing studies to overcome the limitations encountered during the detection process. The objective of this study is to overcome the constraints of the existing line-swept spectral confocal displacement sensor’s limited measuring range and lack of theoretical foundation for the entire system. This is accomplished by suggesting an appropriate approach for creating the optical design of the dispersive objective lens in the line-swept spectral confocal displacement sensor. Additionally, prism-grating beam splitting is employed to simulate and analyze the imaging spectrometer’s back end. The combination of a prism and a grating eliminates the spectral line bending that occurs in the imaging spectrometer. The results indicate that a complete optical pathway for the line-scanning spectral confocal displacement sensor has been built, achieving an axial resolution of 0.8 μm, a scanning line length of 24 mm, and a dispersion range of 3.9 mm. This sensor significantly expands the range of measurements and fills a previously unaddressed gap in the field of analyzing the current stage of line-scanning spectral confocal displacement sensors. This is a groundbreaking achievement for both the sensor itself and the field it operates in. The line-scanning spectral confocal displacement sensor’s design addresses a previously unmet need in systematic analysis by successfully obtaining a wide measuring range. This provides systematic theoretical backing for the advancement of the sensor, which has potential applications in the industrial detection of various ranges and complicated objects.
Research on the Technological Progress of CZT Array Detectors
Authors: Li Zhangwen , Cheng Jinxing , Liu Fang , Wang Qingbo , Wen Wei-Wei , Huang Guangwei , Wu Zeqian
Published: January 2024

CdZnTe (CZT) is a new type of compound semiconductor that has emerged in recent years. Compared to other semiconductor materials, it possesses an ideal bandgap, high density, and high electron mobility, rendering it an excellent room-temperature composite semiconductor material for X-ray and γ-ray detectors. Due to the exceptional performance of CZT material, detectors manufactured using it exhibit high energy resolution, spatial resolution, and detection efficiency. They also have the advantage of operating at room temperature. CZT array detectors, furthermore, demonstrate outstanding spatial detection and three-dimensional imaging capabilities. Researchers worldwide have conducted extensive studies on this subject. This paper, building upon this foundation, provides a comprehensive analysis of CZT crystals and CZT array detectors and summarizes existing research to offer valuable insights for envisioning new detector methodologies.
Investigating the Effect of Living Walls on Cooling Energy Consumption in Various Urban Microclimates, Building Heights, and Greenery Coverage Areas
Authors: Bakhtyari Vahid , Fattahi Kaveh , Movahed Khosro , Franz Anna
Published: January 2024

With the aim of addressing the significant contribution of buildings to global energy consumption and the growing need to establish a more harmonious connection between humans and nature in urban environments, the concept of green vertical systems has garnered considerable attention. These systems possess the potential to enhance the energy efficiency and environmental sustainability of buildings. This study seeks to explore the impact of living walls on the energy performance of buildings, specifically investigating the influence of a living-walled urban block on the ambient air temperature and its subsequent effect on building energy consumption. By comparing the cooling energy consumption of two typical buildings situated in Shiraz, southern Iran, with varying levels of greenery in different microclimates, we further ascertain the effectiveness of living walls in reducing energy consumption. To conduct this analysis, we employed coupled simulations utilizing EnergyPlus and Envi-met, which incorporated both the outdoor microclimate and the cooling energy consumption of the buildings. The urban block under consideration consisted of 48 three-story buildings (Case A) and five-story buildings (Case B) within a site measuring 120 m × 150 m. Our findings substantiate that the implementation of a living wall system can lower the ambient air temperature by a significant extent, with an average decrease of 1.35 °C and a maximum decrease of 2.25 °C. Consequently, living walls can effectively mitigate the urban heat island phenomenon by decreasing the temperatures of the surrounding buildings. Additionally, our investigations revealed a maximum energy saving of 15%, with microclimate exerting a 4.3% influence on these savings.
Age-Friendly Transportation Policies and Practices in the U.S. and China: A Comparative Study
Authors: Chen Xueming , Feng Suwei
Published: January 2024

Despite significant political, cultural, and socioeconomic differences, the U.S. and China share some common development issues, including, but not limited to, an aging population, deficient age-friendly transportation systems, and insufficient government funding support to address the issues faced by their transportation-disadvantaged populations (TDP). Through an extensive literature review, this paper first evaluates and compares the major TDP-related laws, regulations, transportation service delivery procedures, and existing age-friendly transportation improvements made in the U.S. and China. Next, it highlights the differences between the U.S. and China in their socioeconomic characteristics and the implications these have on transportation modal shares and age-friendly transportation planning priorities. In the concluding section, it summarizes the research findings and makes preliminary recommendations.
Research on the Measurement of Low-Carbon Competitiveness of Regional Cold Chain Logistics Capacity Based on Triangular Fuzzy Evaluation Rating–Gray Correlation Analysis
Authors: Yu Juan , Zhang Shiqing
Published: January 2024

Cold chain logistics is an industry that generates high levels of carbon emissions. In the context of a low-carbon economy, it is crucial to recognize the low-carbon competitiveness of regional cold chain logistics and to implement effective measures to guide the development and improvement of their low-carbon competitiveness. This is essential for transitioning the economic development model and promoting low-carbon economic growth. This article proposes a low-carbon competitiveness evaluation model known as the Triangular Fuzzy–Gray Correlation Evaluation Model. This model is based on the Triangular Fuzzy Theory and Gray System Theory. According to the calculated logistics low-carbon competitiveness index, a scatter plot is used to rank and classify the evaluation objects. This method utilizes triangular fuzzy numbers as evaluation levels and further expands upon them by introducing the concept of gray correlation in group decision making. By constructing relative closeness based on curve similarity, the improved method possesses a strong ability to capture information and objectivity compared to traditional models. The selected critical indicators cover four significant aspects: low-carbon environment, low-carbon flow service capability, energy consumption in cold chain logistics, and low-carbon energy transition. Empirical research is being conducted using relevant data from Henan in 2022. The measured results are divided into four levels of competition. Using the diamond model, this study analyzes the development of low-carbon cold chain logistics at different levels in each city and provides corresponding recommendations.
Multidimensional Measurement and Regulation of Regional Coordinated and Balanced Development Levels: Using the Yangtze River Delta Region in China as an Example
Authors: Ye Lei , Wang Guiling , Meng Yuenan
Published: January 2024

In recent years, the problem of unbalanced and insufficient development in the Yangtze River Delta (YRD) region has become increasingly prominent, posing higher requirements for regional coordinated development. Based on elucidating the connotations of the balanced development of regional coordination, this article constructed an evaluation index system for the balanced development of regional coordination in the YRD region in 12 dimensions, such as people’s living standards, basic public services, and beautiful ecology. It attempted to quantitatively reveal the level of balanced development of regional coordination in the YRD region in 2020 and develop optimization strategies using mathematical models such as the entropy method, spatial autocorrelation, and the Gini coefficient, which have important value for clarifying the inherent contradictions in the balanced development of regional coordination in this region and promoting regional sustainable development. The main conclusions are as follows: (1) At the provincial level, Jiangsu Province won in two sub-categories, coordination and integration; Zhejiang won in the balance sub-category; and Anhui performed better in the integration sub-category. (2) The main reasons for the significant differences between the cities were the public basic services in the equilibrium index, the industrial coordination and human–nature coordination in the coordination index, and the market unity sub-item in the integration index. (3) Based on the coordinated and balanced development level in each city’s regions, four types of regulatory areas were further divided, namely, key development areas, optimized development areas, relatively underdeveloped areas, and important safety barrier areas. Differentiated regulatory policies were proposed for these areas.
Smart Cities and Greener Futures: Evidence from a Quasi-Natural Experiment in China’s Smart City Construction
Authors: Yu Chengfeng , Yu Jiyu , Gao Da
Published: January 2024

As the digital economy becomes the new engine of economic growth, China has introduced a series of smart city policies aimed at promoting high-quality and sustainable urban development. This paper aims to evaluate the green development effects of China’s “Smart City Pilot” policy and to explore the heterogeneity of policy effects across different types of cities. Using panel data from 283 prefecture-level cities in China from 2006 to 2020, this study examines the relationship between smart city construction policy and urban green development efficiency using the green total factor productivity (GTFP). We employ the Causal Forest and mediation effect models to estimate the impact of smart city pilot policy on GTFP and explore the underlying mechanisms. The main results are: (1) The smart city pilot policy significantly enhances urban GTFP, a finding consistent across diverse policy evaluation approaches. (2) The influence of the policy on green development varies among cities, and such heterogeneity is effectively captured by the Causal Forest. (3) This varied impact primarily stems from urban location factors and inherent characteristics. Notably, the policy effect in Eastern China outpaces that in other regions. The policy yields greater green benefits with financial development and medical capital rises, but excessive government public expenditure curtails its positive influence. (4) The mediation mechanisms through which the smart city pilot policy promotes green development exhibit certain differences between the “high-effect group” and the “low-effect group”. The former predominantly leverages innovation-driven and agglomeration effects, while the latter chiefly relies on industrial structural advancement and rationalization.
Investigating the Social Sustainability of Immersive Virtual Technologies in Higher Educational Institutions: Students’ Perceptions toward Metaverse Technology
Authors: Alkhwaldi Abeer F.
Published: January 2024

The Metaverse technology (MVTECH) is an immersive virtual sphere where people interact with each other via avatars. The MVTECH promised to provide a number of potentials for various sectors including higher education. Despite the fact that MVTECH promotes virtual social interaction between people (e.g., university students), there is a lack of knowledge on what affects users’ perceptions regarding its social sustainability in HEIs, specifically in developing nations. Therefore, this research paper aims to determine the variables that affect the learners’ perceptions toward social sustainability (SS) of MVTECH in higher educational institutions (HEIs) in Jordan. A study model was formulated by integrating the core factors of the “unified theory of acceptance and use of technology” (UTAUT) (“performance expectancy, PE; effort expectancy, EE; social influence, SI; and facilitating conditions, FC”) with “perceived curiosity” (PC) and “extraversion” (EXT) factors. Both PC and EXT were included as context-related variables that may possibly contribute to enhancing the applicability of UTAUT to a wide range of information technologies and settings. Data were collected from 422 students enrolled in Jordanian universities based on an online survey. The analysis of the “structural equation modeling” (SEM) found that students’ perceptions toward Metaverse were significantly influenced by PE, FC, and EXT. Furthermore, the PC construct significantly affected the EE construct. However, EE and SI were revealed to have no significant impact on SS. Drawing from these results, the study makes a number of theoretical advances and clarifies a number of practical implications for those involved in the development, design, and decision-making processes that support the use of the Metaverse in HEIs.
Research on the Collaborative Pollution Reduction Effect of Carbon Tax Policies
Authors: Yang Li
Published: January 2024

This study builds a Computable General Equilibrium model to investigate the synergistic effects and simulate the co-benefits of carbon tax policies. The conclusions are as follows: After implementing a carbon tax policy, when the carbon tax increases from 30 CNY/ton to 130 CNY/ton, and the reduction in CO2 emissions increases from 1.223 billion tons to 3.943 billion tons. At the same time, the reduction in SO2 emissions rises from 326,200 tons to 1,052,200 tons. However, overall, the reduction rate of SO2 is around 88.87% of the CO2 reduction rate. Thus, a carbon tax is also an effective policy pathway for synergistic pollution reduction and carbon mitigation. In terms of industry output, among the 15 industries, sectors such as electricity generation, aviation, and tertiary industries have increased their output, with the electricity sector achieving the highest increase of 2.9816%. Other industries have exhibited varying degrees of decline, especially coal, natural gas, oil, nonferrous metals, chemicals, steel, and building materials, with the coal industry output decreasing the most, by −49.4924%. Regarding energy consumption, as the carbon tax increases, the consumption of coal, oil, and natural gas all show a downward trend, with coal experiencing the largest decrease, at −49.5640%.
Optimal Allocation of Water Reservoirs for Sustainable Wildfire Prevention Planning via AHP-TOPSIS and Forest Road Network Analysis
Authors: Arabatzis Garyfallos , Kolkos Georgios , Stergiadou Anastasia , Kantartzis Apostolos , Tampekis Stergios
Published: January 2024

The sustainable management of forest ecosystems is directly linked to the management of forest fires. The increasing occurrence of wildfires has prompted the need for the establishment of infrastructure aimed at addressing them. The placement of anti-fire water reservoirs can address the lack of water intake points. This study introduces a decision support system (DSS) tailored for the optimal allocation of anti-fire water reservoirs in Mediterranean forest ecosystems, ensuring a reliable water supply for firefighting operations. The methodology integrates the analytical hierarchy process (AHP) and the technique of order of preference by similarity to ideal solutions (TOPSIS) methods, facilitating precise location determination through comprehensive criteria analysis. Additionally, the analysis of the forest road network is incorporated to optimize the placement of water reservoirs. In the forest complex of Taxiarchis, Chalkidiki, Greece, 100 potential reservoir sites were identified and prioritized based on factors such as fire risk, proximity to existing water sources, and coverage area using optimal pathways. The study’s findings demonstrate that by establishing 34 water reservoirs, firefighting forces can access a replenishment point within a 5-min travel time. The conclusions underscore the efficacy of this methodology as a valuable decision-making tool for sustainable wildfire prevention planning. This approach contributes to allocating resources judiciously, effectively mitigating the wildfire risk in Mediterranean forest ecosystems, and therefore promoting sustainability.
Come and Gone! Psychological Resilience and Organizational Resilience in Tourism Industry Post COVID-19 Pandemic: The Role of Life Satisfaction
Authors: Elshaer Ibrahim A.
Published: January 2024

This research paper delves into the multifaceted relationships between psychological resilience, organizational trust, life satisfaction, and organizational resilience within the context of tourism firms in Egypt. Against the backdrop of the COVID-19 pandemic and its profound effects on the tourism industry, the study aims to unravel the intricate interplay of individual and organizational factors that contribute to the adaptive capacity and well-being of employees. The research employs a quantitative methodology, engaging full-time sales and marketing employees from five-star hotels and class A travel agents (660) as key participants, employing SmartPLS-SEM vs4 to analyze the collected data. Through a nuanced examination of their experiences post-pandemic, the study investigates how psychological resilience, defined as the ability to bounce back from adversity, influences both life satisfaction and organizational resilience. Additionally, the impact of organizational trust, characterized by the confidence and faith employees place in their organization, on life satisfaction and organizational resilience is explored. Preliminary findings suggest a positive association between psychological resilience and both life satisfaction and organizational resilience. Employees exhibiting higher levels of psychological resilience tend to not only experience greater life satisfaction but also contribute significantly to their organization’s resilience. Furthermore, organizational trust emerges as a critical factor, positively influencing life satisfaction and organizational resilience. The study contributes valuable insights to the evolving landscape of tourism management and lays the foundation for future research endeavors in this domain.
Embedding Sustainability into Mechanical Engineering Master Programs—A Case Study of the Top Technical Universities in Europe
Authors: Hąbek Patrycja , Palacz Magdalena , Saeed Fizza
Published: January 2024

Considering the vital role of higher education institutions (HEIs) in accomplishing sustainable development goals, this study examines the ways in which sustainability is integrated into mechanical engineering master’s programs in the selected top technical universities in the EU. The content analysis was employed to evaluate the universities’ commitment to sustainability and approach to integrating sustainability into mechanical engineering programs. The Sustainability Tracking, Assessment, and Rating SystemTM (STARS) credit AC1 was used as a reference to categorise the courses into sustainability-focused courses (SF) and courses that include sustainability content (SI). We used the Sustainability Tool for Auditing University Curricula in Higher Education (STAUNCH) to identify the sustainability-related topics integrated into the mechanical engineering programs. The empirical findings indicate that while all three top technical universities in Europe demonstrate a comprehensive commitment to sustainability, their approaches for integrating sustainability into their mechanical engineering master’s programs vary, leaving room for further improvements. The paper thoroughly analyses the top technical universities’ sustainability efforts, offering valuable insights for educators and institutions seeking to enhance sustainability integration in higher education curricula.
The Design of Ecological Compensation for Air Pollution Based on Differential Game
Authors: Luo Enquan , Hu Zuopeng , Xiang Shuwen , Yang Yanlong , Hu Zhijun
Published: January 2024

Establishing a scientific ecological compensation mechanism for air pollution is crucial for air protection. This study models the ecological compensation mechanism of the Stackelberg differential game between the local regulator and an enterprise with a competitor by introducing the air quality index and the social welfare benefits of the local regulator. Using the Pontryagin maximum principle, this study obtains dynamic strategies for the local regulator and the enterprise while maximizing the benefits. The evolution of the shadow price is analyzed with the inverse differential equation method. Then, the effects of the shadow price on the optimal dynamic strategies are analyzed using numerical simulation, together with the effects of the introduction of social welfare benefits on the efforts of the local regulator to protect the air environment. The conclusions show that introducing social welfare benefits as an ecological compensation criterion for air pollution promotes air protection by the local regulator.
Correction: Zhao et al. A New Synchronous Handling Technology of Double Stack Container Trains in Sea-Rail Intermodal Terminals. Sustainability 2022, 14, 11254
Authors: Zhao Zhongbin , Wang Xifu , Cheng Suxin , Liu Wei , Jiang Lijun
Published: January 2024

The authors would like to make the following corrections to the published paper [...]
Tracing the Maternal Line in Glacial–Interglacial Migrations of Populus tremuloides: Finding Trees for Future Sustainable Forests by Searching in the Past
Authors: Tembrock Luke R. , Zink Frida A. , Zhang Guozhe , Schuhmann Andrea , Gu Cuihua , Wu Zhiqiang
Published: January 2024

Maintaining and planting sustainable forests is fundamental in perpetuating the essential functions of these ecosystems. A central aspect of managing forests for future resilience is the consideration of past migration and evolution of trees using genetic and genomic data to ensure that functionally appropriate diversity is conserved and utilized. In our study, we generated and compared genetic and genomic data from the plastome to better understand phylogeography and molecular evolution in the tree species Populus tremuloides (aspen). With these analyses, we found evidence of divergence and migration between northern and southern sites. Additionally, evidence of deep incomplete plastome sorting across the Salicaceae was found when examining insertion–deletion (indel) sites associated with DNA repair. By examining these indels in plastomic genes with introns across Salicaceae, we found a strong correlation between the abundance of DNA repair with genomic position and transcript abundance. From our findings, we conclude that previously ignored plastomic data are essential in understanding phylogeography and the evolution of key metabolic processes for improved aspen forest planning. Given the propensity of aspen forests to host high levels of biodiversity, rapidly sequester carbon, absorb excess nitrogen, and efficiently regulate snowmelt, improvements to planning and conservation will be highly impactful.
Towards a Holistic Framework for the Olympic-Led Sustainable Urban Planning Process
Authors: Baroghi Farideh , Ribeiro Paulo J. G. , Fonseca Fernando
Published: January 2024

Sport mega-events, like the Olympics, are renowned for their urban and socioeconomic impacts. Based on a literature review, this paper proposes a holistic framework for an Olympic-led sustainable planning process, encompassing five key sustainable urban principles: accessibility, integration, flexibility/adaptability, security, and sustainability compliance. The framework provides a structured approach to assess these principles at three different temporal and spatial levels: location selection, pre-event planning, and post-event planning. The proposed holistic framework is applied to the Rio 2016 Summer Olympics, revealing a significant disconnection between the initially promised sustainable development goals and practical achievements. While enhancements in accessibility were observed, the other key sustainable urban principles exhibited limited or negligible improvements. The proposed holistic framework holds the potential to foster lasting positive impacts and sustainable urban improvements in host cities, particularly in developing countries.
Corn Grain Fatty Acid Contents in Response to Organic Fertilisers from Meat Industry Waste
Authors: Stępień Arkadiusz , Wojtkowiak Katarzyna , Kolankowska Ewelina , Pietrzak-Fiećko Renata
Published: January 2024

Organic waste can provide an alternative to synthetic fertilisers for maintaining productivity with limited environmental impact. Our research evaluates the potential use of processed animal waste in corn fertilisation, which may represent a partially closed nutrient cycle of importance in a sustainable agricultural system. The objective of this study was to evaluate the quantity and quality of fat obtained from corn grain fertilised with meat and bone meal (MBM) produced from animal waste. A static field experiment using MBM was conducted at the Experimental Station in Tomaszkowo (53°71′ N, 20°43′ E), Poland. The field experiment was conducted in 2014–2017 with continuous corn cultivation. The course of weather conditions in the years of this study influenced the fat content, with the lowest amount found in 2016. The application of fertilisers in the form of MBM and mineral fertilisation resulted in a slightly lower fat content compared to the variant without fertilisation. The application of mineral fertilisers and MBM influenced an increase in the content of the predominant C18:2 acid compared to the variant without fertilisation, while the opposite was shown for C18:1 cis-9 acid. The fertiliser variants are most correlated with fat yield and total polyunsaturated fatty acids. The fertiliser variants in their effects on fat yield, fat content, fatty acid profiles, and their ratios can be divided into three groups, which were related to the effects of organic fertilisers during the years of this study. The use of meat and bone meal as fertilisers cannot be regarded as a factor in increasing the fat content of corn grain. Meat and bone meal applied over several years to the same field in the quantities required to achieve optimum yield can be an element that shapes fatty acid profiles.
The Content and Stratification of SOC and Its Humified Fractions Using Different Soil Tillage and Inter-Cropping
Authors: Slepetiene Alvyra , Kadziene Grazina , Suproniene Skaidre , Skersiene Aida , Auskalniene Ona
Published: January 2024

Five different tillage systems were researched in a Cambisol of a loam texture in the long-term experiment: conventional ploughing at 22–24 cm (CT), shallow ploughing at 16–18 cm (ShT), harrowing at 8–10 cm (MT1), harrowing at 14–16 cm (MT2), and no tilling (NT). The aim of this study was to determine how different tillage and inter-cropping influence the accumulation and distribution of SOC (soil organic carbon) and its compounds in different soil layers. SOC content changed depending on the soil tillage system and inter-crops used. Stratification ratios (SR) of SOC in the surface soil (0–10 cm) to that in the 10–20 cm (SR1) and 20–30 cm (SR2) were calculated. In our research, SR for SOC varied in the range from 0.97 to 1.35 for SR1 and from 1.02 to 1.99 for SR2. The main conclusion was that inter-crops increased the SOC accumulation in the 0–10 cm layer of all investigated treatments. It was concluded that different soil tillage systems and inter-crops influenced processes of soil carbon changes and affected OM humification in the soil. The formation of humified carbon compounds should be considered not only as a preservation and improvement of the soil productivity, but also as an environmental assessment of their impact on the soil sustainability and reduction in carbon dioxide emissions into the atmosphere. Our results suggest that sustainable tillage and inter-cropping management may contribute to climate mitigation regarding SOC accumulation in soil.
A Comprehensive Review of Remediation Strategies for Soil and Groundwater Contaminated with Explosives
Authors: Mystrioti Christiana , Papassiopi Nymphodora
Published: January 2024

This study offers an updated overview of the soil and water remediation strategies employed to address the widespread environmental and public health risks associated with explosive compounds, particularly TNT and RDX. Recognizing soil contamination originating from military activities, industrial accidents, and historical land use, this review delves into physical, chemical, and biological approaches to mitigating ecological and human health concerns. While physical methods like excavation and disposal are effective, their applicability is constrained by cost and logistical challenges for large contaminated areas. Chemical methods, such as oxidation and reduction, focus on transforming explosives into less toxic byproducts. Biological remediation utilizing plants and microorganisms emerges as a cost-effective and sustainable alternative. This review highlights challenges, including the persistence of explosive compounds, potential groundwater leaching, and the necessity for long-term monitoring. Emphasizing the need for site-specific strategies, considering the contaminant type, concentration, soil properties, and regulatory requirements, this study advocates for integrated and sustainable remediation approaches in pilot-scale applications. It concludes by evaluating the appropriate solution based on the advantages and disadvantages of the categories of soil and groundwater remediation methods. The duration, the effectiveness, and the cost of available technologies were estimated.
Development of Community-Level Capacity of Resilience to Natural Hazards for Environmental- and Social-Justice-Challenged Communities: 1. Approach, Concepts, and Assessment of Existing Information
Authors: Summers J. Kevin , Sanderson Rachelle , Trahan Rachelle , Hendricks Kendra , Ruffin Mia , Williams Adam , Lamper Andrea , Lowery Mason , Harwell Linda C.
Published: January 2024

Impoverished and under-served communities are often exposed to the worst environmental and climate hazards. Identifying these communities and building their resilience capacity to withstand such hazards is a vital justice aspect of environmental management. Building community resilience requires five activities: (1) examination of existing information, (2) community engagement and assessment of local knowledge, (3) development of reasonable strategies to build resilience, (4) implementation and these strategies, and (5) monitoring and transability of the process. This manuscript examines the first component of this process. The attributes of multiple parishes in Louisiana are examined using available data and existing models of human well-being, community resilience, and environmental/climate/socioeconomic justice. These existing models and tools were used to determine parish-level resilience to natural hazards including flooding, hurricanes, and other potential natural climatic hazards in central Louisiana (U.S.). Through consultation with state officials and local community groups, candidate environmental justice (EJ) and social justice (SJ) communities were selected to develop resilience capacity enhancement plans to address potential adverse parish and community outcomes of natural hazard events. Of the available parishes, St. Helena Parish was selected as an entity that would significantly benefit from resilience capacity building. The remaining two activities, community engagement and strategy development, will be examined in sister manuscripts. Continuing studies, to be described elsewhere, will describe community engagement and the determination of strategies, implementation plans, and the monitoring of the success of these strategic implementations.
Variable Speed Limit Intelligent Decision-Making Control Strategy Based on Deep Reinforcement Learning under Emergencies
Authors: Yang Jingwen , Wang Ping , Ju Yongfeng
Published: January 2024

Uncertain emergency events are inevitable and occur unpredictably on the highway. Emergencies with lane capacity drops cause local congestion and can even cause a second accident if the response is not timely. To address this problem, a self-triggered variable speed limit (VSL) intelligent decision-making control strategy based on the improved deep deterministic policy gradient (DDPG) algorithm is proposed, which can eliminate or alleviate congestion in a timely manner. The action noise parameter is introduced to improve exploration efficiency and stability in the early stage of the algorithm training and then maximizes differential traffic flow as the control objective, taking the real-time traffic state as the input. The reward function is constructed to explore the values of the speed limit. The results show that in terms of safety, under different traffic flow levels, the proposed strategy has improved by over 28.30% compared to other methods. In terms of efficiency, except for being inferior to the no-control condition during low-traffic-flow conditions, our strategy has improved over 7.21% compared to the others. The proposed strategy greatly benefits traffic sustainability in Intelligent Transport Systems (ITSs).
Design of a Pedagogical Model to Foster Ocean Citizenship in Basic Education
Authors: Schio Caroline , Reis Pedro
Published: January 2024

Following a design-based research methodology, this investigation develops a pedagogical model to foster ocean citizenship through the application of a design cycle consisting of four phases: (1) preliminary research, (2) planning, (3) action and (4) evaluation. This article presents the results of phases 1 and 2, which define the conceptual foundation of the pedagogical model, and the planning of actions for its implementation in the school environment. The conceptual foundation was established by drawing upon the theoretical principles of a systemic/complex approach to education, along with theoretical-methodological elements compiled from the literature in the field of ocean literacy and ocean citizenship. During the planning phase, six educational activities were defined, to be conducted as part of a citizen science project to monitor the coastal zone. This model was developed with the objective of going beyond theoretical concepts, to offer schools a practical and objective guide for fostering ocean citizenship in basic education.
Using Remote Sensing to Assess the Vegetation Cover of a Protected Salt Marsh Subjected to Artificial Recharge and Groundwater Abstractions during the Period 1925–2022 (Alicante, SE Spain)
Authors: Salcedo José Marín , Alhama Iván , Alcaraz Manuel , Álvarez-Rogel José , Jiménez-Valera José Antonio
Published: January 2024

The Agua Amarga salt marsh has been subjected to artificial seawater recharge on its surface during the period 1925–1969 for industrial purposes (saltwork activity) and from 2008 to present to compensate for coastal groundwater abstraction to supply Alicante desalination plants. This groundwater abstraction has caused piezometric depletion in the coastal aquifer connected to the protected salt marsh. The seawater recharge program also involved vegetation monitoring to control the impact on the salt marsh ecosystem, allowing data to be collected about the halophyte vegetation species growing in the salt marsh (Arthrocnemum macrostachyum, Sarcocornia fruticosa, and Ruppia maritima, among others) from spring and autumn field surveys. In this work, vegetation development is assessed with remote sensing for the period 1929–2022 using images with visible and near-infrared spectral resolution. Different spectral indices (NDVI, BI, and NDWI) and classification algorithms (random forest) are used to calculate the vegetation cover. Field data are employed to evaluate the protocols and compare the results, showing a 46% decrease caused by the salt works and a 50% increase as a result of natural evolution and artificial recharge. The spread of Phragmites australis is also addressed by comparing LiDAR data with field monitoring, showing an increase of 12% during the period 2005–2023. The advantages and complementarity of field monitoring and remote sensing information are explained.
The Response of Rapeseed (Brassica napus L.) Seedlings to Silver and Gold Nanoparticles
Authors: Tomaszewska-Sowa Magdalena , Pańka Dariusz , Lisiecki Karol , Lemańczyk Grzegorz
Published: January 2024

With the advancement of nanotechnology and the increasing utilization of nanoparticles (NPs), their production and release into the environment are on the rise. Consequently, it is crucial to continuously monitor the toxicity of nanoparticles for humans, animals, and plants, as well as their impact on the environment. This is particularly significant in relation to human health and food production, given the escalating use of nanomaterials in agriculture and horticulture. The aim of the study was to investigate the response of rapeseed seedlings to silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) over different periods of exposure. This research analyzed the impact of these nanoparticles on the biochemical response of rapeseed seedlings after 7, 14, and 21 days of growth in their presence. This study assessed the activity of guaiacol peroxidase (GPOX), pyrogallol peroxidase (PPOX), superoxide dismutase (SOD), and free protein content, as well as the interactions between key elements responsible for oxidative stress and the antioxidant response. The findings demonstrated a significant effect of AgNPs and AuNPs on stimulating the response of rapeseed seedlings, with the activity of PPOX, GPOX, and SOD being dependent on the exposure time and the type and dose of nanoparticles used. Enzyme activity increased with the length of exposure time, while the content of free protein decreased over the weeks. The most intense reaction of seedlings was observed in the case of GPOX, with the lowest activity observed in PPOX and SOD. High effects of the nanoparticle type and rate were also observed in the correlation matrix. This study suggests that a comprehensive analysis of plant reactions to nanoparticles could have a significant impact on the proper and effective use of nanoparticles in agriculture and horticulture. This could lead to the environmentally friendly production of high-quality plant material.
Teachers’ AI-TPACK: Exploring the Relationship between Knowledge Elements
Authors: Ning Yimin , Zhang Cheng , Xu Binyan , Zhou Ying , Wijaya Tommy Tanu
Published: January 2024

The profound impact of artificial intelligence (AI) on the modes of teaching and learning necessitates a reexamination of the interrelationships among technology, pedagogy, and subject matter. Given this context, we endeavor to construct a framework for integrating the Technological Pedagogical Content Knowledge of Artificial Intelligence Technology (Artificial Intelligence—Technological Pedagogical Content Knowledge, AI-TPACK) aimed at elucidating the complex interrelations and synergistic effects of AI technology, pedagogical methods, and subject-specific content in the field of education. The AI-TPACK framework comprises seven components: Pedagogical Knowledge (PK), Content Knowledge (CK), AI-Technological Knowledge (AI-TK), Pedagogical Content Knowledge (PCK), AI-Technological Pedagogical Knowledge (AI-TCK), AI-Technological Content Knowledge (AI-TPK), and AI-TPACK itself. We developed an effective structural equation modeling (SEM) approach to explore the relationships among teachers’ AI-TPACK knowledge elements through the utilization of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The result showed that six knowledge elements all serve as predictive factors for AI-TPACK variables. However, different knowledge elements showed varying levels of explanatory power in relation to teachers’ AI-TPACK. The influence of core knowledge elements (PK, CK, and AI-TK) on AI-TPACK is indirect, mediated by composite knowledge elements (PCK, AI-TCK, and AI-TPK), each playing unique roles. Non-technical knowledge elements have significantly lower explanatory power for teachers of AI-TPACK compared to knowledge elements related to technology. Notably, content knowledge (C) diminishes the explanatory power of PCK and AI-TCK. This study investigates the relationships within the AI-TPACK framework and its constituent knowledge elements. The framework serves as a comprehensive guide for the large-scale assessment of teachers’ AI-TPACK, and a nuanced comprehension of the interplay among AI-TPACK elements contributes to a deeper understanding of the generative mechanisms underlying teachers’ AI-TPACK. Such insights bear significant implications for the sustainable development of teachers in the era of artificial intelligence.
Sustainability Indices and RAM Analysis for Maintenance Decision Making Considering Environmental Sustainability
Authors: Barbieri Giacomo , Hernandez Jose Daniel
Published: January 2024

Maintenance is becoming an increasingly green process, aiming to simultaneously minimize the impact of assets on the economy, society, and the surrounding environment while also mitigating any adverse consequences arising from maintenance activities. To manage maintenance from a sustainable perspective, appropriate indices able to represent environmental assessment results in an aggregated and synthetic way are necessary, along with rational decision-making tools able to simulate different maintenance alternatives considering various sustainability dimensions. In response to this challenge, a methodology rooted in sustainability indices and RAM analysis is proposed to support decision making with respect to sustainable maintenance practices. By applying the proposed methodology to a proof of concept we demonstrate that the approach enables the evaluation of both the environmental and economic impacts of different maintenance activities. Furthermore, the methodology facilitates the identification of specific environmental dimensions that need improvement, in addition to discerning the distinct contributions of individual components to the environmental and economic impacts at the system level. These insights offer valuable information to support informed decision making regarding the allocation of internal resources for impact mitigation. The obtained results underscore the potential applicability of this approach to industrial systems, signifying its contribution to the goal of achieving sustainable maintenance practices.
Integral Transforms and the Hyers–Ulam Stability of Linear Differential Equations with Constant Coefficients
Authors: Anderson Douglas R.
Published: January 2024

Integral transform methods are a common tool employed to study the Hyers–Ulam stability of differential equations, including Laplace, Kamal, Tarig, Aboodh, Mahgoub, Sawi, Fourier, Shehu, and Elzaki integral transforms. This work provides improved techniques for integral transforms in relation to establishing the Hyers–Ulam stability of differential equations with constant coefficients, utilizing the Kamal transform, where we focus on first- and second-order linear equations. In particular, in this work, we employ the Kamal transform to determine the Hyers–Ulam stability and Hyers–Ulam stability constants for first-order complex constant coefficient differential equations and, for second-order real constant coefficient differential equations, improving previous results obtained by using the Kamal transform. In a section of examples, we compare and contrast our results favorably with those established in the literature using means other than the Kamal transform.