bluuebunny/crossref_metadata_2025 huggingface dataset:
How AI from Automated Driving Systems Can Contribute to the Assessment of Human Driving Behavior
Authors: Driessen Tom , Siebinga Olger , de Boer Thomas , Dodou Dimitra , de Waard Dick , de Winter Joost
Published: November 2024

This paper proposes a novel approach to measuring human driving performance by using the AI capabilities of automated driving systems, illustrated through three example scenarios. Traditionally, the assessment of human driving has followed a bottom-up methodology, where raw data are compared to fixed thresholds, yielding indicators such as the number of hard braking events. However, acceleration threshold exceedances are often heavily influenced by the driving context. We propose a top-down context-aware approach to driving assessments, in which recordings of human-driven vehicles are analyzed by an automated driving system. By comparing the human driver’s speed to the AI’s recommended speed, we derive a level of disagreement that can be used to distinguish between hard braking caused by aggressive driving and emergency braking in response to a critical event. The proposed method may serve as an alternative to the metrics currently used by some insurance companies and may serve as a template for future AI-based driver assessment.
Characterization of CYGNSS Ocean Surface Wind Speed Products
Authors: Ruf Christopher , Al-Khaldi Mohammad , Asharaf Shakeel , Balasubramaniam Rajeswari , McKague Darren , Pascual Daniel , Russel Anthony , Twigg Dorina , Warnock April
Published: November 2024

Since its launch in 2016, a number of wind speed retrieval algorithms have been developed for the NASA CYGNSS satellite observations. We assess their accuracy and precision and characterize the dependence of their performance on environmental factors. The dependence of retrieval uncertainty on the wind speed itself is considered. The triple colocation method of validation is used to correct for the quality of the reference wind speed products with which CYGNSS is compared. The dependence of retrieval performance on sea state is also considered, with particular attention being paid to the long wave portion of the surface roughness spectrum that is less closely coupled to the instantaneous local wind speed than the capillary wave portion of the spectrum. The dependence is found to be significant, and the efficacy of the approaches taken to account for it is examined. The dependence of retrieval accuracy on wind speed persistence (the change in wind speed prior to a measurement) is also characterized and is found to be significant when winds have increased markedly in the ~2 h preceding an observation.
Urban Multi-Scenario Land Use Optimization Simulation Considering Local Climate Zones
Authors: Chen Jie , Dong Zikun , Shi Ruijie , Sun Geng , Guo Ya , Peng Zhuopeng , Deng Min , Chen Kaiqi
Published: November 2024

The urban heat island (UHI) effect, a significant environmental challenge within the global urbanization process, poses severe threats to human health, ecological security, and life safety while also impacting the achievement of the United Nations Sustainable Development Goals. This study proposes a multi-scenario optimization method for urban thermal environments based on local climate zones (LCZs) in Changsha City. The research employs a genetic algorithm to optimize the LCZ quantity structure in order to improve the urban temperature environment. Subsequently, the optimized quantity structure is integrated with the future land use simulation (FLUS) model under multi-scenario constraints to achieve optimal spatial distribution of LCZs, providing scientific guidance for urban planning decision-makers. Results demonstrate that the LCZ-based optimization method can effectively regulate the urban thermal environment and maintain a suitable urban temperature range, offering both theoretical foundation and practical guidance for mitigating UHI effects.
Distributed High-Speed Videogrammetry for Real-Time 3D Displacement Monitoring of Large Structure on Shaking Table
Authors: Shi Haibo , Chen Peng , Liu Xianglei , Hong Zhonghua , Ye Zhen , Gao Yi , Liu Ziqi , Tong Xiaohua
Published: November 2024

The accurate and timely acquisition of high-frequency three-dimensional (3D) displacement responses of large structures is crucial for evaluating their condition during seismic excitation on shaking tables. This paper presents a distributed high-speed videogrammetric method designed to rapidly measure the 3D displacement of large shaking table structures at high sampling frequencies. The method uses non-coded circular targets affixed to key points on the structure and an automatic correspondence approach to efficiently estimate the extrinsic parameters of multiple cameras with large fields of view. This process eliminates the need for large calibration boards or manual visual adjustments. A distributed computation and reconstruction strategy, employing the alternating direction method of multipliers, enables the global reconstruction of time-sequenced 3D coordinates for all points of interest across multiple devices simultaneously. The accuracy and efficiency of this method were validated through comparisons with total stations, contact sensors, and conventional approaches in shaking table tests involving large structures with RCBs. Additionally, the proposed method demonstrated a speed increase of at least six times compared to the advanced commercial photogrammetric software. It could acquire 3D displacement responses of large structures at high sampling frequencies in real time without requiring a high-performance computing cluster.
Rehabilitated Tailing Piles in the Metropolitan Ruhr Area (Germany) Identified as Green Cooling Islands and Explained by K-Mean Cluster and Random Forest Regression Analyses
Authors: Stumpe Britta , Marschner Bernd
Published: November 2024

Urban green spaces, such as parks, cemeteries, and allotment gardens provide important cooling functions for mitigating the urban heat island (UHI) effect. In the densely populated Ruhr Area (Germany), rehabilitated tailing piles (TPs), as relicts of the coal-mining history, are widespread hill-shaped landscape forms mainly used for local recreation. Their potential role as cooling islands has never been analyzed systematically. Therefore, this study aimed at investigating the TP surface cooling potential compared to other urban green spaces (UGSs). We analyzed the factors controlling the piles’ summer land surface temperature (LST) patterns using k-mean clustering and random forest regression modeling. Generally, mean LST values of the TPs were comparable to those of other UGSs in the region. Indices describing vegetation moisture (NDMI), vitality (NDVI), and height (VH) were found to control the LST pattern of the piles during summer. The index for soil moisture (TVDI) was directly related to VH, with the highest values on the north and northeast-facing slopes and lowest on slopes with south and southeast expositions. Terrain attributes such as altitude, slope, aspect, and curvature were of minor relevance in that context, except on TPs exceeding heights of 125 m. In conclusion, we advise urban planners to maintain and improve the benefit of tailing piles as green cooling islands for UHI mitigation. As one measure, the soil’s water-holding capacity could be increased through thicker soil covers or soil additives during mine tailing rehabilitation, especially on the piles’ south and southeast expositions.
Impact of Turbidity on Satellite-Derived Bathymetry: Comparative Analysis Across Seven Ports in the South China Sea
Authors: Wei Chunzhu , Xiao Yaqi , Fu Dongjie , Zhou Tingting
Published: November 2024

This study investigates the uncertainty of satellite-derived bathymetry (SDB) in turbid port environments by integrating multi-temporal composites of Sentinel-2 and Landsat 8 satellite imagery with in situ bathymetry and turbidity data. The research aims to evaluate the effectiveness of SDB and its spatiotemporal correlation with satellite-based turbidity indicators across seven Chinese port areas. Results indicate that both Sentinel-2 and Landsat 8, using a three-band combination, achieved comparable performance in SDB estimation, with R2 values exceeding 0.85. However, turbidity showed a negative correlation with SDB accuracy, and higher turbidity levels limited the maximum retrievable water depth, resulting in SDB variances ranging from 0 to 15 m. Landsat 8 was more accurate in low to moderate turbidity environments (12–15), where SDB variance was lower, while higher turbidity (above 15) led to greater SDB variance and reduced accuracy. Sentinel-2 outperformed Landsat 8 in moderate to high turbidity environments (36–203), delivering higher R2 values and more consistent SDB estimates, making it a more reliable tool for areas with variable turbidity. These findings suggest that SDB is a viable method for bathymetric and turbidity mapping in diverse port settings, with the potential for broader application in coastal monitoring and marine management.
Gradual Failure of a Rainfall-Induced Creep-Type Landslide and an Application of Improved Integrated Monitoring System: A Case Study
Authors: Guo Jun , Meng Fanxing , Guo Jingwei
Published: November 2024

Landslides cause severe damage to life and property with a wide-ranging impact. Infiltration of rainfall is one of the significant factors leading to landslides. This paper reports on a phase creep landslide caused by long-term rainfall infiltration. A detailed geological survey of the landslide was conducted, and the deformation development pattern and mechanism of the landslide were analyzed in conjunction with climatic characteristics. Furthermore, reinforcement measures specific to the landslide area were proposed. To monitor the stability of the reinforced slope, a Beidou intelligent monitoring and warning system suitable for remote mountainous areas was developed. The system utilizes LoRa Internet of Things (IoT) technology to connect various monitoring components, integrating surface displacement, deep deformation, structural internal forces, and rainfall monitoring devices into a local IoT network. A data processing unit was established on site to achieve preliminary processing and automatic handling of monitoring data. The monitoring results indicate that the reinforced slope has generally stabilized, and the improved intelligent monitoring system has been able to continuously and accurately reflect the real-time working conditions of the slope. Over the two-year monitoring period, 13 early warnings were issued, with more than 90% of the warnings accurately corresponding to actual conditions, significantly improving the accuracy of early warnings. The research findings provide valuable experience and reference for the monitoring and warning of high slopes in mountainous areas.
Multi-Camera Calibration Using Far-Range Dual-LED Wand and Near-Range Chessboard Fused in Bundle Adjustment
Authors: Jatesiktat Prayook , Lim Guan Ming , Ang Wei Tech
Published: November 2024

This paper presents a calibration approach for multiple synchronized global-shutter RGB cameras surrounding a large capture volume for 3D application. The calibration approach uses an active wand with two LED-embedded markers waved manually within the target capture volume. Data from the waving wand are combined with chessboard images taken at close range during each camera’s intrinsic calibration, optimizing camera parameters via our proposed bundle adjustment method. These additional constraints from the chessboard are developed to overcome an overfitting issue of wand-based calibration discovered by benchmarking its 3D triangulation accuracy in an independent record against a ground-truth trajectory and not on the record used for calibration itself. Addressing this overfitting issue in bundle adjustment leads to significant improvements in both 3D accuracy and result consistency. As a by-product of this development, a new benchmarking workflow and our calibration dataset that reflects realistic 3D accuracy are proposed and made publicly available to allow for fair comparisons of various calibration methods in the future. Additionally, our experiment highlights a significant benefit of a ray distance-based (RDB) triangulation formula over the popular direct linear transformation (DLT) method.
Does Muscle Pain Induce Alterations in the Pelvic Floor Motor Unit Activity Properties in Interstitial Cystitis/Bladder Pain Syndrome? A High-Density sEMG-Based Study
Authors: Albaladejo-Belmonte Monica , Houston Michael , Dias Nicholas , Spitznagle Theresa , Lai Henry , Zhang Yingchun , Garcia-Casado Javier
Published: November 2024

Several studies have shown interstitial cystitis/bladder pain syndrome (IC/BPS), a chronic condition that poses challenges in both diagnosis and treatment, is associated with painful pelvic floor muscles (PFM) and altered neural drive to these muscles. However, its pathophysiology could also involve other alterations in the electrical activity of PFM motor units (MUs). Studying these alterations could provide novel insights into IC/BPS and help its clinical management. This study aimed to characterize PFM activity at the MU level in women with IC/BPS and pelvic floor myalgia using high-density surface electromyography (HD-sEMG). Signals were recorded from 15 patients and 15 healthy controls and decomposed into MU action potential (MUAP) spike trains. MUAP amplitude, firing rate, and magnitude-squared coherence between spike trains were compared across groups. Results showed that MUAPs had significantly lower amplitudes during contractions on the patients’ left PFM, and delta-band coherence was significantly higher at rest on their right PFM compared to controls. These findings suggest altered PFM tissue and neuromuscular control in women with IC/BPS and pelvic floor myalgia. Our results demonstrate that HD-sEMG can provide novel insights into IC/BPS-related PFM dysfunction and biomarkers that help identify subgroups of IC/BPS patients, which may aid their diagnosis and treatment.
Scheimpflug LIDAR for Gas Sensing at Elevated Temperatures
Authors: Bhatt Chet R. , Hartzler Daniel A. , McIntyre Dustin L.
Published: November 2024

Localized operating conditions inside boilers, heat recovery steam generators, or other large thermal systems have a huge impact on the efficiency, environmental performance, and lifetime of components. It is extremely difficult to measure species accurately within these systems due to the high temperatures and harsh environments, locally oxidizing or reducing atmospheres, ash, other particulates, and other damaging chemical species. Physical probes quickly suffer damage and are rendered nonfunctional. This work has attempted to adapt the measurement approach based on Scheimpflug light detection and ranging (S-LIDAR) for the remote sensing of gas species inside the high-temperature boiler environment. For a proof-of-concept, the detection of Raman signals of N2, O2, and CO2 and their behavior with increasing temperature have been presented.
Borehole Optical Fibre Distributed Temperature Sensing vs. Manual Temperature Logging for Geothermal Condition Assessment: Results of the OptiSGE Project
Authors: Kłonowski Maciej R. , Nermoen Anders , Thomas Peter J. , Wyrwalska Urszula , Pratkowiecka Weronika , Ładocha Agnieszka , Midttømme Kirsti , Brytan Paweł , Krzonkalla Anna , Maćko Adrianna , Zawistowski Karol , Duczmańska-Kłonowska Jolanta
Published: November 2024

Geothermal energy is a crucial component contributing to the development of local thermal energy systems as a carbon-neutral and reliable energy source. Insights into its availability derive from knowledge of geology, hydrogeology and the thermal regime of the subsurface. This expertise helps to locate and monitor geothermal installations as well as observe diverse aspects of natural and man-made thermal effects. Temperature measurements were performed in hydrogeological boreholes in south-western Poland using two methods, i.e., manual temperature logging and optical fibre distributed temperature sensing (OF DTS). It was assumed the water column in each borehole was under thermodynamic equilibrium with the local geothermal gradient of the subsurface, meaning rocks and aquifers. Most of the acquired results show typical patterns, with the upper part of the log depending on altitude, weather and climate as well as on seasonal temperature changes. For deeper parts, the temperature normally increases depending on the local geothermal gradient. The temperature logs for some boreholes located in urban agglomerations showed anthropogenic influence caused by the presence of infrastructure, the urban heat island effect, post-mining activities, etc. The presented research methods are suitable for applications connected with studies crucial to selecting the locations of geothermal installations and to optimize their technical parameters. The observations also help to identify zones of intensified groundwater flow, groundwater inrush into wells, fractured and fissured zones and many others.
Using a Webcam to Assess Upper Extremity Proprioception: Experimental Validation and Application to Persons Post Stroke
Authors: Cornella-Barba Guillem , Farrens Andria J. , Johnson Christopher A. , Garcia-Fernandez Luis , Chan Vicky , Reinkensmeyer David J.
Published: November 2024

Many medical conditions impair proprioception but there are few easy-to-deploy technologies for assessing proprioceptive deficits. Here, we developed a method—called “OpenPoint”—to quantify upper extremity (UE) proprioception using only a webcam as the sensor. OpenPoint automates a classic neurological test: the ability of a person to use one hand to point to a finger on their other hand with vision obscured. Proprioception ability is quantified with pointing error in the frontal plane measured by a deep-learning-based, computer vision library (MediaPipe). In a first experiment with 40 unimpaired adults, pointing error significantly increased when we replaced the target hand with a fake hand, verifying that this task depends on the availability of proprioceptive information from the target hand, and that we can reliably detect this dependence with computer vision. In a second experiment, we quantified UE proprioceptive ability in 16 post-stroke participants. Individuals post stroke exhibited increased pointing error (p < 0.001) that was correlated with finger proprioceptive error measured with an independent, robotic assessment (r = 0.62, p = 0.02). These results validate a novel method to assess UE proprioception ability using affordable computer technology, which provides a potential means to democratize quantitative proprioception testing in clinical and telemedicine environments.
Minimum Electromyography Sensor Set Needed to Identify Age-Related Impairments in the Neuromuscular Control of Walking Using the Dynamic Motor Control Index
Authors: Collimore Ashley N. , Pohlig Ryan T. , Awad Louis N.
Published: November 2024

The dynamic motor control index is an emerging biomarker of age-related neuromuscular impairment. To date, it has been computed by quantifying the co-activity of eleven lower limb muscles. Because clinics that routinely employ electromyography typically collect from fewer muscles, a reduced muscle sensor set may improve the clinical usability of this metric of motor control. This study aimed to test if commonly used eight- and five-muscle electromyography (EMG) sensor sets produce similar dynamic motor control indices as the previously examined eleven-muscle sensor set and similarly differentiate across age subgroups. EMG data were collected during treadmill walking from 36 adults separated into young (N = 18, <35 yrs.), young-old (N = 13, 65–74 yrs.), and old-old (N = 5, ≥75 yrs.) subgroups. Dynamic motor control indices generated using the sensor set with eleven muscles correlated with the eight-muscle set (R2 = 0.70) but not the five-muscle set (R2 = 0.30). Regression models using the eleven-muscle (χ2(4) = 10.62, p = 0.031, Nagelkerke R2 = 0.297) and eight-muscle (χ2(4) = 9.418, p = 0.051, Nagelkerke R2 = 0.267) sets were significant and approaching significance, respectively, whereas the model for the five-muscle set was not significant (p = 0.663, Nagelkerke R2 = 0.073). In both the eleven-muscle (Wald χ2 = 5.16, p = 0.023, OR = 1.26) and eight-muscle models (Wald χ2 = 4.20, p = 0.04, OR = 1.19), a higher index significantly predicted being in the young group compared to the old-old group. Age-related differences in the neuromuscular control of walking can be detected using dynamic motor control indices generated using eleven- and eight-muscle sensor sets, increasing clinical usability of the dynamic motor control index.
Hierarchically Ordered Macroporous–Mesoporous (HOM-m) MgFe2O4/MgO for Highly Efficient Adsorption of Ce(III) and La(III): Experimental Study and DFT Calculation Analysis
Authors: Zhang Lina , Lu Jiarui , Liu Baixiong
Published: November 2024

This study employed a template method to prepare a highly ordered and interconnected porous HOM-m MgFe2O4/MgO rare earth ion-efficient adsorbent. The specific surface area of the adsorbent was as high as 130 m2/g, with saturation adsorption capacities for Ce(Ⅲ) and La(Ⅲ) of 5689.69 mg/g and 2123.50 mg/g, respectively. The adsorbent exhibited superparamagnetism with efficient and rapid separation from an aqueous solution using a magnet. The adsorption results indicated that the adsorption mechanism of HOM-m MgFe2O4/MgO towards Ce(III) and La(III) primarily involved the ion exchange and redox reactions between Mg(II) hydrolyzed from MgO and Ce(III)/La(Ⅲ), as well as the electrostatic attraction between MgFe2O4 and Ce(Ⅲ)/La(Ⅲ). Density functional theory (DFT) calculations revealed that the adsorption process was driven by the interaction of Ce(III) and La(III) ions with the surface oxygen atoms of MgFe2O4/MgO. Moreover, MgFe2O4/MgO showed a higher affinity and stronger adsorption effect towards Ce(III) than La(III). Adsorption cycling experiments demonstrated that even after three cycles, HOM-m MgFe2O4/MgO maintained good removal efficiency for Ce(III) and La(III). Therefore, this adsorbent shows promise as an effective material for removing Ce(III) and La(III) and has significant implications for the remediation of water resources in ion adsorption-type rare earth mining areas.
Populism as a Conceptual Problem: Disciplinary Differentiation, Specialization, and the Complex Approach
Authors: Dominguez Lopez Ernesto , Thielicke-Witt Valerian , Arya Nitin
Published: November 2024

Populism is a global phenomenon that has been widely debated in academia (particularly in political science), the media, and politics for decades. This has led to many different definitions which exclude or include different forms, and focus on different aspects. This article discusses and systematizes these different approaches and explains them based on their core logics and empirical support. Their differences are rooted in their disciplinary differentiation and specialization. This process is absolutely necessary to conduct research in modern and complex societies, but it can make grasping complex problems difficult. Especially, if the ontological and epistemological assumptions are not properly supported and classified, this will lead to a cacophony of definitions. To overcome this problem, a new epistemological approach is needed, one that is capable of integrating the different empirically supported perspectives. The paper will point out that embracing the complexity of society is fruitful and necessary as it allows for a new understanding of the phenomenon by integrating the current research into one common framework, based on the concept of cultural complexus. In this approach, populism is a complex and multifaceted phenomenon—thus, the complex approach—with multiple variants that has a set of necessary and sufficient dimensions that identify it and that can be observed empirically.
Decision Analysis of Manufacturers’ Misreporting Behavior Considering Retailer Corporate Social Responsibility
Authors: Zhao Jun , Li Tao , Tan Qi , Liu Weirong
Published: November 2024

Under the increasingly competitive environment, some manufacturers may misreport costs to boost their own profits, potentially harming the overall interests of the supply chain. Conversely, some retailers may engage in corporate social responsibility (CSR) to promote sustainable development within the supply chain. Thus, this study considers a competitive supply chain comprising one retailer and two manufacturers, and investigates the impact of the manufacturer’s misreporting behavior on the chain supply members’ pricing decisions and performances as well as the impact of retailer CSR on the manufacturer’s misreporting behavior. When the retailer does not engage in CSR, the manufacturers’ misreporting behavior is solely influenced by misreporting factors. If the misreporting factors of both manufacturers are low, they can always benefit from their misreporting behavior. Interestingly, if one manufacturer has a high misreporting factor while the other has a low one, the manufacturer whose misreport factor is high does not misreport its cost, instead benefiting from the competitor’s misreporting behavior. When the retailer engages in CSR, the manufacturer’s misreporting behavior is influenced not only by their misreporting factors but also by the degree of product substitutability. If product substitutability is low, both manufacturers do not have an incentive to misreport their costs. If product substitutability is moderate and both misreporting factors are low, they can benefit from their misreporting behavior. However, when product substitutability is high, if one manufacturer misreports, the other will refrain from doing so.
The Suppression of Nitrite-Oxidizing Bacteria Using Free Nitrous Acid and Limited Available Dissolved Oxygen to Maintain the Stability of Toilet Wastewater Biofilm Nitritation
Authors: Li Ao , Lv Minghuan , Jing Xue , Wang Hongliang , Feng Huijuan
Published: November 2024

Researchers have found that maintaining the long-term stability of nitritation becomes challenging when relying on a single inhibitor. Currently, a feasible solution to this problem is to apply two or more inhibitors to achieve the synergistic suppression of NOB. However, studies on this solution have mainly focused on mainstream wastewater, while few have focused on non-mainstream wastewater. Moreover, most of the studies relating to non-mainstream wastewater have only focused on the spontaneous achievement of nitritation within a short operation time or have described nitritation collapse. Since toilet wastewater (TW), as non-mainstream wastewater, can endogenously produce free nitrous acid (FNA) through spontaneous nitritation, an attempt was made in this study through a series of field experiments to combine another inhibitor—a low concentration of dissolved oxygen (DO) available to NOB in the inner layer of biofilm—for biofilm nitritation. Under different levels of DO in the nitritation unit, the working effect and mechanism of high FNA–low available DO dual-factor suppression in maintaining nitritation stability were investigated. The results showed that the dual-factor suppression maintained the long-term stability of TW biofilm nitritation and triggered negative feedback regulation when the nitritation was unstable. A feasible method for establishing a low level of available DO based on a normalized FNA inhibitor when the COD/TN in the nitritation unit exceeds 0.50 is possible when the influent COD/TN of the unit is over 1.57. This study aimed to construct an endogenous and unregulated synergistic suppression strategy for stabilizing nitritation in non-mainstream wastewater to support the application of efficient and sustainable N-removal technology.
An Improved Real-Time Detection Transformer Model for the Intelligent Survey of Traffic Safety Facilities
Authors: Wan Yan , Wang Hui , Lu Lingxin , Lan Xin , Xu Feifei , Li Shenglin
Published: November 2024

The undertaking of traffic safety facility (TSF) surveys represents a significant labor-intensive endeavor, which is not sustainable in the long term. The subject of traffic safety facility recognition (TSFR) is beset with numerous challenges, including those associated with background misclassification, the diminutive dimensions of the targets, the spatial overlap of detection targets, and the failure to identify specific targets. In this study, transformer-based and YOLO (You Only Look Once) series target detection algorithms were employed to construct TSFR models to ensure both recognition accuracy and efficiency. The TSF image dataset, comprising six categories of TSFs in urban areas of three cities, was utilized for this research. The dimensions and intricacies of the Detection Transformer (DETR) family of models are considerably more substantial than those of the YOLO family. YOLO-World and Real-Time Detection Transformer (RT-DETR) models were optimal and comparable for the TSFR task, with the former exhibiting a higher detection efficiency and the latter a higher detection accuracy. The RT-DETR model exhibited a notable reduction in model complexity by 57% in comparison to the DINO (DETR with improved denoising anchor boxes for end-to-end object detection) model while also demonstrating a slight enhancement in recognition accuracy. The incorporation of the RepGFPN (Reparameterized Generalized Feature Pyramid Network) module has markedly enhanced the multi-target detection accuracy of RT-DETR, with a mean average precision (mAP) of 82.3%. The introduction of RepGFPN significantly enhanced the detection rate of traffic rods, traffic sign boards, and water surround barriers and somewhat ameliorated the problem of duplicate detection.
Leverage Points for Decelerating Wetland Degradation: A Case Study of the Wetland Agricultural System in Uganda
Authors: Kayendeke Ellen Jessica , Olabisi Laura Schmitt , Kansiime Frank , Mfitumukiza David
Published: November 2024

Indiscriminate expansion of agricultural activities into wetlands affects the sustainability of wetland-dependent livelihoods. Systems research is an important tool for identifying and dealing with the underlying drivers of wetland degradation; however, there is limited research employing system tools in Sub-Saharan Africa. This research employed causal loop diagrams and system archetypes to characterize common wetland resource systems in Sub-Saharan Africa, using the wetland agricultural system of Uganda as a case study. Mental models of wetland users were indirectly elicited by interviewing 66 wetland users. Causal loop diagrams were generated to illustrate the multiple, interdependent feedback linkages within the system. The case study wetland is mainly used for farming (40%), vegetation harvesting (26%), and fishing (24%), while other activities like hunting and grazing are carried out by 10% of wetland users. A reinforcing feedback loop was dominant, illustrating how initial encroachment on the wetland to meet livelihood needs can accelerate further encroachment. Based on the dominant loop and current interventions, we characterized the system using three archetypes: tragedy of the commons, shifting the burden, and fixes that fail. A two-pronged approach was proposed, where solutions for decelerating wetland degradation, like restoration activities, can be implemented in the short term while planning long-term measures that take into account the need for alternative livelihoods for wetland-dependent communities and targeting a paradigm shift through continuous sensitization of stakeholders on the benefits of sustainable wetland management.
The Development of a Zero Waste and Sustainable Waste Management Behavior Scale in Türkiye
Authors: Ikizoglu Bahar
Published: November 2024

Zero waste (ZW) and sustainable waste management (SWM) can vary based on environmental factors, economic and technological developments, social and cultural norms, and political and administrative differences across countries, as well as within rural or highly urbanized regions of the same country. The research aims to obtain a valid and reliable scale that measures the multidimensional structure of ZW and SWM. Three hundred and thirty participants, including 213 women and 117 men, participated in the study. Participants had a mean age of 41.09 ± 12.31, with the majority (56.7%) holding a Bachelor’s degree. The study unfolded in two phases: initially, the item pool was reviewed, leading to the development of the final scale by eliminating unsuitable items. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were conducted using IBM SPSS and IBM SPSS AMOS, and the scale provided construct validity with seven subdimensions and acceptable DFA parameters: χ2 = 933.249; df = 437; CMIN/DF = 2.136; CFI = 0.913; NFI = 0.905; RMSEA = 0.056; p = 0.010. The internal consistency of the scale was calculated using Cronbach’s alpha, and total scores and subdimensions ranged from 0.701 to 0.912, indicating an acceptable level of internal consistency. Thus, this new measurement tool can be used in various studies on ZW and SWM by facilitating the analysis of behavioral motivation, satisfaction, expectation, awareness, e-waste knowledge, and access to facilities regarding existing zero waste and sustainable waste management opportunities.
Developing an Integrated Analytical Framework for Sustainability Assessment: Focusing on Selected Projects in Riyadh
Authors: Selim Haitham Sadek , Abuzaid Abdullah , Mayhoub Mohammed Salah
Published: November 2024

Riyadh, the capital of the Kingdom of Saudi Arabia, is now presenting itself as one of the most attractive capitals in the Middle East, with a number of ambitious expansion projects that aim to develop the city and align its urban development with the goals of Vision 2030. This urban renaissance requires researchers to adopt evaluation approaches (BSAMs) based on comprehensive sustainability criteria represented by environmental and cultural sustainability, community engagement, and economic feasibility. This research relies on the ETE methodology to determine evaluation criteria and their weights, which is a systematic and interactive method of prediction based on the opinion of a group of experts, or what is known as the Delphi method. Experts answered questionnaires to determine the weights of the criteria in three rounds where they received an anonymous summary of the experts’ predictions from the previous round with the reasons they provided for their judgments. The responses were then analyzed to identify recurring and converging themes and contradictions using the top-of-priority similarity to ideal solution (TOPSIS) technique, thus deriving an integrated evaluation model. The model was applied to evaluate architectural practices in Riyadh through three major projects: the King Abdullah Petroleum Studies and Research Center, the King Abdullah Financial District, and the King Abdullah Financial District Metro Station. Data sources included comprehensive site visits, detailed project documentation, and expert evaluation through structured questionnaires to gain a realistic view of attitudes towards architectural needs and sustainability. This adds to the knowledge on how globalization interacts with the urban renewal landscape in Riyadh and encourages us to continue proposing effective evaluation models by drawing attention to the multidimensional nature of sustainability. This in turn points to the need for continuous re-evaluation of architectural activities in Riyadh through project evaluation results that attest to their compatibility with international standards and local cultural contexts. Overall, the proposed evaluation model has proven successful in testing projects at the local level by providing a sustainable framework. The results showed that projects adhere to varying levels of sustainability requirements, but, more importantly, these evaluation models were developed to rationalize accelerated construction processes.
Ecological Carrying Capacity and Driving Factors of the Source Region of the Yellow River in China over the Past 30 Years
Authors: Lu Sujin , Zhou Shipeng , Zhang Xiaoyan , Ma Xujie , Tian Jiawei , Gong Yanhong , Zheng Xiaojing , Si Jianhua , Qin Biyu
Published: November 2024

The source region of the Yellow River (SRYR) serves as a crucial ecological barrier on the Qinghai–Tibet Plateau in China. In recent decades, the ecological condition of the SRYR has deteriorated, resulting in a state of ecological insecurity. This state of affairs endangers the region’s living environment, aggravates poverty, and seriously hinders the region’s sustainable ecological, social, and economic development. Ecosystems, landscape patterns, ecological carrying capacity (ECC), and drivers interact with each other in the region, shaping the regional ecological pattern’s past, present, and future. However, the specific mechanisms underlying these interactions have yet to be elucidated. Based on the land use type data of the SRYR in China for the last 30 years in seven periods (1990, 1995, 2000, 2005, 2010, 2015, and 2020), and combined with the ecological footprint method, we carried out a study of spatial and temporal changes at the county scale and the source region scale, used the landscape pattern index to describe the changes in ECC, and analyzed the main drivers that affect the ECC of the source region. The results indicate the following: (1) Over the past 30 years, the greatest changes in the area have occurred in grasslands and unused lands. Between 2005 and 2010, a significant conversion of unused lands to grasslands occurred in the SRYR, amounting to 7382.33 km2, mainly distributed in Maduo County and Maqin County. (2) The absolute ecological carrying capacity (AECC) of grasslands in the SRYR has shown an upward trend, while that of forests has declined. The ECC of the source region has generally increased, with higher ECC observed in Maqin County, Maduo County, and Xinghai County. (3) The spatial distribution of ECC in the SRYR has shown non-uniform changes, with an increasing trend observed across all county-level areas. The spatial heterogeneity of AECC is high, with minor overall spatial distribution changes. (4) There is a positive correlation between the ECC of the SRYR with SPLIT, PARA_MN, and COHESION (p < 0.05). The impact of landscape pattern indices on ECC ranked as COHESION > PARA_MN > SPLIT. (5) Principal component analysis indicates that the primary driving forces of the SRYR’s ECC are social factors, such as urban population (X5) and per capita GDP (X8), with natural factors being less significant than social factors. This research is crucial for maintaining ECC in the SRYR, protecting and restoring the ecological environment, and ensuring the sustainable development of the economy and society.
Measuring Up? The Illusion of Sustainability and the Limits of Big Tech Self-Regulation
Authors: Vrikki Photini
Published: November 2024

This paper offers a critical analysis of the 2023 sustainability reports of five major ICT corporations: Amazon, Apple, Google, Meta, and Microsoft. It scrutinises how these organisations use sustainability data, particularly within the context of their actions, their planned initiatives, and visions for the future to report on three overarching sustainability narratives: 1. Reducing the climate footprint of their own operations; 2. Influencing and reducing the climate footprint of their supply chain and consumers; and 3. Financing innovation for climate change. Despite all five corporations expressing a commitment to sustainability and confronting climate change, their specific actions and planned initiatives differ, influenced by their core businesses and existing sustainability practices. This becomes more apparent in their choice to use their own intricate measuring infrastructures for self-tracking and self-reporting environmental data. Such infrastructures, although purportedly aimed at showcasing progress towards sustainability goals, face scrutiny due to their lack of transparency and the potential for manipulation and greenwashing, especially given the lack of standardised reporting protocols within the sector. This analysis highlights that, despite these companies’ claims of commitment to carbon neutrality, their climate pledges and sustainability goals are rarely achieved. In this framework, this paper suggests that a critical approach is essential when evaluating Big Tech’s often deceptive sustainability narratives and underscores the need for more rigorous regulatory frameworks and independent third-party audits to ensure genuine progress towards a sustainable future and true accountability.
Determinants of the Intention to Use Refills in the Cosmetic Industry
Authors: Zdonek Iwona , Jaworska Aleksandra
Published: November 2024

The aim of the paper is to identify factors determining the intention to use refill cartridges in the cosmetics industry. As part of the work, two research questions and twelve corresponding hypotheses were formulated. Achieving the assumed goal was possible thanks to literature research and empirical research based on survey results from a sample of 226 respondents from different countries. The analysis of the collected data was carried out using the structural equation modelling method (PLS-SEM), thanks to which the scales measuring individual constructs (factors) were validated and a model was generated, based on which the constructs that had the greatest impact on the intentions to use refill technology were determined. The study showed that the factors that have the strongest impact on intentions to use refills are the expected ease of use and expected economic usefulness. Expected environmental utility turned out to be a non-significant predictor. Factors influencing actual consumer behaviour were also examined, including usage intentions and promotion. The study also analysed the mediating role of usage intention, which was confirmed in relation to the relationship of the constructs, including expected economic utility, the expected ease of use, and social pressure relating to actual behaviours, but was not confirmed in the relationship of the construct expected environmental utility with actual behaviours. The moderating role of the dichotomous variable background, dividing the respondents into the group of Poles and foreigners, was also examined. The obtained results showed that the moderation effect was confirmed only for the relationship between expected economic utility and intentions to use refills.
The Growth and Stagnation of US Life Expectancy: A Dynamic Simulation Model and Implications
Authors: Homer Jack
Published: November 2024

US life expectancy now lags significantly behind the majority of high-income countries, having grown more slowly since 1980 for reasons that are not evident and have been debated. An exploratory system dynamics model is presented that reproduces the full pattern of US life expectancy from 1960 to the present. Multiple socioeconomic and behavioral factors help to explain the historical pattern, two of them apparently most responsible for the stagnation since 1980: the growth of obesity and the leveling off of growth in social spending. Some of the factors in the model are traced back to earlier causes, and obesity’s growth in particular is traced back to excess growth in private health care spending and its adverse effect on workers’ wages. The model’s base run does a good job of reproducing a variety of historical time series data going back to the 1960s, and counterfactual tests produce plausible results and clarify the model’s main themes. The model may thus be considered a reasonable starting point for more conclusive future modeling of US life expectancy.
Applying a Modified Technology Acceptance Model to Explore Individuals’ Willingness to Use Mobility as a Service (MaaS): A Case Study of Beijing, China
Authors: Yu Shuai , Li Bin , Wang Haipeng , Liu Yuqing , Hu Song
Published: November 2024

The sustainable development of urban transportation is facing various challenges, including traffic congestion, increasing carbon emissions, and diversified travel demands. New concepts of mobility and business models are emerging to address these challenging conditions, such as mobility as a service (MaaS). As a new paradigm of travel services, users’ recognition, acceptance, and continuous use of MaaS are prerequisites for its survival and development. Hence, to ensure the successful implementation of MaaS, it is crucial to precisely identify the key factors influencing individuals’ willingness to use MaaS. In order to analyze the mechanisms that influence individuals’ willingness to use MaaS, this study first conceptualized a behavioral model by drawing on the modified Technology Acceptance Model (TAM) and the fundamental characteristics of MaaS. Based on the behavioral model, a structured questionnaire consisting of eight sections and thirty-three questions was designed and conducted online in Beijing, China. A total of 1260 valid questionnaire data were collected, and a descriptive analysis was conducted on the collected data, including the frequency distribution and intention to use MaaS based on the socioeconomic and mobility characteristics. Then, reliability and validity analyses were conducted on the questionnaire data using Cronbach’s alpha coefficient method and the Confirmatory Factor Analysis (CFA) method, respectively. Finally, the behavioral model was analyzed quantitatively using the Structural Equation Model (SEM). The results show that 77.62% of the respondents are willing to use MaaS after it is implemented, and 44.29% of them strongly agree to using it, while 2.06% of them strongly disagree to using it. Travel philosophy, travel preference, and perceived usefulness have positive impacts on individuals’ behavioral intention to use MaaS, while perceived usefulness exerts the greatest influence, with a coefficient of 0.364. Meanwhile, the latent variable of perceived risk has a significantly negative impact on behavioral intention, with a coefficient of −0.141. From the perspective of observed variables, convenience and efficiency are the most important factors affecting intention to use MaaS, while environment protection is the least influential factor. The results of this study can provide a decision-making basis for transportation planners, MaaS service providers, and policymakers, enhancing the level of sustainable development of urban transportation.