bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Spirituality on Bitter Kola Consumption Among Pretoria Residents in Response to COVID-19 and Related Illnesses
Authors: Orogun Daniel , Koenig Harold G.
Published: December 2024

The agrarian continent of Africa has many fruits with nutritional, medicinal and spiritual values. Regardless, Africa leads the statistics of poor healthcare globally. Two major challenges in Africa’s healthcare system are poor access and the high cost of medical healthcare. Among others, the effects of such challenges include low responsiveness to medical treatment and a high mortality rate. However, it seems the nosophobia that accompanied the global mortality rate during the COVID-19 pandemic may have triggered a spiritually influenced alternative. One of the traditional alternatives was a subscription to Garcinia Kola, popularly known as Bitter Kola (BK). This article, majoring in spiritual and not psychological influence, raised a hypothetical question: does spirituality influence Africans’ traditional response to COVID-19? To answer this question, Sunnyside in Pretoria was chosen as a demography to investigate the hypothesis. Data were collected via mixed research methods. There were 16 qualitative respondents, including sellers, herbalists and clergies, and 75 consumers as quantitative respondents under probability sampling. The results analysed using Excel and Python’s regression analysis demonstrated strong connections between consumers’ spiritual motivations, the sales period, the sales rate, and the swift traditional response to the pandemic and related illnesses. The outcome validated the influence of spirituality on 60.9% of quantitative respondents and showed how 25–72% responded to COVID-19 symptoms with BK. Likewise, 87.5% of qualitative respondents consumed BK via indigenous spiritual knowledge in response to the pandemic. Subsequently, this article discussed the benefits, limitations and lessons of spiritual influence on BK consumption in the post-COVID-19 era.
Suffering: An Eastern Patristic Timetic Perspective
Authors: Moldovan Sebastian
Published: December 2024

The essay explores the theme of suffering from an Eastern Patristic perspective, focusing on its spiritual and communal dimensions. It draws on the works of Maximos the Confessor, a famous 7th-century Byzantine theologian, particularly on his Amiguum 8. Maximos presents suffering not only as an inevitable consequence of the lapsarian human condition but also as a providential opportunity for moral and spiritual growth. Through suffering, individuals can reorient themselves towards God, fostering virtues like compassion and gratitude. This kenotic love, modeled after Christ’s sacrificial love, reveals the inherent dignity and equality of all human beings. Maximos’ perspective is at odds with the modern technological and political systems, which often depersonalize care and diminish the role of spiritual transformation, especially in the end-of-life context. The essay suggests that, while technological advancements address suffering, they may overlook the spiritual truth that suffering reveals—a truth central to human dignity and salvation. This perspective invites further exploration into the interplay between Christian theology, suffering, and modern biopolitics.
Pre-Launch Thermal Emissive Band Radiometric Performance for JPSS-3 and -4 VIIRS
Authors: Moyer David , Angal Amit , McIntire Jeff , Xiong Xiaoxiong
Published: December 2024

The Joint Polar Satellite System 3 (JPSS-3) and 4 (JPSS-4) Visible Infrared Imaging Radiometer Suite (VIIRS) are the fourth and fifth in its series of instruments designed to provide high-quality data products for environmental and climate data records. The VIIRS instrument must be calibrated and characterized prior to launch to meet the data product needs. A comprehensive test program was conducted at the Raytheon Technologies facility in 2020 (JPSS-3) and 2023 (JPSS-4) that included extensive functional and environmental testing. The thermal band radiometric pre-launch performance and stability are the focus of this article, which also compares several instrument performance metrics to the design requirements. Brief comparisons with the JPSS-1 and -2 VIIRS instrument performance will also be discussed.
Active Hyperspectral Scanning of Rock Face with a Supercontinuum Laser
Authors: van der Werff Harald , Hecker Christoph , Baines Alfred , Botha Andries E. J. , Fletcher Joe , Portela Bruno
Published: December 2024

Underground environments present a challenge for hyperspectral outcrop analysis. In addition to operational safety and moisture, illumination is the main concern in data acquisition. We report a supercontinuum laser for illuminating rock faces in hyperspectral data acquisition. We present the early results of combining an off-the-shelf hyperspectral camera with a supercontinuum laser system, measured at night on rock faces in a former open-pit mine in southeast Spain as a proxy for underground lighting conditions. Band ratios specifically developed for this geological setting and low-light conditions highlight key minerals that can be used as a vector toward the ore zone. We successfully highlight the key indicator minerals and their distribution patterns for defining gold-bearing ore zones and that supercontinuum white laser light is a feasible illumination source for hyperspectral line scanners under field conditions.
A Survey on Deep Learning for Few-Shot PolSAR Image Classification
Authors: Wang Ningwei , Jin Weiqiang , Bi Haixia , Xu Chen , Gao Jinghuai
Published: December 2024

Few-shot classification of polarimetric synthetic aperture radar (PolSAR) images is a challenging task due to the scarcity of labeled data and the complex scattering properties of PolSAR data. Traditional deep learning models often suffer from overfitting and catastrophic forgetting in such settings. Recent advancements have explored innovative approaches, including data augmentation, transfer learning, meta-learning, and multimodal fusion, to address these limitations. Data augmentation methods enhance the diversity of training samples, with advanced techniques like generative adversarial networks (GANs) generating realistic synthetic data that reflect PolSAR’s polarimetric characteristics. Transfer learning leverages pre-trained models and domain adaptation techniques to improve classification across diverse conditions with minimal labeled samples. Meta-learning enhances model adaptability by learning generalizable representations from limited data. Multimodal methods integrate complementary data sources, such as optical imagery, to enrich feature representation. This survey provides a comprehensive review of these strategies, focusing on their advantages, limitations, and potential applications in PolSAR classification. We also identify key trends, such as the increasing role of hybrid models combining multiple paradigms and the growing emphasis on explainability and domain-specific customization. By synthesizing SOTA approaches, this survey offers insights into future directions for advancing few-shot PolSAR classification.
The Influence of Spatial Scale Effect on Rock Spectral Reflectance: A Case Study of Huangshan Copper–Nickel Ore District
Authors: Wang Ziwei , Zhao Huijie , Jia Guorui , Wang Feixiang
Published: December 2024

The spectral reflectance measured in situ is often regarded as the “truth”. However, its limited coverage and large spatial heterogeneity often make the ground-based reflectance unable to represent the remote sensing images. Since the spatial scale mismatch between ground-based, airborne, and spaceborne measurements, the applications of geological exploration, metallogenic prognosis and mine monitoring are facing severe challenges. In order to explore the influence of spatial scale effect on rock spectra, spectral reflectance with uncertainty caused by differences in illumination view geometry and spatial heterogeneity is introduced into the Bayesian Maximum Entropy (BME) method. Then, the rock spectra are upscaled from the point-scale to meter-scale and to 10 m-scale, respectively. Finally, the influence of spatial scale effect is evaluated based on the reflectance value, spectral shape, and spectral characteristic parameters. The results indicate that the BME model shows better upscaling accuracy and stability than Ordinary Kriging and Ordinary Least Squares model. The maximum Euclidean Distance of rock spectra caused by spatial resolution change is 6.271, and the Spectral Angle Mapper can reach 0.370. The spectral absorption position, absorption depth, and spectral absorption index are less affected by scale effect. For the area with similar spatial heterogeneity to the Huangshan Copper–Nickel Ore District, when the spatial resolution of the image is greater than 10 m, the rock’s spectrum is less influenced by the change in spatial resolution. Otherwise, the influence of spatial scale effect should be considered in applications. In addition, this work puts forward a set of processes to evaluate the influence of spatial scale effect in the study area and carry out the upscaling.
Assessment of the Accuracy of Terrestrial Laser Scanners in Detecting Local Surface Anomaly
Authors: Algadhi Ali , Psimoulis Panos , Grizi Athina , Neves Luis
Published: December 2024

The surface anomaly is a common defect for structures that resist lateral stresses, such as retaining walls. The accurate detection of an anomaly using contactless techniques, such as the Terrestrial Laser Scanner (TLS), is significant for the reliable structural assessment. The influence of the scanning geometry on the accuracy of the TLS point-clouds was investigated in previous studies; however, a deeper analysis is needed to investigate their impact in the context of structural health monitoring. This paper aims to empirically assess the performance of the TLS in detecting surface anomalies, with respect to the scanning distance and angle of incidence in two cases: (i) when both the reference and deformed clouds are taken from the same scanning position, and (ii) the scans are from different positions. Furthermore, the paper examines the accuracy of estimating the depth of the anomaly using three cloud comparison techniques (i.e., C2C, C2M, and M3C2 methods). The results show that the TLS is capable of detecting the surface anomaly for distances between 2 and 30 m and angles of incidence between 90° and 30°, with a tolerance of within a few millimeters. This is achieved even for the case where scans from different locations (i.e., angles and distances) are applied.
LiDAR-Based Negative Obstacle Detection for Unmanned Ground Vehicles in Orchards
Authors: Xie Peng , Wang Hongcheng , Huang Yexian , Gao Qiang , Bai Zihao , Zhang Linan , Ye Yunxiang
Published: December 2024

In orchard environments, negative obstacles such as ditches and potholes pose significant safety risks to robots working within them. This paper proposes a negative obstacle detection method based on LiDAR tilt mounting. With the LiDAR tilted at 40°, the blind spot is reduced from 3 m to 0.21 m, and the ground point cloud density is increased by an order of magnitude. Based on geometric features of laser point clouds (such as rear wall height and density, and spacing jump between points), a method for detecting negative obstacles is presented. This method establishes a mathematical model by analyzing changes in point cloud height, density, and point spacing, integrating features captured from multiple frames to enhance detection accuracy. Experiments demonstrate that this approach effectively detects negative obstacles in orchard environments, achieving a success rate of 92.7% in obstacle detection. The maximum detection distance reaches approximately 8.0 m, significantly mitigating threats posed to robots by negative obstacles in orchards. This research contributes valuable technological advancements for future orchard automation.
Addressing Disparities in Urological Training Across Low- and Middle-Income Countries. Comment on Baqain et al. Post-Graduate Urology Training in Low- and Middle-Income Countries. Soc. Int. Urol. J. 2024, 5, 339–348
Authors: Nedjim Saleh Abdelkerim , Biyani Chandra Shekhar
Published: December 2024

The global demand for urologists is increasing, particularly in low- and middle-income countries (LMICs), where urological problems continue to pose a significant public health burden [...]
Performance Optimization of 5G–Satellite Integrated Networks for IoT Applications in Smart Cities: A Two-Ray Propagation Model Approach
Authors: Uko Mfonobong , Ekpo Sunday C. , Enahoro Sunday , Elias Fanuel
Published: December 2024

The convergence of 5G terrestrial networks with satellite systems offers a revolutionary approach to achieving global, seamless connectivity, particularly for Internet of Things (IoT) applications in urban and rural settings. This paper investigates the implications of this 5G–satellite integrated network architecture, specifically through the application of the two-ray propagation model and the free-space path loss (FSPL) model. By simulating signal characteristics over varying distances, altitudes, and environmental parameters, we explore how factors such as transmitter height, satellite altitude, and frequency impact received power, path loss, channel capacity, and outage probability. The key findings indicate that received power decreases significantly with increasing distance, with notable oscillations in the two-ray model due to interference from ground reflections, particularly evident within the first 100 km. For example, at 50 km, a 300 km satellite altitude yields approximately −115 dBm in received power, while at 1000 km altitude, this power drops to around −136 dBm. Higher frequencies (e.g., 32 GHz) exhibit greater path loss than lower frequencies (e.g., 24 GHz), with a 5 dB difference observed at 1000 km, reinforcing the need for frequency considerations in long-range communication design. In terms of channel capacity, increasing bandwidth enhances achievable data rates but declines with distance due to diminishing received power. At 100 km, a 50 MHz bandwidth supports up to 4500 Mbps, while at 3000 km, capacity drops to around 300 Mbps. The outage probability analysis shows that higher signal-to-noise ratio (SNR) thresholds substantially increase the likelihood of communication failures, especially at distances exceeding 2000 km. For instance, at 3000 km, the outage probability for a 15 dB SNR threshold reaches approximately 25%, compared to less than 5% for a 5 dB threshold. These results underscore the critical trade-offs in designing 5G–satellite IoT networks, balancing bandwidth, frequency, SNR thresholds, and satellite altitudes for optimal performance across diverse IoT applications. The analysis provides valuable insights for enhancing connectivity and reliability in 5G–satellite integrated networks, especially in remote and underserved regions.
Factors Determining Ageing Processes and Well-Being of Older Adults Serving Prison Sentences in Germany
Authors: Kenkmann Andrea , Meyer Liane , Ghanem Christian , Verhülsdonk Sandra
Published: December 2024

The well-being of older adults is influenced by their physical and mental health, their opportunities to complete activities of daily living effectively and autonomously, as well as their social connectedness, meaningfulness and positive outlook to the future. Older adults with a prison sentence face numerous challenges that affect their well-being and influence their opportunities to age well. This paper aims to synthesize and analyse factors that determine what opportunities older adults have during and after their prison sentences in Germany. Data from several studies by the authors are used to identify factors affecting ageing processes. Older adults with a prison sentence are a heterogeneous population in Germany where health conditions, social relations and impairments vary on entry in the prison system. Regional differences in sentencing as well as support structures within the prison system further affect older adults’ health and opportunities to lead self-determined lives after their release. While factors influencing older adults with a prison sentence and their ageing are identified, more research is needed to evaluate the impact of each of them to assess older adults’ well-being after their release from prison.
Reduction of Potassium Supply Alters the Production and Quality Traits of Ipomoea batatas cv. BAU Sweetpotato-5 Tubers
Authors: Sharmin Shaila , Arfin Md. Nazmul Hasan , Tareque Abu Musa Md Main Uddin , Kafi Abdullah Al , Miah Md. Shohidullah , Hossen Md. Zakir , Talukder Md. Abdus Shabur , Robin Arif Hasan Khan
Published: December 2024

In Bangladesh, sweetpotato is the fourth most important source of carbohydrates behind rice, wheat, and potatoes. Potassium is vital for sweetpotato growth, boosting tuber size, sweetness, disease resistance, and yield quality, with deficiencies leading to poor tuber formation and increased stress susceptibility. The present study evaluated the effect of varying dosages of potassium fertilizer (Muriate of Potash, MoP) on the growth, yield, and biochemical qualities of sweetpotato. As a genetic material, BAU sweetpotato-5 was chosen as it is recognized for its high yield, short duration, and nutritional advantages. There were three treatments—full dosage of MoP (321.6 kg ha−1, T0), half dosage of MoP (160.8 kg ha−1, T1) and no MoP (T2). Four replications of a randomized complete block design (RCBD) were used in the experiment. According to analysis of variance, the morphological and biochemical parameters, such as the fresh weight plant−1, number of tuber plant−1, chlorophyll content, total phenolic content, vitamin C, carotenoid, anthocyanin, Zn, and Fe content varied significantly among treatments. The application of the full recommended dosage of MoP resulted in the highest values for several traits, including the fresh weight plant−1, number of tuber plant−1, chlorophyll content, carotenoid, anthocyanin, and Fe content. Conversely, total phenolic content and vitamin C were highest without MoP application. Principal component analysis (PCA) differentiated treatment T0 from T1 and T2 due to higher positive coefficients of the number of leaves at 115 days after transplantation, vine length at 115 days after transplantation, number of branches, stem diameter, fresh weight plant−1, tuber length, tuber diameter, tuber weight, number of tuber plant−1, SPAD, carotenoid, anthocyanin, Fe, and negative coefficients of total phenolic content, vitamin C, and Zn. The findings suggest that potassium is integral to maximizing both yield and key nutritional components in sweetpotato cultivation.
Sustainable Construction Practices in Building Infrastructure Projects: The Extent of Implementation and Drivers in Malawi
Authors: Malik Abubakari , Mbewe Peter B. K. , Kavishe Neema , Mkandawire Theresa , Adetoro Pelumi
Published: December 2024

Sustainable practice is considered a significant practice in modern construction for infrastructure development as it promotes economic growth and improves quality of life. Despite the importance of sustainable practices in construction, few studies have explored the implementation of these practices in low-income countries like Malawi. Therefore, this study aims to assess the extent of the implementation of sustainable construction practices (SCPs) in building infrastructure projects in Malawi. Following an in-depth literature review, 22 sustainable construction practices and 13 drivers were identified. A survey of 193 construction professionals was conducted, and the data were analysed using descriptive statistics and the Relative Importance Index (RII). The findings revealed that economic practices such as efficient allocation of resources, use of quick construction tools and a coordinated supply chain in the construction process are widely implemented with emphasis on the economic aspect of sustainability for infrastructure projects in Malawi. The study further identified global trends and industry standards, social and health benefits, market demand and awareness and access to green technologies and innovation as the main drivers for adopting and implementing SCPs in Malawi. This study provides policymakers and stakeholders with valuable insights to develop policy regulations that would improve the sustainability performance of infrastructure projects.
Sustainability of Digital Initiatives in Public Services in Digital Transformation of Local Government: Insights and Implications
Authors: Sigurjonsson Throstur Olaf , Jónsson Einar , Gudmundsdottir Svala
Published: December 2024

This study examines municipalities’ challenges in digital transformation, focusing on an Icelandic municipality. It aims to determine whether these challenges align with those reported in academic literature, particularly in public service delivery and the sustainability of digital initiatives from an operational perspective. A mixed-methods approach, including interviews with municipal employees and a survey, was used to analyze the municipality’s experiences. An evaluation framework introduced by Lafioune et al. guided the analysis. Key findings highlight the importance of senior management support, adequate funding, staff collaboration, and effective data management for making successful and digital transformation sustainable in the long run. Resistance to change, especially among staff, emerged as a significant obstacle to long-term sustainability. The study reveals that the challenges Icelandic municipalities face are consistent with broader research on digital transformation in public administration. The research emphasizes the need for a comprehensive approach integrating technological, organizational, and cultural changes to ensure a sustainable result from these initiatives. It also underscores the potential of digitalization to enhance public service accessibility and efficiency, promoting social cohesion, equity, and long-term sustainability. Practical recommendations include fostering strong leadership, securing strategic funding, and promoting a collaborative culture to ensure the success of digital initiatives in public services.
Sustainable Lighting Systems Implementation Methodology Aligned with SDGs and International Standards: A Case Study in a Mexican Technological Institute
Authors: Cárdenas Magaña Jorge Alberto , Celis Crisóstomo Marco Antonio , González López Juan M. , Sandoval Pérez Sergio , Verde Romero Daniel A. , Hernández López Francisco Miguel , Villalvazo Laureano Efrain , Vega Negrete Emmanuel , Jalomo Cuevas Jaime , Chávez Bracamontes Ramón , Barragán Sánchez Paulina
Published: December 2024

This paper presents a comprehensive holistic methodology implemented for sustainable lighting systems in educational institutions. The proposed methodology is aligned with the Sustainable Development Goals (SDGs), particularly with SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action), and it follows international standards. The six-step process includes viability analysis, project design simulation using DIALux 4.13 software, the installation of LED lighting systems, and the redesign of some electrical circuits, followed by an analysis of return on investment and the monitorization of CO2 and energy consumption. The proposed methodology results in significant return on investment (ROI), primarily achieved through energy savings and reduced maintenance costs. The implementation of LED tubes, combined with occupancy and natural light sensors, leads to a 66% reduction in energy consumption and a reduction of 15.63 tons (metric tons) of CO2 annually, translating into a quick payback period of approximately 2.36 years. Additionally, the system includes Long-Term Monitoring, which ensures that energy consumption and lighting levels are continuously tracked.
Steel Fiber Reinforced Concrete: A Systematic Review of Usage in Shield Tunnel Segment
Authors: Ren Xianda , Xie Yongli , Ding Fan , Sun Dazhao , Liu Haiyang
Published: December 2024

With the advancement of tunnel construction, the load-bearing capacity of shield tunnel segments is diminishing, while issues of deformation and fissuring are becoming more conspicuous, posing direct threats to structural integrity and functionality. Steel fiber reinforced concrete (SFRC) is considered a prevalent material, endowed with high strength, excellent crack control, fracture toughness, and remarkable economic advantages. This paper surveys the state-of-the-art research on SFRC, systematically encapsulating key aspects regarding its composition, attributes, methods of segment reinforcement, constitutive models for SFRC segments, and performance enhancements of SFRC segments. By optimizing steel fiber content, aggregate preparation, and selection of chemical admixtures, the mechanical performance of SFRC can be augmented, among which the aspect ratio (l/d) and volume fraction (Vf) of steel fibers exert the most significant influence. Compared with conventional reinforcing materials, SFRC possesses benefits of low cost, uncomplicated fabrication, and superior durability. As a heterogeneous multiphase composite, SFRC exhibits high strength, stiffness, and excellent crack resistance, which can amplify the load-bearing capacity and deformation resistance of the segments, defer damage inception, and thereby enhance the safety and durability of tunnel-lining segments. This study assists in redressing the deficiencies of current shield tunnel segment reinforcement technologies and further facilitates the extensive employment of SFRC in tunnel segment strengthening and restoration.
Simulation Approach as an Educational Tool for Comparing NOx Emission Reductions in Two-Stroke Marine Diesel Engines During Low-Load Operation: Water–Fuel Emulsion vs. Late Injection
Authors: Stipanov Mario , Dujmović Josip , Pelić Vladimir , Radonja Radoslav
Published: December 2024

Shipping, as the most efficient, cheapest, and most widespread mode of transporting goods, also generates significant exhaust emissions. This has led to the adoption of stringent regulatory restrictions on emissions from ship propulsion systems. Consequently, the education and training of marine engineers can significantly impact their understanding of how emissions are generated and their potential for reduction. The engine room simulator is an indispensable tool in the training of marine engineers. Since operating conditions and parameters have the greatest impact on NOx emissions, this forms the primary focus of this research. This study tests the accuracy and precision of the engine room simulator in simulating emissions and evaluating the influence of operating conditions on them. Furthermore, the implementation and testing of NOx emission reduction technologies are vital for promoting sustainable shipping, ensuring regulatory compliance, and training personnel to support environmentally conscious maritime operations. Using the example of a two-stroke marine diesel engine, the results obtained are compared with test bench data from similar engines. Special emphasis is placed on simulating the operation of a two-stroke diesel engine at low speed, or low load, where secondary NOx reduction methods cannot be used. Therefore, the simulator is tested using two available technologies: water–fuel emulsion and altering the fuel injection timing to reduce NOx emissions. The simulation results for the water–fuel emulsion show high accuracy in predicting NOx emission trends when changing the water content in the emulsion at nominal power. However, at low load, the results show significant deviations. Testing the effect of altering fuel injection timing under low load using the engine room simulator shows significant differences compared to available research. Nonetheless, research on NOx emissions in this engine mode is limited, presenting a potential area for further study. When comparing the results for nominal power operation, the simulation provides more accurate results, particularly in terms of the influence of fuel injection timing on NOx emissions. However, engine tests on the test bench still reveal more substantial changes in emissions than those obtained using the engine room simulator.
Sustainable Smart Education Based on AI Models Incorporating Firefly Algorithm to Evaluate Further Education
Authors: Li Enhui , Wang Zixi , Liu Jin , Huang Jiandong
Published: December 2024

With the popularity of higher education and the evolution of the workplace environment, graduate education has become a key choice for students planning their future career paths. Therefore, this study proposes to use the data processing ability and pattern recognition ability of machine learning models to analyze the relevant information of graduate applicants. This study explores three different models—backpropagation neural networks (BPNN), random forests (RF), and logistic regression (LR)—and combines them with the firefly algorithm (FA). Through data selection, the model was constructed and verified. By comparing the verification results of the three composite models, the model whose evaluation results were closest to the actual data was selected as the research result. The experimental results show that the evaluation result of the BPNN-FA model is the best, with an R value of 0.8842 and the highest prediction accuracy. At the same time, the influence of each characteristic parameter on the prediction result was analyzed. The results show that CGPA has the greatest influence on the evaluation results, which provides the evaluation direction and evaluation results for the evaluators to analyze the level of students’ scientific research ability, as well as providing impetus to continue to promote the combination of education and artificial intelligence.
New Infrastructure Construction and Coordinated Development of the Regional Economy: The Empirical Evidence from the Yangtze River Delta Region in China
Authors: Feng Chaonan , Gan Qinfan , Li Hao
Published: December 2024

This study explores the “gap reduction effect” of new infrastructure on regional economic disparities, investigating both its impact and underlying mechanisms in narrowing these gaps. Focusing on 41 prefecture-level cities within the Yangtze River Delta, this paper constructs an evaluation index system for new infrastructure and quantitatively measures its development. The results reveal that while the overall level of new infrastructure in the region is relatively advanced, there are notable disparities between cities. The benchmark analysis demonstrates a significant positive relationship between the development of new infrastructure and the promotion of coordinated regional economic growth. New infrastructure fosters industrial and spatial integration through three primary pathways: enhancing the efficiency of the resource allocation within regions, driving industrial upgrades, and facilitating the diffusion of technological innovations. These factors collectively contribute to the balanced and coordinated development of regional economies. Further investigation uncovers a threshold effect, suggesting that the level of digitalization plays a crucial role in facilitating the regional economic integration catalyzed by new infrastructure.
The Effect of Awe on Willingness to Pay for Construction Waste Recycled Products: A Functional Near-Infrared Spectroscopy Study
Authors: Ding Zhikun , Huang Tao , Yang Qifan , Duan Lian
Published: December 2024

The development of the construction industry has generated a large amount of construction waste, and resource utilization of construction waste is an effective means of recycling. However, such recycled construction waste products still lack market competitiveness and recognition. Consumers’ psychological activities are often influenced by emotions, and the sense of awe plays an important role in green consumption. This study aims to investigate how the sense of awe affects consumers’ willingness to pay for construction waste recycled products. The study used functional near-infrared spectroscopy (fNIRS) with a willingness-to-pay task paradigm for experiments, which aims to reveal how different types of awe affect willingness to pay for construction waste recycled products. The behavioral results showed that two conditions effectively induced awe and enhanced consumers’ willingness to pay, but the difference between nature awe and social awe was not significant. The neural activation results showed significant activation in the inferior prefrontal gyrus and dorsolateral prefrontal cortex. In particular, dorsolateral prefrontal cortex activity was significantly enhanced in the social awe condition. The functional connectivity results showed that, compared to the control condition experiment, the awe condition experiment triggered stronger functional connectivity. Therefore, exploring the effect of awe on the willingness to pay for construction waste recycled products can provide a basis reference for companies to develop marketing strategies and corporate pricing and promote the promotion and application of construction waste recycled products in the market.
Heritage on the High Plains: Motive-Based Market Segmentation for a US National Historic Site
Authors: Andereck Kathleen L. , Wise Nicholas , Budruk Megha , Bricker Kelly S.
Published: December 2024

Over the past several years, many iconic national parks in the US have experienced large increases in visitation. At the same time, lesser-known units have had declining numbers. Both issues challenge the sustainable management of parks. The purpose of this study is to use motivation theory to develop and test the differences between market segments at a western US national historic site. The ultimate goal is to contribute to sustainable visitation management by increasing visitation and enhancing the visitor experience. A market segmentation analysis can identify and describe promising target markets. The data were collected using an onsite exit survey, resulting in a sample of 570 visitors over the high season. Three clusters of visitors were identified: heritage immersers, history appreciators, and casual sightseers. The groups differed significantly with respect to visitation motives, travel, and visitation patterns. Segments are described and implications offered. The study confirms differences among cultural heritage visitors, with some being promising as target markets for the historic site. The study underscores the importance of tailoring site management and marketing strategies to meet the diverse needs of visitors and supports the use of motive-based segmentation as a means of better understanding and sustainably managing visitor experiences.
The Role of Corporate Agility in Advancing Sustainable Strategy: Examining the Influence of Shareholder Activism and Board Commitment
Authors: Saragih Henri Harapan , Saifi Muhammad , Nuzula Nila Firdausi , Worokinasih Saparila
Published: December 2024

This study investigates the impact of shareholder activism and board of directors (BOD) commitment on corporate agility and sustainability strategy within Indonesia’s inland container depot (ICD) industry. Data from 147 ICDs were collected using a census sampling method and a standardized questionnaire with a Likert scale. Using a quantitative explanatory research design, the data were analyzed using Structural Equation Modeling (SEM) via WarpPLS. The findings show that both shareholder activism and BOD commitment have a significant positive effect on corporate agility. Additionally, shareholder activism and corporate agility positively influence sustainability strategy, while BOD commitment has no direct significant impact on sustainability strategy. However, corporate agility mediates the relationship between BOD commitment and sustainability strategy, suggesting that BOD commitment enhances corporate agility, which, in turn, fosters the integration of sustainable practices. These results highlight the critical roles of shareholder activism and BOD commitment in enhancing corporate agility and driving sustainable practices within Indonesia’s ICD sector.
Identification of the Compounds Used in Waste Bottle Caps Using Terahertz Radiation for Sustainable Resource Recycling to Benefit International Cooperation
Authors: Manago Gaku , Okubo Kazuaki , Yu Jeongsoo , Tanabe Tadao , Sasaki Tetsuo
Published: December 2024

In Japan, when people take their waste bottle caps to designated recycling companies, JPY 5/kg is donated to developing countries for polio vaccine dissemination activities. The waste volume of plastic bottles and caps is increasing every year, and there is not a day that goes by that we do not see more bottles and caps. PET bottles are more easily recycled, as the bottle body is made of a single material. However, bottle caps are made of two different materials (PP and PE), which are difficult to identify perfectly when utilising the existing NIR technology in the recycling field. This is because the designs and colours of PP and PE bottle caps are becoming more diverse, with black and dark-coloured caps being difficult to sort using NIR technology. In addition, their specific gravity is almost the same; therefore, it is difficult to separate them by their water-based specific gravity, which is an approach commonly used by recyclers. Unidentified caps are sent for thermal recycling, which runs counter to the need for decarbonisation. They may also be mixed with identified caps and sold as recycled raw material, resulting in a reduction in the purity of the recycled plastic. If PP and PE caps can be identified using simple technology, it is expected to promote high resource recycling. Therefore, in order to develop such a sorting process, this study proposes a new method for the material identification of waste caps using terahertz waves. Therefore, this research aims to identify a new identification method for waste plastic caps, which has been a challenge both domestically and internationally. Specifically, we describe the limitations of the conventional methods for identifying PP and PE bottle caps according to their weight, specific gravity, and melting point and propose an identification method using terahertz waves, demonstrating its measurement-related merits and high identification accuracy.
Building Towards One Health: A Transdisciplinary Autoethnographic Approach to Understanding Perceptions of Sustainable Aquatic Foods in Vietnam
Authors: Li Saihong , Ang Soon Yong , Hunter Angus M. , Erdem Seda , Bostock John , Da Chau Thi , Nguyen Ngoc Tuan , Moss Amina , Hope William , Howie Charles , Newton Richard , Casteleiro Mercedes Arguello , Little Dave
Published: December 2024

As Vietnam navigates challenges to its animal, human, and environmental health (One Health) during rapid economic transitions, understanding local perceptions of sustainable food systems, particularly aquatic foods, is vital. This study employs a transdisciplinary, autoethnographic approach to exploring the cultural significance of aquatic food perceptions within Vietnamese communities. Data were primarily sourced through an autoethnographic triangulation method, involving detailed field diaries, vignettes, and interactive workshop data collected from local stakeholders. Our distinctive approach, involving researchers from environmental science, computer science, linguistics, political ecology, aquaculture, nutrition, human physiology, marketing, and accounting and accountability, as both participants and observers, illuminates the lived experiences that shape food perceptions within Vietnam’s specific food agro-ecosystems. By embedding aquatic food perceptions within the One Health framework, we identify key intersections between human, animal, and environmental health. Through cross-disciplinary narrative analysis, our study uncovers the social, political, economic, cultural, and linguistic dimensions surrounding aquatic food perceptions at local, regional, and national levels in Vietnam. Our study highlights the unique contribution of qualitative methods to addressing questions that hard data cannot answer in understanding perceptions of aquatic foods. The study emphasizes the need for an integrated, culturally informed, and transdisciplinary approach to addressing the complex factors influencing One Health outcomes in Vietnam. This research contributes to the broader discourse on sustainable food practices and One Health initiatives, proposing culturally informed interventions aimed at enhancing ecological resilience and public health.
Environmental Impacts and Biological Technologies Toward Sustainable Treatment of Textile Dyeing Wastewater: A Review
Authors: Liu Yuqi , Chen Junsheng , Duan Dianrong , Zhang Ziyang , Liu Chang , Cai Wei , Zhao Ziwen
Published: December 2024

Textile, printing, and dyeing industries in China are expanding annually, resulting in the discharge of significant volumes of wastewater. These effluents have complex compositions and contain diverse pollutants that pose severe hazards to aquatic systems, ecological environments, and nearby flora, fauna, and human populations. The inadequate or rudimentary treatment of these effluents can cause substantial environmental damage. Current technologies for treating textile dyeing wastewater (TDW) include physical, chemical, and biological methods, with biological treatment being noted for its low cost and environmental sustainability. In the realm of biotechnological treatment, microorganisms, such as bacteria, fungi, and algae, exhibit significant potential. This review highlights the urgent need for effective treatment of textile dyeing wastewater (TDW), which poses severe environmental and health risks. It provides a comparative analysis of physical, chemical, and biological treatment methods, with a focus on the unique advantages of biological approaches, such as biodegradation and biosorption, for sustainable wastewater management. Key findings include recent advancements in microbial applications, challenges in scaling up, and integration into existing treatment systems. This review aims to guide future research and practical applications in achieving eco-friendly and cost-effective solutions for TDW remediation.
The Role of Communication Tools in the Knowledge and Diffusion of Sustainable Development Goals: Insights from Multiple Correspondence Analysis
Authors: Maschio Maria Rosaria , Spada Alessia , Fiore Mariantonietta
Published: December 2024

The Sustainable Development Goals are the core of public debate due to their crucial aims of combating poverty, inequality, and climate change. Communication, strategies, and tools play a crucial role in spreading awareness about the 17 goals, but communication campaigns remain ineffective and unattractive. This study aims to analyze the importance and the role that Italians attribute to communication tools for disseminating information about sustainability and the SDGs. In particular, this work seeks to examine whether there is a connection between age and the importance given to sustainability, and how communication tools influence citizens’ perceptions of the significance of sustainability. An online questionnaire was carried out to collect responses, which were then subjected to Multiple Correspondence Analysis. The results show how the importance given to sustainability is linked to age and identify the communication tools through which citizens have learned about sustainability and the SDGs. Furthermore, respondents confirm that communication campaigns are still ineffective, and that there is still little engagement from stakeholders in their creation. The study produces implications for stakeholders to create adequate communication campaigns that help raise awareness and encourage citizens to pay more attention to the world around them.
Clean Production of Sugars from Brewer’s Spent Grains Using Subcritical Water Hydrolysis and Steam Explosion
Authors: Nunes Lucielle Ferreira , Ugalde Gustavo Andrade , Anschau Kéllen Francine , Müller Edson Irineu , Tres Marcus Vinícius , Zabot Giovani Leone , Kuhn Raquel Cristine
Published: December 2024

Brewer’s spent grains (BSG) are a by-product of the beer industry and can be used to produce biofuels. In this case, the objective of this study was to obtain reducing sugars from this biomass by subcritical water hydrolysis in a semi-continuous mode after steam explosion. Temperatures of 120–180 °C, reaction times of 1–5 min, and pressures of 15–25 MPa were used for the steam explosion without CO2. Moistures of 10–50% (w/v), temperatures of 120–180 °C, reaction times of 1–5 min, and pressures of 15–25 MPa were used for the steam explosion with CO2. Subcritical water hydrolysis of solid-exploded material was developed at 210 °C, 15 MPa, a solid/feed ratio of 16 g/g, and a flow rate of 20 mL/min. The characterization of BSG, reducing sugar yields, kinetic profiles, the composition of monosaccharides and furanic moieties, and the characterization of remaining solid by Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM) were performed. For steam explosion with CO2, the significant variables were the temperature and moisture, and the optimized conditions were moisture of 50% (w/v), 120 °C, pretreatment for 1 min, and 15 MPa, with a reducing sugars yield of 18.41 ± 1.02 g/100 g BSG. For steam explosion without CO2, the significant variables were the time and temperature, and the optimized conditions were 120 °C, pretreatment for 1 min, and 15 MPa, with a reducing sugars yield of 17.05 ± 0.48 g/100 g BSG. The process was successful because the steam explosion ruptured the lignocellulosic matrix, and the subsequent process of subcritical water hydrolysis could dissociate the polymers into low-chain saccharides.
Probability Distribution of Extreme Events in Complex Systems: Application to Climate Data
Authors: Otiniano Cira G. , Oliveira Yasmin S. , Maluf Yuri S.
Published: December 2024

It has been observed that the statistical structure of certain climate vectors, such as wind speed versus air density and temperature versus humidity, may exhibit more than one mode due to the complexity of climate systems. This study proposes a new bivariate extreme value distribution, called the transformed symmetric logistic extreme value distribution, which can capture the multimodal characteristics of the joint distribution of extreme observations in complex systems. We derive some of its properties, such as marginal distributions, tail indices, conditional distribution, and P(Y<X). The parameters of the new distribution were estimated using the maximum likelihood method. The applicability of the proposed model is illustrated with climate data, including the analysis of the result P(Y<X).
Characterization of Bi-Starlike Functions: A Daehee Polynomial Approach
Authors: Shaba Timilehin Gideon , Araci Serkan , Adebesin Babatunde Olufemi , Usta Fuat , Khan Bilal
Published: December 2024

This research investigates the second Hankel determinant for a specific class of functions associated with the Daehee polynomial. To achieve this, we introduce new subclasses of starlike functions in the context of Daehee polynomials. In complex analysis, establishing precise bounds for coefficient estimates in bi-univalent functions is essential, as these coefficients define the fundamental properties of conformal mappings. In this study, we derive sharp bounds for coefficient estimates within new subclasses of starlike functions related to Daehee polynomials, with most of the obtained limits demonstrating high accuracy. This work aims to inspire further exploration of rigorous bounds for analytic functions associated with innovative mapping domains.