bluuebunny/crossref_metadata_2025 huggingface dataset:
Structural and Physiochemical Properties of Polyvinyl Alcohol–Succinoglycan Biodegradable Films
Authors: Jeong Jae-pil , Yoon Inwoo , Kim Kyungho , Jung Seunho
Published: June 2024

Polyvinyl alcohol (PVA)–bacterial succinoglycan (SG) biodegradable films were developed through a solvent-casting method. Effects of the PVA/SG ratio on the thickness, transmittance, water holding capacity, and structural and mechanical properties were investigated by various analytical methods. All the prepared films were transparent and uniform, and XRD and FTIR analyses confirmed that PVA was successfully incorporated into SG. The films also showed excellent UV-blocking ability: up to close to 80% with increasing SG concentration. The formation of effective intermolecular interactions between these polymers was evidenced by their high tensile strength and moisture transport capacity. By measuring the biodegradation rate, it was confirmed that films with high SG content showed the fastest biodegradation rate over 5 days. These results confirm that PVA/SG films are eco-friendly, with both excellent biodegradability and effective UV-blocking ability, suggesting the possibility of industrial applications as a packaging material in various fields in the future.
The Imago Dei and the Market Economy: Libertarian Tensions in Michael Novak’s Political Theology
Authors: Yonts Timothy A.
Published: June 2024

The paper explores Michael Novak’s understanding of the human person and his normative case for the market economy, specifically its points of agreement and tension with natural rights libertarianism. For Michael Novak, the imago dei provides the strongest account for the relationship between the market economy, human dignity, and natural rights. Rationalistic attempts, such as those within libertarianism, cannot adequately ground human dignity or sustain free institutions capable of serving the common good, the market economy, and political liberty. However, Novak’s affinity to his libertarian interlocutors presents an opportunity for dialogue on the necessity of economic freedom and related theological influences on natural rights theory for securing human flourishing.
How Can Digital Maps of Religions Inform Us about Fractionalization and Polarization in Post-Communist Romania?
Authors: Rotaru Marina-Alexandra , Creţan Remus , Jucu Ioan Sebastian , Ianăş Ana-Neli , Török-Oance Marcel
Published: June 2024

This study explores religious diversity in Romania and how the trends of indices of religious fractionalization and polarization manifest at the county level in a post-communist period. The county level was selected as the relevant level for analysis due to its more clearly visible spatial dynamics with regard to religions. Recent studies have revealed that the erosion of diversity is an important aspect for any country and needs to be considered as an important aspect of democracy. This paper highlights how digital mapping of religious polarization and fractionalization in Romania has been generally maintained, although the regions of Transylvania, Banat, Dobrogea and Western Moldova remain areas in which there are different religions. Other than the general aspect of religious diversity depending on ethnic trends, there has been a rise of Pentecostals and Baptists at the county level. This aspect has further implications for our study, which calls for creating new institutions for dialogue between majority Orthodox communities and Protestants, not only so that potential conflicts do not appear between Orthodox and emerging religious communities but also to ensure objective, cultural, religious coherence. Our maps revealed the distribution patterns and the temporal evolution of religious denominations for the 1992–2011 period. The major line of originality in our research rests in the findings that after conducting a bivariate spatial autocorrelation analysis of religious fractionalization and polarization, we were able to identify two distinct clusters with spatial overlap over historical provinces.
Endogamy in Iran between Tradition, Religion, and Modernity
Authors: Cohen Ronen A. , Julian-Cohen Tamar
Published: June 2024

The family, which is one of the oldest and most established institutions in human history, has not always just been a reasonable arrangement for achieving biological continuance as well as sexual, emotional, and material support, it has also been one of the basic components for the creation of civilization, culture, and society. There are various types of families, one of which is the endogamous family formed by the custom of consanguineous marriage within a very defined and distinct group. Our article concentrates on the question of how modernity and prosperity have influenced endogamy in modern Iran and whether this will change historical patterns and traditions or, perhaps, only broaden them within Iran’s newly developed and modern society. Our conclusion is that, in Iran’s uncertain environment, tradition may actually be strengthened.
Gingival Cyst of the Adult: A Case Description with a Relevant Literature Analysis
Authors: Forte Marta , d’Amati Antonio , Manfuso Alfonso , Vittoli Massimiliano , Girone Giorgia , Cascardi Eliano , Capodiferro Saverio
Published: June 2024

Gingival cysts of the adult are rare and benign odontogenic lesions of the oral cavity, accounting for almost 0.3% of all odontogenic cysts. Their differential diagnosis is still challenging for surgeons as it includes other gingival inflammatory or non-inflammatory lesions and peripheral odontogenic tumors. The aim of this paper is to report a new case occurring in an adult, analyzing the clinical, radiographic, and histopathological features as guidelines for a differential diagnosis. We report a 49-year-old patient complaining of a small, pigmented lesion localized on the attached gingiva with no history of trauma, which was surgically excised and histologically diagnosed as a gingival cyst. A differential diagnosis may be challenging for clinicians it includes a wide spectrum of inflammatory and non-inflammatory lesions, so a correct diagnostical–therapeutical approach is needed to avoid possible overtreatment and minimize the recurrence rate.
Telescopic Network of Zhulong for Orbit Determination and Prediction of Space Objects
Authors: Lei Xiangxu , Lao Zhendi , Liu Lei , Chen Junyu , Wang Luyuan , Jiang Shuai , Li Min
Published: June 2024

The increasing proliferation of space debris, intermittent space incidents, and the rapid emergence of massive LEO satellite constellations pose significant threats to satellites in orbit. Ground-based optical observations play a crucial role in space surveillance and space situational awareness (SSA). The Zhulong telescopic observation network stands as a pivotal resource in the realm of space object tracking and prediction. This publicly available network plays a critical role in furnishing essential data for accurately delineating and forecasting the orbit of space objects in Earth orbit. Comprising a sophisticated array of hardware components including precise telescopes, optical sensors, and image sensors, the Zhulong network synergistically collaborates to achieve unparalleled levels of precision in tracking and observing space objects. Central to the network’s efficacy is its ability to extract positional information, referred to as angular data, from consecutive images. These angular data serve as the cornerstone for precise orbit determination and prediction. In this study, the CPF (Consolidated Prediction Format) orbit serves as the reference standard against which the accuracy of the angular data is evaluated. The findings reveal that the angular data error of the Zhulong network remains consistently below 3 arcseconds, attesting to its remarkable precision. Moreover, through the accumulation of angular data over time, coupled with the utilization of numerical integration and least squares methods, the Zhulong network facilitates highly accurate orbit determination and prediction for space objects. These methodologies leverage the wealth of data collected by the network to extrapolate trajectories with unprecedented accuracy, offering invaluable insights into the behavior and movement of celestial bodies. The results presented herein underscore the immense potential of electric optic telescopes in the realm of space surveillance. By harnessing the capabilities of the Zhulong network, researchers and astronomers can gain deeper insights into the dynamics of space objects, thereby advancing our understanding of the cosmos. Ultimately, the Zhulong telescopic observation network emerges as a pioneering tool in the quest to unravel the mysteries of the universe.
Towards a Novel Generative Adversarial Network-Based Framework for Remote Sensing Image Demosaicking
Authors: Guo Yuxuan , Zhang Xuemin , Jin Guang
Published: June 2024

During satellite remote sensing imaging, the use of Bayer mode sensors holds significant importance in saving airborne computing resources and reducing the burden of satellite transmission systems. The demosaicing techniques play a key role in this process. The integration of Generative Adversarial Networks (GANs) has garnered significant interest in the realm of image demosaicking, owing to their ability to generate intricate details. However, when demosaicing mosaic images in remote sensing techniques, GANs, although capable of generating rich details, often introduce unpleasant artifacts while generating content. To address this challenge and differentiate between undesirable artifacts and realistic details, we have devised a novel framework based on a Progressive Discrimination Strategy within a Generative Adversarial Network architecture for image demosaicking. Our approach incorporates an artifact-weighted Location Map refinement technique to guide the optimization process towards generating authentic details in a stable and precise manner. Furthermore, our framework integrates a global attention mechanism to boost the interaction of spatial-channel information across different dimensions, thereby enhancing the performance of the generator network. Moreover, we conduct a comparative analysis of various prevalent attention mechanisms in the context of remote sensing image demosaicking. The experimental findings unequivocally demonstrate that our proposed methodology not only achieves superior reconstruction accuracy on the dataset but also enhances the perceptual quality of the generated images. By effectively mitigating artifacts and emphasizing the generation of true details, our approach represents a significant advancement in the field of remote sensing image demosaicking, promising enhanced visual fidelity and realism in reconstructed images.
Monitoring Biophysical Variables (FVC, LAI, LCab, and CWC) and Cropland Dynamics at Field Scale Using Sentinel-2 Time Series
Authors: Hassanpour Reza , Majnooni-Heris Abolfazl , Fakheri Fard Ahmad , Verrelst Jochem
Published: June 2024

Biophysical variables play a crucial role in understanding phenological stages and crop dynamics, optimizing ultimate agricultural practices, and achieving sustainable crop yields. This study examined the effectiveness of the Sentinel-2 Biophysical Processor (S2BP) in accurately estimating crop dynamics descriptors, including fractional vegetation cover (FVC), leaf area index (LAI), leaf chlorophyll a and b (LCab), and canopy water content (CWC). The evaluation was conducted using estimation quality indicators (EQIs) and comprehensive ground throughout the entire growing season at the field scale. To identify soil and vegetation pixels, the spectral unmixing technique was employed. According to the EQIs, the best retrievals were obtained for FVC in around 99.9% of the 23,976 pixels that were analyzed during the growth season. For LAI, LCab, and CWC, over 60% of the examined pixels had inputs that were out-of-range. Furthermore, in over 35% of the pixels, the output values for LCab and CWC were out-of-range. The FVC, LAI, and LCab estimates agreed well with ground measurements (R2 = 0.62–0.85), whereas a discrepancy was observed for CWC estimates when compared with ground measurements (R2 = 0.51). Furthermore, the uncertainties of FVC, LAI, LCab, and CWC estimates were 0.09, 0.81 m2/m2, 60.85 µg/cm2, and 0.02 g/cm2 through comparisons to ground FVC, LAI, Cab, and CWC measurements, respectively. Considering EQIs and uncertainty metrics, the order of the estimation accuracy of the four variables was FVC > LAI > LCab > CWC. Our analysis revealed that temporal variations of FVC, LAI, and LCab were primarily driven by field-scale events like sowing date, growing period, and harvesting time, highlighting their sensitivity to agricultural practices. The robustness of S2BP results could be enhanced by implementing a pixel identification algorithm, like embedding spectral unmixing. Overall, this study provides detailed, pixel-by-pixel insights into the performance of S2BP in estimating FVC, LAI, LCab, and CWC, which are crucial for monitoring crop dynamics in precision agriculture.
Influence of Radiation Stress on Upper-Layer Ocean Temperature under Geostrophic Condition
Authors: Cao Xuhui , Shi Jian , Chen Jie , Wang Qianhui , Lv Jialei , Zhao Zeqi
Published: June 2024

Wave-induced radiation stress (RS), as a primary driver of ocean currents influenced by waves, plays an important role in the response of upper ocean temperatures under typhoons. Previous studies have mainly focused on wave-generated currents and coastal currents in nearshore areas. This paper incorporates the geostrophic effect into the wave-induced radiation stress of wave-current interaction, and the effect of waves on the changes in upper ocean temperature (including sea surface temperature (SST) and mixed layer temperature) under typhoon Nanmadol (2022) is studied. The FVCOM-SWAVE model is used to conduct a preliminary numerical study in the western Pacific Ocean. The RS with the geostrophic effect increased the horizontal and vertical components, leading to an enhancement in turbulent mixing and a decrease in SST by up to 1.0 °C to 1.4 °C, which is closer to the SST obtained by OISST remote sensing fusion observation data. In the strong divergence domain, the direction of the vortex flow exhibits a more pronounced turn to the right, accompanied by an increase in water velocity. The vertical temperature profile of the ocean shows that the water below is perturbed by the RS component of the geostrophic effect, and the depth of the mixed layer increases by about 2 m, which is closer to the depth of the mixed layer observed by the Argo floats, indirectly enhancing the vertical mass transport of the ocean. In general, this shows that RS, which takes into account geostrophic effects, enhances the effect of waves on the water below, indirectly leading to lower temperatures in the upper ocean, and the simulated results align more closely with the observed data, offering valuable insights for enhancing marine numerical forecasting accuracy.
Predicting Urban Trees’ Functional Trait Responses to Heat Using Reflectance Spectroscopy
Authors: Kyaw Thu Ya , Alonzo Michael , Baker Matthew E. , Eisenman Sasha W. , Caplan Joshua S.
Published: June 2024

Plant traits are often measured in the field or laboratory to characterize stress responses. However, direct measurements are not always cost effective for broader sampling efforts, whereas indirect approaches such as reflectance spectroscopy could offer efficient and scalable alternatives. Here, we used field spectroscopy to assess whether (1) existing vegetation indices could predict leaf trait responses to heat stress, or if (2) partial least squares regression (PLSR) spectral models could quantify these trait responses. On several warm, sunny days, we measured leaf trait responses indicative of photosynthetic mechanisms, plant water status, and morphology, including electron transport rate (ETR), photochemical quenching (qP), leaf water potential (Ψleaf), and specific leaf area (SLA) in 51 urban trees from nine species. Concurrent measures of hyperspectral leaf reflectance from the same individuals were used to calculate vegetation indices for correlation with trait responses. We found that vegetation indices predicted only SLA robustly (R2 = 0.55), while PLSR predicted all leaf trait responses of interest with modest success (R2 = 0.36 to 0.58). Using spectral band subsets corresponding to commercially available drone-mounted hyperspectral cameras, as well as those selected for use in common multispectral satellite missions, we were able to estimate ETR, qP, and SLA with reasonable accuracy, highlighting the potential for large-scale prediction of these parameters. Overall, reflectance spectroscopy and PLSR can identify wavelengths and wavelength ranges that are important for remote sensing-based modeling of important functional trait responses of trees to heat stress over broad ranges.
Assessment of Carbon Sink and Carbon Flux in Forest Ecosystems: Instrumentation and the Influence of Seasonal Changes
Authors: Lu Dangui , Chen Yuan , Feng Zhongke , Wang Zhichao
Published: June 2024

Accurate measurement and estimation of forest carbon sinks and fluxes are essential for developing effective national and global climate strategies aimed at reducing atmospheric carbon concentrations and mitigating climate change. Various errors arise during forest monitoring, especially measurement instability due to seasonal variations, which require to be adequately addressed in forest ecosystem research and applications. Seasonal fluctuations in temperature, precipitation, aerosols, and solar radiation can significantly impact the physical observations of mapping equipment or platforms, thereby reducing the data’s accuracy. Here, we review the technologies and equipment used for monitoring forest carbon sinks and carbon fluxes across different remote sensing platforms, including ground-based, airborne, and spaceborne remote sensing. We further investigate the uncertainties introduced by seasonal variations to the observing equipment, compare the strengths and weaknesses of various monitoring technologies, and propose the corresponding solutions and recommendations. We aim to gain a comprehensive understanding of the impact of seasonal variations on the accuracy of forest map data, thereby improving the accuracy of forest carbon sinks and fluxes.
EWMACD Algorithm in Early Detection of Defoliation Caused by Dendrolimus tabulaeformis Tsai et Liu
Authors: Zhao Yuxin , Cui Zeyu , Liu Xiangnan , Liu Meiling , Yang Ben , Feng Lei , Zhou Botian , Zhang Tingwei , Tan Zheng , Wu Ling
Published: June 2024

The persistent increase in forest pest outbreaks requires timely detection methods to monitor the disaster precisely. However, early detection is challenging due to insufficient temporal observation and subtle tree changes. This article proposed a novel framework that collaborates multi-source remote sensing data and uses a change detection algorithm to archive early detection of infestation caused by Dendrolimus tabulaeformis Tsai et Liu (D. tabulaeformis) attacks. First, all available Sentinel-2 images with less than 20% cloud cover were utilized. During periods with long intervals (>16 days) between Sentinel-2 images, Landsat-8 images with less than 20% cloud cover were downscaled to a spatial resolution of 10 m using a deep learning algorithm to meet the requirement for a high temporal frequency of clear observations. Second, the spectral index differences between healthy and infested trees were examined to address the challenge of detecting subtle changes in pest attacks. The Enhanced Vegetation Index (EVI) was selected for early defoliation detection. On this basis, the EWMACD (Exponentially Weighted Moving Average Change Detection) algorithm, which is sensitive to subtle changes, was enhanced to improve the capability of detecting early D. tabulaeformis attacks. The assessment showed that the overall accuracy of the change detection (F1 score) reached 0.86 during the early stage and 0.88 during the late stage. The temporal accuracy (Precision) was 84.1% during the early stage. The accuracy significantly improved compared to using a single remote sensing data source. This study presents a new framework capable of monitoring early forest defoliation caused by D. tabulaeformis attacks and offering opportunities for predicting future outbreaks and implementing preventive measures.
A Time-Domain Doppler Estimation and Waveform Recovery Approach with Iterative and Ensemble Techniques for Bi-Phase Code in Radar Systems
Authors: Youssef Ahmed , Moa Belaid , Driessen Peter F.
Published: June 2024

This paper presents a novel, cost-effective technique for estimating the Doppler effect in the time domain using a single pulse and subsequently leveraging the precise Doppler value to recover the radar waveform. The proposed system offers several key advantages over existing techniques, including the ability to calculate the target speed without any frequency ambiguity and the ability to detect a wide range of target speeds. These two features are not available in any existing techniques, including the conventional moving target detection (MTD) processor. To ensure improved accuracy and robust estimation, the system employs ensemble and iterative techniques by recursively and efficiently reducing the Doppler residues from the signal. Furthermore, the proposed system demonstrates effective signal recovery of a well-known bi-phase code shape at low signal-to-noise ratios in just a few iterations. The performance evaluation of the new algorithm demonstrates its practicability and its superiority over traditional radar systems. Implementation on software-defined radio (SDR) reveals that the proposed system excels in Doppler estimation and signal recovery at low SNRs, demonstrating promising results.
Ionospheric F Layer Radial Current in Response to Southward and Northward IMF Turnings
Authors: Zhong Yunfang , Wang Hui , Zhang Kedeng
Published: June 2024

In this work, local time variations of the response of the ionospheric F layer radial current (IRC) to southward and northward IMF turning events at low and high solar activity are investigated for the first time using Challenging Minisatellite Payload (CHAMP) observations from 2001 to 2010. The response strength of disturbed IRC to the southward and northward IMF turnings does not show any preference for low or high solar activity. At low and high solar activity, the IRC increases in the upward (downward) direction in the daytime (nighttime) within 1.5 h after a sudden southward IMF turning. Conversely, the IRC increases in the downward (upward) direction in the daytime (nighttime) within 1.5 h after a sudden northward IMF turning. The response of zonal wind is insignificant or opposite to that of the IRC. F region electron density may only contribute to the response of the IRC in certain local time sectors. This work indicates that the enhanced convection electric field induced by southward IMF turnings and the reduced convection electric field combined with the overshielding electric field during northward IMF turnings impact the prompt penetration electric field from high latitudes to low latitudes and cause local time differences in the responses of the IRC.
An Improved Method for Detecting Crane Wheel–Rail Faults Based on YOLOv8 and the Swin Transformer
Authors: Li Yunlong , Tang Xiuli , Liu Wusheng , Huang Yuefeng , Li Zhinong
Published: June 2024

In the realm of special equipment, significant advancements have been achieved in fault detection. Nonetheless, faults originating in the equipment manifest with diverse morphological characteristics and varying scales. Certain faults necessitate the extrapolation from global information owing to their occurrence in localized areas. Simultaneously, the intricacies of the inspection area’s background easily interfere with the intelligent detection processes. Hence, a refined YOLOv8 algorithm leveraging the Swin Transformer is proposed, tailored for detecting faults in special equipment. The Swin Transformer serves as the foundational network of the YOLOv8 framework, amplifying its capability to concentrate on comprehensive features during the feature extraction, crucial for fault analysis. A multi-head self-attention mechanism regulated by a sliding window is utilized to expand the observation window’s scope. Moreover, an asymptotic feature pyramid network is introduced to augment spatial feature extraction for smaller targets. Within this network architecture, adjacent low-level features are merged, while high-level features are gradually integrated into the fusion process. This prevents loss or degradation of feature information during transmission and interaction, enabling accurate localization of smaller targets. Drawing from wheel–rail faults of lifting equipment as an illustration, the proposed method is employed to diagnose an expanded fault dataset generated through transfer learning. Experimental findings substantiate that the proposed method in adeptly addressing numerous challenges encountered in the intelligent fault detection of special equipment. Moreover, it outperforms mainstream target detection models, achieving real-time detection capabilities.
Morphometric Analysis of Grape Seeds: Looking for the Origin of Spanish Cultivars
Authors: Espinosa-Roldán Francisco Emanuel , Rodríguez-Lorenzo José Luis , Martín-Gómez José Javier , Tocino Ángel , Ruiz Martínez Víctor , Remón Elola Adrián , Cabello Sáenz de Santamaría Félix , Martínez de Toda Fernando , Cervantes Emilio , Muñoz-Organero Gregorio
Published: June 2024

The Vitis IMIDRA collection contains 3699 entries, representing a significant percentage of the variation in traditional and commercial Vitis cultivars used in Spain. The classification and identification of new entries are currently conducted based on ampelography and molecular methods. Here, we propose a new method of classification of the cultivars based on seed morphology and its application to a total of 224 varieties from the collection. Based on seed shape, fourteen groups have been defined according to the similarity of the seeds, with geometric figures used as models. The new models are Cariñena Blanca, Chardonnay, Parraleta, and Parduca, defining new groups to be added to the ten groups previously described. The study results in 14 groups comprising the Spanish cultivar’s seed shape and morphological variation. Seed morphology can help to identify varieties cultivated in the past through archaeological finds.
Rapid Discovery of Antimicrobial and Antimalarial Agents from Natural Product Fragments
Authors: Han Jianying , Liu Xueting , Zhang Lixin , Van Voorhis Wesley C. , Quinn Ronald J. , Liu Miaomiao
Published: June 2024

Fragment-based drug discovery (FBDD) focuses on small compounds, known as fragments, typically with a molecular weight of less than 300 Da. This study highlights the benefits of employing a pure natural product library for FBDD, contrasting with the predominant use of synthetic libraries. Practical methods for rapidly constructing such libraries from crude extracts were demonstrated across various plant and microbial samples. Twenty-nine (29) natural product fragments, including a new compound (20), were identified. Antimicrobial activities were assessed for a subset of the isolated compounds, revealing potent fragments (MICs 4–8 μg/mL) against Mycobacterium bovis bacille Calmette-Guérin (BCG), Staphylococcus aureus (SA), and methicillin-resistant S. aureus (MRSA). Furthermore, a native mass spectrometry technique was introduced to rapidly identify non-competitive fragments against malarial proteins. As a result, two pairs of non-competitive fragments, lepiotin C (31) and 7-amino deacetoxy cephalosporanic acid (32) binding to dynein light chain 1, methyl gallate (33) and β-santanin (34) binding to dUTPase, were identified, serving as promising starting points for developing potent malarial protein inhibitors.
Winter and Summer PM2.5 Land Use Regression Models for the City of Novi Sad, Serbia
Authors: Dmitrašinović Sonja , Radonić Jelena , Živković Marija , Ćirović Željko , Jovašević-Stojanović Milena , Davidović Miloš
Published: June 2024

In this study, we describe the development of seasonal winter and summer (heating and non-heating season) land use regression (LUR) models for PM2.5 mass concentration for the city of Novi Sad, Serbia. The PM2.5 data were obtained through an extensive seasonal measurement campaign conducted at 21 locations in urban, urban/industrial, industrial and background areas in the period from February 2020–July 2021. At each location, PM2.5 samples were collected on quartz fibre filters for 10 days per season using a reference gravimetric pump. The developed heating season model had two predictors, the first can be associated with domestic heating over a larger area and the second with local traffic. These predictors contributed to the adjusted R2 of 0.33 and 0.55, respectively. The developed non-heating season model had one predictor which can be associated with local traffic, which contributed to the adjusted R2 of 0.40. Leave-one-out cross-validation determined RMSE/mean absolute error for the heating and non-heating season model were 4.04/4.80 μg/m3 and 2.80/3.17 μg/m3, respectively. For purposes of completeness, developed LUR models were also compared to a simple linear model which utilizes satellite aerosol optical depth data for PM2.5 estimation, and showed superior performance. The developed LUR models can help with quantification of differences between seasonal levels of air pollution, and, consequently, air pollution exposure and association between seasonal long-term exposure and possible health risk implications.
Methodology for Stakeholder Prioritization in the Context of Digital Transformation and Society 5.0
Authors: Osorio Ana M. , Úsuga Luisa F. , Restrepo-Carmona Jaime A. , Rendón Isabel , Sierra-Pérez Julián , Vásquez Rafael E.
Published: June 2024

This paper addresses a pragmatic and well-articulated qualitative methodology for the identification, prioritization, and consultation of stakeholder groups for a higher education institution as a key element for the organization in the context of digital transformation and Industry 5.0. First, the identification phase required technological surveillance and competitive intelligence, which allowed for defining the organization’s stakeholders and their characteristics. Then, the prioritization phase was performed to determine the stakeholders that potentially will have the greatest impact on achieving the institution’s strategic objectives to the targets of the Sustainable Development Goals prioritized by the institution, and those who will be most affected (positively or negatively) by the HEI activities. Finally, different methods and technological tools were used for consulting internal and external stakeholders, according to the type of relationship with each group, which allowed the understanding of the perceptions of different stakeholder groups on issues such as gender equity, mental health, regenerative economy, and diversity training. The results are then presented in terms of organizational context, where the concept of stakeholder group was defined by the dynamics of the selected HEI; the prioritized stakeholders include students, employees, academic and research sector, public sector, business sector, social sector, community, archdiocese and diocese, alumni, donors, and benefactors. This approach enabled the identification of issues that became a priority in the university’s actions towards the future. Although the presented methodology is mainly qualitative, which can represent a high degree of subjectivity, the stakeholder prioritization exercise provides organizations with inputs for decision making aligned with their needs and expectations. Using such a methodology can help the organization to experience structural changes reflected in improved strategic alignment, understanding, and satisfaction of stakeholders’ expectations and needs, enhancement of reputation, risk and conflict mitigation, and the consolidation of long-term healthy and trustworthy relationships, in the context of Society 5.0, where human-centered solutions are expected.
Carbon Emission Heterogeneity in Developed Countries: Insights for China’s Neutrality Strategy
Authors: Zhang Yansong , Hou Gefei , Zhang Yan
Published: June 2024

This study investigates the heterogeneity and driving factors of carbon emission reduction in developed countries, providing insights for formulating carbon neutrality strategies and plans in China. Firstly, typical developed countries worldwide are categorized into four modes: high energy consumption–high emissions, high energy consumption–low emissions, low energy consumption–low emissions and low energy consumption–high emissions, based on the “per capita energy consumption–emission intensity” classification method. Secondly, the LMDI decomposition model is employed to calculate the carbon emission-reduction driving effects of each mode, thereby analyzing the evolution path of carbon emissions. Finally, carbon emission-reduction policy recommendations are proposed based on the current situation of provincial carbon emissions in China. The research findings are as follows: (1) Carbon emissions in developed countries follow the Environmental Kuznets Curve (EKC) law, exhibiting an inverted U-shaped trajectory. In the per capita GDP range of USD 12,000–20,000, carbon emissions in most countries have reached or are close to their peak, with per capita carbon emissions in different modes decreasing and tending towards a level of 4000 kg/person. (2) There is heterogeneity in the EKC of carbon emissions in developed countries, which can be divided into technological, structural, comprehensive and clean types based on differences in emission-reduction factors. The trajectories of carbon emissions in most developed countries follow a clean path, while those in newly developed countries are constrained by environmental pressures and are expected to be between mixed and structural types before the emission peak, and tend towards a clean type after the peak. (3) Energy clean-up is the most direct and efficient method for carbon emission reduction, which can significantly and efficiently achieve carbon emission reduction. Industrial restructuring and technological progress play a significant role in suppressing carbon emissions. Policy recommendations are proposed as follows: first, reduce the proportion of fossil energy and increase energy cleanliness; second, promote industrial restructuring to reduce energy dependence; third, enhance production technology and improve energy-utilization efficiency; fourth, increase technological breakthroughs to support low-carbon transformation; fifth, correctly recognize the differences among provinces in China and formulate differentiated carbon emission-reduction policies.
To What Extent Do Alternative Energy Sources Displace Coal and Oil in Electricity Generation? A Mean-Group Panel Analysis
Authors: Liddle Brantley
Published: June 2024

This paper determines by how much alternative electricity generation sources—natural gas, nuclear, hydro, and renewables—displace electricity generation from coal and oil. It does so by employing a first-difference model and a mean-group estimator applied to a panel that spans 1985–2019 for 27 high- and 13 middle-income countries. As such, our approach avoids/addresses several statistical issues common in long-macro panel analyses—heterogeneity, nonstationarity, and cross-sectional dependence—that have largely been ignored/unaddressed in previous displacement studies. Ultimately, we find that the displacement effect is small and only marginally significant for nuclear, and is significant though less than unity for natural gas and hydro, whereas intermittent renewables (solar and wind) have unitary displacement effect. These results suggest a substantially greater displacement potential for alternative generation sources than typically found by the previous literature. In other words, increasing hydro and wind and solar are all impactful ways to decarbonize the electricity system.
Predicting Teacher’s Information and Communication Technology-Enabled Education for Sustainability Self-Efficacy
Authors: Ghazali Munirah , Makrakis Vassilios , Kostoulas-Makrakis Nelly , Yakob Nooraida , Rashid Rabiatul Adawiah Ahmad , Othman Widad , Fitriyanto Nanung Agus
Published: June 2024

This study focused on the development of a teacher self-efficacy measurement addressing the contextualization of information and communication technologies (ICTs) with education for sustainability (EfS) using principal component analysis. Furthermore, this study, with the participation of 1815 teachers, examined the predictive value of some hypothesized predictors of the ICTeEfS self-efficacy construct such as gender, school setting, years of teaching, knowledge of education for sustainability, knowledge of ICTs, and experience in using ICTs to support the integration of education for sustainability in teaching and school curricula using multiple regression analysis. The research results revealed that gender did not explain any statistically significant variance of teachers’ ICTeEfS self-efficacy; contrary to this, teachers possessing a high level of knowledge on issues about sustainability and ICT competence explained most of the extracted variance. However, a gap remains in utilizing these skills pedagogically. This study also discusses the varying levels of self-efficacy among teachers based on their workplace location, finding that urban teachers demonstrate higher self-efficacy compared to their rural counterparts. This could be attributed to the disparities in resources and support systems, thereby affecting their capacity to employ ICT in EfS effectively. It was also found that novice teachers exhibited higher predictive power to ICTeEfS self-efficacy, possibly due to their recent exposure to ICT training. This study assumes that a profound understanding of EfS, coupled with ICT tools, bolsters the creation of contextualized curricula and enriches the teaching and learning experience towards sustainability.
Integrating Technology Roadmaps into the Construction of Learning Indicators
Authors: Tseng Fan-Lung , Yao Kai-Chao , Chen Hsiang-Wei , Yang Jen-Sheng
Published: June 2024

In the era of rapid technological advancement and the ascent of the United Nations’ Sustainable Development Goals (SDGs), addressing the persistent gap between education and employment is crucial to ensure “decent work for all” and enhance human well-being. This study initiates its inquiry from the construction of learning indicators, aiming to facilitate the early exposure of learners to relevant industrial technologies and the acquisition of future-oriented competencies. Firstly, through a review of the literature and an analysis of the current situation, the concept of technology mapping in the industrial sector is employed for technology forecasting. This involves the development of a technology roadmap and the identification of key technologies. Subsequently, the Delphi method is utilized to invite expert scholars to assess the suitability and importance of learning indicators. Data processing is carried out using descriptive statistics, qualitative recommendations, and the Kolmogorov–Smirnov single-sample analysis. Using a smart home system practice curriculum as an example, this study’s final development includes 9 main constructs and 56 sub-constructs, serving as the foundation for curriculum and instructional material development. Upon receiving relevant instruction, students can swiftly integrate into related industries.
Unveiling Deep-Seated Gravitational Slope Deformations via Aerial Photo Interpretation and Statistical Analysis in an Accretionary Complex in Japan
Authors: Kikuchi Teruyuki , Nishiyama Satoshi , Hatano Teruyoshi
Published: June 2024

The objective of this study was to identify the locations of deep-seated gravitational slope deformations (DGSDs) and define the numerical characteristics of these deformations to contribute to the sustainable management of social infrastructure in the event of an increased disaster. The topographic features of the DGSDs were quantitatively characterized based on their surface morphologies. Topographic features indicative of gravitational deformation in pre-slide topographic maps, such as terminal cliff failures, irregular undulations, and gullies, suggest that progressive deformation occurred over a prolonged period. To track the gravitational deformation over time, we interpreted aerial photographs of DGSDs from 1948 and 2012 associated with deep-seated landslides on the Kii Peninsula induced by Typhoon Talas on 2–5 August 2011. Corresponding numerical analysis of the gravitational deformations using 1 m digital elevation models reveals that landslide areas exhibit eight characteristic influencing factors, demonstrating that characteristic morphologies exist in areas that eventually experience landslides. One such morphological feature is the existence of a gently sloping area in the upper section of the deep-seated landslide mass, which comprises a catchment basin without a corresponding valley or gully. These findings suggest that rainwater penetrates the ground, and degrades and deforms the rock within the landslide mass, causing the slope to fail after torrential rainfall. This study holds great significance for advancing sustainable infrastructure development and management and mitigating environmental changes.
Assessing the Potential for Valorisation of a Pulp and Paper Industry Byproduct for the Construction of Unpaved Forest Roads: A Geotechnical Perspective
Authors: Carlos David Miranda , Martins Catarina , Rodrigues Daniela , Macedo Joaquim , Pinho-Lopes Margarida
Published: June 2024

Integration of sustainability into industry has encouraged practices of circular economy, reusing and recycling resources. This paper studies alternative solutions to materials traditionally used for unpaved roads, with a byproduct of the pulp and paper industry (not pre-treated), and analyses its valorisation potential from a geotechnical perspective. Two approaches were adopted: (1) assessment of geotechnical properties of base materials (aggregate, local soil and byproduct) and mixtures (aggregate/local soil and byproduct, 3% or 6%); (2) design of the base layer (case study), considering different solutions for the material forming that layer, assessing its height and life cycle. The small incorporation percentages studied changed the geotechnical properties of aggregate and local soil, reducing sensitivity to water and increasing the water content for optimum compaction. The CBR of mixtures reduced with the incorporation of the byproduct. For the case study, incorporation of byproduct (6% maximum) in the local soil did not significantly affect the base layer height. Total replacement with the byproduct is mechanically possible. For the fixed height of the base layer, incorporating the byproduct in traditional materials reduced the unpaved road life cycle, reflecting CBR reductions. From a geotechnical perspective, the valorisation of this byproduct is promising, and from an industry point of view, its use (geotechnical valorisation) represents a way to promote circular economy and sustainability.
Beneficial Use of Water Treatment Sludge with Stabilizers for Application in Road Pavements
Authors: Takao Túlio W. , Bardini Vivian S. , de Jesus Amanda D. , Marchiori Leonardo , Albuquerque Antonio , Fiore Fabiana A.
Published: June 2024

Water treatment sludge (WTS) is the residue produced during water treatment processes for public use. Exploring the reintroduction of these wastes into the production chain to generate new, value-added materials presents a current challenge. This could promote their reuse and reduce the negative environmental impacts associated with their disposal. This study assessed the technical feasibility of using aluminum-based WTS to partially replace silty sand soil in mixtures that include two stabilizers (hydrated lime and Portland cement), potentially for use in road pavements. After conducting a thorough physical, chemical, and geotechnical characterization of both the soil and the sludge, bench-scale experiments were carried out to test the mixtures’ resistance, with WTS proportions of 5%, 8%, 10%, 15%, and 20%, stabilized with either lime or cement. The findings confirm that WTS does not contain potentially toxic elements, according to Brazilian standards, and all tested composites appear suitable for paving. However, the mechanical resistance of the soil–sludge–cement mixtures decreases as the WTS content increases, with an optimum California bearing ratio (CBR) of 41.50% achieved at a 5% WTS addition. Meanwhile, incorporating 15% WTS into soil–sludge–lime mixtures resulted in the highest CBR value of 21.25% for this type of mixture. It is concluded that incorporating stabilizers into soil–WTPS mixtures for road construction allows for an increased percentage of WTPS in silty-sandy soils. Further studies are recommended with different soil types and the addition of fibers to the mixes, to assess the long-term performance of the structure, along with economic and environmental analyses.
Sustainable Reclaimed Asphalt Emulsified Granular Mixture for Pavement Base Stabilization: Prediction of Mechanical Behavior Based on Repeated Load Triaxial Tests
Authors: Coelho Lisley Madeira , Guimarães Antônio Carlos Rodrigues , Azevedo Afonso Rangel Garcez de , Monteiro Sergio Neves
Published: June 2024

The stabilization of asphalt pavement bases with granular soil and aggregates emulsified with asphalt is a widely used technique in road construction and maintenance. It aims to improve the mechanical properties and durability of the lower pavement layers. Currently, there is no consensus on the most suitable method for designing emulsified granular aggregates with reclaimed asphalt pavement (RAP), as it is very complex. Therefore, the methodology is generally based on compliance with one or more volumetric or mechanical parameters established in the highway regulations for conventional asphalt mixtures, which does not guarantee the optimization and characterization of the recycled mixture in the base course. In this study, granular mixtures were developed, including five with emulsion and one emulsion-free as a control mix. Granular RAP mixes were designed in this study, including five with emulsion and one emulsion-free as a control mix. The five mixes ranged from 1% to 5% emulsion and were characterized by multi-stage triaxial tests with repeated load resilient modulus (RM) and permanent deformation (PD) to evaluate their mechanical behavior. The results showed that the mixes had RM values between 350 and 500 MPa, consistent with literature values. However, they showed similar levels of accumulated deformation to the control mix without RAP emulsion. The sample with 1 % RAP emulsion exhibited a satisfactory RM value and better performance in PD than the control mix (5 mm) and showed accumulated PD values of up to 4 mm. In contrast, the other samples exhibited deformations of up to 6 mm. In this study, the multi-stagge triaxial RM and PD tests were found to be an effective predictive method for characterizing the behavior of RAP materials in base courses, regardless of the types of admixtures contained. Multi-stage resilient modulus and PD tests can be considered as a predictive method for the behavior of milled material in base courses. They were able to provide initial data for interpreting the behavior of ETB mixtures.