bluuebunny/crossref_metadata_2025 huggingface dataset:
Complexity and Timeliness of the Term “Christendom” for Ecumenical Ecclesiology
Authors: Krauze Filip
Published: May 2024

The purpose of this paper is to examine whether and why the term “Christendom”, despite its ambiguous historical connotations, can be taken into account in contemporary ecumenical ecclesiology. This will be performed through a linguistic, historical, and theological analysis of the term in question. Its uses in the literature and occurrences in the historical contexts have been reviewed. Particularly important in this case turned out to be St. Augustine’s work “The City of God”, excerpts of which shed light on some stereotypes that can place the term “Christendom” in merely political meaning. For correct discourse, one needs, on the one hand, an awareness of the traumas that the community of believers have gone through in the history of humanity along with the entire humanity, and on the other hand, the outright revolution that has taken place in post-conciliar theology. It seems that the term “Christendom” retains its relevance especially in the context of the conciliar images of the Kingdom of God and the theology of the Church of Christ. In another way then, “Christianity” reminds one of the Church’s rootedness in a particular place, time, and culture, providing a tool for the humble contextualization of ecclesiology in the history of humanity.
AI and East Asian Philosophical and Religious Traditions: Relationality and Fluidity
Authors: Trothen Tracy J. , Kwok Pui Lan , Lee Boyung
Published: May 2024

This article examines aspects of the intersection of artificial intelligence (AI) and religion, challenging Western Christian perspectives that warn against playing God and ascribing human and God-like characteristics to AI. Instead of a theistic emphasis, East Asian religious perspectives emphasize concern for the potential implications of AI on communities and relationships. This article argues for the inclusion of perspectives from Chinese and Korean traditions in the growing discourse on AI and religion to adequately address the potential social impacts of AI technologies. First, we describe some of the questions and concerns being posed regarding AI and consider how certain normative interpretations of Western Christianity may influence some of these issues. Second, we discuss the contributions of Asian philosophies and religious traditions, which emphasize relationality and fluidity, to provide alternative approaches to AI. Third, we outline the discussion of AI from Confucian, Daoist, and Buddhist traditions, which see the cosmos as an interwoven whole and both humans and the cosmos as evolving. Lastly, we introduce the example of digital resurrection (e.g., deadbots) and consider how the philosophical and theological Korean concept of Jeong might refocus our understanding of the potential impacts of this AI technology.
Laozi’s Ecofeminist Ethos: Bridging Ancient Wisdom with Contemporary Gender and Environmental Justice
Authors: Liu Pinghua
Published: May 2024

This paper delves into the convergence of Laozi’s Daoist mysticism with the principles of ecofeminism, highlighting the potential for ancient wisdom to inform contemporary issues of gender and environmental justice. Through an examination of the Dao De Jing, we uncover insights into a holistic approach to social justice that integrates ecological sustainability and gender equality. Laozi’s teachings, characterized by the principles of Dao, Wu-wei, and Ziran, offer a foundational framework for understanding the interconnectedness of all beings and the importance of living in harmony with the natural world. By analyzing relevant passages and concepts from the Dao De Jing, this paper demonstrates how Daoist philosophy aligns with and enriches ecofeminist values, advocating for a society that honors the balance between humanity and nature and recognizes the integral role of women in achieving environmental and social harmony. This paper presents case studies that illustrate the practical application of Daoist principles in ecological feminist practices, shedding light on the successes and challenges of integrating ancient philosophical insights into modern activism. The fusion of Daoist mysticism and ecofeminism provides a compelling vision for addressing the intertwined challenges of gender inequality and environmental degradation, suggesting pathways toward a more just, sustainable, and harmonious world. In doing so, it calls for a reimagined approach to social justice that is deeply informed by an understanding of ecological sustainability and gender equality as mutually reinforcing goals.
Novel Chymotrypsin Purified and Biochemically Characterized from Digestive Organs of Bigfin Reef Squid (Sepioteuthis lessoniana)
Authors: Satjarak Jirapan , Klomklao Sappasith , Zhang Yi , Thongprajukaew Karun
Published: May 2024

Chymotrypsin from the digestive organs of bigfin reef squid, a major commercial squid species in Thailand, was purified to 41-fold with 5.7% yield by a sequential purification process including ammonium sulfate precipitation, size exclusion, and ion exchange chromatography. According to SDS-PAGE, the molecular weight of purified chymotrypsin was 43 kDa. Native-PAGE analysis revealed a single band for this purified enzyme. The optimum pH and temperature for chymotrypsin activity of the purified enzyme were a pH of 7.0 with a temperature of 55 °C. The purified chymotrypsin remained stable throughout a wide range of pH levels (6–11) and at relatively high temperature (55 °C). It was significantly inhibited by PMSF and TPCK. The values of the kinetic constants Km and Kcat were found to be 1.33 mM and 31.46 s−1, respectively. The purified chymotrypsin has the N-terminal amino acid IVGGQEATPGEWPWQAALQV. This study provided new information about the biochemical properties of pure chymotrypsin from bigfin reef squid, which will be useful in the future investigation, aquaculture, and application of bigfin reef squid.
Spondias tuberosa and Spondias mombin: Nutritional Composition, Bioactive Compounds, Biological Activity and Technological Applications
Authors: de Freitas Jaqueline Souza , Novo Alex de Aguiar , Kunigami Claudete Norie , Moreira Davyson de Lima , Freitas Suely Pereira , da Matta Virgínia Martins , Jung Eliane Przytyk , Ribeiro Leilson de Oliveira
Published: May 2024

The genus Spondias has two species of native trees from Brazil that deserve to be highlighted: Spondias tuberosa (“umbu”) and Spondias mombin (“cajá”). Their fruit contain bioactive compounds which have been associated with several biological activities. However, they remain little exploited in the development of food and pharmaceutical products. In this perspective, the present review summarizes the literature data about the physicochemical and nutritional characteristics, bioactive compounds, potential health benefits, and industrial applications of these fruit, including their pulp, seed, and peel. The current scenery mapping for scientific articles was performed in the Scopus and Web of Science databases. The study also considered patent applications collected in the Derwent database. Results showed an increase in scientific publications in recent years for both species. Many applications are related to food technology; nevertheless, due to the composition of their non-edible fractions, they have the potential for use in biorefinery, being their use an opportunity for bioeconomy. Thus, this review provides a comprehensive overview of these Brazilian native fruit to offer a theoretical foundation and valuable data for future investigations and exploitation.
Porcospino Flex: A Bio-Inspired Single-Track Robot with a 3D-Printed, Flexible, Compliant Vertebral Column
Authors: Nodehi Shahab , Bruzzone Luca , Lalegani Dezaki Mohammadreza , Zolfagharian Ali , Bodaghi Mahdi
Published: May 2024

This paper is focused on the design and development of the Porcospino Flex, a single-track robot inspired by nature and featuring a meta-material structure. In the earlier version of the Porcospino, the main body was composed of a chain of vertebrae and two end sections linked by flexible joints, but the excessive use of materials in 3D printing and the resulting weight of the robot posed challenges, ultimately leading to a decrease in its overall efficiency and performance. The Porcospino Flex is manufactured through the fused deposition modeling process using acrylonitrile butadiene styrene and thermoplastic polyurethane, featuring a singular meta-material structure vertebral column. The adoption of a lattice structure in the main body of the Porcospino Flex leads to a substantial increase in performance, reducing its weight from 4200 g to 3600 g. Furthermore, the decrease in weight leads to a reduction in material usage and waste, making a substantial contribution to the sustainability of the robot. The discussion focuses on the testing results of the Porcospino Flex prototype, highlighting the enhancements observed compared to its prior version.
PARTS—A 2D Self-Reconfigurable Programmable Mechanical Structure
Authors: Gerbl Michael , Pieber Michael , Ulrich Emanuel , Gerstmayr Johannes
Published: May 2024

Modular self-reconfigurable robots hold the promise of being capable of performing a wide variety of tasks. However, many systems fall short of either delivering this promised functionality due to constraints in system architecture or validating it on functional hardware prototypes. This paper demonstrates the functional capabilities of the Planar Adaptive Robot with Triangular Structure (PARTS) and documents the versatility of this robot system using a holistic approach that combines simulations and hardware demonstrations on a prototype with nine fabricated modules. PARTS is a two-dimensional modular robot consisting of modules with a shape-shifting triangular geometry capable of forming adaptable space-covering structures. Meta-modules and mesh restructuring techniques are presented as methods for achieving topological self-reconfiguration. The feasibility of these methods is demonstrated by applying them on a simulated reconfiguration example of 62 modules. The paper showcases the versatility of PARTS on the hardware prototype using task-specific configurations, including locomotion using a meta-module and a walker configuration, module-module interaction by establishing a bridge between two separated module clusters, and interaction with the environment using a gripper and supporting structure configuration. The results validate the versatility and emphasize the potential of the system’s design concept, motivating the transfer of the hardware architecture to the third dimension.
A Comprehensive Examination of the Medvezhiy Glacier’s Surges in West Pamir (1968–2023)
Authors: Murodov Murodkhudzha , Li Lanhai , Safarov Mustafo , Lv Mingyang , Murodov Amirkhamza , Gulakhmadov Aminjon , Khusrav Kabutov , Qiu Yubao
Published: May 2024

The Vanj River Basin contains a dynamic glacier, the Medvezhiy glacier, which occasionally poses a danger to local residents due to its surging, flooding, and frequent blockages of the Abdukahor River, leading to intense glacial lake outburst floods (GLOF). This study offers a new perspective on the quantitative assessment of glacier surface velocities and associated lake changes during six surges from 1968 to 2023 by using time-series imagery (Corona, Hexagon, Landsat), SRTM elevation maps, ITS_LIVE, unmanned aerial vehicles, local climate, and glacier surface elevation changes. Six turbulent periods (1968, 1973, 1977, 1989–1990, 2001, and 2011) were investigated, each lasting three years within a 10–11-year cycle. During inactive phases, a reduction in the thickness of the glacier tongue in the ablation zone occurred. During a surge in 2011, the flow accelerated, creating an ice dam and conditions for GLOF. Using these datasets, we reconstructed the process of the Medvezhiy glacier surge with high detail and identified a clear signal of uplift in the surface above the lower glacier tongue as well as a uniform increase in velocities associated with the onset of the surge. The increased activity of the Medvezhiy glacier and seasonal fluctuations in surface runoff are closely linked to climatic factors throughout the surge phase, and recent UAV observations indicate the absence of GLOFs in the glacier’s channel. Comprehending the processes of glacier movements and related changes at a regional level is crucial for implementing more proactive measures and identifying appropriate strategies for mitigation.
Mobile Laser Scanning Data Collected under a Forest Canopy with GNSS/INS-Positioned Systems: Possibilities of Processability Improvements
Authors: Čeňava Juraj , Tuček Ján , Chudá Juliána , Koreň Milan
Published: May 2024

GNSS/INS-based positioning must be revised for forest mapping, especially inside the forest. This study deals with the issue of the processability of GNSS/INS-positioned MLS data collected in the forest environment. GNSS time-based point clustering processed the misaligned MLS point clouds collected from skid trails under a forest canopy. The points of a point cloud with two misaligned copies of the forest scene were manually clustered iteratively until two partial point clouds with the single forest scene were generated using a histogram of GNSS time. The histogram’s optimal bin width was the maximum bin width used to create the two correct point clouds. The influence of GNSS outage durations, signal strength statistics, and point cloud parameters on the optimal bin width were then analyzed using correlation and regression analyses. The results showed no significant influence of GNSS outage duration or GNSS signal strength from the time range of scanning the two copies of the forest scene on the optimal width. The optimal bin width was strongly related to the point distribution in time, especially by the duration of the scanned plot’s occlusion from reviewing when the maximum occlusion period influenced the optimal bin width the most (R2 = 0.913). Thus, occlusion of the sub-plot scanning of tree trunks and the terrain outside it improved the processability of the MLS data. Therefore, higher stem density of a forest stand is an advantage in mapping as it increases the duration of the occlusions for a point cloud after it is spatially tiled.
Comparison between Satellite Derived Solar-Induced Chlorophyll Fluorescence, NDVI and kNDVI in Detecting Water Stress for Dense Vegetation across Southern China
Authors: Wang Chunxiao , Liu Lu , Zhou Yuke , Liu Xiaojuan , Wu Jiapei , Tan Wu , Xu Chang , Xiong Xiaoqing
Published: May 2024

In the context of global climate change and the increase in drought frequency, monitoring and accurately assessing the impact of hydrological process limitations on vegetation growth is of paramount importance. Our study undertakes a comprehensive evaluation of the efficacy of satellite remote sensing vegetation indices—Normalized Difference Vegetation Index (MODIS NDVI product), kernel NDVI (kNDVI), and Solar-Induced chlorophyll Fluorescence (GOSIF product) in this regard. Initially, we applied the LightGBM-Shapley additive explanation framework to assess the influencing factors on the three vegetation indices. We found that Vapor Pressure Deficit (VPD) is the primary factor affecting vegetation in southern China (18°–30°N). Subsequently, using Gross Primary Productivity (GPP) estimates from flux tower sites as a performance benchmark, we evaluated the ability of these vegetation indices to accurately reflect vegetation GPP changes during drought conditions. Our findings indicate that SIF serves as the most effective surrogate for GPP, capturing the variability of GPP during drought periods with minimal time lag. Additionally, our study reveals that the performance of kNDVI significantly varies depending on the estimation of different kernel parameters. The application of a time-heuristic estimation method could potentially enhance kNDVI’s capacity to capture GPP dynamics more effectively during drought periods. Overall, this study demonstrates that satellite-based SIF data are more adept at monitoring vegetation responses to water stress and accurately tracking GPP anomalies caused by droughts. These findings not only provide critical insights into the selection and optimization of remote sensing vegetation product but also offer a valuable framework for future research aimed at improving our monitoring and understanding of vegetation growth status under climatic changes.
Change Detection Based on Existing Vector Polygons and Up-to-Date Images Using an Attention-Based Multi-Scale ConvTransformer Network
Authors: Wang Shengli , Zhu Yihu , Zheng Nanshan , Liu Wei , Zhang Hua , Zhao Xu , Liu Yongkun
Published: May 2024

Vector polygons represent crucial survey data, serving as a cornerstone of national geographic censuses and forming essential data sources for detecting geographical changes. The timely update of these polygons is vital for governmental decision making and various industrial applications. However, the manual intervention required to update existing vector polygons using up-to-date high-resolution remote sensing (RS) images poses significant challenges and incurs substantial costs. To address this, we propose a novel change detection (CD) method for land cover vector polygons leveraging high-resolution RS images and deep learning techniques. Our approach begins by employing the boundary-preserved masking Simple Linear Iterative Clustering (SLIC) algorithm to segment RS images. Subsequently, an adaptive cropping approach automatically generates an initial sample set, followed by denoising using the efficient Visual Transformer and Class-Constrained Density Peak-Based (EViTCC-DP) method, resulting in a refined training set. Finally, an enhanced attention-based multi-scale ConvTransformer network (AMCT-Net) conducts fine-grained scene classification, integrating change rules and post-processing methods to identify changed vector polygons. Notably, our method stands out by employing an unsupervised approach to denoise the sample set, effectively transforming noisy samples into representative ones without requiring manual labeling, thus ensuring high automation. Experimental results on real datasets demonstrate significant improvements in model accuracy, with accuracy and recall rates reaching 92.08% and 91.34%, respectively, for the Nantong dataset, and 93.51% and 92.92%, respectively, for the Guantan dataset. Moreover, our approach shows great potential in updating existing vector data while effectively mitigating the high costs associated with acquiring training samples.
Formative Period Tracing and Driving Factors Analysis of the Lashagou Landslide Group in Jishishan County, China
Authors: Fan Qianyou , Zhang Shuangcheng , Niu Yufen , Si Jinzhao , Li Xuhao , Wu Wenhui , Zeng Xiaolong , Jiang Jianwen
Published: May 2024

The continuous downward movement exhibited by the Lashagou landslide group in recent years poses a significant threat to the safety of both vehicles and pedestrians traversing the highway G310. By integrating geomorphological interpretation using multi-temporal optical images, interferometric synthetic aperture radar (InSAR) measurements, and continuous global navigation satellite system (GNSS) observations, this paper traced the formation period of the Lashagou landslide group, and explored its kinematic behavior under external drivers such as rainfall and snowmelt. The results indicate that the formation period can be specifically categorized into three periods: before, during, and after the construction of highway G310. The construction of highway G310 is the direct cause and prerequisite for the formation of the Lashagou landslide group, whereas summer precipitation and spring snowmelt are the external driving factors contributing to its continuous downward movement. Additionally, both the long-term seasonal downslope movement and transient acceleration events are strongly controlled by rainfall, and there is a time lag of approximately 1–2 days between the transient acceleration and heavy rainfall events. This study highlights the benefits of leveraging multi-source remote sensing data to investigate slow-moving landslides, which is advantageous for the implementation of effective control and engineering intervention to mitigate potential landslide disasters.
Satellite Advanced Spaceborne Thermal Emission and Reflection Radiometer Mineral Maps of Australia Unmixed of Their Green and Dry Vegetation Components: Implications for Mapping (Paleo) Sediment Erosion–Transport–Deposition Processes
Authors: Cudahy Tom , Cudahy Liam
Published: May 2024

The 2012 satellite ASTER geoscience maps of Australia were designed to provide public, web-accessible, and spatially comprehensive surface mineralogy for improved mapping and solutions to geoscience challenges. However, a number of the 2012 products were clearly compromised by variable green and/or dry vegetation cover. Here, we show a strategy to first estimate and then unmix the contributions of both these vegetation components to leave, as residual, the target surface mineralogy. The success of this unmixing process is validated by (i) visual suppression/removal of the regional climate and/or local fire-scar vegetation patterns; and (ii) pixel values more closely matching field sample data. In this process, we also found that the 2012 spectral indices used to gauge the AlOH content, AlOH composition, and water content can be improved. The updated (new indices and vegetation unmixed) maps reveal new geoscience information, including: (i) regional “wet” and “dry” zones that appear to express “deep” geological characters often expressed through thick regolith cover, with one zone over the Yilgarn Craton spatially anti-correlated with Archaean gold deposits; (ii) a ~1000 km wide circular feature over the Lake Eyre region defined by a rim of abundant “muscovite” that appears to coincide with opal deposits; (iii) a N–S zonation across the western half of the continent defined by abundant muscovite in the south and kaolinite in the north, which appears to reflect opposing E ↔ W aeolian sediment transport directions across the high-pressure belt; (iv) various paleo-drainage networks, including those over aeolian sand covered the “lowlands” of the Canning Basin, which are characterized by low AlOH content, as well as those over eroding “uplands”, such as the Yilgarn Craton, which have complicated compositional patterns; and (v) a chronological history of Miocene barrier shorelines, back-beach lagoons, and alluvial fans across the Eucla Basin, which, to date, had proved elusive to map using other techniques, with potential implications for heavy mineral sand exploration. Here, we explore the latter three issues.
High-Frequency and High-Current Transmission Techniques for Multiple Earth Electrical Characteristic Measurement Systems Based on Adaptive Impedance Matching through Phase Comparison
Authors: Zhang Kuiyuan , Yang Shulin , Wang Meng , Zhang Rongbo
Published: May 2024

With the increase in groundwater exploration, underground mineral resource exploration, and non-destructive investigation of cultural relics, high-resolution earth electrical characteristic measurement has emerged as a mainstream technique owing to its advantageous non-destructive detection capability. To enhance the transmission power of the high-frequency transmitter in high-resolution multiple earth electrical characteristic measurement systems (MECS), this study proposes a high-frequency, high-current transmission technique based on adaptive impedance matching and implemented through the integration of resonant capacitors, a controllable reactor, high-frequency transformers, and corresponding control circuits. A high-current precisely controllable reactor with a 94% inductance variation range was designed and combined with resonant capacitors to reduce circuit impedance. Additionally, high-frequency transformers were employed to further increase the transmission voltage. A prototype was developed and tested, demonstrating an increase in transmission current at frequencies between 10 and 120 kHz with a peak active power of 200 W. Under the same transmission voltage, compared to the transmission circuit without impedance matching, the transmission current increased to a maximum of 16.7 times (average of 10.8 times), whereas compared to the transmission circuit using only traditional impedance matching, the transmission current increased by a maximum of 10.0 times (average of 4.2 times), effectively improving the exploration resolution.
Wireless Underground Sensor Communication Using Acoustic Technology
Authors: Al Moshi Md Adnan , Hardie Marcus , Choudhury Tanveer , Kamruzzaman Joarder
Published: May 2024

The rapid advancement toward smart cities has accelerated the adoption of various Internet of Things (IoT) devices for underground applications, including agriculture, which aims to enhance sustainability by reducing the use of vital resources such as water and maximizing production. On-farm IoT devices with above-ground wireless nodes are vulnerable to damage and data loss due to heavy machinery movement, animal grazing, and pests. To mitigate these risks, wireless Underground Sensor Networks (WUSNs) are proposed, where devices are buried underground. However, implementing WUSNs faces challenges due to soil heterogeneity and the need for low-power, small-size, and long-range communication technology. While existing radio frequency (RF)-based solutions are impeded by substantial signal attenuation and low coverage, acoustic wave-based WUSNs have the potential to overcome these impediments. This paper is the first attempt to review acoustic propagation models to discern a suitable model for the advancement of acoustic WUSNs tailored to the agricultural context. Our findings indicate the Kelvin–Voigt model as a suitable framework for estimating signal attenuation, which has been verified through alignment with documented outcomes from experimental studies conducted in agricultural settings. By leveraging data from various soil types, this research underscores the feasibility of acoustic signal-based WUSNs.
Evaluating the Non-Invasive Measurement of Apple Aroma Using Electronic Nose Device through Comparison with Direct Mass Spectrometry, Sugar Content, and Ripeness Measurements
Authors: Fujioka Kouki
Published: May 2024

To compare apple aroma intensities, apples were analyzed from the calyx side (on the opposite side of the stem) using an electronic nose (e-nose) sensor device and direct mass spectrometry. The results indicated that the sensor value tended to increase in accordance with the total intensity of apple aroma components measured by direct mass spectrometry. In addition, the e-nose sensor values for apple aroma did not correlate with the sugar content and ripeness measurements using optical sensors. Moreover, the relative standard deviations of repeatability and intermediate precision in the measurement of apple flavor (apple lip balm) were within 1.36–9.96%. Similar to the utilization of sugar content and ripeness values, the aroma measured from the calyx side can be potentially used for apple evaluation.
Accurate Range Modeling for High-Resolution Spaceborne Synthetic Aperture Radar
Authors: Li Haisheng , An Junshe , Jiang Xiujie
Published: May 2024

Spaceborne synthetic aperture radar (SAR) is an advanced microwave imaging technology that provides all-weather and all-day target information. However, as spaceborne SAR resolution improves, traditional echo signal models based on airborne SAR design become inadequate due to the curved orbit, Earth rotation, and increased propagation distance. In this study, we propose an accurate range model for high-resolution spaceborne SAR by analyzing motion trajectory and Doppler parameters from the perspective of the space geometry of spaceborne SAR. We evaluate the accuracy of existing range models and propose an advanced equivalent squint range model (AESRM) that accurately fits the actual range history and compensates for high-order term errors by introducing third-order and fourth-order error terms while maintaining the simplicity of the traditional model. The proposed AESRM’s concise two-dimensional frequency spectrum form facilitates the design of imaging algorithms. Point target simulations confirm the effectiveness of the proposed AESRM, demonstrating significant improvements in fitting accuracy for range histories characterized by nonlinear trajectories. The developed AESRM provides a robust foundation for designing imaging algorithms and enables higher resolution and more accurate radar imaging.
Human Motion Enhancement and Restoration via Unconstrained Human Structure Learning
Authors: He Tianjia , Yang Tianyuan , Konomi Shin’ichi
Published: May 2024

Human motion capture technology, which leverages sensors to track the movement trajectories of key skeleton points, has been progressively transitioning from industrial applications to broader civilian applications in recent years. It finds extensive use in fields such as game development, digital human modeling, and sport science. However, the affordability of these sensors often compromises the accuracy of motion data. Low-cost motion capture methods often lead to errors in the captured motion data. We introduce a novel approach for human motion reconstruction and enhancement using spatio-temporal attention-based graph convolutional networks (ST-ATGCNs), which efficiently learn the human skeleton structure and the motion logic without requiring prior human kinematic knowledge. This method enables unsupervised motion data restoration and significantly reduces the costs associated with obtaining precise motion capture data. Our experiments, conducted on two extensive motion datasets and with real motion capture sensors such as the SONY (Tokyo, Japan) mocopi, demonstrate the method’s effectiveness in enhancing the quality of low-precision motion capture data. The experiments indicate the ST-ATGCN’s potential to improve both the accessibility and accuracy of motion capture technology.
Characterization of the SPIRITAS: A Disposable Sampling Setup for Volatile Organic Compound Collection and Analysis
Authors: Mager David J. , van Dijk Yoni E. , Varan Özgü , Vijverberg Susanne J. H. , Terheggen-Lagro Suzanne W. J. , Maitland-van der Zee Anke-Hilse , Janssens Hettie M. , Brinkman Paul
Published: May 2024

Analyzing exhaled breath for volatile organic compounds (VOCs) using thermal desorption–gas chromatography–mass spectrometry (TD-GC-MS) offers a non-invasive diagnostic approach for various diseases. Despite its promise, the method faces challenges like sampling heterogeneity and high costs. Following the European Respiratory Society’s advocacy for methodological standardization, we developed the SPIRITAS (Standardized Product for Inexpensive Respiratory InvesTigation: A breath Sampler), a low-cost, disposable breath sampler. This study evaluates the SPIRITAS’s effectiveness in detecting targeted VOCs. We tested the SPIRITAS using the Peppermint Experiment, a standardized protocol that allows for comparison between different breath sampling and analytical practices by assessing the ability to detect five peppermint-specific VOCs after ingestion of a 200-milligram peppermint oil capsule. We included ten subjects and performed six breath samples per participant, including a baseline measurement taken before ingestion. We used the Wilcoxon signed-rank test to evaluate whether baseline values were significantly lower than the peak values of the targeted VOCs. Additionally, we conducted an experiment utilizing humidified medical-grade air to identify any VOCs attributable to the SPIRITAS setup itself. Results showed successful detection of four out of five targeted “peppermint-associated” VOCs: alpha-pinene (p ≤ 0.01), beta-pinene (p ≤ 0.01), menthone (p = 0.01), and menthol (p = 0.02), indicating significant differences between the baseline and peak values in the volunteers’ breath. However, detection of eucalyptol was inconsistent. In addition, we identified 16 VOCs that were released by the SPIRITAS, one of which remains unidentified. Our findings underscore the SPIRITAS’s potential for clinical applications, paving the way for broader biomarker research. The combination of ease of use, low cost, reduced risk of contamination, and standardization makes SPIRITAS very suitable for large-scale international studies. Furthermore, we have demonstrated the SPIRITAS’s effectiveness in detecting specific VOCs and identified 16 compounds originating from the SPIRITAS, ensuring that these compounds would not be mis-qualified as potential biomarkers in future clinical studies.
Using the Blockchain to Reduce Carbon Emissions in the Visitor Economy
Authors: Goean Eduard Romulus , Font Xavier , Xiong Yu , Becken Susanne , Chenoweth Jonathan L. , Fioramonti Lorenzo , Higham James , Jaiswal Amit Kumar , Sadhukhan Jhuma , Sun Ya-Yen , Treiblmaier Horst , Xia Senmao , Zhou Xun
Published: May 2024

The visitor economy is responsible for a substantial percentage of the global carbon footprint. The mechanisms used to decarbonize it are insufficient, and the industry is relying on carbon trading with substandard credits that allow businesses to outsource the responsibility to decarbonize. We aim to transform carbon markets, help finance climate investments, and support decarbonization strategies. We identify and define the problem, outline the components and their interactions, and develop a conceptual model to transform carbon markets. The new, blockchain-based Carbon Tokenomics Model rolls out a decentralized database to store, trade, and manage carbon credits, with the goal of enabling sustainable climate finance investment. We outline the criteria needed for an industry-wide carbon calculator. We explain the process needed to increase rigor in climate investments in the visitor economy and introduce a delegated Proof of Commitment consensus mechanism. Our inclusive and transparent model illustrates how to reduce transaction costs and how to build consumer and industry trust, generating much-needed investments for decarbonization.
Augmented Reality and Wearable Technology for Cultural Heritage Preservation
Authors: Ibiş Ali , Çakici Alp Neşe
Published: May 2024

The main goal of this study is to provide a more interactive experience with AR technology and wearable devices compared to traditional preservation methods in order to protect, promote, and transfer cultural heritage to future generations. It aims to evaluate the usability of the developed AR application with SUS and WARUS analyses. During the research process, similar studies were conducted, street texture and historical buildings were examined, 3D models were created with terrestrial laser scanning, and an AR application was developed with the Unity3D program and presented for user evaluation. The findings of this research show that users can access historical and cultural information interactively, and that presenting historical places interactively contributes to conservation efforts by allowing users to gain more in-depth information. In the discussion section of this paper, the opportunities and limitations offered by AR technology and the wearable device through the ARKON application are discussed in a sustainable way in terms of usability. According to the research results, while usability analyses showed that user satisfaction was high, no significant difference was observed according to gender in the similar age group.
The Impact of the Carbon Emission Trading Shadow Price on the Green Total Factor Productivity of the Power Industry in China
Authors: Zhang Longtian , Pan Zheng
Published: May 2024

To mitigate the problem of global climate change, governments have taken measures to reduce greenhouse gas emissions. Carbon emission trading has gradually attracted attention as a market-oriented option. Power industry panel data from 30 provinces in China were used for an empirical analysis in this study. The super-efficiency Slack-Based Measure (SBM) model was used to calculate the shadow price of carbon trading and the green total factor productivity (GTFP), and the Ordinary Least Squares (OLS) regression model was used to quantitatively analyze the correlation between the shadow price of carbon trading and the GTFP of the power industry. The results showed that the shadow price of carbon trading had a significantly negative impact on the GTFP of the power industry; therefore, it needs to be improved and perfected. Through a further analysis using the heterogeneity test, it was found that there were problems in the current carbon trading price mechanism. In the face of the above problems, we offer suggestions for improvement from the perspectives of the government and companies. This study helps deepen the understanding of carbon trading prices and the GTFP in the power industry, and it provides a reference for formulating more effective carbon trading policies and corporate green management strategies.
A Study on the Impact of Enterprise Digital Evolution on Outward Foreign Investments
Authors: Yang Xinhua , Gan Haimei , Luo Shuai , Lv Jingjing
Published: May 2024

In the age of the digital economy, digital evolution has emerged as a central focus in academic research. The achievement is of paramount importance for augmenting their international investments. This research utilizes data from publicly listed manufacturing firms in China from 2010 to 2021 to examine the influence of enterprise digital evolution on outbound foreign investments. The research findings reveal that enterprise digital evolution has a significant positive impact on the outward foreign investments of enterprises and exhibits heterogeneity in terms of region, company size, and industry type. Mechanism tests reveal that the impact of enterprise digital evolution on outward foreign investments can be realized through four pathways: enhancing ESG performance, reducing debt financing costs (COD1) (representing the proportion of interest costs to the total of long and short-term debts), company age, and debt financing costs (COD2) (denoting the proportion of financial expenses to the total of long and short-term debts). In the context of digitization, enterprise digital evolution continues to hold positive significance for outward foreign investments, contributing to the enrichment of the theoretical research on the subject to a certain extent.
Taking Charge of One’s Own Safety While Collaborating with Robots: Enhancing Situational Awareness for a Safe Environment
Authors: San Martin Ane , Kildal Johan , Lazkano Elena
Published: May 2024

Collaborative robots, designed to work alongside humans in industrial manufacturing, are becoming increasingly prevalent. These robots typically monitor their distance from workers and slow down or stop when safety thresholds are breached. However, this results in reduced task execution performance and safety-related uncertainty for the worker. To address these issues, we propose an alternative safety strategy, where the worker is responsible for their own safety and the robot executes its task without modifying its speed except in the case of imminent contact with the worker. The robot provides precise situation-awareness information to the worker using a mixed-reality display, presenting information about relative distance and movement intentions. The worker is then responsible for placing themselves with respect to the robot. A user study was conducted to evaluate the efficiency of task execution, worker safety, and user experience. Results suggest a good user experience and safety perception while maintaining worker safety, which would support social sustainability of human activities in industrial production contexts that require collaboration with robots.
Low-Carbon Economic Dispatch of Virtual Power Plants Considering the Combined Operation of Oxygen-Enriched Combustion and Power-to-Ammonia
Authors: He Jun , Mao Zimu , Huang Wentao , Zhang Bohan , Xiao Jianbo , Zhang Zuoming , Liu Xinyu
Published: May 2024

In order to achieve sustainable development, China has proposed to “strive to peak carbon dioxide emissions by 2030 and strive to achieve carbon neutrality by 2060”. Virtual power plants (VPPs) are an effective means to achieve carbon neutrality goals. In order to improve the economy and low-carbon performance of virtual power plants, this paper proposes a low-carbon economic optimization dispatching model considering the combined operation of oxygen-enriched combustion (OEC) and electricity-to-ammonia (P2A). Firstly, the mechanism of the combined operation of OEC and P2A is proposed. The oxygen-enriched combustion technology can reduce the carbon emissions of the system and enhance the flexibility of the system operation; P2A can effectively consume renewable energy and improve the energy utilization rate. The by-product of the P2A process, oxygen, is the raw material needed for oxygen-enriched combustion, which reflects the complementary nature of the OEC and P2A.Then, an optimal dispatching model is established with the objective function of minimizing the total cost. Finally, the validity of the proposed model is verified by comparing and analyzing the simulation results of five different models. After the introduction of the combined operation of OEC and P2A, the total cost of the system decreases by 10.95%, and the carbon emission decreases by 34.79%.
Wholesale Price Contract or Mixed Wholesale-Option-Contract? Procurement Strategy for a Contract Farming Supply Chain under Flexible Supply
Authors: Hu Shengqiang , Liu Lou , Liu Xing
Published: May 2024

Due to the uncertainty of world economic development, market demands are stochastic and the supply quantities of suppliers in the supply chain are always flexible, so a mixed wholesale-option-contract (abbreviated as a mixed contract) is one of the good ways for commodity distributors to cope with flexible supply. For a contract farming supply chain composed of a distributor and two suppliers under random demand and yield, we propose the new mixed contracts with flexible supply for the players to make better procurement and inventory decisions. Therefore, with decentralized decision making with a wholesale price contract and centralized decision making as benchmarks for comparison, the advantages of mixed contracts were demonstrated in this paper. The expected profit function under each transaction mode was proved to be concave and the optimal orders or production quantities were obtained and compared. Theoretical derivation and numerical examples were carried out and the main conclusions are as follows. First, the distributor’s total order quantities are the largest under centralized decision making, then the second largest under mixed contracts, then the least under wholesale price contracts. Second, for the dealer under mixed contracts, within the feasible range, the smaller the option price (or option exercise price) is, the greater the dealer’s profit is. Third, with increasing initial order quantity, the gap between the dealer’s profits under different option prices (or option exercise prices) narrows, and eventually tends to the same point. For both the suppliers as a whole, a mixed contract is better than the wholesale price one. Fourth, when the prices of the option contract change within a reasonable range (they may not be too small or too large), the profits of both the dealer and suppliers under a mixed contract are not only higher than those under the wholesale price contract, but also higher than those under centralized decision making. Finally, policies and suggestions (such as full investigation, explicitly defining the process of contracts, establishing real-time supervision and information sharing mechanisms, and so on) were put forward to improve the accuracy of supply and demand forecasting, better implement mixed contracts under flexible supply, and strengthen reforms about agricultural supply side.
A Study on a Health Impact Assessment and Healthcare Cost Calculation of Beijing–Tianjin–Hebei Residents under PM2.5 and O3 Pollution
Authors: Hu Yanyong , Chao Kun , Zhu Zhujun , Yue Jiaqi , Qie Xiaotong , Wang Meijia
Published: May 2024

Excessive fine particulate matter (PM2.5) and ozone (O3) are invisible killers affecting our wellbeing and safety, which cause great harm to people’s health, cause serious healthcare and economic losses, and affect the sustainable development of the social economy. The effective evaluation of the impact of pollutants on the human body, the associated costs, and the reduction of regional compound air pollution is an important research direction. Taking Beijing–Tianjin–Hebei (BTH) as the research area, this study constructs a comprehensive model for measuring the healthcare costs of PM2.5 and O3 using the Environmental Benefits Mapping and Analysis Program (BenMAP) as its basis. First, this study establishes a health impact assessment model and calculates the number of people affected by PM2.5 and O3 exposure using the health impact function in the BTH region. Then, the willingness to pay (WTP) and cost of illness (COI) methods are used to estimate the healthcare costs inflicted by the two pollutants upon residents from 2018 to 2021. The calculation results show that the total healthcare costs caused by PM2.5 and O3 pollution in BTH accounted for 1%, 0.7%, 0.5%, and 0.3% of the regional GDP in 2018, 2019, 2020, and 2021, respectively. Based on the research results, to further reduce these high healthcare costs, we propose policy suggestions for PM2.5 and O3 control in the BTH region.
Integrated Adaptation Strategies for Human–Leopard Cat Coexistence Management in Taiwan
Authors: Nguyen Linh Bao , Chen Hsing-Chih , Seekings Timothy Bernd Wallace , Dhungana Nabin , Chen Chi-Cheng , Lee Chun-Hung
Published: May 2024

In Taiwan, the leopard cat (Prionailurus bengalensis chinensis) remains the only extant native wild cat species. Previous studies have suggested anthropogenic factors as a cause of their decline, mainly due to conflicts with local farmers. Adaptation strategies that generate co-benefits are key to achieving human–wildlife coexistence. However, an understanding of the local views on such strategies is currently lacking. In this study, we performed the first regional assessment of 10 adaptation strategies for human–leopard cat coexistence and examined the impact of the socio-demographic factors affecting farmers’ willingness to participate in these strategies based on quantitative interviews with 418 farmers in Miaoli County, employing an importance–performance analysis. We also present an integrated conceptual framework capturing five adaptation strategy domains and their resulting benefits, which lay the structural foundation for facilitating resilient coexistence. Our findings suggest that (1) respondents’ perceived importance and performance of adaptation strategies were significantly different; (2) respondents most agreed with improvements in the incorporation of local knowledge/skills into science and policy and the establishment of adaptive co-management with local associations/non-governmental organisations; and (3) respondents aged below 49 years, supportive of coexistence, who did not own poultry, and preferred local farmer organisations to facilitate coexistence, were more likely to participate in the proposed adaptation strategies. Our findings provide guidelines for the future direction of the conservation and management of leopard cats that help achieve harmonious coexistence in shared landscapes.
A Cloud- and Game Model-Based Approach to Project Evaluations of Sustainable Power Supply Investments
Authors: Lin Kuoyi , Li Bin
Published: May 2024

In light of electrical energy’s increasing role in economic systems worldwide, prioritizing investments in sustainable power supplies has become paramount. This study proposes a model based on cloud theory and game theory to evaluate sustainable power supply investment projects. It establishes a foundation for assessing the merits of power supply investments, which are crucial for continuous electricity provision and economic advancement. By integrating an enhanced analytic hierarchy process and the entropy method, the study develops a dual-weighted evaluative index system. This hybrid approach addresses ambiguities and enhances the weight determination accuracy, which, when applied to the Liaojiawan Transformer Substation, verifies the project’s high benefit level, corroborated by empirical data. This innovative methodology offers a strategic framework for future power supply investments.