bluuebunny/crossref_metadata_2025 huggingface dataset:
“New Creation:” Grace and Experiences of a Renewed Nature
Authors: Wolfe Kyril
Published: August 2024

In everyday life, one encounters many experiences of affliction that, for whatever reason, nature (ours or others’) cannot resolve. Yet, when nature’s finite resources are exhausted and hope seems in vain, humans often experience extra-ordinary moments of renewal and resolution—breakthroughs, remissions, insights, and conversions. We experience these moments in our natural existence; yet, we feel they cannot originate, cannot be attributed to nature alone. Rather, these experiences, called “graces” in Christianity, are attributed to a divine power acting in us. How do we come to describe these experiences in this way? Is it possible to formulate a general theory of these experiences as “graces”? Is there an “experience” of grace in general, a “state of grace”, which serves as ground and unifying experience for the “graces” we receive? Working from the Catholic theological point of view, this paper examines such experiences of affliction and renewal, as well as the basic Catholic framework schematizing them as found in the Bible and Catholic religious writings. In doing so, this paper highlights the theme of impossibility (absolutely or in context) underlying each experience, and broadly categorizes them as happening within three regions of human life: the external, ethical sphere, the interior self-relationship, and the vertical relationship to the Divine. In dialogue with theologians and phenomenological thinkers, general formulations of the experiences are placed within their respective spheres, and certain problems in the identification or interpretation of these experiences are identified. The paper then explores how the experience of a “New Creation” can serve not only as a label for the totality of these experiences, but also as a totalizing and overarching ground-experience of “grace” and an interpretive hermeneutic for graces in general. As a result, a graced moment of total personal “rebirth” or “recreation”, prevenient with respect to any personal co-operation or experiences of grace as grace, is identified as a potential ground for all other graces considered. Finally, this paper considers some potential implications of this account of grace for both Catholic thought and Phenomenology more generally.
The Combined Use of GIS and Generative Artificial Intelligence in Detecting Potential Geodiversity Sites and Promoting Geoheritage
Authors: Wolniewicz Paweł
Published: August 2024

The concept of geosites and geodiversity sites that document selected elements of geodiversity has proved to be extremely useful in the preservation and communication of the abiotic diversity of the Earth. However, the process of the designation, description, evaluation and, finally, promotion of geosites requires a fair amount of effort. This hinders the recognition of geosites and the development of geoparks in many areas that would otherwise benefit from their rich but undervalued abiotic environment. To rectify this, the present study introduces the use of automated geographic information system (GIS) mapping and generative artificial intelligence (GAI) for the designation and promotion of points of geological interest and potential geodiversity sites. When used effectively, these techniques permit the rapid development of geodiversity site inventories and, eventually, their dissemination to the general public and decision-makers. In this study, GAI is employed to produce diverse promotional content, both textual and visual, that facilitates geoscientific communication. A case study of an aspiring geopark located in Poland (Central Europe) is discussed, showing that GAI has the potential to enable the rapid development of easy-to-understand and diverse educational materials, limiting the amount of resources and labour required for the effective promotion of geodiversity.
Experimental Comparison of Two 6D Pose Estimation Algorithms in Robotic Fruit-Picking Tasks
Authors: Alterani Alessio Benito , Costanzo Marco , De Simone Marco , Federico Sara , Natale Ciro
Published: August 2024

This paper presents an experimental comparison between two existing methods representative of two categories of 6D pose estimation algorithms nowadays commonly used in the robotics community. The first category includes purely deep learning methods, while the second one includes hybrid approaches combining learning pipelines and geometric reasoning. The hybrid method considered in this paper is a pipeline of an instance-level deep neural network based on RGB data only and a geometric pose refinement algorithm based on the availability of the depth map and the CAD model of the target object. Such a method can handle objects whose dimensions differ from those of the CAD. The pure learning method considered in this comparison is DenseFusion, a consolidated state-of-the-art pose estimation algorithm selected because it uses the same input data, namely, RGB image and depth map. The comparison is carried out by testing the success rate of fresh food pick-and-place operations. The fruit-picking scenario has been selected for the comparison because it is challenging due to the high variability of object instances in appearance and dimensions. The experiments carried out with apples and limes show that the hybrid method outperforms the pure learning one in terms of accuracy, thus allowing the pick-and-place operation of fruits with a higher success rate. An extensive discussion is also presented to help the robotics community select the category of 6D pose estimation algorithms most suitable to the specific application.
Comparative Study of Seafloor Topography Prediction from Gravity–Geologic Method and Analytical Algorithm
Authors: Tian Yuwei , Xu Huan , Yu Jinhai , Wang Qiuyu , Jia Yongjun , Chen Xin
Published: August 2024

Seafloor topography prediction can fill in sea areas without ship sounding data. However, the dependence of various topographic prediction algorithms on ship soundings varies significantly. Hence, this study explores the impact of the number and distributions of ship soundings on topographic prediction using the gravity–geologic method (GGM) and an analytical algorithm. Firstly, this study investigates the influence of ship sounding coverage on the two algorithms. The simulation results demonstrate that increasing coverage from 5.40% to 31.80%, coupled with more uniform distributions across the study area, substantially reduces the RMS error of the GGM. Specifically, the RMS error decreases from 238.68 m to 42.90 m, an improvement of 82.03%. The analytical algorithm maintains a consistent RMS error of 40.39 m because it does not depend on ship soundings. Furthermore, we select a 1° × 1° sea area (134.8°–135.8°E, 30.0°–31.0°N), and the ship soundings are divided into two control groups, Part I and Part II, with coverages of 8.19% and 33.19%, respectively. When Part II is used for calculation, the RMS error of the GGM decreases from 204.17 m to 126.95 m compared to when Part I is used, while the analytical algorithm exhibits an RMS error of 167.94 m. The findings indicate that the prediction accuracy of the GGM is significantly affected by ship soundings, whereas the analytical algorithm is more stable and independent of ship soundings. Based on simulation experiments and realistic examples, when the effective ship soundings coverage exceeds 30%, the GGM may have more advantages. Conversely, the analytical algorithm may be better. This suggests that effectively combining and utilizing different algorithms based on the ship sounding coverage can improve the accuracy of topographic prediction. This will provide a basis for integrating multiple algorithms to construct a global seafloor topography model.
Exploring Spatial Non-Stationarity and Scale Effects of Natural and Anthropogenic Factors on Net Primary Productivity of Vegetation in the Yellow River Basin
Authors: Wang Xiaolei , He Wenxiang , Huang Yilong , Wu Xing , Zhang Xiang , Zhang Baowei
Published: August 2024

Investigating the spatiotemporal dynamics of vegetation net primary productivity (NPP) and its influencing factors are crucial for green and low-carbon development and facilitate human well-being in the Yellow River Basin (YRB). Although the research on NPP has advanced rapidly, in view of the regional particularity of the YRB, the persistence of its NPP change trend needs to be further discussed and more comprehensive impact factors need to be included in the analysis. Meanwhile, the spatial non-stationarity and scale effects of the impact on NPP when multiple factors are involved remain uncertain. Here, we selected a total of twelve natural and anthropogenic factors and used multi-scale geographically weighted regression (MGWR) to disentangle the spatial non-stationary relationship between vegetation NPP and related factors and identify the impact scale difference in the YRB. Additionally, we analyze the spatiotemporal variation trend and persistence of NPP during 2000–2020. The results revealed the following: (1) The annual NPP showed a fluctuating increasing trend, and the vegetation NPP in most regions will exhibit a future trend of increasing to decreasing. (2) The effects of different factors show significant spatial non-stationarity. Among them, the intensity of the impact of most natural factors shows a clear strip-shaped distribution in the east-west direction. It is closely related to the spatial distribution characteristics of natural factors in the YRB. In contrast, the regularity of anthropogenic influences is less obvious. (3) The impact scales of different factors on vegetation NPP were significantly different, and this scale changed with time. The factors with small impact scales could better explain the change in vegetation NPP. Interestingly, the impact size and scale of relative humidity on NPP in the YRB are both larger. This may be due to the arid and semi-arid characteristics of the YRB. Our findings could provide policy makers with specific and quantitative insights for protecting the ecological environment in the YRB.
Exploring Factors Affecting the Performance of Neural Network Algorithm for Detecting Clouds, Snow, and Lakes in Sentinel-2 Images
Authors: Huang Kaihong , Sun Zhangli , Xiong Yi , Tu Lin , Yang Chenxi , Wang Hangtong
Published: August 2024

Detecting clouds, snow, and lakes in remote sensing images is vital due to their propensity to obscure underlying surface information and hinder data extraction. In this study, we utilize Sentinel-2 images to implement a two-stage random forest (RF) algorithm for image labeling and delve into the factors influencing neural network performance across six aspects: model architecture, encoder, learning rate adjustment strategy, loss function, input image size, and different band combinations. Our findings indicate the Feature Pyramid Network (FPN) achieved the highest MIoU of 87.14%. The multi-head self-attention mechanism was less effective compared to convolutional methods for feature extraction with small datasets. Incorporating residual connections into convolutional blocks notably enhanced performance. Additionally, employing false-color images (bands 12-3-2) yielded a 4.86% improvement in MIoU compared to true-color images (bands 4-3-2). Notably, variations in model architecture, encoder structure, and input band combination had a substantial impact on performance, with parameter variations resulting in MIoU differences exceeding 5%. These results provide a reference for high-precision segmentation of clouds, snow, and lakes and offer valuable insights for applying deep learning techniques to the high-precision extraction of information from remote sensing images, thereby advancing research in deep neural networks for semantic segmentation.
Acquisition of Bathymetry for Inland Shallow and Ultra-Shallow Water Bodies Using PlanetScope Satellite Imagery
Authors: Kulbacki Aleksander , Lubczonek Jacek , Zaniewicz Grzegorz
Published: August 2024

This study is structured to address the problem of mapping the bottom of shallow and ultra-shallow inland water bodies using high-resolution satellite imagery. These environments, with their diverse distribution of optically relevant components, pose a challenge to traditional mapping methods. The study was conducted on several research issues, each focusing on a specific aspect of the SDB, related to the selection of spectral bands and regression models, regression models creation, evaluation of the influence of the number and spatial distribution of reference soundings, and assessment of the quality of the bathymetric surface, with a focus on microtopography. The study utilized basic empirical techniques, incorporating high-precision reference data acquired via an unmanned surface vessel (USV) integrated with a single-beam echosounder (SBES), and Global Navigation Satellite System (GNSS) receiver measurements. The performed investigation allowed the optimization of a methodology for bathymetry acquisition of such areas by identifying the impact of individual processing components. The first results indicated the usefulness of the proposed approach, which can be confirmed by the values of the obtained RMS errors of elaborated bathymetric surfaces in the range of up to several centimeters in some study cases. The work also points to the problematic nature of this type of study, which can contribute to further research into the application of remote sensing techniques for bathymetry, especially during acquisition in optically complex waters.
Soil Organic Carbon Estimation via Remote Sensing and Machine Learning Techniques: Global Topic Modeling and Research Trend Exploration
Authors: Li Tong , Cui Lizhen , Wu Yu , McLaren Timothy I. , Xia Anquan , Pandey Rajiv , Liu Hongdou , Wang Weijin , Xu Zhihong , Song Xiufang , Dalal Ram C. , Dang Yash P.
Published: August 2024

Understanding and monitoring soil organic carbon (SOC) stocks is crucial for ecosystem carbon cycling, services, and addressing global environmental challenges. This study employs the BERTopic model and bibliometric trend analysis exploration to comprehensively analyze global SOC estimates. BERTopic, a topic modeling technique based on BERT (bidirectional encoder representatives from transformers), integrates recent advances in natural language processing. The research analyzed 1761 papers on SOC and remote sensing (RS), in addition to 490 related papers on machine learning (ML) techniques. BERTopic modeling identified nine research themes for SOC estimation using RS, emphasizing spectral prediction models, carbon cycle dynamics, and agricultural impacts on SOC. In contrast, for the literature on RS and ML it identified five thematic clusters: spatial forestry analysis, hyperspectral soil analysis, agricultural deep learning, the multitemporal imaging of farmland SOC, and RS platforms (Sentinel-2 and synthetic aperture radar, SAR). From 1991 to 2023, research on SOC estimation using RS and ML has evolved from basic mapping to topics like carbon sequestration and modeling with Sentinel-2A and big data. In summary, this study traces the historical growth and thematic evolution of SOC research, identifying synergies between RS and ML and focusing on SOC estimation with advanced ML techniques. These findings are critical to global ecosystem SOC assessments and environmental policy formulation.
Effect of Primary Cable Position on Accuracy in Non-Toroidal-Shaped Pass-Through Current Transformer
Authors: Guerrero José M. , Platero Carlos A. , Blázquez Francisco , Sánchez José A.
Published: August 2024

Non-toroidal-shaped primary pass-through protection current transformers (CTs) are used to measure high currents. Their design provides them with a big airgap that allow the passing of several cables per phase though them, which is the main advantage versus toroidal types, as the number of CTs required to measure the whole phase current is drastically reduced. The cables passed through the transformer window can be in several positions. As the isolines of the magnetic field generated by the primary currents are centered in the cables, if these cables are not centered in the transformer window, then the magnetic field will be non-uniform along the transformer core. Consequently, local saturations can appear if the cables are not properly disposed, causing the malfunction of the CT. In this paper, the performance of a non-toroidal-shaped protection CT is studied. This research is focused on the influence of the cable position on possible partial saturations of the CT when it is operating near to its accuracy limit. Depending on the cable position, the ratio of the primary and secondary currents can depart from the assigned ratio. The validation of this phenomenon was carried out via finite element analysis (FEA), showing that partial transformer core saturations appear in areas of the magnetic core close to the cable. By applying FEA, the admissible accuracy region for cable positioning inside the CT is also delimited. Finally, the simulation results are ratified with experimental tests performed in non-toroidal protection CTs, varying the primary cables’ positions, which are subjected to currents up to 5 kA, achieving satisfactory results. From this analysis, installation recommendations are given.
Cable Eccentricity Detection Method Based on Magnetic Field
Authors: Liu Yuandi , Wei Pengxuan , Zhang Yinghong
Published: August 2024

Amid the rapid advancement of electronic information technology, the need for cable eccentricity measurement in the industry is increasing both in China and across the globe. Current detection methods have several flaws, including high costs, insufficient accuracy, and instability. In this paper, we introduce a magnetic field-based detection method for cable eccentricity that provides high precision and cost-effectiveness. We position three pairs of magnetic field-collection modules in a circular array to gather magnetic flux density information induced by the electrified cable. We apply the law of electromagnetic induction to calculate the cable eccentricity. Our method is non-contact, preserving the cable’s integrity. Our method outperforms traditional detection methods, not only in achieving greater accuracy and stability but also in significantly lowering the detection cost. Simulations and experiments show that our method’s error rate under specified conditions is 0~4%, with a maximum standard deviation of 0.11, confirming its precision and stability in detecting cable eccentricity. The effectiveness of our method is influenced by two factors: lift-off value and loading current intensity. Our method presents a novel concept and a dependable strategy for the progress of cable eccentricity-detection technology.
Research on Mobile Network Parameters Using Unmanned Aerial Vehicles
Authors: Warczek Jan , Kozuba Jarosław , Marcisz Marek , Pamuła Wiesław , Dyl Krzysztof
Published: August 2024

The study of phenomena related to the propagation of electromagnetic waves is a necessity with the development of mobile telephony networks. This paper deals with the problem of the quality of mobile telephony signals. The study uses a BTS scanner, dedicated to scanning the frequency spectrum and decoding information from base stations. The device is capable of scanning mobile networks from the second, third, fourth, and fifth generation (2G/3G/4G/5G) using a passive sensor. The article presents preliminary results of monitoring cellular network signals using a scanner mounted on an unmanned aircraft. The collected data call for the need to evaluate the signal parameters of the cellular network depending on the altitude of signal reception. This property emerges as very important in the case of areas with a high level of urbanization.
Development of Simplified Methods for Levitation Force Distribution in Maglev Vehicles Using Frequency Ratio Tests
Authors: Ji Wen , Ma Weihua , Luo Shihui , Zeng Guofeng , Ye Feng , Liu Mingbo
Published: August 2024

Maglev vehicles apply the entire vehicle load uniformly onto bridges through levitation forces. In assessing the dynamic characteristics of the maglev train–bridge coupling system, it is reasonable to simplify the distributed levitation force as a concentrated force. This article theoretically derives the analytical response of bridge dynamics under the action of a single constant force and conducts numerical simulations for a moving single constant force and a series of equally spaced constant forces passing over simply supported beams and two-span continuous beams, respectively. The topic of discussion is the response of bridge dynamics when different degrees of force concentration are involved. High-precision displacement and acceleration sensors were utilized to conduct tests on the Shanghai maglev line to verify the accuracy of the simulation results. The results indicate that when simplifying the distributed levitation force into a concentrated force model, a frequency ratio can be used to analyze the conditions for resonance between the train and the bridge and to calculate the critical speed of the train; the levitation distribution force of a high-speed maglev vehicle can be simplified into four groups of concentrated forces based on the number of levitation frames to achieve sufficient accuracy, with the dynamic response of the bridge being close to that under distributed loads.
Detecting and Mitigating Attacks on GPS Devices
Authors: Burbank Jack , Greene Trevor , Kaabouch Naima
Published: August 2024

Modern systems and devices, including unmanned aerial systems (UASs), autonomous vehicles, and other unmanned and autonomous systems, commonly rely on the Global Positioning System (GPS) for positioning, navigation, and timing (PNT). Cellular mobile devices rely on GPS for PNT and location-based services. Many of these systems cannot function correctly without GPS; however, GPS signals are susceptible to a wide variety of signal-related disruptions and cyberattacks. GPS threat detection and mitigation have received significant attention recently. There are many surveys and systematic reviews in the literature related to GPS security; however, many existing reviews only briefly discuss GPS security within a larger discussion of cybersecurity. Other reviews focus on niche topics related to GPS security. There are no existing comprehensive reviews of GPS security issues in the literature. This paper fills that gap by providing a comprehensive treatment of GPS security, with an emphasis on UAS applications. This paper provides an overview of the threats to GPS and the state-of-the-art techniques for attack detection and countermeasures. Detection and mitigation approaches are categorized, and the strengths and weaknesses of existing approaches are identified. This paper also provides a comprehensive overview of the state-of-the-art on alternative positioning and navigation techniques in GPS-disrupted environments, discussing the strengths and weaknesses of existing approaches. Finally, this paper identifies gaps in existing research and future research directions.
Analysis of Gait Kinematics in Smart Walker-Assisted Locomotion in Immersive Virtual Reality Scenario
Authors: Loureiro Matheus , Elias Arlindo , Machado Fabiana , Bezerra Marcio , Zimerer Carla , Mello Ricardo , Frizera Anselmo
Published: August 2024

The decline in neuromusculoskeletal capabilities of older adults can affect motor control, independence, and locomotion. Because the elderly population is increasing worldwide, assisting independent mobility and improving rehabilitation therapies has become a priority. The combination of rehabilitation robotic devices and virtual reality (VR) tools can be used in gait training to improve clinical outcomes, motivation, and treatment adherence. Nevertheless, VR tools may be associated with cybersickness and changes in gait kinematics. This paper analyzes the gait parameters of fourteen elderly participants across three experimental tasks: free walking (FW), smart walker-assisted gait (AW), and smart walker-assisted gait combined with VR assistance (VRAW). The kinematic parameters of both lower limbs were captured by a 3D wearable motion capture system. This research aims at assessing the kinematic adaptations when using a smart walker and how the integration between this robotic device and the VR tool can influence such adaptations. Additionally, cybersickness symptoms were investigated using a questionnaire for virtual rehabilitation systems after the VRAW task. The experimental data indicate significant differences between FW and both AW and VRAW. Specifically, there was an overall reduction in sagittal motion of 16%, 25%, and 38% in the hip, knee, and ankle, respectively, for both AW and VRAW compared to FW. However, no significant differences between the AW and VRAW kinematic parameters and no adverse symptoms related to VR were identified. These results indicate that VR technology can be used in walker-assisted gait rehabilitation without compromising kinematic performance and presenting potential benefits related to motivation and treatment adherence.
Energy Consumption Minimization with SNR Constraint for Wireless Powered Communication Networks
Authors: Shih Kuei-Ping , Tsai Yu-Sheng , Chen Yen-Da , Wang San-Yuan
Published: August 2024

The article addresses the energy consumption minimization problem in wireless powered communication networks (WPCNs) and proposes a time allocation scheme, named DaTA, which is based on the Different Target Simultaneous Wireless Information and Power Transfer (DT-SWIPT) scheme such that the wireless station can share the remaining energy after transmission to the Hybrid Access Point (HAP) to those who have not transmitted to the HAP to minimize the energy consumption of the WPCN. In addition to proposing a new frame structure, the article also considers the Signal-to-Noise (SNR) constraint to guarantee that the HAP can successfully receive data from wireless stations. In the article, the problem of minimization of energy consumption is formulated as a nonlinear programming model. We employ the SQP (Sequential Quadratic Programming) algorithm to figure out the optimal solution. Moreover, a heuristic method is proposed as well to obtain a near-optimal solution in a shorter time. The simulation results showed that the proposed scheme outperforms the related work in terms of energy consumption and energy efficiency.
Multi-Sensory Tool Holder for Process Force Monitoring and Chatter Detection in Milling
Authors: Schuster Alexander , Otto Andreas , Rentzsch Hendrik , Ihlenfeldt Steffen
Published: August 2024

Sensor-based monitoring of process and tool condition in milling is a key technology for improving productivity and workpiece quality, as well as enabling automation of machine tools. However, industrial implementation of such monitoring systems remains a difficult task, since they require high sensitivity and minimal impact on CNC machines and cutting conditions. This paper presents a novel multi-sensory tool holder for measurement of process forces and vibrations in direct proximity to the cutting tool. In particular, the sensor system has an integrated temperature sensor, a triaxial accelerometer and strain gauges for measurement of axial force and bending moment. It is equipped with a self-sufficient electric generator and wireless data transmission, allowing for a tool holder design without interfering contours. Milling and drilling experiments with varying cutting parameters are conducted. The measurement data are analyzed, pre-processed and verified with reference signals. Furthermore, the suitability of all integrated sensors for detection of dynamic instabilities (chatter) is investigated, showing that bending moment and tangential acceleration signals are the most sensitive regarding this monitoring task.
Photobleaching Effect on the Sensitivity Calibration at 638 nm of a Phosphorus-Doped Single-Mode Optical Fiber Dosimeter
Authors: Fricano Fiammetta , Morana Adriana , Roche Martin , Facchini Alberto , Mélin Gilles , Clément Florence , Balcon Nicolas , Mekki Julien , Marin Emmanuel , Ouerdane Youcef , Boukenter Aziz , Robin Thierry , Girard Sylvain
Published: August 2024

We investigated the influence of the photobleaching (PB) effect on the dosimetry performances of a phosphosilicate single-mode optical fiber (core diameter of 6.6 µm) operated at 638 nm, within the framework of the LUMINA project. Different irradiation tests were performed under ~40 keV mean energy fluence X-rays at a 530 µ Gy(SiO2)/s dose rate to measure in situ the radiation-induced attenuation (RIA) growth and decay kinetics while injecting a 638 nm laser diode source with powers varying from 500 nW to 1 mW. For injected continuous power values under 1 µW, we did not measure any relevant influence of the photobleaching effect on the fiber radiation sensitivity coefficient of ~140 dB km−1 Gy−1 up to ~30 Gy. Above 1 µW, the fiber radiation sensitivity is significantly reduced due to the PB associated with the signal and can decrease to ~80 dB km−1 Gy−1 at 1 mW, strongly affecting the capability of this fiber to serve as a dosimeter-sensitive element. Higher power values up to 50 µW can still be used by properly choosing a pulsed regime with periodic injection cycles to reduce the PB efficiency and maintain the dosimetry properties. Basing on the acquired data, a simple model of the photobleaching effect on a coil of the investigated fiber is proposed in order to estimate its sensitivity coefficient evolution as a function of the cumulated dose and its fiber length when injecting a certain laser power. Additional studies need to investigate the influence of the temperature and the dose rate on the PB effects since these parameters were fixed during all the reported acquisitions.
Analyzing the Impact of Metaverse Technology on Social Development: A Field Study on Generation Z in the United Arab Emirates
Authors: Youssef Enaam , Medhat Mervat , Abdellatif Soumaya , Babiker Yousif Nagwa
Published: August 2024

Considering the current role of technology, this research aims to investigate the impact of the metaverse on social development and psychological well-being in the United Arab Emirates (UAE). The focus remains on Generation Z, as an important portion of the country’s metaverse users. Supported by the technology determinism theory, this research used a structured questionnaire to gather data from 363 respondents. The analysis indicates that metaverse technology significantly impacts social development and psychological well-being. The effect of metaverse technology on social development remained positive, with the p-value at p > 0.000. In addition, metaverse technology also has a significant positive effect on psychological well-being (p > 0.000), with the findings showing strong statistical support for this relationship. These results confirm that metaverse technology plays a significant role in improving both social and psychological facets. Thus, it is concluded that the metaverse creates immersive virtual environments that help unique forms of social interaction and connectivity, confounding geographical barriers. This can improve social skills and communication and promote a strong sense of community. The metaverse offers a directed and engaging space to practice social interactions and gain confidence, indicating its positive, constructive role in society.
Unveiling the Opportunities of Unexplored Use of Cover Crop in Mediterranean Agriculture through Systematic Review and Meta-Analysis
Authors: Ziche Zakaria Islem , Mezzapesa Giuseppe Natale , Dragonetti Giovanna , Piscitelli Lea
Published: August 2024

Cover crops are multifunctional, and contribute to improving soil properties and reducing environmental impact compared to no-cover crops, thus could provide multiple soil, agricultural, and environmental benefits, and they are recognized as a valid strategy for the achievement of sustainable agriculture. However, cover crops’ impacts on subsequent cash crops and soil characteristics are dependent on several factors, such as pedoclimatic conditions, cover crop species, agricultural practices, method of termination, and irrigation management. The fact that cover crops are never applied as a single practice in the real agricultural sector, but are instead combined with other factors or agricultural practices, deeply affects their performance, but the scientific literature nevertheless keeps considering the use of cover crops alone. Moreover, the potential outcomes of cover crops that encompass other factors or agricultural practices affecting soil quality, weed control, and cash crops are still unclear. Additionally, cover crops are still poorly use in the Mediterranean type of climate. Therefore, this study reviewed the scientific literature to identify the most relevant factors or agricultural practices driving cover crops’ performance, and to outline future fields of investigation looking towards promising sustainable agriculture in Mediterranean areas with a view to minimizing the competition for soil water with the cropping systems and to reduce soil degradation. Furthermore, the investigation includes multiple factors or agricultural practices that better represent the real farming system, contributing to a comprehensive understanding of their interactions with cover crops, and suggests alternative strategies for reducing yield gap while seeking to achieve agricultural sustainability.
Screening and Physiological Responses of Maize Inbred Lines to Drought Stress in South China
Authors: Zhang Zhiqin , Xie Xiaodong , Naseer Muhammad Asad , Zhou Haiyu , Cheng Weidong , Xie Hexia , Qin Lanqiu , Yang Xiang , Jiang Yufeng , Zhou Xunbo
Published: August 2024

The frequent occurrence of localized and seasonal droughts has caused severe economic losses in maize production in South China. To promote sustainable maize production, selecting and breeding drought-tolerant varieties is vital for addressing water scarcity. Drought stress affects all aspects of crop morphological performance. In this study, the morphological performance of 285 maize inbred lines under drought stress was investigated using D-value analysis, correlation analysis, principal component analysis, cluster analysis and stepwise regression analysis. All indicators were significantly different in the regular treatment compared to the drought treatment. Specifically, survival rate, root fresh weight, root dry weight, plant dry weight, root/crown ratio, and plant fresh weight were used as indicators for drought-tolerance evaluation. Furthermore, the drought-tolerant inbred line CML323 and the drought-sensitive inbred line CB2-49-1 were screened by comprehensively evaluating D values. The drought-tolerant inbred line CML323 exhibits higher leaf relative water content, chlorophyll content, proline content, and ascorbate peroxidase and peroxidase activity while having lower malondialdehyde content, consequently demonstrating excellent drought tolerance. This study provides valuable insights into drought-tolerance indicators and reference materials for breeding maize varieties.
Digitalization and Digital Applications in Waste Recycling: An Integrative Review
Authors: Onur Neslihan , Alan Hale , Demirel Hüsne , Köker Ali Rıza
Published: August 2024

The rapid growth of urbanization and industrialization has brought the issue of waste management to the forefront. Industrial, household, and medical waste management and disposal are major issues affecting the whole world. The adoption of digital technologies across society is largely a result of the increasing processing power of waste and decreasing costs. Waste management and recycling is also benefiting from emerging digital technologies. The Internet of Things, cloud computing, artificial intelligence, robotics, and data analytics are a few examples of specific digital technologies that are currently in use and are predicted to have a significant impact on the efficiency of the waste recycling industry in the future. The objective of this review, which was conducted using the bibliometric method and visualized with scientific mapping, is to demonstrate how the digital transformation of waste recycling has evolved over the last decade and to identify which issues have been overlooked or have become more prominent. The scope of the research is based on studies carried out all over the world and on digital applications and works in the field of waste recycling. In this review, bibliometric analysis was used to scan the entire field and the results were classified and interpreted according to the PRISMA (preferred reporting of systematic reviews and meta-analyses) methodology.
Environmental Behavior Framework Revisited: Where Do We Stand Ten Years Later and Where Do We Go from Here?
Authors: Pelcher Jamee A. , Trendafilova Sylvia , McCullough Brian P.
Published: August 2024

Increasing environmental challenges are prompting sport managers to act to minimize negative ecological impacts. Educational opportunities for sport management students are critical for developing awareness and understanding of environmental sustainability across the sport industry. In 2012, Casper and Pfahl examined the personal environmental actions of sport administration and recreation students. The purpose of our current research is to expand on Casper and Pfahl’s work by assessing the predictive relationships of values, beliefs, and norms on behaviors related to environmental sustainability using the Value–Belief–Norm (VBN) framework. Sport management students (N = 510) representing 23 higher education institutions completed the online survey. Structural equation modeling showed minimal changes over ten years. Norms were the strongest predictors of pro-environmental behaviors, and results indicated that students hold sport management organizations to a higher environmental standard than traditional businesses. The authors provide discussion and recommendations on bridging the gap between academia and industry to better prepare students for their professional futures in the sport industry.
Navigating the Nexus: Stakeholder Engagement in Hybrid Renewable Energy Power Purchase Agreements (PPAs) for Sustainable Development
Authors: Stanitsas Marios , Kirytopoulos Konstantinos
Published: August 2024

In the quest for a sustainable energy landscape, renewable energy sources are positioned to lead. Among these, power purchase agreements (PPAs) have emerged as indispensable tools, particularly when combined with energy storage solutions, in supporting grid stability and ensuring the reliability of energy provision. The aim of this study is to undertake a rigorous systematic literature review to delve into the pivotal role that community engagement and stakeholder involvement play in shaping the contours of hybrid PPAs, which amalgamate renewable energy with storage technologies. Through a comprehensive synthesis of the previous literature, this research elucidates the nuanced dimensions and consequential benefits inherent in cultivating robust agreements. The objectives include examining the tangible benefits of prioritizing community empowerment, such as securing local acceptance and support, alleviating opposition, and tailoring project designs to harmonize with specific community requirements and preferences. Moreover, this study underscores the critical role of stakeholder engagement in ensuring compliance with regulatory mandates, thereby addressing sustainability outcomes while fostering the enduring success and feasibility of renewable energy projects.
Research on Energy Saving Effect of Parallel and Perpendicular Yard Layouts under Different Proportions of Transshipment at the Automated Container Terminal
Authors: Li Xiaojun , Zhou Ran , Zhu Lequn
Published: August 2024

The proportions of container transshipment is the key factor in determining the proportion of automated guided vehicle (AGV) and external container truck operations. In terms of parallel and perpendicular layouts of automated container terminals (ACTs), varying proportions of container transshipment result in different proportions of AGVs and external container truck operations, subsequently leading to distinct impacts on energy consumption (EC) for each ACT layout. This paper deemed EC as the primary evaluation criterion, established an EC model encompassing yard cranes (YCs) and container trucks, and investigated the EC of parallel and perpendicular layouts at different proportions of container transshipment. The results indicate that when the proportions of container transshipment were less than 17%, the parallel layout had lower EC; when it was between 17% and 21%, there was not much difference between the two layouts; when it was greater than 21%, the perpendicular layout had lower EC. This conclusion was based on an ideal environment established in this paper. When making decisions, decision makers should use this model as a starting point and adapt it flexibly to the actual situation of the port, in order to arrive at a reasonable and feasible plan.
Starlike Functions in the Space of Meromorphic Harmonic Functions
Authors: Dziok Jacek
Published: August 2024

The Geometric Theory of Analytic Functions was initially developed for the space of functions that are analytic in the unit disk. The convexity and starlikeness of functions are the first geometric ideas considered in this theory. We can notice a symmetry between the subjects considered in the space of analytic functions and those in the space of harmonic functions. In the presented paper, we consider the starlikeness of functions in the space of meromorphic harmonic functions.
Residents’ Perceptions of the Benefits and Costs of Tourism Development: A Case Study of Riyadh City (Saudi Arabia)
Authors: Alsaloum Moteab , Romagosa Francesc , Alotaibi Salman
Published: August 2024

This study examines residents’ perceptions of tourism development in Riyadh city, Saudi Arabia, focusing on its benefits and costs, guided by social exchange theory. The objective is to explore how the perceived impacts of tourism development, along with external factors such as community attachment, residents’ knowledge of tourism development, and community involvement, affect locals’ satisfaction with tourism and their intention to support tourism development. A survey of 427 locals, analyzed using structural equation modeling (SEM), reveals a positive correlation between community attachment and the perceived benefits from tourism. Residents’ knowledge about tourism is linked to perceived benefits, but not to perceived costs, and community involvement does not significantly impact perceptions. Perceived benefits positively influence support for tourism, while perceived costs have a negative effect. Residents’ satisfaction with tourism, shaped by their perceptions of the benefits and costs, influences their future support for tourism initiatives. The theoretical implications highlight social exchange theory’s role in understanding community perceptions, while the practical implications emphasize inclusive and transparent tourism planning to gain local support. These results underscore the importance of considering locals’ perceptions and satisfaction in both current and future tourism planning and development strategies.
The Selectively Nontargeted Analysis of Halogenated Disinfection Byproducts in Tap Water by Micro-LC QTOFMS
Authors: Wu Jing , Zhang Yulin , Zhang Qiwei , Tan Fang , Liu Qiongyu , Yang Xiaoqiu
Published: August 2024

With the rapid development of society, more and more unknown halogenated disinfection byproducts (DBPs) enter into drinking water and pose potential risks to humans. To explore the unknown halogenated DBPs in tap water, a selectively nontargeted analysis (SNTA) method was developed by conducting micro-liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (micro-LC-QTOFMS). In this method, two runs were employed: in the first run, the modes of TOFMS and precursor ion (the fragments were set as Cl35/Cl37, Br79/Br81, and I126.9) were performed, and the molecular ions or precursor ions of the halogenated organics could be obtained; in the second run, the product ion mode was conducted by setting the molecular ion screened above, and the MS/MS spectrums could be acquired to speculate concerning the structure. Two kinds of model DBPs (one kind had an aliphatic structure and the other was an aromatic compound) were used to optimize the parameters of the MS, and their MS characteristics were summarized. With this SNTA method, 15 halogenated DBPs were screened in two tap water samples and their structures were proposed. Of them, six DBPs had not been reported before and were assumed to be new DBPs. Overall, the detected halogenated DBPs were mostly acidic substances.
Endurance Exercise Does Not Exacerbate Cardiac Inflammation in BALB/c Mice Following mRNA COVID-19 Vaccination
Authors: Eens Sander , Van Hecke Manon , Van den Bogaert Siel , Favere Kasper , Cools Nathalie , Fransen Erik , Roskams Tania , Heidbuchel Hein , Guns Pieter-Jan
Published: August 2024

The mechanism underlying myopericarditis associated with mRNA COVID-19 vaccination, including increased susceptibility in young males, remains poorly understood. This study aims to explore the hypothesis that engaging in physical exercise at the time of mRNA COVID-19 vaccination may promote a cardiac inflammatory response, leading to the development of myopericarditis. Male BALB/c mice underwent treadmill running or remained sedentary for five weeks. Subsequently, two doses of the Pfizer/BioNTech vaccine or vehicle were administered with a 14-day interval, while the exercise regimen continued. The animals were euthanized days after the second vaccination. Vaccination was followed by body weight loss, increased hepatic inflammation, and an antigen-specific T cell response. Small foci of fibrovascular inflammation and focal cell loss were observed in the right ventricle, irrespective of vaccination and/or exercise. Vaccination did not elevate cardiac troponin levels. Cardiac tissue from the vaccinated mice showed upregulated mRNA expression of the genes IFNγ and IL-1β, but not IL-6 or TNFα. This pro-inflammatory signature in the heart was not exacerbated by endurance exercise. Ex vivo vascular reactivity remained unaffected by vaccination. Our data provide evidence for the cardiac safety of mRNA COVID-19 vaccination. The role of exercise in the development of pro-inflammatory cardiac changes post mRNA vaccination could not be established.
Establishment of a Reference Material in Quality Control for Use in Infectivity and Identity Assays of Recombinant COVID-19 Vaccine, in Accordance with International Standards Organization Guidance
Authors: Ajorio Ana Carolina Ferreira Ballestê , Chagas Michel Gomes , Rhodes Vinicius Pessanha , Rodrigues Anderson Peclat , Gonçalves Natália Pedra , Godinho Rodrigo Maciel da Costa , Forsythe Stephen James , da Costa Luciana Veloso , Brandão Marcelo Luiz Lima
Published: August 2024

The COVID-19 pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), began in 2019. One of the strategies for pandemic control was mass vaccination. In Brazil, the recombinant COVID-19 vaccine (RCV) was produced on a large scale and offered at no charge to the population. The specifications for quality control analyses of RCV included identity and infectivity determination. To validate the results, a reference material (RM) must be analyzed in parallel with the sample vaccine. This research aimed to establish the RM for use in the identity and infectivity assay for RCV. The candidate RM was analyzed using homogeneity and stability studies. The RM was considered homogeneous for identity (cycle threshold (Ct) ≤ 25.19) and infectivity (average x- was 9.25 log10 infectious units/mL). The RM was considered adequately stable for identity during the total period in all studies, being stable at −70, 5, and 22.5 °C for 380, 313, and 14 days, respectively (Ct ≤ 21.81). For infectivity, the RM was stable at −70, 5, and 22.5 °C for 380, 97, and three days, respectively. Since the property identity and infectivity values of the RM were established, the new RM could be used in quality control analysis.