bluuebunny/crossref_metadata_2025 huggingface dataset:
AM–GM Algorithm for Evaluating, Analyzing, and Correcting the Spatial Scaling Bias of the Leaf Area Index
Authors: Zhang Jingyu , Sun Rui , Xiao Zhiqiang , Zhao Liang , Xie Donghui
Published: June 2023

The leaf area index (LAI) is a crucial variable in climate, ecological, and land surface modeling. However, the estimation of the LAI from coarse-resolution remote sensing data can be affected by the spatial scaling bias, which arises from the nonlinearity of retrieval models and the heterogeneity of the land surface. This study provides an algorithm named Arithmetic Mean and Geometric Mean (AM–GM) to correct the spatial scaling bias. It is established based on negative logarithmic functions and avoids second-order stationarity. In this algorithm, relationships are derived between the scaling bias of LAI and the arithmetic and geometric means of directional gap probability for two commonly used remote sensing models, the Beer–Lambert law and a semi-empirical transfer function, respectively. According to the AM–GM algorithm, the expression representing the model nonlinearity is derived and utilized for the analysis of LAI scaling bias. Furthermore, the AM–GM algorithm is simplified by a linear relationship, which is constructed between two quantities related to the directional gap probability between two specific resolutions. Two scenes simulated by the LargE-Scale remote sensing data and image Simulation framework (LESS) model and three sites are used to evaluate the proposed algorithm and analyze the scaling bias of LAI. The validation results show that the AM–GM algorithm provides accurate correction of LAI scaling bias. The analyses based on the AM–GM algorithm demonstrate that the scaling bias of LAI increases with the increase in the LAI value, with stronger surface heterogeneity and coarser spatial resolution. The validation results of the simplified AM–GM algorithm demonstrate that at the Sud-Ouest site, the absolute value of the bias for the estimated LAI decreases from 0.10, 0.22, 0.29, and 0.31 to 0.04, 0.01, 0.04, and 0.05 at 200 m, 500 m, 1000 m, and 1500 m resolutions, respectively. In conclusion, the proposed algorithm is effective in the analysis and correction of the scaling bias for coarse-resolution LAI.
Analysis on BDS-3 Autonomous Navigation Performance Based on the LEO Constellation and Regional Stations
Authors: Xu Baopeng , Su Xing , Liu Zhimin , Su Mudan , Cui Jianhui , Li Qiang , Xu Yan , Ma Zeyu , Geng Tao
Published: June 2023

The global navigation satellite system (GNSS) is developing rapidly, and the related market applications and scientific research are increasing. Studies based on large low Earth orbit (LEO) satellite constellations have become research hotspots. The global coverage of the LEO constellation can reduce the dependence of navigation satellites on ground-monitoring stations and improve the precise orbit determination (POD) accuracy of navigation satellites. In this paper, we simulate various LEO satellite constellations (with 12, 30, and 60 satellites), along with ground stations’ observation data, to examine the impact of LEO satellites on the precision of the BeiDou-3 Global Navigation Satellite System (BDS-3) in terms of its POD accuracy. Using the simulated observation data of both LEO satellites and ground-monitoring stations, we analyze the integrated orbit determination for the LEO and BDS-3 satellites. The findings reveal that the 3D orbital accuracy of BDS-3 is 9.51 dm by using only seven ground-monitoring stations, and it is improved to a centimeter level after adding the LEO constellations. As the number of LEO constellation satellites increases, the impact on improving accuracy gradually diminishes. In terms of time synchronization accuracy in the BDS-3, compared to the results of clock offset using only ground stations, the addition of 12 LEO satellites resulted in an improvement of 49% for RMS1(root mean square) and 52% for RMS2 (standard deviation), the addition of 30 LEO satellites resulted in an improvement of 66% for RMS1 and 70% for RMS2, and the addition of 60 LEO satellites resulted in an improvement of 87% for RMS1 and 90% for RMS2. The integrated orbit determination of the LEO and BDS-3 satellites constellation greatly improves the accuracy of time synchronization. In addition, we also use simulated inter-satellite link (ISL) data to perform enhanced BDS-3 satellites POD and time synchronization experiments. The experiments showed that the orbit determination accuracy of the seven sta (seven stations) and ISL scheme is comparable to that of the seven sta and LEO12 scheme, and that the time synchronization accuracy of the seven sta and ISL scheme is slightly worse. The preliminary experiments showed that the LEO satellite could enhance the orbit determination accuracy of BDS-3 and obtain a higher time synchronization accuracy.
Annual Sexual Behavior in Boer Bucks Located in the Guerrero Tropics in Mexico
Authors: Ponce-Covarrubias José Luis , García y González Ethel Caterina , Pineda-Burgos Blanca Celia , Guevara-Arroyo Aurora Matilde , Hernández-Ruiz Pedro Enrique , Torres-Agatón Fernando , Ruiz-Ortega Maricela , Paredes-Alvarado Marisol , Robles-Robles José Manuel , Rodríguez-Castillo José del Carmen , Ángel-García Oscar , Valencia-Franco Edgar
Published: June 2023

The aim of this study was to evaluate the intensity of the annual sexual behavior (SB) of Boer bucks under tropical conditions in southern Mexico. For one year, 16 extensively grazing males were evaluated for SB individually with estrogenized goats. From the beginning of the experiment and every 30 days, body weight (BW), body condition (BC), testicular circumference (TC), odor intensity (OI), and SB (nudging, ano-genital sniffing, flehmen, mounting attempts, mounts with intromission, and self-urination) were recorded. The bucks showed more intense SB during the months of November to May than during the months of June to October (p < 0.05). Greater frequencies were found for nudging, ano-genital sniffing, mounting attempts, and self-urination in the months of November to May (p < 0.001). BW was lower during the months of January to August than in the months of September to December (p < 0.05). On the other hand, TC increased from October to December (p < 0.05). Similarly, the OI in males varied over time (time effect; p < 0.001). In fact, an increased odor was found from October to December. The conclusions are that breed male goats from the tropics of Guerrero have a more intense SB during the months of November to May, but TC, OI, BW, and BC correspond to the time of the year when forage availability is the greatest.
Wireless Local Area Networks Threat Detection Using 1D-CNN
Authors: Natkaniec Marek , Bednarz Marcin
Published: June 2023

Wireless Local Area Networks (WLANs) have revolutionized modern communication by providing a user-friendly and cost-efficient solution for Internet access and network resources. However, the increasing popularity of WLANs has also led to a rise in security threats, including jamming, flooding attacks, unfair radio channel access, user disconnection from access points, and injection attacks, among others. In this paper, we propose a machine learning algorithm to detect Layer 2 threats in WLANs through network traffic analysis. Our approach uses a deep neural network to identify malicious activity patterns. We detail the dataset used, including data preparation steps, such as preprocessing and division. We demonstrate the effectiveness of our solution through series of experiments and show that it outperforms other methods in terms of precision. The proposed algorithm can be successfully applied in Wireless Intrusion Detection Systems (WIDS) to enhance the security of WLANs and protect against potential attacks.
MuTr: Multi-Stage Transformer for Hand Pose Estimation from Full-Scene Depth Image
Authors: Kanis Jakub , Gruber Ivan , Krňoul Zdeněk , Boháček Matyáš , Straka Jakub , Hrúz Marek
Published: June 2023

This work presents a novel transformer-based method for hand pose estimation—DePOTR. We test the DePOTR method on four benchmark datasets, where DePOTR outperforms other transformer-based methods while achieving results on par with other state-of-the-art methods. To further demonstrate the strength of DePOTR, we propose a novel multi-stage approach from full-scene depth image—MuTr. MuTr removes the necessity of having two different models in the hand pose estimation pipeline—one for hand localization and one for pose estimation—while maintaining promising results. To the best of our knowledge, this is the first successful attempt to use the same model architecture in standard and simultaneously in full-scene image setup while achieving competitive results in both of them. On the NYU dataset, DePOTR and MuTr reach precision equal to 7.85 mm and 8.71 mm, respectively.
Identification and Tracking of Vehicles between Multiple Cameras on Bridges Using a YOLOv4 and OSNet-Based Method
Authors: Jin Tao , Ye Xiaowei , Li Zhexun , Huo Zhaoyu
Published: June 2023

The estimation of vehicle loads is a rising research hotspot in bridge structure health monitoring (SHM). Traditional methods, such as the bridge weight-in-motion system (BWIM), are widely used but they fail to record the locations of vehicles on the bridges. Computer vision-based approaches are promising ways for vehicle tracking on bridges. Nevertheless, keeping track of vehicles from the video frames of multiple cameras without an overlapped visual field poses a challenge for the tracking of vehicles across the whole bridge. In this study, a method that was You Only Look Once v4 (YOLOv4)- and Omni-Scale Net (OSNet)-based was proposed to realize vehicle detecting and tracking across multiple cameras. A modified IoU-based tracking method was proposed to track a vehicle in adjacent video frames from the same camera, which takes both the appearance of vehicles and overlapping rates between the vehicle bounding boxes into consideration. The Hungary algorithm was adopted to match vehicle photos in various videos. Moreover, a dataset with 25,080 images of 1727 vehicles for vehicle identification was established to train and evaluate four models. Field validation experiments based on videos from three surveillance cameras were conducted to validate the proposed method. Experimental results show that the proposed method has an accuracy of 97.7% in terms of vehicle tracking in the visual field of a single camera and over 92.5% in tracking across multiple cameras, which can contribute to the acquisition of the temporal–spatial distribution of vehicle loads on the whole bridge.
Digital Pulmonology Practice with Phonopulmography Leveraging Artificial Intelligence: Future Perspectives Using Dual Microwave Acoustic Sensing and Imaging
Authors: Sethi Arshia K. , Muddaloor Pratyusha , Anvekar Priyanka , Agarwal Joshika , Mohan Anmol , Singh Mansunderbir , Gopalakrishnan Keerthy , Yadav Ashima , Adhikari Aakriti , Damani Devanshi , Kulkarni Kanchan , Aakre Christopher A. , Ryu Alexander J. , Iyer Vivek N. , Arunachalam Shivaram P.
Published: June 2023

Respiratory disorders, being one of the leading causes of disability worldwide, account for constant evolution in management technologies, resulting in the incorporation of artificial intelligence (AI) in the recording and analysis of lung sounds to aid diagnosis in clinical pulmonology practice. Although lung sound auscultation is a common clinical practice, its use in diagnosis is limited due to its high variability and subjectivity. We review the origin of lung sounds, various auscultation and processing methods over the years and their clinical applications to understand the potential for a lung sound auscultation and analysis device. Respiratory sounds result from the intra-pulmonary collision of molecules contained in the air, leading to turbulent flow and subsequent sound production. These sounds have been recorded via an electronic stethoscope and analyzed using back-propagation neural networks, wavelet transform models, Gaussian mixture models and recently with machine learning and deep learning models with possible use in asthma, COVID-19, asbestosis and interstitial lung disease. The purpose of this review was to summarize lung sound physiology, recording technologies and diagnostics methods using AI for digital pulmonology practice. Future research and development in recording and analyzing respiratory sounds in real time could revolutionize clinical practice for both the patients and the healthcare personnel.
Cloud and Precipitation Profiling Radars: The First Combined W- and K-Band Radar Profiler Measurements in Italy
Authors: Montopoli Mario , Bracci Alessandro , Adirosi Elisa , Iarlori Marco , Di Fabio Saverio , Lidori Raffaele , Balotti Andrea , Baldini Luca , Rizi Vincenzo
Published: June 2023

Clouds cover substantial parts of the Earth’s surface and they are one of the most essential components of the global climate system impacting the Earth’s radiation balance as well as the water cycle redistributing water around the globe as precipitation. Therefore, continuous observation of clouds is of primary interest in climate and hydrological studies. This work documents the first efforts in Italy in remote sensing clouds and precipitation using a combination of K- and W-band (24 and 94 GHz, respectively) radar profilers. Such a dual-frequency radar configuration has not been widely used yet, but it could catch on in the near future given its lower initial cost and ease of deployment for commercially available systems at 24 GHz, with respect to more established configurations. A field campaign running at the Casale Calore observatory at the University of L’Aquila, Italy, nestled in the Apennine mountain range is described. The campaign features are preceded by a review of the literature and the underpinning theoretical background that might help newcomers, especially in the Italian community, to approach cloud and precipitation remote sensing. This activity takes place in interesting time for radar sensing clouds and precipitation, stimulated both by the launch of the ESA/JAXA EarthCARE satellite missions scheduled in 2024, which will have on-board, among other instruments, a W-band Doppler cloud radar and the proposal of new missions using cloud radars currently undergoing their feasibility studies (e.g., WIVERN and AOS in Europe and Canada, and U.S., respectively)
Nondestructive Detection of Egg Freshness Based on Infrared Thermal Imaging
Authors: Zhang Jingwei , Lu Wei , Jian Xingliang , Hu Qingying , Dai Dejian
Published: June 2023

In this paper, we proposed a nondestructive detection method for egg freshness based on infrared thermal imaging technology. We studied the relationship between egg thermal infrared images (different shell colors and cleanliness levels) and egg freshness under heating conditions. Firstly, we established a finite element model of egg heat conduction to study the optimal heat excitation temperature and time. The relationship between the thermal infrared images of eggs after thermal excitation and egg freshness was further studied. Eight values of the center coordinates and radius of the egg circular edge as well as the long axis, short axis, and eccentric angle of the egg air cell were used as the characteristic parameters for egg freshness detection. After that, four egg freshness detection models, including decision tree, naive Bayes, k-nearest neighbors, and random forest, were constructed, with detection accuracies of 81.82%, 86.03%, 87.16%, and 92.32%, respectively. Finally, we introduced SegNet neural network image segmentation technology to segment the egg thermal infrared images. The SVM egg freshness detection model was established based on the eigenvalues extracted after segmentation. The test results showed that the accuracy of SegNet image segmentation was 98.87%, and the accuracy of egg freshness detection was 94.52%. The results also showed that infrared thermography combined with deep learning algorithms could detect egg freshness with an accuracy of over 94%, providing a new method and technical basis for online detection of egg freshness on industrial assembly lines.
Impact of Personality Traits on Small Charitable Donations: The Role of Altruism and Attitude towards an Advertisement
Authors: Balaskas Stefanos , Panagiotarou Aliki , Rigou Maria
Published: June 2023

Given the serious humanitarian crises encountered by the modern world, it is more crucial than ever to build a society based on solidarity, compassion, empathy, and a sense of teamwork and cooperation. This research provides insight into how the factors of personality traits, altruistic behaviors, and humanitarian actions can positively influence citizens’ behavioral intentions, allowing for a deeper understanding of the motives behind charitable giving. To this end, a study was conducted with 332 Greek respondents, which used a special purpose questionnaire, including the HEXACO-24 questions and 13 additional questions, that addressed attitude towards advertisement, charitable giving, as well as the behavioral intention to donate. The findings add to current research by underlining the relevance of individuals’ altruistic character, since our analysis revealed a statistically significant relationship between charitable giving and behavioral intention to donate. All HEXACO personality traits, excluding emotionality, demonstrated a statistically significant positive relationship with the attitude towards advertising, while none of the personality traits exhibited a statistically significant positive relationship with the concept of charitable giving, which calls for further investigation. Our findings also revealed that attitude towards an advertisement had no drastic effect on charitable giving and behavioral intention.
High-Intensity Functional Training: Perceived Functional and Psychosocial Health-Related Outcomes from Current Participants with Mobility-Related Disabilities
Authors: Koon Lyndsie M. , Hall Jean P. , Arnold Kristen A. , Donnelly Joseph E. , Heinrich Katie M.
Published: June 2023

Background: People with mobility-related disabilities (MRDs) experience many personal and environmental barriers to engagement in community-based exercise programs. We explored the experiences of adults with MRD who currently participate in high-intensity functional training (HIFT), an inclusive and accessible community-based exercise program. Methods: Thirty-eight participants completed online surveys with open-ended questions, with ten individuals also participating in semi-structured interviews via telephone with project PI. Surveys and interviews were designed to examine changes to perceived health, and the elements of HIFT that promote sustained participation. Results: Thematic analysis revealed themes related to health changes following HIFT participation including improved physical, functional, and psychosocial health outcomes. Other themes emerged within the HIFT environment that promoted adherence for participants such as accessible spaces and equipment, and inclusive HIFT sessions and competitions. Additional themes included participants’ advice for the disability and healthcare communities. The resulting themes are informed by the World Health Organization’s International Classification of Functioning, Disability, and Health. Conclusion: The findings provide initial data on the potential effects of HIFT on multiple dimensions of health outcomes and contribute to the growing literature on community-based programs that are adaptable and inclusive for people with MRD.
Agreement between Force Platform and Smartphone Application-Derived Measures of Vertical Jump Height in Youth Grassroots Soccer Players
Authors: Tallis Jason , Morris Rhys O. , Duncan Michael J. , Eyre Emma L. J. , Guimaraes-Ferreira Lucas
Published: June 2023

Given the importance of vertical jump assessments as a performance benchmarking tool, the assessment of neuromuscular function and indicator of health status, accurate assessment is essential. This study compared countermovement jump (CMJ) height assessed using MyJump2 (JHMJ) to force-platform-derived jump height calculated from time in the air (JHTIA) and take-off velocity (JHTOV) in youth grassroots soccer players. Thirty participants (Age: 8.7 ± 0.42 yrs; 9 females) completed bilateral CMJs on force platforms whilst jump height was simultaneously evaluated using MyJump2. Intraclass correlation coefficients (ICC), Standard error of measurement (SEM), coefficient of variance (CV) and Bland–Altman analysis were used to compare performance of MyJump2 to force-platform-derived measures of CMJ height. The median jump height was 15.5 cm. Despite a high level of agreement between JHTIA and JHTOV (ICC = 0.955), CV (6.6%), mean bias (1.33 ± 1.62 cm) and 95% limits of agreement (LoA −1.85–4.51 cm) were greater than in other comparisons. JHMJ performed marginally better than JHTIA when compared to JHTOV (ICC = 0.971; 95% CI’s = 0.956–0.981; SEM = 0.3 cm; CV = 5.7%; mean bias = 0.36 ± 1.61 cm; LoA = −3.52–2.80 cm). Irrespective of method, jump height did not differ between males and females (p > 0.381; r < 0.093), and the comparison between assessment tools was not affected by sex. Given low jump heights achieved in youth, JHTIA and JHMJ should be used with caution. JHTOV should be used to guarantee accuracy in the calculation of jump height.
A Systematic Review and Meta-Analysis of the Differences in Mean Propulsive Velocity between Men and Women in Different Exercises
Authors: Nieto-Acevedo Raúl , Romero-Moraleda Blanca , Díaz-Lara Francisco Javier , Rubia Alfonso de la , González-García Jaime , Mon-López Daniel
Published: June 2023

The purpose of this paper was to conduct a systematic review and meta-analysis of studies examining the differences in the mean propulsive velocities between men and women in the different exercises studied (squat, bench press, inclined bench press and military press). Quality Assessment and Validity Tool for Correlational Studies was used to assess the methodological quality of the included studies. Six studies of good and excellent methodological quality were included. Our meta-analysis compared men and women at the three most significant loads of the force–velocity profile (30, 70 and 90% of 1RM). A total of six studies were included in the systematic review, with a total sample of 249 participants (136 men and 113 women). The results of the main meta-analysis indicated that the mean propulsive velocity is lower in women than men in 30% of 1RM (ES = 1.30 ± 0.30; CI: 0.99–1.60; p < 0.001) and 70% of 1RM (ES = 0.92 ± 0.29; CI: 0.63, 1.21; p < 0.001). In contrast, for the 90% of the 1RM (ES = 0.27 ± 0.27; CI: 0.00, 0.55), we did not find significant differences (p = 0.05). Our results support the notion that prescription of the training load through the same velocity could cause women to receive different stimuli than men.
Exploring the Landscape of Social Entrepreneurship and Crowdfunding: A Bibliometric Analysis
Authors: Talukder Saurav Chandra , Lakner Zoltán
Published: June 2023

The aim of this article is to identify, synthesize, and evaluate the existing research on the nexus of the SE–crowdfunding domain. The researchers used a variety of bibliometric tools, Biblioshiny, and VOSviewer, to examine the scholarly literature on SE and crowdfunding from 2013 through 2022. The data were gathered from the Web of Science and Scopus databases, and the researchers ultimately collected 105 documents for the analysis. As can be seen from the findings, there has been a steady increase in the number of articles published in SE crowdfunding throughout the past decade. The USA seems to be the main research region for SE–crowdfunding literature. Both of the most prolific writers, Maija Renkor and Aaron H. Anglin, are also from the USA. The results also show that the Journal of Business Venturing Insights ranks first for most productive sources, followed by Technological Forecasting and Social Change, Business Horizons, Sustainability, and the Academy of Entrepreneurship Journal. The temporal diagram of co-occurrence analysis indicates that performance, impact, altruism, motivation, and commercialization are emerging topics in the SE–crowdfunding research field. Moreover, the result of the co-citation analysis found four themes in the SE–crowdfunding domain. These include ‘crowdfunding for social entrepreneurship’, ‘impact investing in social enterprises’, ‘crowdfunding as an innovative way to fund social entrepreneurship’, and ‘social innovation and crowdfunding’. In addition, the article provides a helpful starting point for policymakers and practitioners involved in obtaining funds for SE through crowdfunding by considering the associated technological, administrative, and organizational consequences.
Theoretical Study and Experimental Validation on the Applicable Refrigerant for Space Heating Air Source Heat Pump
Authors: Nie Jinzhe , Wang Kaiqiao , Kong Xiangrui , Zhang Han , Zhang Shuai
Published: June 2023

The air source heat pump (ASHP) is developing rapidly and is widely used for space heating due to its potential for increasing energy efficiency and reducing greenhouse gas emissions. The choice of appropriate low global warming potential (GWP) alternative refrigerants is one of the challenges that ASHP systems face. Alternative refrigerants also affect the energy performance of these systems. Thus, it is essential to evaluate the performance of ASHP using environmentally friendly refrigerants to facilitate reasonable refrigerant selection. A theoretical model for simulating ASHP performance with different refrigerants is developed in this study. Experiments are conducted to validate the theoretical model. The simulation and the experimental results are found to be in good agreement. The ASHP performance indices, such as compression ratio (CR), discharging temperature (DT) and coefficients of performance (COP), are investigated using R22, R417A, R410A, R134a, R152a, R161 and R1234yf as working fluids. The results show that R152a has an average COP of 2.7% higher than R22, and R161 has an average COP of 1.4% higher than R22. R152a and R161 also have a higher CR but a lower DT than R22 under the same design conditions. In addition, R152a and R161 have ozone depletion potentials (ODP) of zero and extremely low GWPs; thus, they can be candidates to replace R22 in ASHP heating systems. This research provides a reference on refrigerant replacements for ASHP heating systems in North China.
Assessment of New Bio-Cement Method for Sand Foundation Reinforcement
Authors: Sun Jinzheng , Song Zhichao , Zhang Rongzheng , Shen Danyi , Wu Chuangzhou
Published: June 2023

Microbially induced carbonate precipitation (MICP) is a new method used in recent years to improve the soil. However, this method still faces challenges related to low grouting reinforcement strength and efficiency. In this study, both the bio-cement infiltration method and bio-cement mixed method for sand foundation were proposed, and physical model tests were conducted to investigate the mechanical properties of sand treated with the bio-cement method. The results showed that the bio-cement maximized the utilization rate of bacterial liquid and reduced the waste caused by the loss of bacteria compared with traditional methods. Both the size of the reinforced area and bearing capacity of the sand reinforced by bio-cement infiltration method were controlled by the volume ratio of the bio-cement, calcareous sand powder, and the inflow rate. The maximum bearing capacity was 125 N when using a mixture of bio-cement and calcareous sand powder with a ratio of 400/80, with an inflow rate of 20 mL/min. The UCS of the sand reinforced by the bio-cement mixed method gradually decreased from 3.44 MPa to 0.88 MPa with depth, but increased with increasing CaCO3 content. The CaCO3 crystals were primarily concentrated at the contact point between the particles, and the formed crystals were mainly polyhedral. Reduction in the CaCO3 content mainly occurred in the central deep part of the reinforcement area. The result provides an experimental basis for the use of bio-cement in the reinforcement of sand soil foundations.
Improving Soil Properties by Sand Application in the Saline-Alkali Area of the Middle and Lower Reaches of the Yellow River, China
Authors: Wang Jian , Yang Chenxi , Zhang Haiou , Li Juan
Published: June 2023

Excessive soil salinity is a problem that makes soil unusable for agriculture, and most current research focuses on either chemical supplements or water conservation measures. Nevertheless, more information is needed about how sand treatment affects soil quality. In this study, a field experiment assessed the effect of sand application and cropping year on soil properties in an arid and semi-arid saline-sodic agricultural ecosystem. We found that sand application significantly improved the saline–alkali soil’s physical (i.e., pH, EC, TSC, BD), chemical (i.e., OC, AN, AP), and enzyme activity (i.e., Amy, Ure, Alp, Cat) properties, and that soil AN, AP, as well as TSC, were the crucial factors affecting soil properties. Simultaneously, soil properties gradually improved along with increasing cropping years, although these increases gradually became small. Our findings highlight the potential of sand as a soil supplement to enhance soil quality and structure in semi-arid agricultural ecosystems, especially when considering the cost.
A Sustainable Port-Hinterland Container Transport System: The Simulation-Based Scenarios for CO2 Emission Reduction
Authors: Hasan Khandaker Rasel , Zhang Wei , Shi Wenming
Published: June 2023

This paper calculates the CO2 emissions for the port-hinterland container transport system and proposes possible emission reduction measures. This paper considers the Dhaka–Chittagong port-hinterland transport system in Bangladesh. The port-hinterland transport system represents 70% of the total international maritime containerised trade, including more than 2.0 million twenty-foot equivalent units (TEUs) per year. By implementing different scenarios using a simulation approach, this research suggests a substantial reduction in CO2 emissions for the port-hinterland transport system. The scenarios include infrastructure development and performance and operational efficiency improvement in the port and modal shift for the hinterland. In formulating the scenarios, the current performance statistics of the port and its hinterland as well as the possibility of the implementation of these scenarios are carefully analysed. The findings depict that Bangladesh could significantly contribute to the reduction in port-hinterland CO2 emissions by implementing the suggested scenarios.
The Role of Artificial Intelligence within Circular Economy Activities—A View from Ireland
Authors: Pathan Muhammad Salman , Richardson Edana , Galvan Edgar , Mooney Peter
Published: June 2023

The world’s current linear economic model is unsustainable. This model encourages improper use of limited natural resources and causes abundant waste production resulting in severe harm to the environment. A circular economy (CE) is a sustainable, restorative, and regenerative alternative to the current linear economy and is gaining popularity worldwide. Amongst various digital technologies, Artificial intelligence (AI) is a crucial enabler for CE and can aid significantly with the adoption and implementation of CE in real-world applications. In this paper, we describe the intersection of AI and CE and policies around implementing CE principles using AI. As a means of grounding the discussion, we discuss some initiatives taken by the Irish government to adopt circularity and explore the role AI plays in these. We present a number of practical examples of AI and CE from Ireland. We argue that digitalisation has potential in CE and it has a major role to play in the transition towards CE. We close the paper by reflecting on future steps around practical implementations of AI-based CE processes.
Archaeology of a Rural Qanāt: Water Management and Social Relations in 17th Century Isfahān, Iran
Authors: Sarga Fabian
Published: June 2023

This study investigates the water management structures and social relations that centred around a specific qanāt line in a rural setting in Iran during the Safavid period, specifically in the mid-17th c. CE. The setting is northwest of Isfahān, near Varkān, at a site called Mobārrak Ābād. The method combines analysis of documentary evidence and remote sensing of historical aerial photography. The documentary evidence provides administrative details of a suyūrghāl grant to Mohammad Beig E’temād-al-Dowleh by Shah ‘Abbās II. In combining this with the physical characteristics of the qanāt of Mobārrak Ābād, as derived from the aerial photograph, I provide identification and analysis of the two canals providing water beyond the garden and the use of the water derived from the qanāt for agricultural irrigation and in Aranjon’s village infrastructure. The conclusions discuss the material conditions in the periphery of the prosperous and fertile Isfahān region and provide a relative dating to the qanāt and associated infrastructure. The personal and social relations that can be derived from this evidence are relations of personal and economic dependency between Mohammad Beig E´temād-al-Dowleh and the Shah on the one hand, as well as the labour relations between the peasant population living with and from the qanāt who maintain this infrastructure and the administrative superstructure on the other. The article thus provides new insights into an under-investigated subject and region in the period.
Responses of Soil CO2 Emission and Tree Productivity to Nitrogen and Phosphorus Additions in a Nitrogen-Rich Subtropical Chinese Fir Plantation
Authors: Lu Xiaochen , Li Binjie , Chen Guangsheng
Published: June 2023

Nitrogen (N) and phosphorus (P) nutrients have been regularly applied to improve productivity in intensively managed and short-rotation forest plantations in subtropical China. Under the constraint of the national policy of “carbon neutrality”, it is necessary to determine the rational fertilization options by considering both forest productivity and soil CO2 emissions. Past worldwide studies have shown varied responses of forest soil heterotrophic respiration and CO2 emissions to N and P additions. This study designed six treatments with N additions (high level: 15 g N/m2, HN), P (low: 5 g P/m2, LP; high: 15 g P/m2, HP), and their interactions (HNLP and HNHP) to explore the effects of N and P additions on soil CO2 emissions in a P-limited and N-rich Chinese fir plantation (Cunninghamia lanceolata), and we identified the underlying controls using the structural equation model (SEM). The results indicated that LP, HNLP, and HNHP treatments significantly increased soil CO2 emissions in the first four months after treatment and the effects leveled since then. The balance between N and P inputs affected the responses of soil CO2 emissions to P additions. A low P addition significantly increased tree productivity, but the promoting effect gradually declined and was no longer significant after 3 years. Other treatments did not significantly affect tree productivity. The SEM analysis revealed that the promoting effects of P additions on CO2 emission were mainly due to their effects on increasing soil water-soluble organic carbon content and reducing microbial biomass nitrogen content. Considering both soil respiration and tree productivity, this study suggested that LP treatment can effectively balance the N and P nutrients and, in the meantime, maintain relatively low greenhouse gas emissions; thus a low P application level is suggested for N-rich Chinese fir plantations.
Machine Learning-Based Land Use and Land Cover Mapping Using Multi-Spectral Satellite Imagery: A Case Study in Egypt
Authors: Mahmoud Rehab , Hassanin Mohamed , Al Feel Haytham , Badry Rasha M.
Published: June 2023

Satellite images provide continuous access to observations of the Earth, making environmental monitoring more convenient for certain applications, such as tracking changes in land use and land cover (LULC). This paper is aimed to develop a prediction model for mapping LULC using multi-spectral satellite images, which were captured at a spatial resolution of 3 m by a 4-band PlanetScope satellite. The dataset used in the study includes 105 geo-referenced images categorized into 8 LULC different classes. To train this model on both raster and vector data, various machine learning strategies such as Support Vector Machines (SVMs), Decision Trees (DTs), Random Forests (RFs), Normal Bayes (NB), and Artificial Neural Networks (ANNs) were employed. A set of metrics including precision, recall, F-score, and kappa index are utilized to measure the accuracy of the model. Empirical experiments were conducted, and the results show that the ANN achieved a classification accuracy of 97.1%. To the best of our knowledge, this study represents the first attempt to monitor land changes in Egypt that were conducted on high-resolution images with 3 m of spatial resolution. This study highlights the potential of this approach for promoting sustainable land use practices and contributing to the achievement of sustainable development goals. The proposed method can also provide a reliable source for improving geographical services, such as detecting land changes.
How Job Crafting Affects Hotel Employees’ Turnover Intention during COVID-19: An Empirical Study from China
Authors: Xu Jiahui , Wang Chaohui , Zhang Tingting (Christina) , Zhu Lei
Published: June 2023

Based on self-regulation theory, this study examines the relationship between job crafting, career identity, job engagement, and turnover intention among hotel staff in China amid the COVID-19 pandemic. This research draws on the observations of 1453 hotel employees in China for its empirical data and analysis by SPSS and AMOS. Job crafting positively impacts career identity and job engagement but negatively impacts turnover intention. The turnover intentions of hotel employees are negatively impacted by their feelings of career identity and job engagement. Additionally, the mediating role of career identity and job engagement in the connection between job crafting and turnover intention is further discussed and illustrated. Research on the topic of job crafting in the hotel sector workplace is examined in this study, and its influence on job performance measures is evaluated. Both hotel employees and academics may benefit greatly from this study’s conclusions.
Can Farmers’ Satisfaction with Green Production Policies Be Explained by Policy Structure and Policy Implementation? Evidence from China
Authors: Zhang Biao , Fu Sang
Published: June 2023

The implementation of green production policies (GPPs) is an important guarantee to improve the utilization of agricultural resources and adapt to climate change and plays an important role in supporting and guiding farmers. The overall goal of this study is to explore the mechanisms of the impacts of policy structure and implementation on the satisfaction of farmers with GPPs. Data analysis was based on 1180 observations collected from a field survey in Anhui Province, China, in 2021. The results revealed that the satisfaction of farmers with GPPs is not high. Policy structure affects the satisfaction of farmers with GPPs, and there are differences in the impacts of agricultural service, financial, technical, subsidy, and supervision policies. The results also showed that a positive evaluation of policy implementation by farmers can significantly improve their satisfaction with GPPs, and there are differences in the effectiveness of evaluating the support intensity, degree of promotion, policy sustainability, and implementation effect. Further analysis revealed that the impact of policy structure on the satisfaction of farmers with GPPs is transmitted through policy implementation evaluation. The impacts of policy structure and policy implementation on the satisfaction of farmers with GPPs are heterogeneous in terms of gender, age, and education. Finally, some policy recommendations are proposed to construct GPPs for farmers across the entire industrial chain, increase policy promotion efforts, ensure the sustainability of policy formulation and implementation, and consider farmers’ subjective evaluations of policy implementation effects. The results of this study and the related policy recommendations can provide support for the formulation and optimization of agricultural GPPs in China and other countries.
Editorial for the Special Issue “Corporate Governance, Social Responsibility, Innovation, and Sustainable Business Development Goals”
Authors: Helfaya Akrum , Aboud Ahmed
Published: June 2023

Corporate governance, social responsibility, and innovation play an important role in achieving sustainable business development goals (SDGs) [...]
Physicochemical Properties and Leaching Toxicity Assessment of Jarosite Residue
Authors: Peng Jun , Liu Hui , He Luhua , Sun Zhumei , Peng Yanmei , Huang Xiaofang , Yan Xu
Published: June 2023

The safe disposal of hazardous waste from zinc hydrometallurgy, such as jarosite residue, is crucial for the sustainable development of the industry. The chemical, structural and morphological properties of jarosite residue from zinc smelting were studied by a combination of various characterizations, and environmental stability was evaluated using the toxicity characteristic leaching procedure (TCLP), Chinese standard leaching tests (CSLT) and long-term leaching experiments (LTLE). Phase composition analysis revealed that zinc ferrite and sodium jarosite were the main phases present in the jarosite residue. TCLP and CSLT analyses indicated that the Zn and Pb contents exceeded their respective toxicity identification standards by more than 30 times and 8 times, respectively, exceeding the threshold values of the standard. The LTLE results demonstrated that Pb concentrations continued to exceed the standard limits, even after long contact times. This study has paramount significance in the prediction of jarosite residue stability and the evaluation of its potential for secondary environmental pollution.
Two-Sided Beneficial Value-Added Service Investment and Pricing Strategies in Asymmetric/Symmetric Investment Scenarios
Authors: An Fengyue , Liu Gang
Published: June 2023

We explore media platforms’ investment strategies for two-sided beneficial value-added services, which can directly benefit both consumers and advertisers, and ad pricing strategies by using game theory. We consider an asymmetric investment scenario, scenario A, and a symmetric investment scenario, scenario S, and develop game models under each scenario. First, we obtain the equilibrium investments, prices and profits and analyze the influence of the three important parameters—marginal investment costs, positive consumer effects and negative advertising effects, on the equilibrium outcomes in each scenario. Then we compare these equilibrium outcomes between both scenarios. Finally, we conduct numerical simulations to verify the conclusions obtained in both scenarios. We show that in scenario A, the value-added service levels and ad prices of the investment platforms remain constant and then decrease with marginal investment costs. The ad prices and profits of the investment platforms increase (decrease) with positive consumer effects (negative advertising effects). The same change is true for the value-added service levels only under certain conditions. In scenario S, the value-added service levels of the investment platforms change with positive consumer effects or negative advertising effects only when marginal investment costs are high. The ad prices of the platforms always increase with positive consumer effects but increase with negative advertising effects only when marginal costs are low. The profits of the platforms vary monotonically with negative advertising effects, but not necessarily with positive consumer effects. Compared to scenario S, the ad prices of the investment platforms in scenario A are higher, but that is not always true for the value-added service levels.
Event-Triggered Distributed Sliding Mode Control of Fractional-Order Nonlinear Multi-Agent Systems
Authors: Jin Yi , Xu Yan , Liu Gang , Jin Zhenghong , Li Huanhuan
Published: June 2023

In this study, the state consensus problem is investigated for a class of nonlinear fractional-order multi-agent systems (FOMASs) by using a dynamics event-triggered sliding mode control approach. The main objective is to steer all agents to some bounded position based on their own information and the information of neighbor agent. Different from the existing results, both asymptotic consensus problem and Zeno-free behavior are ensured simultaneously. To reach this objective, a novel event-triggered sliding mode control approach is proposed, composed of distributed dynamic event-triggered schemes, event-triggered sliding mode controllers, and auxiliary switching functions. Moreover, to implement the distributed control scheme, the fractional-order adaptive law is also developed to tuning the coupling weight, which is addressed in distributed protocol. With the improved distributed control scheme, all signals in the fractional-order closed-loop systems are guaranteed to be consensus and bounded, and a novel approach is developed to avoid the Zeno behavior. Finally, the availability and the effectiveness of the above-mentioned approach are demonstrated by means of a numerical example.
Numerical Solution of Nonlinear Problems with Multiple Roots Using Derivative-Free Algorithms
Authors: Kumar Sunil , Sharma Janak Raj , Bhagwan Jai , Jäntschi Lorentz
Published: June 2023

In the study of systems’ dynamics the presence of symmetry dramatically reduces the complexity, while in chemistry, symmetry plays a central role in the analysis of the structure, bonding, and spectroscopy of molecules. In a more general context, the principle of equivalence, a principle of local symmetry, dictated the dynamics of gravity, of space-time itself. In certain instances, especially in the presence of symmetry, we end up having to deal with an equation with multiple roots. A variety of optimal methods have been proposed in the literature for multiple roots with known multiplicity, all of which need derivative evaluations in the formulations. However, in the literature, optimal methods without derivatives are few. Motivated by this feature, here we present a novel optimal family of fourth-order methods for multiple roots with known multiplicity, which do not use any derivative. The scheme of the new iterative family consists of two steps, namely Traub-Steffensen and Traub-Steffensen-like iterations with weight factor. According to the Kung-Traub hypothesis, the new algorithms satisfy the optimality criterion. Taylor’s series expansion is used to examine order of convergence. We also demonstrate the application of new algorithms to real-life problems, i.e., Van der Waals problem, Manning problem, Planck law radiation problem, and Kepler’s problem. Furthermore, the performance comparisons have shown that the given derivative-free algorithms are competitive with existing optimal fourth-order algorithms that require derivative information.
Imaging in Non-Traumatic Emergencies
Authors: Scaglione Mariano , Masala Salvatore , Iacobellis Francesca , Tonerini Michele , Sica Giacomo , Liguori Carlo , Saba Luca , Tamburrini Stefania
Published: June 2023

“Emergency” is a scenario that every medical professional must face since the first day of her/his career [...]