bluuebunny/crossref_metadata_2025 huggingface dataset:
Ethylene Is Crucial in Abscisic Acid-Mediated Modulation of Seed Vigor, Growth, and Photosynthesis of Salt-Treated Mustard
Authors: Masood Asim , Khan Sheen , Mir Iqbal R. , Anjum Naser A. , Rasheed Faisal , Al-Hashimi Abdulrahman , Khan Nafees A.
Published: August 2024

The current study explored the differential interaction between ethylene (ET) and abscisic acid (ABA) in relation to salt stress in mustard (Brassica juncea L.) plants. Significant reductions in seed germination, growth, and photosynthesis were observed with 100 mmol NaCl. Among the cultivars tested, the Pusa Vijay cultivar was noted as ET-sensitive. Pusa Vijay responded maximally to an application of 2.0 mmol ethephon (Eth; 2-chloethyl phosphonic acid-ethylene source), and exhibited the greatest growth, photosynthesis, activity of 1-aminocyclopropane carboxylic acid (ACC) synthase (ACS), and ET evolution. Notably, Eth (2.0 mmol) more significantly improved the seed germination percentage, germination and vigor index, amylase activity, and reduced H2O2 content under salt stress, while ABA (25 µmol) had negative effects. Moreover, the individual application of Eth and ABA on Pusa Vijay under both optimal and salt-stressed conditions increased the growth and photosynthetic attributes, nitrogen (N) and sulfur (S) assimilation, and antioxidant defense machinery. The addition of aminoethoxyvinylglycine (0.01 µmol AVG, ET biosynthesis inhibitor) to ABA + NaCl-treated plants further added to the effects of ABA on parameters related to seed germination and resulted in less effectiveness of growth and photosynthesis. In contrast, the effects of Eth were seen with the addition of fluoridone (25 µmol Flu, ABA biosynthesis inhibitor) to Eth + NaCl. Thus, it can be suggested that ET is crucial for alleviating salt-induced inhibition in seed germination, growth, and photosynthesis, while ABA collaborated with ET to offer protection by regulating nutrient assimilation and enhancing antioxidant metabolism. These findings provide insight into the complex regulatory processes involved in ET–ABA interaction, enhancing our understanding of plant growth and development and the mitigation of salt stress in mustard. It opens pathways for developing hormonal-based strategies to improve crop productivity and resilience, ultimately benefiting agricultural practices amidst a challenging environment.
Study on Betaine and Growth Characteristics of Lycium chinense Mill. in Different Cultivation Environments in South Korea
Authors: Cho Hyejung , Lee Dong Hwan , Jeong Dae Hui , Jang Jun Hyuk , Son Yonghwan , Lee Sun-Young , Kim Hyun-Jun
Published: August 2024

Betaine is a useful compound that has various activities and is the marker compound of Lycium chinense fruit in Korean Pharmacopoeia. we seek to support the stable production of medicinal goji berries, which have significant potential in the pharmaceutical industry due to their high values, and to provide foundational data for consistent quality control. This study’s purpose was to examine the correlation among betaine content, environmental variables, and the growth characteristics of L. chinense fruits. The fruits were collected from 25 cultivation sites across South Korea. We investigated five growth characteristics and betaine contents in L. chinense fruits and twelve soil physicochemical properties, and seven meteorological data at cultivation sites. The fruit’s growth characteristics included a length of 15.62–26.49 mm, a width of 7.09–11.38 mm, a fresh weight of 0.73–1.62 g, and a sugar content of 11.10–19.62 Brix°. Its betaine content ranged from 0.54% to 0.97%. The betaine content was positively correlated with electrical conductivity (0.327 **), exchangeable potassium (0.314 **), and sodium (0.259 *) and negatively correlated with annual average minimum temperature (−0.256 *) and annual average temperature (−0.242 *). Also, betaine showed a positive correlation with the length of the fruit (0.294 *) and the fresh weight of the fruit (0.238 *). These results can be used to find the best cultivation method and to manage quality control for the highly economical L. chinense fruit.
Microbiological Evaluation of Thermoplastic PETG Dental Appliances Related to Surface Characteristics
Authors: Porojan Liliana , Bejan Flavia Roxana , Tirziu Emil , Gașpar Cristina Mirabela , Moza Alex Cristian , Gherban Mihaela Ionela , Vasiliu Roxana Diana , Matichescu Anamaria
Published: August 2024

(1) Background: The adhesion and microbiological behaviour of thermoplastic PETG dental appliance surfaces is governed by roughness parameters. The aim of this research was to evaluate the antibiofilm activity of alkaline peroxide-based disinfectant in Candida albicans biofilms on thermoplastic PETG, related to artificial ageing and surface characteristics, on multiscale levels. (2) Methods: In the present study, two PETG materials were investigated: Crystal® (Bio Art Dental Equipment, Sao Carlos, Brazil), noted as C, and Duran® (Scheu-Dental GmbH, Iserlohn, Germany)—noted as D. Half of the specimens were thermally cycled (TC), resulting in four sample groups, as follows: C, CTC, D, and DTC. Surface roughness was evaluated on different scale topographies. The biofilms were grown on the surfaces. An alkaline peroxide-based disinfectant was used. Statistical analyses were performed. (3) Results: Related to nanoroughness, there are insignificant differences among materials or related to thermocycling. More irregular surfaces are associated with larger grain sizes. After thermocycling, micro-roughness values increase. Disinfectant activity decreases the amount of biofilm developed on the surfaces, significantly in the two groups, but is not correlated to the material and artificial ageing. (4) Conclusion: The impact of surface roughness (Ra) on biofilm constitution is controlled by different scale topographies.
Direct Acrylation of Soybean Oil and the Influence of the Acrylation Degree on Waterborne Acrylic Systems
Authors: Perez Beatriz , Blanco Noelia , Villaverde Haizea , Echeverria Oihane , Gomez de Miranda Olga , Rodriguez Raquel
Published: August 2024

The direct acrylation of soybean oil was investigated by the activation of soybean oil’s (SO’s) internal fatty unsaturation with acidic catalysts. The effect of the catalyst and the reactant ratio with respect to the unsaturation and reaction time on the direct acrylation process were explored. ASO (acrylated soybean oil) with acrylation degrees (the number of acrylate molecules introduced in a triglyceride molecule) between 1.6 and 2.55 were obtained. The effect of the ASO acrylation degree on copolymerization processes was investigated. The resulting monomers were successfully copolymerized with meth(acrylate) monomers by the miniemulsion polymerization process, favoring the droplet nucleation mechanism and showing conversions higher than 97%. The acrylic–ASO copolymers presented lower Tg and higher hydrophobicity and oleophobicity than the acrylic copolymer.
Study on the Relationship between Electron Transfer and Electrical Properties of XLPE/Modification SR under Polarity Reversal
Authors: Wu Zhi-Yuan , Jin Yu-Zhi , Shi Zhe-Xu , Wang Zhi-Yuan , Wang Wei
Published: August 2024

The insulation of high-voltage direct-current (HVDC) cables experiences a short period of voltage polarity reversal when the power flow is adjusted, leading to sever field distortion in this situation. Consequently, improving the insulation performance of the composite insulation structure in these cables has become an urgent challenge. In this paper, SiC-SR (silicone rubber) and TiO2-SR nanocomposites were chosen for fabricating HVDC cable accessories. These nanocomposites were prepared using the solution blending method, and an electro-acoustic pulse (PEA) space charge test platform was established to explore the electron transfer mechanism. The space charge characteristics and field strength distribution of a double-layer dielectric composed of cross-linked polyethylene (XLPE) and nano-composite SR at different concentrations were studied during voltage polarity reversal. Additionally, a self-built breakdown platform for flake samples was established to explore the effect of the nanoparticle doping concentration on the breakdown field strength of double-layer composite media under polarity reversal. Therefore, a correlation was established between the micro electron transfer process and the macro electrical properties of polymers (XLPE/SR). The results show that optimal concentrations of nano-SiC and TiO2 particles introduce deep traps in the SR matrix, significantly inhibiting charge accumulation and electric field distortion at the interface, thereby effectively improving the dielectric strength of the double-layer polymers (XLPE/SR).
The Strike-Slip Fault System and Its Influence on Hydrocarbon Accumulation in the Gudong Area of the Zhanhua Depression, Bohai Bay Basin
Authors: Zhou Hongke , Wu Qunhu , Wang Zhiwei , Teng Fei , Guo Genhou , Zhang Zunxiang , Wu Yanjia , Cheng Yanjun
Published: August 2024

The Gudong area contains abundant petroleum resources. Previous studies have mainly focused on the extension structure in this area, with its strike-slip characteristics remaining poorly understood. In this study, the geometry of the strike-slip faults in the Gudong area was investigated using high-resolution 3D seismic reflection and drilling data, as were their associated releasing and restraining structures. Based on the profile’s flower structure and the plane’s horsetail splay pattern, the Gudong fault in the study area can be characterized as a dextral strike-slip. Three types of strike-slip fault-associated structures can be identified in the study area: (a) a restraining bend occurring in the right-stepping area of the S-shaped Gudong strike-slip fault, (b) a restraining bend identified in the left-stepping, overlapping zone of the Gudong and Kendong faults, and (c) a releasing bend seen in the extensional horsetail splay structure at the southern end of the Gudong fault. The restraining stress induced the formation of a fault-related open anticline, which led to a significant increase in fault sealing efficiency, thereby preserving an estimated 75.479231 million tons of oil and 15.28317145 billion cubic meters of gas. Conversely, releasing transtensional stress has compromised the effectiveness of the traps, preventing hydrocarbon retention. Consequently, oil and gas have migrated upward along the horsetail faults to the top of Cenozoic formations and have then dispersed.
Research and Application for Alternate Production Technology of Dual-Branch Horizontal Wells in an Offshore Oilfield
Authors: Zhang Dong , Li Fenghui , Li Yanlai , Zheng Xu , Liu Chunyan , Liu Hongjie , Wang Xiang
Published: August 2024

Old-well sidetracking is a key method for controlling low-productivity wells in the Bohai oilfield. This study employs reservoir engineering and numerical simulation techniques to investigate the maximum drainage radius and natural coning control mechanism in heavy-oil reservoirs with bottom water. Based on these findings, an alternate production technology was developed for dual-branch horizontal wells. The technology creates a new branch through sidetracking, connecting and isolating the old and new wellbores using a combination of wall hangers and branch guides. Initially, the old wellbore with an ultra-high water cut is temporarily sealed. When the new branch reaches a high water-cut stage, production is switched back to the old wellbore. This technology was successfully applied to three wells in the Bohai oilfield, resulting in the new branch achieving expected production levels, while reopening the old wellbore increased daily oil output by 27 m3 and reduced water cut by 5.6%. Cumulative oil production from these wells reached 95,000 m3. This technology improves well-slot resource utilization, enhances recovery rates, and has significant potential for broader application.
An Ambient Adaptive Global Navigation Satellite System Total Electron Content Predictive Model for Short-Term Rapid Geomagnetic Storm Events
Authors: Filjar Renato , Heđi Ivan , Prpić-Oršić Jasna , Iliev Teodor
Published: August 2024

Satellite navigation is an essential component of the national infrastructure. Space weather and ionospheric conditions are the prime sources of GNSS (global navigation satellite system) positioning, navigation, and timing (PNT) service disruptions and degradations. Protection, toughening, and augmentation (PTA) of GNSS PNT services require novel approaches in ionospheric effects mitigation. Standard global ionospheric correction models fail in the mitigation of high-dynamics and local ionospheric disturbances. Here, we demonstrate that in the case of the short-term fast-developing geomagnetic storm, a machine learning-based environment-aware GNSS ionospheric correction model for sub-equatorial regions may provide a substantial improvement over the existing global Klobuchar model, considered a benchmark. The proposed machine learning-based model utilises just the geomagnetic field density component observations as a predictor to estimate TEC/GNSS ionospheric delay as the prediction model target. Further research is needed to refine the methodology of machine learning model development selection and validation and to establish an architecture-agnostic framework for GNSS PTA development.
Estimating Reactivation Times and Velocities of Slow-Moving Landslides via PS-InSAR and Their Relationship with Precipitation in Central Italy
Authors: Ghaderpour Ebrahim , Masciulli Claudia , Zocchi Marta , Bozzano Francesca , Scarascia Mugnozza Gabriele , Mazzanti Paolo
Published: August 2024

Monitoring slow-moving landslides is a crucial task for socioeconomic risk prevention and/or mitigation. Persistent scatterer interferometric synthetic aperture radar (PS-InSAR) is an advanced remote sensing method for monitoring ground deformation. In this research, PS-InSAR time series derived from COSMO-SkyMed (descending orbit) and Sentinel-1 (ascending orbit) are analyzed for a region in Central Apennines in Italy. The sequential turning point detection method (STPD) is implemented to detect the trend turning dates and their directions in the PS-InSAR time series within areas of interest susceptible to landslides. The monthly maps of significant turning points and their directions for years 2018, 2019, 2020, and 2021 are produced and classified for four Italian administrative regions, namely, Marche, Umbria, Abruzzo, and Lazio. Monthly global precipitation measurement (GPM) images at 0.1∘×0.1∘ spatial resolution and four local precipitation time series are also analyzed by STPD to investigate when the precipitation rate has changed and how they might have reactivated slow-moving landslides. Generally, a strong correlation (r≥0.7) is observed between GPM (satellite-based) and local precipitation (station-based) with similar STPD results. Marche and Abruzzo (the coastal regions) have an insignificant precipitation rate while Umbria and Lazio have a significant increase in precipitation from 2017 to 2023. The coastal regions also exhibit relatively lower precipitation amounts. The results indicate a strong correlation between the trend turning dates of the accumulated precipitation and displacement time series, especially for Lazio during summer and fall 2020, where relatively more significant precipitation rate of change is observed. The findings of this study may guide stakeholders and responsible authorities for risk management and mitigating damage to infrastructures.
Utilizing Multi-Source Geospatial Big Data to Examine How Environmental Factors Attract Outdoor Jogging Activities
Authors: Shi Tingyan , Gao Feng
Published: August 2024

In the post-pandemic era, outdoor jogging has become an increasingly popular form of exercise due to the growing emphasis on health. It is essential to comprehensively analyze the factors influencing the spatial distribution of outdoor jogging activities and to propose planning strategies with practical guidance. Using multi-source geospatial big data and multiple models, this study constructs a comprehensive analytical framework to examine the association between environmental variables and the frequency of outdoor jogging activities in Guangzhou. Firstly, outdoor jogging trajectory data were collected from a fitness app, and potential influencing factors were selected based on multi-source big data from the perspectives of the built environment, street perception, and natural environment. For example, using the street-view imagery, objective environmental elements such as greenery and subjective elements such as safety perception were extracted from a human-centric perspective. Secondly, the framework included three models: a backward stepwise regression, an optimal parameters-based geographical detector, and a geographically weighted regression (GWR) model. These models served, to screen significant variables, identify the synergistic effects among the variables, and quantify the spatial heterogeneity of the effects, respectively. Finally, the study area was clustered based on the results of the GWR model to propose urban planning strategies with clear spatial positions and practical significance. The results indicated the following: (1) Factors related to the built environment and street perception significantly influence jogging frequency distribution. (2) Public sports facilities, the level of greenery, and safety perception were identified as key factors influencing jogging activities, representing the three aspects of service facilities, objective perception, and subjective perception, respectively. (3) Specifically, the influence of each factor on jogging activities displayed significant spatial variation. For instance, sports facilities and greenery level were positively correlated with jogging frequency in the city center. (4) Lastly, the study area was divided into four clusters, each representing different local associative characteristics between variables and jogging activities. The zonal planning recommendations have significant implications for urban planners and policymakers aiming to create jogging-friendly environments.
A Novel Two-Step Channel Estimation Method for RIS-Assisted mmWave Systems
Authors: Yu Jiarun
Published: August 2024

In this work, we resolve the cascaded channel estimation problem and the reflected channel estimation problem for the reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) systems. The novel two-step method contains modified multiple population genetic algorithm (MMPGA), least squares (LS), residual network (ResNet), and multi-task regression model. In the first step, the proposed MMPGA-LS optimizes the crossover strategy and mutation strategy. Besides, the ResNet achieves cascaded channel estimation by learning the relationship between the cascaded channel obtained by the MMPGA-LS and the channel of the user (UE)-RIS-base station (BS). Then, the proposed multi-task-ResNet (MTRnet) is introduced for the reflected channel estimation. Relying on the output of ResNet, the MTRnet with multiple output layers estimates the coefficients of reflected channels and reconstructs the channel of UE-RIS and RIS-BS. Remarkably, the proposed MTRnet is capable of using a lower optimization model to estimate multiple reflected channels compared with the classical neural network with the single output layer. A series of experimental results validate the superiority of the proposed method in terms of a lower norm mean square error (NMSE). Besides, the proposed method also obtains a low NMSE in the RIS with the formulation of the uniform planar array.
Doppler Radar Sensor-Based Fall Detection Using a Convolutional Bidirectional Long Short-Term Memory Model
Authors: Li Zhikun , Du Jiajun , Zhu Baofeng , Greenwald Stephen E. , Xu Lisheng , Yao Yudong , Bao Nan
Published: August 2024

Falls among the elderly are a common and serious health risk that can lead to physical injuries and other complications. To promptly detect and respond to fall events, radar-based fall detection systems have gained widespread attention. In this paper, a deep learning model is proposed based on the frequency spectrum of radar signals, called the convolutional bidirectional long short-term memory (CB-LSTM) model. The introduction of the CB-LSTM model enables the fall detection system to capture both temporal sequential and spatial features simultaneously, thereby enhancing the accuracy and reliability of the detection. Extensive comparison experiments demonstrate that our model achieves an accuracy of 98.83% in detecting falls, surpassing other relevant methods currently available. In summary, this study provides effective technical support using the frequency spectrum and deep learning methods to monitor falls among the elderly through the design and experimental validation of a radar-based fall detection system, which has great potential for improving quality of life for the elderly and providing timely rescue measures.
Sensor-Enhanced Thick Laminated Composite Beams: Manufacturing, Testing, and Numerical Analysis
Authors: Basaran Mustafa , Turkmen Halit Suleyman , Yildiz Mehmet
Published: August 2024

This study investigates the manufacturing, testing, and analysis of ultra-thick laminated polymer matrix composite (PMC) beams with the aim of developing high-performance PMC leaf springs for automotive applications. An innovative aspect of this study is the integration of Fiber Bragg Grating (FBG) sensors and thermocouples (TCs) to monitor residual strain and exothermic reactions in composite structures during curing and post-curing manufacturing cycles. Additionally, the Calibration Coefficients (CCs) are calculated using Strain Gauge measurement results under static three-point bending tests. A major part of the study focuses on developing a properly correlated Finite Element (FE) model with large deflection (LD) effects using geometrical nonlinear analysis (GNA) to understand the deformation behavior of ultra thick composite beam (ComBeam) samples, advancing the understanding of large deformation behavior and filling critical research gaps in composite materials. This model will help assess the internal strain distribution, which is verified by correlating data from FBG sensors, Strain Gauges (SGs), and FE analysis. In addition, this research focuses on the application of FBG sensors in structural health monitoring (SHM) in fatigue tests under three-point bending with the support of load-deflection sensors: a new approach for composites at this scale. This study revealed that the fatigue performance of ComBeam samples drastically decreased with increasing displacement ranges, even at the same maximum level, underscoring the potential of FBG sensors to enhance SHM capabilities linked to smart maintenance.
Slot-Loaded Vivaldi Antenna for Biomedical Microwave Imaging Applications: Influence of Design Parameters on Antenna’s Dimensions and Performances
Authors: Wang Mengchu , Crocco Lorenzo , Li Maokun , Cavagnaro Marta
Published: August 2024

This paper demonstrates the design steps of a slot-loaded Vivaldi antenna for biomedical microwave imaging applications, showing the influence of the design parameters on the antenna’s dimensions and performances. Several antenna miniaturization techniques were taken into consideration during the design: reduction in the electromagnetic wavelength by using a high-permittivity substrate material (relative permittivity ϵr=10.2), the placement of the antenna inside a coupling medium (ϵr=23), and the elongation of the current path by etching slots on each side of the radiator to reduce the antenna’s lowest resonant frequency without increasing its physical dimensions. Moreover, an analysis of different antenna slot design scenarios was performed considering different slot lengths, inclination angles, positions, and numbers. Considering the frequency range of microwave imaging (i.e., about 500 MHz–5 GHz) and the array arrangement typical of microwave imaging, the best design was chosen. Finally, the antenna was fabricated and its performances in the coupling medium were characterized. The simulation and measurement results showed good agreement between each other. In comparison with literature antennas, the one developed in this work shows wide bandwidth and compact dimensions.
MASDF-Net: A Multi-Attention Codec Network with Selective and Dynamic Fusion for Skin Lesion Segmentation
Authors: Fu Jinghao , Deng Hongmin
Published: August 2024

Automated segmentation algorithms for dermoscopic images serve as effective tools that assist dermatologists in clinical diagnosis. While existing deep learning-based skin lesion segmentation algorithms have achieved certain success, challenges remain in accurately delineating the boundaries of lesion regions in dermoscopic images with irregular shapes, blurry edges, and occlusions by artifacts. To address these issues, a multi-attention codec network with selective and dynamic fusion (MASDF-Net) is proposed for skin lesion segmentation in this study. In this network, we use the pyramid vision transformer as the encoder to model the long-range dependencies between features, and we innovatively designed three modules to further enhance the performance of the network. Specifically, the multi-attention fusion (MAF) module allows for attention to be focused on high-level features from various perspectives, thereby capturing more global contextual information. The selective information gathering (SIG) module improves the existing skip-connection structure by eliminating the redundant information in low-level features. The multi-scale cascade fusion (MSCF) module dynamically fuses features from different levels of the decoder part, further refining the segmentation boundaries. We conducted comprehensive experiments on the ISIC 2016, ISIC 2017, ISIC 2018, and PH2 datasets. The experimental results demonstrate the superiority of our approach over existing state-of-the-art methods.
EAIA: An Efficient and Anonymous Identity-Authentication Scheme in 5G-V2V
Authors: Du Qianmin , Zhou Jianhong , Ma Maode
Published: August 2024

Vehicle Ad-hoc Networks (VANETs) have experienced significant development in recent years, playing a crucial role in enhancing the driving experience by enabling safer and more efficient inter-vehicle interactions through information exchange. Vehicle-to-Vehicle (V2V) communication is particularly vital as it not only helps to prevent collisions and improve traffic efficiency but also provides essential situational awareness to drivers or autonomous driving systems. Communication is typically supported by roadside units (RSUs); however, in practical applications, vehicles may exceed the communication range of RSUs, thus exposing them to various malicious attacks. Additionally, considering the limited computational resources of onboard units (OBUs) in vehicles, there is a high demand for designing lightweight security protocols that support V2V communication. To address this issue, this paper proposes an efficient anonymous V2V identity-authentication protocol tailored for scenarios that lack RSU support. The proposed protocol was formally assessed using the Scyther tool, demonstrating its capability to withstand major typical malicious attacks. Performance evaluations indicate that the proposed protocol is efficient in terms of communication and computational overhead, making it a viable solution for V2V communication.
Correlation-Assisted Pixel Array for Direct Time of Flight
Authors: Morsy Ayman , Kuijk Maarten
Published: August 2024

Time of flight is promising technology in machine vision and sensing, with an emerging need for low power consumption, a high image resolution, and reliable operation in high ambient light conditions. Therefore, we propose a novel direct time-of-flight pixel using the single-photon avalanche diode (SPAD) sensor, with an in-pixel averaging method to suppress ambient light and detect the laser pulse arrival time. The system utilizes two orthogonal sinusoidal signals applied to the pixel as inputs, which are synchronized with a pulsed laser source. The detected signal phase indicates the arrival time. To evaluate the proposed system’s potential, we developed analytical and statistical models for assessing the phase error and precision of the arrival time under varying ambient light levels. The pixel simulation showed that the phase precision is less than 1% of the detection range when the ambient-to-signal ratio is 120. A proof-of-concept pixel array prototype was fabricated and characterized to validate the system’s performance. The pixel consumed, on average, 40 μW of power in operation with ambient light. The results demonstrate that the system can operate effectively under varying ambient light conditions and its potential for customization based on specific application requirements. This paper concludes by discussing the system’s performance relative to the existing direct time-of-flight technologies, identifying their strengths and limitations.
Acquisition of Data on Kinematic Responses to Unpredictable Gait Perturbations: Collection and Quality Assurance of Data for Use in Machine Learning Algorithms for (Near-)Fall Detection
Authors: Schneider Moritz , Reich Kevin , Hartmann Ulrich , Hermanns Ingo , Kaufmann Mirko , Kluge Annette , Fiedler Armin , Frese Udo , Ellegast Rolf
Published: August 2024

Slip, trip, and fall (STF) accidents cause high rates of absence from work in many companies. During the 2022 reporting period, the German Social Accident Insurance recorded 165,420 STF accidents, of which 12 were fatal and 2485 led to disability pensions. Particularly in the traffic, transport and logistics sector, STF accidents are the most frequently reported occupational accidents. Therefore, an accurate detection of near-falls is critical to improve worker safety. Efficient detection algorithms are essential for this, but their performance heavily depends on large, well-curated datasets. However, there are drawbacks to current datasets, including small sample sizes, an emphasis on older demographics, and a reliance on simulated rather than real data. In this paper we report the collection of a standardised kinematic STF dataset from real-world STF events affecting parcel delivery workers and steelworkers. We further discuss the use of the data to evaluate dynamic stability control during locomotion for machine learning and build a standardised database. We present the data collection, discuss the classification of the data, present the totality of the data statistically, and compare it with existing databases. A significant research gap is the limited number of participants and focus on older populations in previous studies, as well as the reliance on simulated rather than real-world data. Our study addresses these gaps by providing a larger dataset of real-world STF events from a working population with physically demanding jobs. The population studied included 110 participants, consisting of 55 parcel delivery drivers and 55 steelworkers, both male and female, aged between 19 and 63 years. This diverse participant base allows for a more comprehensive understanding of STF incidents in different working environments.
Peer Review in Urology
Authors: Black Peter
Published: August 2024

Peer review is the cornerstone of scholarly publishing [...]
A Bibliometric Review of Innovations in Sustainable Tourism Research: Current Trends and Future Research Agenda
Authors: Pilelienė Lina , Grigaliūnaitė Viktorija , Bogoyavlenska Yuliya
Published: August 2024

This bibliometric review explores the existing publications regarding innovations in sustainable tourism. The aim of the review was to determine the existing research trends in the field of innovations in sustainable tourism by mapping the research on the innovations and “smart” aspects in sustainable tourism and contributing to the field by outlining the recent research trends, identifying the general topics and subtopics, and thus guiding future researchers in choosing an attractive research direction. The bibliometric analysis based on the PRISMA guidelines was provided to extract 179 all-open-access documents (articles, research papers, conference papers, and book chapters) from the Scopus database. As the research field was found to be expanding (thirty-eight documents were dated 2023 compared to one dated 2010), its attractiveness was confirmed. The analysis of the most-cited publications showed the existence of three research trends: (1) management-focused, (2) sustainability-focused, and (3) smart/ITCs-focused. Moreover, the analysis of the author keywords enabled outlining the main future research themes, namely tourism, sustainability, management, scope, innovation, smart, and method, and providing considerations for the future. For a broader dissemination of their findings, authors are encouraged to pay greater attention to these factors: inter-country collaboration, leading institution, journal choice, and topic choice.
The Evolution of Digital Cultural Heritage Research: Identifying Key Trends, Hotspots, and Challenges through Bibliometric Analysis
Authors: Lian Yuntao , Xie Jiafeng
Published: August 2024

Heritage preservation fundamentally represents an act of communication, with digitization and virtual access driving cultural heritage research development and dissemination. These tools stimulate the creation of cultural heritage content and inspire public engagement in learning about and preserving heritage. Despite substantial academic focus on digital cultural heritage (DCH) research, systematic assessment methods remain lacking. This paper researches the application of digital technologies in cultural heritage studies using CiteSpace 6.2 R4 to analyze the evolution of DCH, identifying research hotspots and predicting future trends. The key findings include the following: (1) Current DCH research focuses on countries with significant national power, but future studies should emphasize regions rich in cultural heritage and promote transnational and interdisciplinary research. (2) DCH research concentrates on three areas: the use of VR, AR, and other interactive digital technologies to enhance cultural heritage experiences; the development of cultural relic databases and digital archives; and the implementation of interactive exhibitions and multimedia guides. (3) Identified research hotspots include user immersion experiences, language and identity, and virtual reality technologies. Digital technologies enhance cultural heritage communication by driving innovations in preservation, information management, and digitization. (4) Future research should focus on practical DCH development, emphasizing innovative virtual technologies, database integration, and standardized assessment methods. These efforts aim to provide valuable insights for the sustainable global preservation and dissemination of cultural heritage. The use of digital technologies in cultural heritage is becoming increasingly important, but there is still a need to strike a balance between technological development and heritage preservation to ensure the sustainability of cultural heritage.
The Role of Some Biostimulants in Improving the Productivity of Orange
Authors: Almutairi Khalid F. , Sas-Paszt Lidia , Mosa Walid F. A.
Published: August 2024

One of the environmental problems that affects negatively orange productivity is drought because it greatly minimizes the growth attributes, photosynthetic process, water uptake, percentage of fruit set, and productivity; meanwhile, it raises the rates of respiration and transpiration, as well as the premature and preharvest fruit drop percentages. In addition, drought creates osmotic stress, affects the relationship between plants and water, reduces the amount of water in shoots, and prevents plant cell development and expansion. It is very important to search for a solution to minimize the effect of drought stress; therefore, the present study has investigated the effect of the application of humic acid (HA) at 0, 1 and 2 kg per tree and spraying of seaweed extract (SWE) at 0.2, 0.3 and 4% in combination with moringa leaf extract (MLE) at 2, 4 and 6%, respectively, on the productivity, fruit quality and nutritional status of navel orange cv. Washington during the 2022 and 2023 seasons. The results proved that the application of the biostimulants individually or in combination significantly positively changed the vegetative growth, productivity, fruit quality parameters and leaf mineral content of macro- and micronutrients of the treated trees compared to untreated trees. The superior treatments which gave the best results were 2 kg HA + 0.4% SWE + 6% MLE followed by 2 kg HA + 0.3% SWE + 4% MLE over the rest of the applied treatments.
Multi-Agent Decision-Making in Construction Engineering and Management: A Systematic Review
Authors: Hu Yifei , Wu Liu , Li Ni , Zhao Tianwei
Published: August 2024

Construction engineering and management (CEM) involves multiple stakeholders, complex interest relationships, and conflicts. All stakeholders must comprehensively consider the interests relating to a project to make decisions. Appropriate multi-agent decision-making can effectively coordinate and integrate the needs or expectations of all stakeholders, which can reduce conflicts, improve the success probability of the project, maximize the overall returns on interest, and contribute to the project’s sustainability. Existing studies have begun to explore the associated theoretical framework and practical methods for multi-agent decision-making. However, early studies mainly focused on the conceptual theories of decision-making models and processes, such as stakeholder analysis, decision evaluation, and risk management. In recent years, increasing research has concerned the application of multi-agent decision-making in CEM. This paper is the first to use a comprehensive review approach to analyze multi-agent decision-making in CEM, providing an overall perspective. In this paper, 105 journal papers are identified and classified into four categories: (1) main concerns regarding multi-agent decision-making in CEM; (2) tools and methods of multi-agent decision-making in practice; (3) research tools and methods of multi-agent decision-making in CEM; (4) critical points on how to solve multi-agent decision-making problems. The findings of this study offer references for future trends in four regards, namely (1) knowledge management, (2) decision resilience, (3) the fusion of many techniques, and (4) technologies for future research.
Unravelling the Missing Link: Climate Risk, ESG Performance and Debt Capital Cost in China
Authors: Yan Yu , Cheng Xinman , Ong Tricia
Published: August 2024

The concept of sustainability has developed significantly from an unrealistic abstract ideology to a framework that can measure companies’ environment, society and corporate governance (ESG) performance. While extensive research has established some relational impacts of ESG performance on debt capital cost (DCC), this paper contends that a comprehensive review of these impacts is incomplete without screening them through the lens of climate risk (CR). Companies are subjected to CR that comprises physical and transition factors resulting from climate change. This paper aims to unravel the missing link between CR and ESG performance, and the consequent impacts on DCC. This paper illustrates using Chinese companies that operate in an emerging economy with robust industrial activities under intense global scrutiny to achieve emission reduction and meet carbon neutrality goals. Through considering CR, the impacts of ESG performance on DCC are explained using panel data and mediation effect tests with A-share listed enterprises on the Shanghai and Shenzhen stock exchanges from 2016 to 2020. The findings show that ESG performance significantly and negatively affects DCC, with debt default risk playing a mediating role. The negative effect of ESG performance on DCC is more significant in non-polluting enterprises and non-state-owned enterprises.
Study on the Mechanism of Multi-Scalar Transboundary Water Security Governance in the Shenzhen River
Authors: Yang Jiangmin , Huang Gengzhi
Published: August 2024

This paper examines the evolution and mechanism of multi-scalar transboundary water governance in the Shenzhen River, flowing through Shenzhen and Hong Kong since the 1980s. The research identifies three phases of governance: negotiation, consultation, and cooperation. It highlights the roles of the Shenzhen government as initiator, the Hong Kong government as collaborator, and the central government of China as participant and coordinator. The analysis indicates that severe flooding events, economic growth, and central government support are key consensus drivers. The research fills a gap in the understanding of transboundary governance, providing insights for improved cooperation and regional development between Shenzhen and Hong Kong.
Mitigation of Photovoltaics Penetration Impact upon Networks Using Lithium-Ion Batteries
Authors: Bin Hudayb Khalid Abdullah , Al-Shaalan Abdullah M. , Hussein Farh Hassan M.
Published: August 2024

The paper conducts a comprehensive analysis of the impact of very large-scale photovoltaic generation systems on various aspects of power systems, including voltage profile, frequency, active power, and reactive power. It specifically investigates IEEE 9-bus, 39-bus, and 118-bus test systems, emphasizing the influence of different levels of photovoltaic penetration. Additionally, it explores the effectiveness of battery energy storage systems in enhancing system stability and transient response. The transition to PV generation alters system stability characteristics, impacting frequency response and requiring careful management of PV plant locations and interactions with synchronous generators to maintain system reliability. This study highlights how high penetration of photovoltaic systems can improve steady-state voltage levels but may lead to greater voltage dips in contingency scenarios. It also explores how battery energy storage system integration supports system stability, showing that a balance between battery energy storage system capacity and synchronous generation is essential to avoid instability. In scenarios integrating photovoltaic systems into the grid, voltage levels remained stable at 1 per unit and frequency was tightly controlled between 49.985 Hz and 50.015 Hz. The inclusion of battery energy storage systems further enhanced stability, with 25% and 50% battery energy storage system levels maintaining strong voltage and frequency due to robust grid support and sufficient synchronous generation. At 75% battery energy storage system, minor instabilities arose as asynchronous generation increased, while 100% battery energy storage system led to significant instability and oscillations due to minimal synchronous generation. These findings underline the importance of synchronous generation for grid reliability as battery energy storage system integration increases.
Health Equity and Health Inequity of Disabled People: A Scoping Review
Authors: Wolbring Gregor , Deloria Rochelle
Published: August 2024

Health equity is an important aspect of wellbeing and is impacted by many social determinants. The UN Convention on the Rights of Persons with Disabilities (CRPD) is a testament to the lack of health equity and the many health inequity issues based on social determinants experienced by disabled people. The health equity/health inequity situation of disabled people is even worse if their identities intersect with those of other marginalized groups. Many societal developments and discussions including discussions around the different sustainability pillars can influence the health equity/health inequity of disabled people. The general aim of this study was to better understand the academic engagement with the health equity and health inequity of disabled people beyond access to healthcare. To fulfill our aim, we performed a scoping review of academic abstracts using a hit count manifest coding and content analysis approach to abstracts obtained from SCOPUS, the 70 databases of EBSCO-HOST, Web of Science, and PubMed. Health equity and health inequity abstracts rarely cover disabled people as a group, less with many specific groups of disabled people, and even less or not at all with the intersectionality of disabled people belonging to other marginalized groups. Many social determinants that can influence the health equity and health inequity of disabled people were not present. Ability-based concepts beyond the term ableism, intersectionality-based concepts, and non-health based occupational concepts were not present in the abstracts. Our qualitative content analysis of the 162 abstracts containing health equity and disability terms and 177 containing health inequity and disability terms found 65 relevant abstracts that covered problems with health equity disabled people face, 17 abstracts covered factors of health inequity, and 21 abstracts covered actions needed to deal with health inequity. Our findings suggest a need as well as many opportunities for academic fields and academic, policy, and community discussions to close the gaps in the coverage of health equity and health inequity of disabled people.
Reducing Ammonia Emissions in Polish Agriculture, the Implementation of the NEC Directive, and the Context of Sustainable Development—Pilot Studies
Authors: Mielcarek-Bocheńska Paulina , Rzeźnik Wojciech
Published: August 2024

Reducing environmental pollution, including air pollution, contributes to improving people’s health and quality of life, which is one of the goals of sustainable development. One of the important air pollutants is ammonia, which is mainly emitted from the agriculture sector. This sector is responsible for over 81% of global ammonia emissions. The aim of this research was a preliminary assessment of the implementation status of methods for reducing ammonia emissions on farms and to learn the views and awareness of agricultural producers on reducing emissions of pollutants into the air. The research was conducted using a survey questionnaire that was made available to farmers in various ways. Based on the results, it can be concluded that farmers have knowledge of environmental protection and agree that people have an impact on the environment. Low-emission practices to reduce ammonia emissions from agricultural sources are not widely used. The best situation is considering reduction practices in the storage of natural fertilizers and the use of low-emission fertilizer application techniques. The results of this type of monitoring research may be useful in determining the level of ammonia emission reduction. In the future, the data may be used during air pollution inventories conducted by state institutions.
Is More Always Better? Government Attention and Environmental Governance Efficiency: Empirical Evidence from China
Authors: Wang Fengyu , Zhou Mi , Yu Huansheng
Published: August 2024

In recent years, the thorough implementation of China’s green development concept has compelled local governments to devote more attention to environmental issues. This study aimed to verify whether increased government environmental attention (GEA) can sustainably ensure the implementation of environmental governance, particularly air pollution control. Using government work reports (GWRs) from local governments, this study employed machine learning methods to identify and quantify the attitudes of government officials as expressed in policy texts. A weighted dictionary method was used to quantify GEA from 2011 to 2016. The results of spatial econometric models indicated that air pollution exhibited positive spatial clustering effects across different regions, with the Yangtze River Delta and the Beijing–Tianjin–Hebei region being classified as high–high areas, while the western regions were classified as low–low areas. Baseline regression results showed that increased GEA can improve the effectiveness of pollution control, but excessive attention leads to a decline in governance efficiency. Overall, this study helps explain the unsustainability of campaign-style environmental governance and provides guidance for local governments on the rational allocation of attention when addressing environmental issues.