bluuebunny/crossref_metadata_2025 huggingface dataset:
System Identification for Robust Control of an Electrode Positioning System of an Industrial Electric Arc Melting Furnace
Authors: Feliu-Batlle Vicente , Rivas-Perez Raul , Borges-Rivero Romar A. , Misa-Llorca Roger
Published: November 2024

Through system identification for robust control methods and utilizing real-time experimental field data, a comprehensive mathematical model is derived that represents the dynamic performance of a single electrode positioning system (EPS) in an industrial electric arc melting furnace (EAF). This EPS is characterized by large, time-varying dynamic parameters, which fluctuate based on operating conditions, specifically as the electrode weight changes within its operational range. The system identification methodology for robust control is developed in four main steps, progressing from experimental design to model validation. This approach yields a nominal model of the actual system and provides a trustworthy estimate of the region of uncertainty of the model, bounded by models of the real system under maximum and minimum electrode weight conditions (limit operating models). The methodology generates three fourth-order time-delay models using an ARMAX structure. The results are promising, as system identification for robust control enables the derivation of mathematical models specifically tailored for designing robust controllers. These controllers significantly enhance the EPS control system’s performance and substantially reduce energy consumption and environmental emissions.
Application of a Reservoir Classification Method Based on Core Data from Offshore Tight Reservoirs: A Case Study of the Liushagang Formation in the Beibu Basin
Authors: Gao Xinchen , Wang Liang , Zeng Zihao , Li Qiangyu , Jin Yuhang , Guo Kangliang
Published: November 2024

Several methods are currently used to test offshore tight reservoirs. However, the effectiveness of these applications varies among wells, and some exhibit unclear reservoir classifications. These issues lead to difficulties in decision-making during tests and result in higher testing costs. Therefore, to address this issue, this study used reservoirs in the Liushagang Formation of the Beibu Basin as the research object and employed core data to apply the multi-stage FZI method. This method computes the FZI and its cumulative probability, classifying the target reservoir into seven distinct types. According to the Winland R35 method, the target reservoir was classified into five distinct types. Seven characteristic parameters were selected based on the mercury injection experimental data. The K-means clustering method was then used to classify the target reservoirs into two types. The conclusions were that, in this formation, there is predominantly low to extra-low porosity and extra-low to ultra-low permeability. According to relationship models, logged porosity can be used to calculate effective permeability. Combining the multi-stage FZI method with the K-means clustering method for reservoir classification is recommended. This integrated approach facilitates a more comprehensive analysis of the characteristics of offshore low-permeability tight reservoirs at both macro and micro scales after classification. This research provides key insights for enhancing offshore well production.
Christian Nationalism, Civic Republicanism, and Radical Secularism in Contemporary American Politics over Time
Authors: Smidt Corwin E.
Published: November 2024

Over the past decade, a burgeoning strand of scholarly and journalistic literature has emerged that emphasizes the role of Christian nationalism within contemporary American politics. Unfortunately, this scholarly literature has mushroomed so quickly that relatively little attention has been given to its conceptual underpinnings and how Christian nationalism may be related to, or different from, other conceptualizations of the role of religion in public life. This article outlines different conceptualizations of Christian nationalism that have been advanced, analyzes how different coding schemes of its present measurement yields different assessments of its presence within American politics, and differentiates between and among different types of approaches to the role of religion in American public life. Using data drawn from Baylor national surveys on religion conducted in 2007, 2017, and 2021, this article examines three distinct groups within American politics—namely, Christian nationalists, civic republicans, and radical secularists—and how the relative size and characteristics of such groups have changed within American society over time.
Defeating the Dark Sides of FinTech: A Regression-Based Analysis of Digitalization’s Role in Fostering Consumers’ Financial Inclusion in Central and Eastern Europe
Authors: Panait Mirela Clementina , Apostu Simona Andreea , Gigauri Iza , Confetto Maria Giovanna , Palazzo Maria
Published: November 2024

Financial technologies metamorphose economies with customer-focused innovation. In this way, financial inclusion is fostered and economic growth is increased. However, risks, trust issues, and ethical concerns stem from the faster advancement of digital technologies and expanding financial innovation. Thus, this paper aims to understand the risks and barriers associated with FinTech and consumer adoption, focussing on the impact of digitalization on financial products/services’ acceptance. The research investigates the impact of digitalization on financial services and the recognition of the role played in the global economy by FinTech. For this reason, the regression analysis was used to explore the influence and correlation of various variables on FinTech in Central and Eastern European (CEE) countries, such as Internet usage, online shopping, paying bills via the Internet, and making and receiving digital payments. The results show differences between three clusters of CEEs in terms of FinTech adoption. While several past studies have explored the advantages of FinTech, few studies have investigated the risks associated with its adoption, trust, and barriers to its usage in different country contexts. The present paper fills the gap by analysing the data on Internet usage, online shopping, paying bills via Internet, and sending or receiving digital payments in CEE countries. The study recommends that FinTech companies share information online not only to present their offerings to users, but also to promote financial education through clear and straightforward communication about the features of their services. This approach can indirectly benefit society by contributing to financial development, inclusion, social stability, and, consequently, sustainable development.
HaptiScan: A Haptically-Enabled Robotic Ultrasound System for Remote Medical Diagnostics
Authors: Najdovski Zoran , Pedrammehr Siamak , Chalak Qazani Mohammad Reza , Abdi Hamid , Deshpande Sameer , Liu Taoming , Mullins James , Fielding Michael , Hilton Stephen , Asadi Houshyar
Published: November 2024

Medical ultrasound is a widely used diagnostic imaging modality that provides real-time imaging at a relatively low cost. However, its widespread application is hindered by the need for expert operation, particularly in remote regional areas where trained sonographers are scarce. This paper presents the development of HaptiScan, a state-of-the-art telerobotic ultrasound system equipped with haptic feedback. The system utilizes a commercially available robotic manipulator, the UR5 robot from Universal Robots, integrated with a force/torque sensor and the Phantom Omni haptic device. This configuration enables skilled sonographers to remotely conduct ultrasound procedures via an internet connection, addressing both the geographic and ergonomic limitations faced in traditional sonography. Key innovative features of the system include real-time force feedback, ensuring that sonographers can precisely control the ultrasound probe from a remote location. The system is further enhanced by safety measures such as over-force sensing, patient discomfort monitoring, and emergency stop mechanisms. Quantitative indicators of the system’s performance include successful teleoperation over long distances with time delays, as demonstrated in simulations. These simulations validate the system’s control methodologies, showing stable performance with force feedback under varying time delays and distances. Additionally, the UR5 manipulator’s precision, kinematic, and dynamic models are mathematically formulated to optimize teleoperation. The results highlight the effectiveness of the proposed system in overcoming the technical challenges of remote ultrasound procedures, offering a viable solution for real-world telemedicine applications.
Automatically Detected CSES Ionospheric Precursors Before Part of the Strong Aftershocks of the 23 January 2024 Wushi MS 7.1 Earthquake in Northwest China
Authors: Li Mei , Yan Hongzhu , Liu Tianyu
Published: November 2024

Earthquake prediction is still a large challenge worldwide so far. In this paper, an automatic detection method was put into service immediately after the Wushi MS 7.1 earthquake on 23 January 2024 to weekly detect possible CSES (China Seismo-Electromagnetic Satellite) precursory information before impending aftershocks. An electron perturbation with an enhanced magnitude of 38.3% was first detected on 24 January 2024 at night orbit 33175 and the corresponding variations in different plasma parameters measured at this orbit presented a typical feature of electron depletion or plasma bubble with an abrupt decrease and then an increase after one minute. The Kp index was also checked during this period and the values reached 3.7 once on 23 and 24 January, which indicates that these ionospheric variations probably originated from solar activities instead of three strong aftershocks with a magnitude more than five in the following three days. However, uncertainties still exist. Then, an electron perturbation with amplitude of 24.6%, as well as an O+ one of 27.3%, was successfully searched automatically at the same revisiting orbit 33251 on 3 February 2024 in a magnetically quiet period. These two plasma variations, as well as ones of other ionospheric parameters, were characterized by highly synchronous properties, which increase the availability as seismic precursors. However, no obvious variations were observed at other revisiting orbits or other orbits near the aftershock areas during this period. An aftershock with magnitude of MS 5.3 and the strongest one of MS 5.8 took place on 24 and 25 February, respectively, 20 days after and 1000 km away.
Estimation of Crop Residue Cover Utilizing Multiple Ground Truth Survey Techniques and Multi-Satellite Regression Models
Authors: Williams Forrest , Gelder Brian , Presley DeAnn , Pape Bryce , Einck Andrea
Published: November 2024

Soil erosion within agricultural landscapes has significant environmental and economic impacts and is strongly driven by reduced residue cover in agricultural fields. Large-area soil erosion models such as the Daily Erosion Project are important tools for understanding the patterns of soil erosion, but they rely on the accurate estimation of crop residue cover over large regions to infer the tillage practices, an erosion model input. Remote sensing analyses are becoming accepted as a reliable way to estimate crop residue cover, but most use localized training datasets that may not scale well outside small study areas. An alternative source of training data may be commonly conducted tillage surveys that capture information via rapid “windshield” surveys. In this study, we utilized the Google Earth Engine to assess the utility of three crop residue survey types (windshield tillage surveys, windshield binned residue surveys, and photo analysis surveys) and one synthetic survey (retroactively binned photo analysis data) as sources of training data for crop residue cover regressions. We found that neither windshield-based survey method was able to produce reliable regressions but that they can produce reasonable distinctions between low-residue and high-residue fields. On the other hand, both photo analysis and retroactively binned photo analysis survey data were able to produce reliable regressions with r2 values of 0.57 and 0.56, respectively. Overall, this study demonstrates that photo analysis surveys are the most reliable dataset to use when creating crop residue cover models, but we also acknowledge that these surveys are expensive to conduct and suggest some ways these surveys could be made more efficient in the future.
The Spatiotemporal Evolution of the Mudflat Wetland in the Yellow Sea Using Landsat Time Series
Authors: Huang Zicheng , Tang Wei , Zhao Chengyi , Jiao Caixia , Zhu Jianting
Published: November 2024

Mudflat wetland, one of the 27 surface elements identified by the International Geographic Data Committee, has undergone substantial transformations with the rapid growth of the social economy and marine hazards, resulting in significant changes in its area and distribution. Quick identification of mudflat wetland evolution is vital to improve the mudflat ecological service value. We employed object-oriented and decision tree classification methods to map the mudflat wetland in the Yellow Sea using the Landsat time series from 1983 to 2020. The Improved Spectral Water Index (IWI) was established by combining the characteristics of many ratio indices and using ratio operation and quadratic power operation. The coefficient of variation (CV) of the IWI was calculated, and the range of the intertidal zone in 1983, 1990, 2000, 2010, and 2020 was obtained by using a threshold method. The results indicate that the mudflat wetland area decreased continuously from 1983 to 2020, with a reduction of 337.38 km2/10a. Among the total area, the natural wetland experienced a decline of 446.9 km2/10a, with the most drastic changes occurring between 2000 and 2010. In contrast, the area of the human-made wetland increased by 109.56 km2/10a. Over the 38 years, the tidal flat has undergone the most drastic reduction, with an average of 157.45 km2/10a. From 1983 to 2020, the intertidal zone area decreased, with a reduction of 429.02 km2/10a. Human activities were the key factors causing mudflat wetland loss. Based on these findings, we propose several policy suggestions. This study provides a scientific basis for understanding the synergetic evolution mechanism of coastal resources utilization and mudflat wetland protection under global change.
A Radio Frequency Interference Screening Framework—From Quick-Look Detection Using Statistics-Assisted Network to Raw Echo Tracing
Authors: Shen Jiayuan , Han Bing , Li Yang , Pan Zongxu , Yin Di , Feng Yugang , Li Guangzuo
Published: November 2024

Synthetic aperture radar (SAR) is often affected by other high-power electromagnetic devices during ground observation, which causes unintentional radio frequency interference (RFI) with the acquired echo, bringing adverse effects into data processing and image interpretation. When faced with the task of screening massive SAR data, there is an urgent need for the global perception and detection of interference. The existing RFI detection method usually only uses a single type of data for detection, ignoring the information association between the data at all levels of the real SAR product, resulting in some computational redundancy. Meanwhile, current deep learning-based algorithms are often unable to locate the range of RFI coverage in the azimuth direction. Therefore, a novel RFI processing framework from quick-looks to single-look complex (SLC) data and then to raw echo is proposed. We take the data of Sentinel-1 terrain observation with progressive scan (TOPS) mode as an example. By combining the statistics-assisted network with the sliding-window algorithm and the error-tolerant training strategy, it is possible to accurately detect and locate RFI in the quick looks of an SLC product. Then, through the analysis of the TOPSAR imaging principle, the position of the RFI in the SLC image is preliminarily confirmed. The possible distribution of the RFI in the corresponding raw echo is further inferred, which is one of the first attempts to use spaceborne SAR data to elucidate the RFI location mapping relationship between image data and raw echo. Compared with directly detecting all of the SLC data, the time for the proposed framework to determine the RFI distribution in the SLC data can be shortened by 53.526%. All the research in this paper is conducted on Sentinel-1 real data, which verify the feasibility and effectiveness of the proposed framework for radio frequency signals monitoring in advanced spaceborne SAR systems.
3Cat-8 Mission: A 6-Unit CubeSat for Ionospheric Multisensing and Technology Demonstration Test-Bed
Authors: Contreras-Benito Luis , Osipova Ksenia , Buitrago-Leiva Jeimmy Nataly , Gracia-Sola Guillem , Coppa Francesco , Climent-Salazar Pau , Sopena-Coello Paula , Garcín Diego , Ramos-Castro Juan , Camps Adriano
Published: November 2024

This paper presents the mission analysis of 3Cat-8, a 6-Unit CubeSat mission being developed by the UPC NanoSat Lab for ionospheric research. The primary objective of the mission is to monitor the ionospheric scintillation of the aurora, and to perform several technological demonstrations. The satellite incorporates several novel systems, including a deployable Fresnel Zone Plate Antenna (FZPA), an integrated PocketQube deployer, a dual-receiver GNSS board for radio occultation and reflectometry experiments, and a polarimetric multi-spectral imager for auroral emission observations. The mission design, the suite of payloads, and the concept of operations are described in detail. This paper discusses the current development status of 3Cat-8, with several subsystems already developed and others in the final design phase. It is expected that the data gathered by 3Cat-8 will contribute to a better understanding of ionospheric effects on radio wave propagation and demonstrate the feasibility of compact remote sensors in a CubeSat platform.
The Seismic Surface Rupture Zone in the Western Segment of the Northern Margin Fault of the Hami Basin and Its Causal Interpretation, Eastern Tianshan
Authors: Sun Hao , Yuan Daoyang , Su Ruihuan , Li Shuwu , Wang Youlin , Wen Yameng , Chen Yanwen
Published: November 2024

The Eastern Tianshan region, influenced by the far-field effect of northward compression and expansion of the Qinghai-Xizang block, features highly developed Late Quaternary active faults that exhibit significant neotectonic activity. Historically, the Barkol-Yiwu Basin, located to the north of the Eastern Tianshan, experienced two major earthquakes in 1842 and 1914, each with a magnitude of M71/2. In contrast, the Hami Basin on the southern margin of the Eastern Tianshan has no historical records of any major earthquakes, and its seismic potential, mechanisms, and future earthquake hazards remain unclear. Based on satellite image interpretation and field surveys, this study identified a relatively recent and well-preserved seismic surface rupture zone with good continuity in the Liushugou area of the western segment of the Northern Margin Fault of the Hami Basin (HMNF), which is the seismogenic structure responsible for the rupture. The surface rupture zone originates at Kekejin in the east, extends intermittently westward through Daipuseke Bulake and Liushugou, and terminates at Wuzun Bulake, with a total length of approximately 21 km. The rupture zone traverses the youngest geomorphic surface units, such as river beds or floodplains and first-order terraces (platforms), and is characterized by a series of single or multiple reverse fault scarps. The morphology of fault scarps is clear, presenting a light soil color with heights ranging from 0.15 m to 2.13 m and an average displacement of 0.56 m, suggesting that this surface rupture zone likely represents the most recent seismic event. Comparison with historical earthquake records in the Eastern Tianshan region suggests that the rupture zone may have been formed simultaneously with the Xiongkuer rupture zone by the 1842 M71/2 earthquake along the boundary faults on both sides of the Barkol Mountains, exhibiting a flower-like structural pattern. Alternatively, it might represent a separate, unrecorded seismic event occurring shortly after the 1842 earthquake. The estimated magnitude of the associated earthquake is about 6.6~6.9. Given that surface-rupturing earthquakes have already occurred in the western segment, the study indicates that the Erdaogou–Nanshankou section of the HMNF has surpassed the average recurrence interval for major earthquakes, indicating a potential future earthquake hazard.
Feature Intensification Using Perception-Guided Regional Classification for Remote Sensing Image Super-Resolution
Authors: Li Yinghua , Xie Jingyi , Chi Kaichen , Zhang Ying , Dong Yunyun
Published: November 2024

In recent years, super-resolution technology has gained widespread attention in the field of remote sensing. Despite advancements, current methods often employ uniform reconstruction techniques across entire remote sensing images, neglecting the inherent variability in spatial frequency distributions, particularly the distinction between high-frequency texture regions and smoother areas, leading to computational inefficiency, which introduces redundant computations and fails to optimize the reconstruction process for regions of higher complexity. To address these issues, we propose the Perception-guided Classification Feature Intensification (PCFI) network. PCFI integrates two key components: a compressed sensing classifier that optimizes speed and performance, and a deep texture interaction fusion module that enhances content interaction and detail extraction. This network mitigates the tendency of Transformers to favor global information over local details, achieving improved image information integration through residual connections across windows. Furthermore, a classifier is employed to segment sub-image blocks prior to super-resolution, enabling efficient large-scale processing. The experimental results on the AID dataset indicate that PCFI achieves state-of-the-art performance, with a PSNR of 30.87 dB and an SSIM of 0.8131, while also delivering a 4.33% improvement in processing speed compared to the second-best method.
Quantifying the Geomorphological Susceptibility of the Piping Erosion in Loess Using LiDAR-Derived DEM and Machine Learning Methods
Authors: Li Sisi , Hu Sheng , Wang Lin , Zhang Fanyu , Wang Ninglian , Wu Songbai , Wang Xingang , Jiang Zongda
Published: November 2024

Soil piping erosion is an underground soil erosion process that is significantly underestimated or overlooked. It can lead to intense soil erosion and trigger surface processes such as landslides, collapses, and channel erosion. Conducting susceptibility mapping is a vital way to identify the potential for soil piping erosion, which is of enormous significance for soil and water conservation as well as geological disaster prevention. This study utilized airborne radar drones to survey and map 1194 sinkholes in Sunjiacha basin, Huining County, on the Loess Plateau in Northwest China. We identified seventeen key hydrogeomorphological factors that influence sinkhole susceptibility and used six machine learning models—support vector machine (SVM), logistic regression (LR), Convolutional Neural Network (CNN), K-Nearest Neighbors (KNN), random forest (RF), and gradient boosting decision tree (GBDT)—for the susceptibility assessment and mapping of loess sinkholes. We then evaluated and validated the prediction results of various models using the area under curve (AUC) of the Receiver Operating Characteristic Curve (ROC). The results showed that all six of these machine learning algorithms had an AUC of more than 0.85. The GBDT model had the best predictive accuracy (AUC = 0.94) and model migration performance (AUC = 0.93), and it could find sinkholes with high and very high susceptibility levels in loess areas. This suggests that the GBDT model is well suited for the fine-scale susceptibility mapping of sinkholes in loess regions.
Mineral Heterostructures for Simultaneous Removal of Lead and Arsenic Ions
Authors: Spasojević Tijana , Ćujić Mirjana , Marjanović Vesna , Veličković Zlate , Kokunešoski Maja , Grujić Aleksandra Perić , Đolić Maja
Published: November 2024

This study focuses on Pb2+ and As(V) adsorption on mineral heterostructures based on a mixture of Si, Fe, and Ti oxides (MOHs). Various techniques were performed to analyze the morphological and structural properties of the synthesized metal oxide samples. In addition to the experimental optimization of the parameters determined by the response surface method (RSM), the effects of pH, adsorbent dosage, temperature, and contact duration on the batch and column system adsorption efficiency of single-component and simultaneous lead and arsenate removal were tested. The pseudo-second-order kinetic model and Weber–Morris model were more relevant to the adsorption on the metal(loid)s. The adsorption of Pb2+ was related to the Langmuir isotherm model, while the adsorption of As(V) was fitted to the Freundlich isotherm model. The thermodynamic parameters indicate the spontaneity of the adsorption process with a low endothermic character. The MOHs were more effective in removing Pb2+ and As(V) in the multi-component system (87.7 and 46.1%, respectively) than in the single-component system (56.3 and 23.4%, respectively). This study demonstrates that mineral heterostructures can be effectively used to remove cations and anions from water systems, and due to their fast kinetics, they can be applied to the needs of rapid interventions after pollution.
Copper–Chitosan-Modified Magnetic Textile as a Peroxidase-Mimetic Catalyst for Dye Removal
Authors: Safarik Ivo , Prochazkova Jitka , Zelena Pospiskova Kristyna
Published: November 2024

Copper chitosan attached to a magnetic synthetic nonwoven textile was manufactured using a simple, rapid, and green procedure employing chitosan dissolved in diluted acetic acid and treatment with copper sulfate solution. The prepared copper–chitosan-modified textile exhibited peroxidase-mimetic activity which was subsequently used for the degradation (decolorization) of important organic dyes, namely methylene blue, Congo red, and Bismarck brown Y, in the presence of hydrogen peroxide. After 5 h of treatment at 22 °C, 87.5%, 79.5%, and 87.7% dye removal were observed for methylene blue, Congo red, and Bismarck brown Y, respectively. The textile bound catalyst can be easily recovered from the reaction mixture after the process is completed.
New Trends of Thought in Response to Post-Pandemic Work Precariousness Among Second-Generation Romanian Citizens in Spain
Authors: Marcu Silvia
Published: November 2024

Drawing on 65 in-depth interviews with young Romanians between 22 and 33 years old, the contribution of this article is to offer an innovative analysis of the work experiences of second-generation young people who, having studied and completed their degrees in Spain during the pandemic, are developing their skills and creativity in a difficult labour market. I argue that unlike their parents’ generation, who in many cases have returned home or practice mobility, this generation wishes to remain in Spain. Consequently, the (im)mobility experienced by second-generation young people has become a fundamental post-pandemic trend. Three interlinked profiles were identified: (1) young graduates doing work for which they are overqualified, who want to find better jobs; (2) young people who have completed master’s or doctoral degrees and now have their own business, are applying for research funding or are unemployed; and (3) unemployed graduates who are making a living from self-employment or aspire to have their own business. The conclusions highlight new trends of thought among young Romanians educated and trained during the pandemic in terms of how to overcome work precariousness and live in Spain.
Some Exact Green Function Solutions for Non-Linear Classical Field Theories
Authors: Frasca Marco , Groote Stefan
Published: November 2024

We consider some non-linear non-homogeneous partial differential equations (PDEs) and derive their exact Green function solution as a functional Taylor expansion in powers of the source. The kind of PDEs we consider are dispersive ones where the exact solution of the corresponding homogeneous equations can have some known shape. The technique has a formal similarity with the Dyson–Schwinger set of equations to solve quantum field theories. However, there are no physical constraints. Indeed, we show that a complete coincidence with the statistical field model of a quartic scalar theory can be achieved in the Gaussian expansion of the cumulants of the partition function.
Point Cloud Registration Method Based on Improved TLBO for Landing Gear Components Measurement
Authors: Xia Junyong , Li Biwei , Xu Zhiqiang , Zhong Fei , Hei Xiaotao
Published: November 2024

When using point cloud technology to measure the dimension and geometric error of aircraft landing gear components, the point cloud data obtained after scanning may have certain differences because of the sophistication and diversity of the components that make up the landing gear. However, when using traditional point cloud registration algorithms, if the initial pose between point clouds is poor, it can lead to significant errors in the final registration results or even registration failure. Furthermore, the significant difference in registration results between point clouds can affect the final measurement results. Adopting Teaching-Learning-Based Optimization (TLBO) to solve some optimization problems has unique advantages such as high accuracy and good stability. This study integrates TLBO with point cloud registration. To increase the probability of using TLBO for point cloud registration to search for the global optimal solution, adaptive learning weights are first introduced during the learner phase of the basic TLBO. Secondly, an additional tutoring phase has been designed based on the symmetry and unimodality of the normal distribution to improve the accuracy of the solution results. In order to evaluate the performance of the proposed algorithm, it was first used to solve the CEC2017 test function. The comparison results with other metaheuristics showed that the improved TLBO has excellent comprehensive performance. Then, registration experiments were conducted using the open point cloud dataset and the landing gear point cloud dataset, respectively. The registration results showed that the point cloud registration method proposed in this paper has strong competitiveness.
Regular Dodecahedron-Based Network Structures
Authors: Jenczyk Jacek
Published: November 2024

The packing and assembly of Platonic solids have fascinated mathematicians for ages. Recently, this fundamental geometrical problem has also attracted the attention of physicists, chemists, and engineers. This growing interest is due to the rapid advancements in various related fields, ranging from the formation of colloidal crystals and the design of metal–organic frameworks to the development of ultra-lightweight metamaterials, which are closely tied to the fast-evolving 3D printing technology. Numerous reports have focused on the assembly of Platonic polyhedra, particularly tetrahedra, for which an optimal packing strategy remains unidentified to this day. However, less attention has been given to the dodecahedron and its networks. This work introduces a new type of framework, designed from regular dodecahedra combined with icosahedron-based binders. The relatively simple design protocol employed here results in a remarkable variety of intriguing networks, which could be potentially useful in fields such as architecture, regenerative medicine, or aeronautics. Additionally, the dodecahedral networks presented in this study led to the discovery of intriguing structures resembling distorted graphene sheets. These structures exhibit features characteristic of both graphene and diamond.
A Variational Approach to Analyze the Settlement of Existing Tunnels Caused by Ground Surcharge
Authors: Chai Tianjian , Yan Jianwei , Jiang Xuehui , Li Jiabao
Published: November 2024

This paper presents a variational approach to assess the settlement of the operational shield tunnels resulting from surface loading. The vertical additional force on the tunnel, induced by the surcharge, was computed using the Boussinesq solution. The structural behavior of the tunnel was modeled using the Timoshenko beam theory, which accounts for both bending and shear deformation mechanisms. Furthermore, the two-parameter Pasternak foundation model, which accounts for the continuity of foundation deformation, was used to model the interaction between the tunnel and the surrounding ground. A finite Fourier series was employed to approximate the vertical displacement and cross-sectional rotation angle of the tunnel. By conducting work and energy analyses, the energy balance equations for the tunnel and the soil were obtained. The governing equations were then formulated according to the minimum potential energy principle. The displacement and cross-sectional rotation angle of the tunnel were then expressed through the variational method. The accuracy of the proposed method was validated by comparison with in situ measurement data, confirming its effectiveness in predicting tunnel responses under a ground surcharge. Finally, a parametric study was conducted to evaluate the impact of various parameters on the settlement of the shield tunnel.
Reliability Analysis for Unknown Age Class of Lifetime Distribution with Real Applications in Medical Science
Authors: Bakr Mahmoud E. , Balogun Oluwafemi Samson , El-Toony Asmaa A. , Gadallah Alaa. M.
Published: November 2024

Analyzing the reliability of the aging class of life distribution provides important information about how long a product lasts and sustainability measures that are essential for determining the environmental impact and formulating resource-saving plans. The study emphasizes the goodness-of-fit technique of the nonparametric test for the NBRUmgf class because age data are crucial for applications. Evaluations were conducted using the test’s asymptotic properties and Pitman efficiency methodology for some selected asymmetric probability models, and the outcomes were compared with those of alternative methods. We assessed the test’s power against widely used reliability distributions for some well-known alternative asymmetric distributions, including the Weibull, Gamma, and linear failure rate (LFR) distributions, and provided percentiles for both censored and uncensored data. This study shows the efficacy of the test in various sectors using real-world datasets and comprehensive tables of test statistics.
An Integrated Fuzzy Delphi and Fuzzy AHP Model for Evaluating Factors Affecting Human Errors in Manual Assembly Processes
Authors: Alqahtani Fahad M. , Noman Mohammed A.
Published: November 2024

Human errors (HEs) are prevalent issues in manual assembly, leading to product defects and increased costs. Understanding and knowing the factors influencing human errors in manual assembly processes is essential for improving product quality and efficiency. This study aims to determine and rank factors influencing HEs in manual assembly processes based on expert judgments. To achieve this objective, an integrated model was developed using two multi-criteria decision-making (MCDM) techniques—specifically, the fuzzy Delphi Method (FDM) and the fuzzy Analytic Hierarchy Process (FAHP). Firstly, two rounds of the FDM were conducted to identify and categorize the primary factors contributing to HEs in manual assembly. Expert consensus with at least 75% agreement determined that 27 factors with influence scores of 0.7 or higher significantly impact HEs in these processes. After that, the priorities of the 27 influencing factors in assembly HEs were determined using a third round of the FAHP method. Data analysis was performed using SPSS 22.0 to evaluate the reliability and normality of the survey responses. This study has divided the affecting factors on assembly HEs into two levels: level 1, called main factors, and level 2, called sub-factors. Based on the final measured weights for level 1, the proposed model estimation results revealed that the most influential factors on HEs in a manual assembly are the individual factor, followed by the tool factor and the task factor. For level 2, the model results showed a lack of experience, poor instructions and procedures, and misunderstanding as the most critical factors influencing manual assembly errors. Sensitivity analysis was performed to determine how changes in model inputs or parameters affect final decisions to ensure reliable and practical results. The findings of this study provide valuable insights to help organizations develop effective strategies for reducing worker errors in manual assembly. Identifying the key and root factors contributing to assembly errors, this research offers a solid foundation for enhancing the overall quality of final products.
An Autotuning Hybrid Method with Bayesian Optimization for Road Edge Extraction in Highway Systems from Point Clouds
Authors: Chen Jingxu , Cao Qiru , Hua Mingzhuang , Liu Jinyang , Ma Jie , Wang Di , Liu Aoxiang
Published: November 2024

In transportation infrastructure systems, feature images and spatial characteristics are generally utilized as complementary elements derived from point clouds for road edge extraction, but the involvement of one or more hyperparameters in each makes the extraction complicated. This study proposes an autotuning hybrid method with Bayesian optimization for road edge extraction in highway systems. The hybrid method combines the strengths of 2D feature images and 3D spatial characteristics while also automatically tuning the hyperparameter combination using Bayesian optimization. The hyperparameters encompass high and low pixel gradient thresholds, neighborhood radius, and normal vector threshold. Later, the point cloud dataset of national highways in Henan Province, China, is taken as the case study to evaluate the performance of the proposed method against three benchmark methods in two typical road scenarios: straight and curved edges. Experimental results show that the proposed method outperforms the benchmarks in detection quality and accuracy. It can serve as a decision-making tool to complement traditional manual road surveying, enabling efficient and automated road edge extraction in highway systems.
Advanced Processing Technologies for Innovative Materials
Authors: Grigoriev Sergey N. , Volosova Marina A. , Okunkova Anna A.
Published: November 2024

There is a need for further, in-depth research that explores the synthesis of newly developed materials created using advanced technologies [...]
Medical VR Simulator for Pediatric Strabismus Treatment
Authors: Obukhov Artem , Kutimova Elena , Matrosova Julia , Teselkin Daniil , Shilcin Maxim
Published: November 2024

In the process of treating pediatric strabismus, great difficulties arise with maintaining attention and a high level of motivation in patients. Existing computer programs and medical equipment should be supplemented with more modern tools and approaches based on virtual reality (VR) technologies, ensuring the full immersion of children in the treatment process. The aim of this study is to develop and evaluate the effectiveness of a virtual reality medical simulator for the treatment of pediatric strabismus. The specifics of the realization of ophthalmic exercises for the virtual simulator and the methods for evaluation of the quality of their performance are considered. In the course of experimental research, a control group of 58 people using the VR simulator and a reference group of 59 people receiving the standard process of strabismus treatment were compared. The average value of visual acuity in the control group increased from 66.1% to 80.4% (p = 0.002); the average value of objective strabismus angle decreased from 5° to 0° (p < 0.001). The subjective strabismus angle was also found to improve from 3° to 0° (p < 0.001). In terms of exercise quality metrics, a selected subgroup of participants who have been training for a long time have shown positive dynamics in terms of improved accuracy and a reduction in their average number of errors. In summary, virtual reality technologies demonstrated a statistically significant improvement in the metrics used to evaluate orthoptic treatment in the control group and the superiority of this approach over standard treatment.
International Proficiency Test Targeting a Large Panel of Botulinum Neurotoxin Sero- and Subtypes in Different Matrices
Authors: Rasetti-Escargueil Christine , Popoff Michel Robert , Kampa Bettina , Worbs Sylvia , Marechal Maud , Guerin Daniel , Paillares Eléa , Luginbühl Werner , Lemichez Emmanuel
Published: November 2024

Detection of botulinum neurotoxins (BoNTs) involves a combination of technical challenges that call for the execution of inter-laboratory proficiency tests (PTs) to define the performance and ease of implementation of existing diagnostic methods regarding representative BoNT toxin-types spiked in clinical, food, or environmental matrices. In the framework of the EU project EuroBioTox, we organized an international proficiency test for the detection and quantification of the clinically relevant BoNT/A, B, E, and F sero- and subtypes including concentrations as low as 0.5 ng/mL. BoNTs were spiked in serum, milk, and soil matrices. Here, we evaluate the results of 18 laboratories participating in this PT. Participants have implemented a wide array of detection methods based on functional, immunological, and mass spectrometric principles. Methods implemented in this proficiency test notably included endopeptidase assays either coupled to mass spectrometry (Endopep-MS) or enzyme-linked immunosorbent assays (Endopep-ELISA). This interlaboratory exercise pinpoints the most effective and complementary methods shared by the greatest number of participants, also highlighting the importance of combining the training of selected methods and of distributing toxin reference material to reduce the variability of quantitative data.
A Cap-Optimized mRNA Encoding Multiepitope Antigen ESAT6 Induces Robust Cellular and Humoral Immune Responses Against Mycobacterium tuberculosis
Authors: Kozlova Alena , Pateev Ildus , Shepelkova Galina , Vasileva Olga , Zakharova Natalia , Yeremeev Vladimir , Ivanov Roman , Reshetnikov Vasiliy
Published: November 2024

Background/Objectives. Tuberculosis is a deadly bacterial disease and the second most common cause of death from monoinfectious diseases worldwide. Comprehensive measures taken by health authorities in various countries in recent decades have saved tens of millions of lives, but the number of new cases of this infection has been steadily increasing in the last few years and already exceeds 10 million new cases annually. The development of new vaccines against tuberculosis is a priority area in the prevention of new cases of the disease. mRNA vaccines have already shown high efficacy against COVID-19 and other viral infections and can currently be considered a promising field of antituberculosis vaccination. In our previous study, we assessed the immunogenicity and protective activity of several types of antituberculosis mRNA vaccines with different 5′ untranslated regions, but the efficacy of these vaccines was either comparable with or lower than that of BCG. Methods. Here, we conducted a comprehensive experiment to investigate the effects of cotranscriptional capping conditions and of cap structure on the magnitude of the mRNAs’ translation in HEK293T and DC2.4 cells. The most effective cap version was used to create an antituberculosis mRNA vaccine called mEpitope-ESAT6. Results and Conclusions. We compared immunogenicity and protective activity between mEpitope-ESAT6 and BCG and found that the vaccine with the new cap type is more immunogenic than BCG. Nonetheless, the increased immunogenicity did not enhance vaccine-induced protection. Thus, the incorporation of different cap analogs into mRNA allows to modulate the efficacy of mRNA vaccines.
Oral Administration of Zinc Sulfate with Intramuscular Foot-and-Mouth Disease Vaccine Enhances Mucosal and Systemic Immunity
Authors: Lee Min Ja , Shin Seokwon , Kim Hyeong Won , Ko Mi-Kyeong , Park So Hui , Kim Su-Mi , Park Jong-Hyeon
Published: November 2024

Background/Objectives: Foot-and-mouth disease (FMD) remains a significant global threat to livestock farming. Current commercial FMD vaccines present several challenges, including the risk of infection and adverse injection site reactions due to oil-based adjuvants. The complex immune environment of the gut-associated lymphoid tissue has the potential to induce broad and diverse immune responses. Therefore, we aimed to explore the potential of zinc sulfate as an oral adjuvant to enhance intestinal mucosal immunity and complement the effects of intramuscular (IM) FMD vaccination. Methods: We conducted serological analyses on mice and pigs, measuring secretory IgA (sIgA) levels and evaluating the expression of mucosal immunity-related genes in pigs. These assessments were used to investigate the systemic and mucosal immune responses induced by oral zinc sulfate administration in combination with an IM FMD vaccine. Results: This combination strategy significantly increased structural protein antibody titers and virus neutralization titers in experimental animals (mice) and target animals (pigs) across early, mid-, and long-term periods. Additionally, this approach enhanced the expression of key cytokines associated with mucosal immunity and increased sIgA levels, which are critical markers of mucosal immunity. Conclusions: Oral zinc sulfate administration may synergize with inactivated FMD vaccines, leading to sustained and enhanced long-term immune responses. This novel strategy could reduce the frequency of required vaccinations or allow for a lower antigen dose in vaccines, effectively stimulating the mucosal immune system and boosting systemic immunity. This approach has the potential to improve the overall efficacy of commercial FMD vaccines.
The Impact of Palivizumab for Respiratory Syncytial Virus Prophylaxis on Preschool Childhood Asthma
Authors: Hasson Hannah Ora , Bachar Yoav , Hazan Itai , Golan-Tripto Inbal , Goldbart Aviv , Greenberg David , Hazan Guy
Published: November 2024

Background: The respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infections in infants and is associated with an increased risk of asthma development. Palivizumab, an RSV prophylactic, reduces RSV-related hospitalizations in high-risk infants, but its impact on long-term asthma outcomes remains unclear. This study compares asthma-related healthcare utilization in preschool children born prematurely between those who received Palivizumab (the Prophylaxis (+) group) and those who did not (the Prophylaxis (–) group). Methods: This nationwide, population-based retrospective cohort study utilized data from Clalit Healthcare Services in Israel. The study included children born between 32 + 6 and 34 + 6 weeks of gestational age from 2011 to 2018. Descriptive analysis, univariate analysis, and multivariate logistic regression were performed to compare the Prophylaxis (+) and the Prophylaxis (–) groups. Results: In total, 4503 children were included, with 3287 in the Prophylaxis (+) group and 1216 in the Prophylaxis (–) group. Palivizumab administration was associated with reduced hospitalizations for RSV bronchiolitis (1.8% vs. 3.3%, p = 0.003). However, no significant differences were observed in multivariate analysis for long-term asthma outcomes, including asthma diagnosis (OR = 1.04, CI = 0.84–1.30, p = 0.7) or emergency department visits for asthma (OR = 0.79, CI = 0.54–1.17, p = 0.2). Similarly, Palivizumab administration was not associated with the purchase of short-acting beta-agonists (OR = 1.14, 95% CI 0.98–1.32, p = 0.084), inhaled corticosteroids (OR = 1.1, CI = 0.93–1.32, p = 0.3), or oral corticosteroids (OR = 1.09, CI = 0.94–1.26, p = 0.3). Conclusions: While Palivizumab effectively reduces RSV acute bronchiolitis in preterm infants, it does not significantly impact long-term preschool asthma-related healthcare utilization.