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25 pages, 1713 KiB  
Article
Experimental Evaluation of Multi- and Single-Drone Systems with 1D LiDAR Sensors for Stockpile Volume Estimation
by Ahmad Alsayed, Fatemeh Bana, Farshad Arvin, Mark K. Quinn and Mostafa R. A. Nabawy
Aerospace 2025, 12(3), 189; https://doi.org/10.3390/aerospace12030189 (registering DOI) - 26 Feb 2025
Abstract
This study examines the application of low-cost 1D LiDAR sensors in drone-based stockpile volume estimation, with a focus on indoor environments. Three approaches were experimentally investigated: (i) a multi-drone system equipped with static, downward-facing 1D LiDAR sensors combined with an adaptive formation control [...] Read more.
This study examines the application of low-cost 1D LiDAR sensors in drone-based stockpile volume estimation, with a focus on indoor environments. Three approaches were experimentally investigated: (i) a multi-drone system equipped with static, downward-facing 1D LiDAR sensors combined with an adaptive formation control algorithm; (ii) a single drone with a static, downward-facing 1D LiDAR following a zigzag trajectory; and (iii) a single drone with an actuated 1D LiDAR in an oscillatory fashion to enhance scanning coverage while following a shorter trajectory. The adaptive formation control algorithm, newly developed in this study, synchronises the drones’ waypoint arrivals and facilitates smooth transitions between dynamic formation shapes. Real-world experiments conducted in a motion-tracking indoor facility confirmed the effectiveness of all three approaches in accurately completing scanning tasks, as per intended waypoints allocation. A trapezoidal prism stockpile was scanned, and the volume estimation accuracy of each approach was compared. The multi-drone system achieved an average volumetric error of 1.3%, similar to the single drone with a static sensor, but with less than half the flight time. Meanwhile, the actuated LiDAR system required shorter paths but experienced a higher volumetric error of 4.4%, primarily due to surface reconstruction outliers and common LiDAR bias when scanning at non-vertical angles. Full article
(This article belongs to the Special Issue UAV System Modelling Design and Simulation)
28 pages, 1352 KiB  
Article
Dynamic Modeling of Limit Order Book and Market Maker Strategy Optimization Based on Markov Queue Theory
by Fei Xie, Yang Liu, Changlong Hu and Shenbao Liang
Mathematics 2025, 13(5), 778; https://doi.org/10.3390/math13050778 (registering DOI) - 26 Feb 2025
Viewed by 4
Abstract
In recent years, high-frequency trading has become increasingly popular in financial markets, making the dynamic modeling of the limit book and the optimization of market maker strategies become key topics. However, existing studies often lacked detailed descriptions of order books and failed to [...] Read more.
In recent years, high-frequency trading has become increasingly popular in financial markets, making the dynamic modeling of the limit book and the optimization of market maker strategies become key topics. However, existing studies often lacked detailed descriptions of order books and failed to fully characterize the optimal decisions of market makers in complex market environments, especially in China’s A-share market. Based on Markov queue theory, this paper proposes the dynamic model of the limit order and the optimal strategy of the market maker. The model uses a state transition probability matrix to refine the market diffusion state, order generation, and trading process and incorporates indicators such as optimal quote deviation and restricted order trading probability. Then, the optimal control model is constructed and the reference strategy is derived using the Hamilton–Jacobi–Bellman (HJB) equation. Then, the key parameters are estimated using the high-frequency data of Ping An Bank for a single trading day. In the empirical aspect, the six-month high-frequency trading data of 114 representative stocks in different market states such as the bull market and bear market in China’s A-share market were selected for strategy verification. The results showed that the proposed strategy had robust returns and stable profits in the bull market and that frequent capture of market fluctuations in the bear market can earn relatively high returns while maintaining 50% of the order coverage rate and 66% of the stable order winning rate. Our study used Markov queuing theory to describe the state and price dynamics of the limit order book in detail and used optimization methods to construct and solve the optimal market maker strategy. The empirical aspect broadens the empirical scope of market maker strategies in the Chinese market and studies the stability and effectiveness of market makers in different market states. Full article
(This article belongs to the Section E: Applied Mathematics)
18 pages, 16369 KiB  
Article
Comparison of Satellite-Derived Vegetation Indices for Assessing Vegetation Dynamics in Central Asia
by Qian Li, Junhui Cheng, Junjie Yan, Guangpeng Zhang and Hongbo Ling
Water 2025, 17(5), 684; https://doi.org/10.3390/w17050684 - 26 Feb 2025
Viewed by 8
Abstract
Each of the NDVI, EVI, NIRv, and kNDVI has varying strengths and weaknesses in terms of representing vegetation dynamics. Identifying the comparative advantages of these indices is crucial to objectively determine the dynamics of vegetation in dryland. In this study, Central Asia was [...] Read more.
Each of the NDVI, EVI, NIRv, and kNDVI has varying strengths and weaknesses in terms of representing vegetation dynamics. Identifying the comparative advantages of these indices is crucial to objectively determine the dynamics of vegetation in dryland. In this study, Central Asia was selected as the research area, which is a typical drought-sensitive and ecologically fragile region. The Mann–Kendall trend test, coefficient of variation, and partial correlation analyses were used to compare the ability of these indices to express the spatiotemporal dynamics of vegetation, its heterogeneity, and its relationships with temperature and precipitation. Moreover, the composite vegetation index (CVI) was constructed by using the entropy weighting method and its relative advantage was identified. The results showed that the kNDVI exhibited a stronger capacity to express the relationship between the vegetation and the temperature and precipitation, compared with the other three indices. The NIRv best represented the spatiotemporal heterogeneity of vegetation in areas with a high vegetation coverage, while the kNDVI had the strongest expressive capability in areas with a low vegetation coverage. The critical value for distinguishing between areas with a high and low vegetation coverage was NDVI = 0.54 for temporal heterogeneity and NDVI = 0.50 for spatial heterogeneity. The CVI had no apparent comparative advantage over the other four indices in expressing the trends of changes in vegetation coverage and their correlations with the temperature and precipitation. However, it enjoyed a prominent advantage over these indices in terms of expressing the spatiotemporal heterogeneity of vegetation coverage in Central Asia. Full article
19 pages, 3116 KiB  
Article
Multitemporal Analysis of Declassified Keyhole Imagery’ for Landuse Change Detection in China (1960~1984): A Python-Based Spatial Coverage and Automation Workflow
by Hao Li, Tao Wang, Weiqi Yao, Huanjun Liu, Chunyu Song and Jinyu Sun
Remote Sens. 2025, 17(5), 822; https://doi.org/10.3390/rs17050822 (registering DOI) - 26 Feb 2025
Viewed by 3
Abstract
Keyhole imagery, acquired between the 1960s and 1980s, offers a unique opportunity to study land use changes prior to the era of modern remote sensing. This study evaluates the potential of free-download Keyhole imagery within China to detect land use changes over five [...] Read more.
Keyhole imagery, acquired between the 1960s and 1980s, offers a unique opportunity to study land use changes prior to the era of modern remote sensing. This study evaluates the potential of free-download Keyhole imagery within China to detect land use changes over five 5-year periods (1960–1984). Using metadata and spatial analysis tools in Python 3.12, we classified images into three resolution categories (meter-level, five-meter-level, and ten-meter-level) and analyzed their spatial distribution and repeated coverage. Results show that 26.5%, 58.9%, and 34.0% of areas were capable of detecting at least one land-use change event for the respective resolution categories. The T3 period (1970–1974) exhibited the greatest diversity of imagery combinations among the five periods. However, uneven spatial and temporal coverage, particularly in western and rural regions, limits the ability of free Keyhole imagery to conduct continuous multi-temporal analysis, and collaboration with paid Keyhole imagery could fill gaps in coverage and improve the accuracy of land use change detection. The study highlights the potential of Keyhole imagery for historical land use research while underscoring the need for methodological refinements to address data limitations. The shared Python scripts and metadata processing techniques could also support other land-use change research using Keyhole imagery globally. Full article
(This article belongs to the Special Issue Geodata Science and Spatial Analysis with Remote Sensing)
25 pages, 15584 KiB  
Article
Inland Water Quality Monitoring Using Airborne Small Cameras: Enhancing Suspended Sediment Retrieval and Mitigating Sun Glint Effects
by Diogo Olivetti, Henrique L. Roig, Jean-Michel Martinez, Alexandre M. R. Ferreira, Rogério R. Marinho, Ronaldo L. Mincato and Eduardo Sávio P. R. Martins
Drones 2025, 9(3), 173; https://doi.org/10.3390/drones9030173 - 26 Feb 2025
Viewed by 63
Abstract
The ongoing advancement of unmanned aerial vehicles (UAVs) and the evolution of small-scale cameras have bridged the gap between traditional ground-based surveys and orbital sensors. However, these systems present challenges, including limited coverage area, image stabilization constraints, and complex image processing. In water [...] Read more.
The ongoing advancement of unmanned aerial vehicles (UAVs) and the evolution of small-scale cameras have bridged the gap between traditional ground-based surveys and orbital sensors. However, these systems present challenges, including limited coverage area, image stabilization constraints, and complex image processing. In water quality monitoring, these difficulties are further compounded by sun glint effects, which hinder the construction of accurate orthomosaics in homogeneous water surfaces and affect radiometric accuracy. This study focuses on evaluating these challenges by comparing two distinct airborne imaging platforms with different spectral resolutions, emphasizing Total Suspended Solids (TSS) monitoring. Hyperspectral airborne surveys were undertaken utilizing a pushbroom system comprising 276 bands, whereas multispectral airborne surveys were conducted employing a global shutter frame with 4 bands. Fifteen aerial survey campaigns were carried out over water bodies from two biomes in Brazil (Amazon and Savanna), at varying concentrations of TSS (0.6–130.7 mg L−1, N: 53). Empirical models using near-infrared channels were applied to accurately monitor TSS in all areas (Hyperspectral camera—RMSE = 3.6 mg L−1, Multispectral camera—RMSE = 9.8 mg L−1). Furthermore, a key contribution of this research is the development and application of Sun Glint mitigation techniques, which significantly improve the reliability of airborne reflectance measurements. By addressing these radiometric challenges, this study provides critical insights into the optimal UAV platform for TSS monitoring in inland waters, enhancing the accuracy and applicability of airborne remote sensing in aquatic environments. Full article
(This article belongs to the Special Issue Applications of UVs in Digital Photogrammetry and Image Processing)
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23 pages, 1206 KiB  
Article
Air Pollution Monitoring Using Cost-Effective Devices Enhanced by Machine Learning
by Yanis Colléaux, Cédric Willaume, Bijan Mohandes, Jean-Christophe Nebel and Farzana Rahman
Sensors 2025, 25(5), 1423; https://doi.org/10.3390/s25051423 - 26 Feb 2025
Viewed by 43
Abstract
Given the significant impact of air pollution on global health, the continuous and precise monitoring of air quality in all populated environments is crucial. Unfortunately, even in the most developed economies, current air quality monitoring networks are largely inadequate. The high cost of [...] Read more.
Given the significant impact of air pollution on global health, the continuous and precise monitoring of air quality in all populated environments is crucial. Unfortunately, even in the most developed economies, current air quality monitoring networks are largely inadequate. The high cost of monitoring stations has been identified as a key barrier to widespread coverage, making cost-effective air quality monitoring devices a potential game changer. However, the accuracy of the measurements obtained from low-cost sensors is affected by many factors, including gas cross-sensitivity, environmental conditions, and production inconsistencies. Fortunately, machine learning models can capture complex interdependent relationships in sensor responses and thus can enhance their readings and sensor accuracy. After gathering measurements from cost-effective air pollution monitoring devices placed alongside a reference station, the data were used to train such models. Assessments of their performance showed that models tailored to individual sensor units greatly improved measurement accuracy, boosting their correlation with reference-grade instruments by up to 10%. Nonetheless, this research also revealed that inconsistencies in the performance of similar sensor units can prevent the creation of a unified correction model for a given sensor type. Full article
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27 pages, 1120 KiB  
Review
Enhancing Cervical Cancer Screening: New Diagnostic Methodologies, Triage, and Risk Stratification in Prevention and Treatment
by Nazira Kamzayeva, Gauri Bapayeva, Milan Terzic, Berik Primbetov, Balkenzhe Imankulova, Yevgeniy Kim, Arailym Sultanova, Kuralay Kongrtay, Nazira Kadroldinova and Talshyn Ukybassova
Life 2025, 15(3), 367; https://doi.org/10.3390/life15030367 - 26 Feb 2025
Viewed by 43
Abstract
Human papillomavirus (HPV) is a well-established etiological factor in the development of precancerous cervical lesions and cervical cancer. This narrative review synthesizes current evidence on the global prevalence, genotype distribution, and pathophysiological mechanisms of HPV infection, emphasizing regional epidemiological variations that influence prevention [...] Read more.
Human papillomavirus (HPV) is a well-established etiological factor in the development of precancerous cervical lesions and cervical cancer. This narrative review synthesizes current evidence on the global prevalence, genotype distribution, and pathophysiological mechanisms of HPV infection, emphasizing regional epidemiological variations that influence prevention and treatment strategies. Particular attention is given to high-risk HPV genotypes, their role in carcinogenesis, and the impact of co-infections and the cervicovaginal microbiota on infection persistence and disease progression. Advances in diagnostic methodologies, including E6/E7 oncoprotein detection, DNA methylation, and microRNA-based assays, are examined in the context of improving screening accuracy and early detection. Furthermore, the review explores the psychological implications of HPV diagnosis and underscores the importance of integrating psychosocial support into clinical management. Given the challenges associated with screening coverage, the potential of self-sampling techniques, particularly in resource-limited settings, is discussed as a means to enhance accessibility and participation in cervical cancer prevention programs. By providing a comprehensive overview of these interrelated factors, this review highlights the necessity of a multidisciplinary approach that integrates novel diagnostic strategies, targeted prevention efforts, and supportive care to mitigate the burden of HPV-associated diseases. Full article
(This article belongs to the Special Issue Innovations in Pathology and Viral Oncology)
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13 pages, 1176 KiB  
Review
Respiratory Vaccines in Older Adults: A Bibliometric Analysis and Future Research Agenda
by Jose F. Parodi, Fernando Runzer-Colmenares, Carlos Cano-Gutiérrez, José Luis Dinamarca-Montecinos, Patricio Bendía-Gomez de La Torre, Paulo Fortes Villas Boas, Javier Flores-Cohaila, Diego Urrunaga-Pastor and Luis Miguel Gutiérrez-Robledo
Vaccines 2025, 13(3), 240; https://doi.org/10.3390/vaccines13030240 - 26 Feb 2025
Viewed by 82
Abstract
Background/Objectives: Respiratory infections impact older adults due to immunosenescence and comorbidities, resulting in increased healthcare costs and mortality. While vaccination is a critical preventive measure, research on respiratory vaccines in older adults in Latin America and the Caribbean (LAC) remains underexplored. This study [...] Read more.
Background/Objectives: Respiratory infections impact older adults due to immunosenescence and comorbidities, resulting in increased healthcare costs and mortality. While vaccination is a critical preventive measure, research on respiratory vaccines in older adults in Latin America and the Caribbean (LAC) remains underexplored. This study aims to map the research landscape and identify emerging themes to guide future studies. Methods: A bibliometric analysis was conducted using the Web of Science database, focusing on publications up to 2023 related to respiratory vaccines in LAC’s older adult population. PRISMA-ScR guidelines were followed for data extraction and analysis, with performance metrics and scientometric mapping conducted using Biblioshiny 4.1 and VOSviewer. Results: Ninety-nine studies spanning forty-one journals and 575 authors were included. Brazil contributed 70% of publications, followed by Mexico and Argentina. Influenza and pneumococcal vaccines were the most studied, focusing on coverage, acceptance, and cost-effectiveness. Emerging themes included COVID-19 vaccine effectiveness and vaccination-associated factors. Brazil was identified as the primary hub for collaboration across the region, while other countries made limited contributions. Conclusions: The findings highlight disparities in research output, with Brazil dominating and significant gaps in other LAC countries. Future research should prioritize genomic studies, vaccine efficacy in comorbid populations, and adaptive immunization strategies. Building research capacity and fostering international collaborations are essential for improving vaccination outcomes in older adults across LAC. Full article
(This article belongs to the Special Issue Vaccines and Vaccine Preventable Diseases)
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13 pages, 3535 KiB  
Article
Challenges in Amplicon-Based DNA NGS Identification of MET Exon 14 Skipping Events in Non-Small Cell Lung Cancers
by Magdalena Jurkiewicz, Raymond Yeh, Catherine A. Shu, Susan J. Hsiao, Mahesh M. Mansukhani, Anjali Saqi and Helen Fernandes
J. Mol. Pathol. 2025, 6(1), 5; https://doi.org/10.3390/jmp6010005 - 26 Feb 2025
Viewed by 110
Abstract
Introduction: MET Exon 14 skipping alterations are drivers of non-small cell lung carcinoma (NSCLC) with responses to tyrosine kinase inhibitors. Amplicon-based DNA NGS assays (DNA NGSs) for the detection of METex14 skipping can yield false-negative results. We examined the efficacy of [...] Read more.
Introduction: MET Exon 14 skipping alterations are drivers of non-small cell lung carcinoma (NSCLC) with responses to tyrosine kinase inhibitors. Amplicon-based DNA NGS assays (DNA NGSs) for the detection of METex14 skipping can yield false-negative results. We examined the efficacy of METex14 skipping with a DNA NGS and reflex RNA-based NGS (RNA NGS) strategy. Materials and Methods: Clinical cases with definitive or suspected lung adenocarcinoma (LungCa), lacking driver mutations with targeted DNA NGS, underwent the RNA NGS to identify oncogenic drivers. Samples with METex14 skipping identified on reflex RNA NGSs were confirmed with Sanger sequencing. Results:METex14 skipping events were detected in 22/762 (2.9%) samples by DNA NGS. RNA NGS identified 10 additional samples, for an overall frequency of 32/762 (4.1%). All 22 METex14 DNA variants affected the donor splice site. Sanger sequencing revealed that missed METex14 variants were largely deletions spanning the ~30 bp intronic region upstream of the splice acceptor site. The failure of DNA NGS to detect all METex14 mutants was due to a lack of coverage of the 3′ splice acceptor site of intron 13, branch point, and polypyrimidine tract. Conclusions: Modification of amplicon-based DNA hotspot assays, with primers that cover both donor and acceptor splice sites, can identify a larger number of METex14 skipping events. Clinical data show that patients with advanced NSCLC and METex14 variants responded to targeted therapy. Full article
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29 pages, 8502 KiB  
Article
Restorative Environment Design Drives Well-Being in Sustainable Elderly Day Care Centres
by Yuting Li, Xiayan Lin, Shimin Li, Min Huang, Zhipeng Ren and Qi Song
Buildings 2025, 15(5), 757; https://doi.org/10.3390/buildings15050757 - 25 Feb 2025
Viewed by 116
Abstract
At present, China is facing a serious aging problem. Although community daycare centers have been built, they generally have problems such as inadequate facilities, single-service provision, and insufficient environmental design. These problems make it impossible to meet the multifaceted needs of the elderly [...] Read more.
At present, China is facing a serious aging problem. Although community daycare centers have been built, they generally have problems such as inadequate facilities, single-service provision, and insufficient environmental design. These problems make it impossible to meet the multifaceted needs of the elderly in their old age, enhance their sense of wellbeing, and achieve sustainable development. Therefore, relevant policies indicate that the elderly service model of community day care centers should be actively constructed and upgraded. However, most of the existing research focuses on service models or single-design practice studies, and there are relatively few studies that address the integration of restorative environmental design and sustainability. Therefore, this paper systematically explores the current research status of restorative environmental design in daycare centers for the elderly through macro quantitative bibliometric analysis and micro qualitative content analysis based on Web of Science (WOS) data, then proposes design practice strategies, implementation paths, and evaluation methods to enhance wellbeing. Through keyword network visualization analysis, this paper identifies eight main clusters: physical literacy, public preschool services, social support, elderly day care centers, hospice use, designing leisure products, risk factors, and communicative skills. The high-frequency keywords “health”, “elderly”, “cultural diversity”, “children”, and “quality of life” are further categorized into “caregiving”, “Alzheimer’s disease”, “adult day care”, and “daycare centers”, with the latter split into three further categories: design strategy, implementation approach, and evaluation. In addition, this paper combines SDG3 goals such as reducing premature mortality from non-communicable diseases, achieving universal health coverage, etc., in order to explore the potential of resilience-based environmental design to promote the sustainable development of elderly daycare centers. This study not only complements the research related to restorative environmental design in daycare centers for the elderly but also provides specific guidelines and references for future environmental design, policy planning, and elderly service practices. Full article
(This article belongs to the Special Issue Art and Design for Healing and Wellness in the Built Environment)
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27 pages, 19628 KiB  
Article
Analysis of the Spatiotemporal Characteristics of Gross Primary Production and Its Influencing Factors in Arid Regions Based on Improved SIF and MLR Models
by Wei Liu, Ali Mamtimin, Yu Wang, Yongqiang Liu, Hajigul Sayit, Chunrong Ji, Jiacheng Gao, Meiqi Song, Ailiyaer Aihaiti, Cong Wen, Fan Yang, Chenglong Zhou and Wen Huo
Remote Sens. 2025, 17(5), 811; https://doi.org/10.3390/rs17050811 - 25 Feb 2025
Viewed by 116
Abstract
In this study of constructing gross primary production (GPP) based on solar-induced chlorophyll fluorescence (SIF) and analyzing its spatial–temporal characteristics and influencing factors, numerous challenges are encountered, especially in arid regions with fragile ecologies. Coupling SIF with other factors to construct the GPP [...] Read more.
In this study of constructing gross primary production (GPP) based on solar-induced chlorophyll fluorescence (SIF) and analyzing its spatial–temporal characteristics and influencing factors, numerous challenges are encountered, especially in arid regions with fragile ecologies. Coupling SIF with other factors to construct the GPP and elucidating the influencing mechanisms of environmental factors could offer a novel theoretical method for the comprehensive analysis of GPP in arid regions. Therefore, we used the GPP station data from three different ecosystems (grasslands, farmlands, and desert vegetation) as well as the station and satellite data of environmental factors (including photosynthetically active radiation (PAR), a vapor pressure deficit (VPD), the air temperature (Tair), soil temperature (Tsoil), and soil moisture content (SWC)), and combined these with the TROPOMI SIF (RTSIF, generated through the reconstruction of SIF from the Sentinel-5P sensor), whose spatiotemporal precision was improved, the mechanistic light reaction model (MLR model), and different weather conditions. Then, we explored the spatiotemporal characteristics of GPP and its driving factors in local areas of Xinjiang. The results indicated that the intra-annual variation of GPP showed an inverted “U” shape, with the peak from June to July. The spatial attributes were positively correlated with vegetation coverage and sun radiation. Moreover, inverting GPP referred to the process of estimating the GPP of an ecosystem through models and remote sensing data. Based on the MLR model and RTSIF, the inverted GPP could capture more than 80% of the GPP changes in the three ecosystems. Furthermore, in farmland areas, PAR, VPD, Tair, and Tsoil jointly dominate GPP under sunny, cloudy, and overcast conditions. In grassland areas, PAR was the main influencing factor of GPP under all weather conditions. In desert vegetation areas, the dominant influencing factor of GPP was PAR on sunny days, VPD and Tair on cloudy days, and Tair on overcast days. Regarding the spatial correlation, the high spatial correlation between PAR, VPD, Tair, Tsoil, and GPP was observed in regions with dense vegetation coverage and low radiation. Similarly, the strong spatial correlation between SWC and GPP was found in irrigated farmland areas. The characteristics of a low spatial correlation between GPP and environmental factors were the opposite. In addition, it was worth noting that the impact of various environmental factors on GPP in farmland areas was comprehensively expressed based on a linear pattern. However, in grassland and desert vegetation areas, the impact of VPD on GPP was expressed based on a linear pattern, while the impact of other factors was more accurately represented through a non-linear pattern. This study demonstrated that SIF data combined with the MLR model effectively estimated GPP and revealed its spatial patterns and driving factors. These findings may serve as a foundation for developing targeted carbon reduction strategies in arid regions, contributing to improved regional carbon management. Full article
(This article belongs to the Special Issue Remote Sensing and Modelling of Terrestrial Ecosystems Functioning)
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17 pages, 815 KiB  
Article
The Post-2021 Afghan Situation: Romanian Students’ Knowledge, Views and Cultural Receptiveness
by Simona Șimon, Gabriel-Mugurel Dragomir and Marcela Alina Fărcașiu
Societies 2025, 15(3), 58; https://doi.org/10.3390/soc15030058 - 25 Feb 2025
Viewed by 137
Abstract
In a world in which the political crisis is escalating, causing the emergence of war and conflict, even in unexpected regions, the post-2021 Afghan situation of the population in general, and of the women in particular, is a reminder of the atrocities caused [...] Read more.
In a world in which the political crisis is escalating, causing the emergence of war and conflict, even in unexpected regions, the post-2021 Afghan situation of the population in general, and of the women in particular, is a reminder of the atrocities caused by colliding political powers. This article aims to raise Romanian students’ awareness of post-2021 Afghanistan, a geographically and culturally distant country, to identify their perceptions of the Afghans’ lives under the current regime as well as to single out the respondents’ cultural receptiveness. To achieve these research objectives, an online survey was carried out at the beginning of 2024 among the students of Politehnica University of Timișoara (Romania), recording 420 responses. The study revealed that, although the majority of the surveyed population is well acquainted with the topic under discussion, there is a significant sample that is still unaware of it despite its media coverage. Furthermore, the subjects’ cultural responsiveness is illustrative of the cultural traits of the Romanians, pointing to the slowness of the cultural change in spite of the incontestable economic growth of the country. Full article
(This article belongs to the Special Issue Gender and Class: Exploring the Intersections of Power and Inequality)
19 pages, 9716 KiB  
Article
Novel Fractional-Order Chaotic System Applied to Mobile Robot Path Planning and Chaotic Path Synchronization
by Yan Cui and Zexi Zheng
Symmetry 2025, 17(3), 350; https://doi.org/10.3390/sym17030350 - 25 Feb 2025
Viewed by 174
Abstract
In this paper, a novel fractional-order chaotic system equipped with symmetric attractors was proposed for the full-coverage path-planning problem of mobile robots, especially in application scenarios where path privacy needs to be protected. By coupling this system with a kinematic model of a [...] Read more.
In this paper, a novel fractional-order chaotic system equipped with symmetric attractors was proposed for the full-coverage path-planning problem of mobile robots, especially in application scenarios where path privacy needs to be protected. By coupling this system with a kinematic model of a mobile robot, a novel path-planning algorithm was designed to realize encrypted full-coverage path planning. A predefined time-synchronization control strategy effectively resolved inconsistencies in the path caused by initial position, time delay, and uncertain disturbances. Numerical simulation results demonstrated that the proposed path-planning method, based on the novel chaotic system, significantly improved coverage and randomness, compared to existing studies. Moreover, it maintained accuracy and stability in path planning, even in the presence of time delays and uncertain disturbances. Full article
(This article belongs to the Section Computer)
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19 pages, 12391 KiB  
Article
Investigation into Enhancing Ultrasonic Cleaning Efficiency Through Symmetrical Transducer Configuration
by Lei Wei, Sheng Liu and Fang Dong
Symmetry 2025, 17(3), 348; https://doi.org/10.3390/sym17030348 - 25 Feb 2025
Viewed by 110
Abstract
This paper investigates the symmetrical layout effect in ultrasonic cleaning via acoustic solid coupling simulation, with emphasis on how the symmetrical arrangement of transducers influences sound pressure distribution. Two specific transducer layout methods are examined: uniform arrangement at the bottom and symmetrical arrangement [...] Read more.
This paper investigates the symmetrical layout effect in ultrasonic cleaning via acoustic solid coupling simulation, with emphasis on how the symmetrical arrangement of transducers influences sound pressure distribution. Two specific transducer layout methods are examined: uniform arrangement at the bottom and symmetrical arrangement along the sides. The findings indicate that when the tank length is an integer multiple of one-quarter of the acoustic wavelength, the symmetrical side arrangement markedly enhances the sound pressure level within the tank and optimizes the propagation and reflection of acoustic waves. In megasonic cleaning, focusing is achieved through a 7 × 7 transducer array by precisely controlling the phase, and the symmetrical arrangement ensures uniform sound pressure distribution. By integrating 1 MHz megasonic sources from both focused and unfocused configurations, the overall sound pressure distribution and peak sound pressure at the focal point are calculated using multi-physics field coupling simulations. A comparative analysis of the sound fields generated by focused and unfocused sources reveals that the focused source can produce significantly higher sound pressure in specific regions. Leveraging the enhanced cleaning capability of the focused acoustic wave in targeted areas while maintaining broad coverage with the unfocused acoustic wave significantly improves the overall cleaning efficiency. Ultrasonic cleaning finds extensive applications in industries such as electronic component manufacturing, medical device sterilization, and automotive parts cleaning. Its efficiency and environmental friendliness make it highly significant for both daily life and industrial production. Full article
(This article belongs to the Section Engineering and Materials)
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15 pages, 1340 KiB  
Article
ctDNA as an Objective Marker for Postoperative Residual Disease in Primary Advanced High-Grade Serous Ovarian Cancer
by Valentina Glueck, Christoph Grimm, Magdalena Postl, Christian Brueffer, Nuria Segui, Miguel Alcaide, Lucia Oton, Yilun Chen, Lao H. Saal, Gerda Hofstetter, Stephan Polterauer and Leonhard Muellauer
Cancers 2025, 17(5), 786; https://doi.org/10.3390/cancers17050786 (registering DOI) - 25 Feb 2025
Viewed by 181
Abstract
Background/Objectives: The surgeon’s subjective intraoperative evaluation is the standard of care to assess postoperative residual disease (RD) in advanced epithelial ovarian cancer (EOC). We investigated the feasibility of ctDNA as an objective marker for postoperative RD. Methods: This prospective study included 27 patients [...] Read more.
Background/Objectives: The surgeon’s subjective intraoperative evaluation is the standard of care to assess postoperative residual disease (RD) in advanced epithelial ovarian cancer (EOC). We investigated the feasibility of ctDNA as an objective marker for postoperative RD. Methods: This prospective study included 27 patients with advanced ovarian cancer (FIGO IIIA1–IVB) who underwent primary surgery between July 2021 and July 2022. Blood samples were analyzed preoperatively and on days 2 (d2) and 10 (d10) postoperatively. Low-coverage whole genome sequencing (WGS) was used to identify structural variants (SVs) at single-base pair resolution, single nucleotide variants (SNVs), and indels in tumor tissue to develop personalized, tumor-informed digital polymerase chain reaction (dPCR) fingerprint assays for each patient. Results: dPCR fingerprint assays were successfully developed for all patients by identifying one to eight SVs/SNVs per patient. ctDNA was detected in 96% (n = 26/27) of patients preoperatively and in 81% (n = 22/27) of patients at d10. Median ctDNA levels at d10 were significantly higher in patients with postoperative RD (median 367.38 copies (cps)/mL, 2.84% variant allele frequency; VAF) than in patients without postoperative RD (median 0.92 cps/mL, 0.017% VAF, p < 0.001). In patients with postoperative RD, ctDNA levels increased from the preoperative stage to d10 in seven out of eight patients (p = 0.016). In patients with complete tumor resection, ctDNA levels decreased from the preoperative stage to d10 in 17/19 patients (p < 0.001). Conclusions: A tumor-informed personalized ctDNA approach demonstrated feasibility, providing extremely high detection rates pre- and postoperatively. These results indicate that this approach could potentially be used for postoperative RD assessment in patients with primary advanced EOC. Full article
(This article belongs to the Section Cancer Therapy)
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