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21 pages, 7030 KiB

Open AccessArticle

Experimental Design and Numerical Optimization of Photochemical Oxidation Removal of Tetracycline from Water Using Fe₃O₄-Supported Fruit Waste Activated Carbon

by Manasik M. Nour, Maha A. Tony, Hossam A. Nabwey and Shaaban M. Shaaban

Catalysts 2025, 15(4), 351; https://doi.org/10.3390/catal15040351 (registering DOI) - 3 Apr 2025

Abstract

The ever-increasing importance of sustainable environmental remediation calls for academics’ contribution to satisfy such a need. The 3R’s criteria of recover, recycle and reuse is designed to sustain the waste stream to produce a valuable product. In this regard, the circular economy looks [...] Read more.

The ever-increasing importance of sustainable environmental remediation calls for academics’ contribution to satisfy such a need. The 3R’s criteria of recover, recycle and reuse is designed to sustain the waste stream to produce a valuable product. In this regard, the circular economy looks to deliver banana peel waste as a photocatalyst for pharmaceutical effluent oxidation, which we investigated in this study. Banana peel waste is treated thermally and chemically then augmented with magnetite nanoparticles and labeled as ACBP-Fe₃O₄. The mixture is characterized through Scanning Electron Microscopy (SEM) and the composition of the composite material is attained by energy dispersive X-ray spectroscopy (EDX), and then introduced as a Fenton catalyst. The notable oxidation of tetracycline (TC), evaluated by TC removal and chemical Oxygen Demand (COD) oxidation tenancy, is achieved. The effectiveness of the operational parameters is also assessed and the most influenced parameters are optimized through numerical optimization based on a Response Surface Methodology (RSM) tool. The effects of initial pH value, ACBP-Fe₃O₄ and H₂O₂ concentrations on the oxidation efficiency of the Tetracycline were optimized at pH 6.6 and 350 mg/L and 43 g/L for H₂O₂ and ACBP-Fe₃O₄, respectively. Thermodynamics and kinetics were also studied and the experimental and model data revealed the reaction is spontaneous and exothermic in nature and follows the first-order reaction kinetics. Also, the thermodynamic results the reaction proceeds at a low energy barrier of 34.33 kJ mol⁻¹. Such a system introduces the role of engineers and academics for a sustainable world without a waste stream. Full article

(This article belongs to the Special Issue Remediation of Natural Waters by Photocatalysis)

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13 pages, 234 KiB

Open AccessArticle

Prevalence of Elevated CK Levels, Myositis-Specific and Myositis-Associated Antibodies, Myositis, and Other Neuromuscular Diseases in Myasthenia Gravis Patients—Experience from an Eastern European Tertiary Center

by Márk Kozák, Edina Kovács, Melinda Nagy-Vince, Attila Tóth and Judit Boczán

J. Clin. Med. 2025, 14(7), 2449; https://doi.org/10.3390/jcm14072449 (registering DOI) - 3 Apr 2025

Abstract

Background: Myasthenia gravis (MG) and idiopathic inflammatory myopathy (IIM) are autoimmune diseases that affect the musculoskeletal system. The association of the two diseases is rare. Their management is different, so it is important to recognize the concomitant presentation. Methods: In this cross-sectional study, [...] Read more.

Background: Myasthenia gravis (MG) and idiopathic inflammatory myopathy (IIM) are autoimmune diseases that affect the musculoskeletal system. The association of the two diseases is rare. Their management is different, so it is important to recognize the concomitant presentation. Methods: In this cross-sectional study, we study the presence of CK elevation, myositis-specific and myositis-associated antibodies (MSA/MAA), and vitamin D levels in a cohort of 101 MG patients. Electromyography, limb magnetic resonance imaging (MRI), and, in some cases, muscle biopsy were performed when IIM was suspected. We reviewed the patients’ medical records to access the results of these tests if they had been performed previously. Results: CK elevation was detected in 10 patients (9.9%). We identified one case of anti-Jo-1 antibody-positive polymyositis and two cases of possible myositis. MSA/MAA antibodies were not found in the patients with high CK levels, except for the one with anti-Jo-1-positive IIM. One patient with elevated CK levels had an overlapping muscular dystrophy. MSA/MAA antibodies were detected in 19 patients (18.8%). A total of 37% had high-titer antibodies and concomitant systemic autoimmune diseases, while 63% had low-titer antibodies, most of whom had no systemic autoimmune disease. Low serum vitamin D levels were found in 67.3% of patients. Comparison of myasthenia gravis composite (MGC) scores between patients with low and normal vitamin D levels did not show a statistically significant difference. Conclusions: Our results may raise awareness among neuromuscular specialists caring for MG patients of the possibility of associated myositis or other neuromuscular diseases and the need to assess vitamin D levels. Although deficiency was frequent, its impact on MG severity remains unclear, necessitating further investigation into its immunological relevance. Full article

(This article belongs to the Special Issue New Advances in Myasthenia Gravis)

12 pages, 3972 KiB

Open AccessArticle

Anticancer Activity of Cerium Oxide Nanoparticles Towards Human Lung Cancer Cells

by Nithin Krisshna Gunasekaran, Nicole Nazario Bayon, Prathima Prabhu Tumkur, Krishnan Prabhakaran, Joseph C. Hall and Govindarajan T. Ramesh

Nanomanufacturing 2025, 5(2), 6; https://doi.org/10.3390/nanomanufacturing5020006 (registering DOI) - 3 Apr 2025

Abstract

Cerium oxide nanoparticles (CeO₂ NPs) have gained significant attention in various fields, including biomedicine, semiconductors, cosmetics, and fuel cells, due to their unique physico-chemical properties. Notably, green-synthesized CeO₂ NPs have demonstrated enhanced potential as drug carriers, particularly in biomedical applications such [...] Read more.

Cerium oxide nanoparticles (CeO₂ NPs) have gained significant attention in various fields, including biomedicine, semiconductors, cosmetics, and fuel cells, due to their unique physico-chemical properties. Notably, green-synthesized CeO₂ NPs have demonstrated enhanced potential as drug carriers, particularly in biomedical applications such as anti-inflammatory, anticancer, antimicrobial, and anti-oxidant therapies. This study aimed to investigate the anticancer effects of cerium oxide nanoparticles synthesized using turmeric rhizomes on human lung cancer cells. The cytotoxicity and proliferation inhibition of these nanoparticles were assessed using MTT and Live/Dead assays, revealing a dose-dependent reduction in cell viability. Additionally, reactive oxygen species (ROS) generation was quantified through ROS assays, confirming oxidative stress induction as a key mechanism of cytotoxicity. Cell proliferation analysis further demonstrated that increasing concentrations of CeO₂ NPs significantly reduced the multiplication of healthy lung cancer cells. These findings highlight the potential of turmeric-derived CeO₂ NPs as a promising therapeutic agent for lung cancer treatment, warranting further exploration of their mechanism of action and in vivo efficacy. Full article

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28 pages, 3972 KiB

Open AccessReview

Doping Detection Based on the Nanoscale: Biosensing Mechanisms and Applications of Two-Dimensional Materials

by Jingjing Zhao, Yu Wang and Bing Liu

Biosensors 2025, 15(4), 227; https://doi.org/10.3390/bios15040227 (registering DOI) - 3 Apr 2025

Abstract

Doping undermines fairness in sports and threatens athlete health, while conventional detection methods like LC-MS and GC-MS face challenges such as complex procedures, matrix interferences, and lengthy processing times, limiting on-site applications. Two-dimensional (2D) materials, including graphene, MoS₂, and metal–organic frameworks [...] Read more.

Doping undermines fairness in sports and threatens athlete health, while conventional detection methods like LC-MS and GC-MS face challenges such as complex procedures, matrix interferences, and lengthy processing times, limiting on-site applications. Two-dimensional (2D) materials, including graphene, MoS₂, and metal–organic frameworks (MOFs), offer promising solutions due to their large surface areas, tunable electronic structures, and special interactions with doping agents, such as hydrogen bonding, π-π stacking, and electrostatic forces. These materials enable signal transduction through changes in conductivity or fluorescence quenching. This review highlights the use of 2D materials in doping detection. For example, reduced graphene oxide–MOF composites show high sensitivity for detecting anabolic steroids like testosterone, while NiO/NGO nanocomposites exhibit strong selectivity for stimulants like ephedrine. However, challenges such as environmental instability and high production costs hinder their widespread application. Future efforts should focus on improving material stability through chemical modifications, reducing production costs, and integrating these materials into advanced systems like machine learning. Such advancements could revolutionize doping detection, ensuring fairness in sports and protecting athlete health. Full article

(This article belongs to the Special Issue Organic Two-Dimensional Material: Synthesis and Biosensing Applications)

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20 pages, 4798 KiB

Open AccessArticle

Solutions for Energy and Raw Material Recovery from Sewage Sludge Within the Concept of Circular Economy

by Elena Pop, Lucian Mihăescu, Carmen Anca Safta, Horațiu Lucian Pop, Gabriel Paul Negreanu and Ionel Pîșă

Sustainability 2025, 17(7), 3181; https://doi.org/10.3390/su17073181 (registering DOI) - 3 Apr 2025

Abstract

Wastewater treatment plants traditionally dispose of sludge using the method of landfilling and incineration, with both being carbon-intensive and environmentally harmful. Converting sludge into energy or reusable materials avoids landfills or incineration, helping reduce the volume of waste and associated pollution. Sludge treatment [...] Read more.

Wastewater treatment plants traditionally dispose of sludge using the method of landfilling and incineration, with both being carbon-intensive and environmentally harmful. Converting sludge into energy or reusable materials avoids landfills or incineration, helping reduce the volume of waste and associated pollution. Sludge treatment with energy recovery can offset fossil fuel use, further reducing the carbon footprint of sewage treatment processes. This research explores ways to recover energy from sewage sludge, a byproduct of wastewater treatment that is often considered waste. Transforming sludge into valuable resources aligns with the principles of the circular economy, where waste streams are repurposed, minimizing environmental impact and enhancing resource efficiency. In this paper, a method is presented to reduce the volume of wastewater sludge by drying it in a hot flue gas stream at 700 °C. The energy of the exhaust gas is recovered in an organic Rankine cycle system, which powers the wastewater treatment facilities themselves, making them more self-sustaining. Full article

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15 pages, 3951 KiB

Open AccessArticle

A Lightweight Machine Learning Model for High Precision Gastrointestinal Stromal Tumors Identification

by Xin Sun, Xiwen Mo, Jing Shi, Xinran Zhou, Yanqing Niu, Xiao-Dong Zhang, Man Li and Yonghui Li

Bioengineering 2025, 12(4), 381; https://doi.org/10.3390/bioengineering12040381 (registering DOI) - 3 Apr 2025

Abstract

Gastrointestinal stromal tumors (GISTs), which usually develop with a significant malignant potential, are a serious challenge in stromal health. With Endoscopic ultrasound (EUS), GISTs can appear similar to other tumors. This study introduces a lightweight convolutional neural network model optimized for the classification [...] Read more.

Gastrointestinal stromal tumors (GISTs), which usually develop with a significant malignant potential, are a serious challenge in stromal health. With Endoscopic ultrasound (EUS), GISTs can appear similar to other tumors. This study introduces a lightweight convolutional neural network model optimized for the classification of GISTs and leiomyomas using EUS images only. Models are constructed based on a dataset that comprises 13277 augmented grayscale images derived from 703 patients, ensuring a balanced representation between GIST and leiomyoma cases. The optimized model architecture includes seven convolutional units followed by fully connected layers. After being trained and evaluated with a 5-fold cross-validation, the optimized model achieves an average validation accuracy of 96.2%. The model achieved a sensitivity, specificity, positive predictive value, and negative predictive value of 97.7%, 94.7%, 94.6%, and 97.7%, respectively, and significantly outperformed endoscopists’ assessments. The study highlights the model’s robustness and consistency. Our results suggest that instead of using developed deep models with fine-tuning, lightweight models with their simpler designs may grasp the essence and drop speckle noise. A lightweight model as a hypothesis with fewer model parameters is preferable to a deeper model with 10 times the model parameters according to Occam’s razor statement. Full article

(This article belongs to the Section Biosignal Processing)

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22 pages, 9404 KiB

Open AccessArticle

Impact of Seasonal Variation and Population Growth on Coliform Bacteria Concentrations in the Brunei River: A Temporal Analysis with Future Projection

by Oluwakemisola Onifade, Zaharaddeen Karami Lawal, Norazanita Shamsuddin, Pg Emeroylariffion Abas, Daphne Teck Ching Lai and Stefan Herwig Gӧdeke

Water 2025, 17(7), 1069; https://doi.org/10.3390/w17071069 (registering DOI) - 3 Apr 2025

Abstract

Coliform bacteria pollution poses a significant challenge to water quality in the Brunei River, a critical resource in Brunei Darussalam. This study investigates the impact of seasonal variations and population growth on coliform concentrations across eight monitoring stations while addressing data limitations in [...] Read more.

Coliform bacteria pollution poses a significant challenge to water quality in the Brunei River, a critical resource in Brunei Darussalam. This study investigates the impact of seasonal variations and population growth on coliform concentrations across eight monitoring stations while addressing data limitations in forecasting future trends. Seasonal variations, analyzed using box plots, revealed significantly higher coliform levels during the rainy season, driven by urban and residential runoff. Population growth, assessed using propensity score matching, showed that stations in densely populated areas experienced elevated contamination levels. Temporal trends, analyzed using the Rescaled Adjusted Partial Sums (RAPS) method, indicated a declining trend from 2013 to 2018, followed by a sharp increase post-2018, linked to urbanization, wastewater discharge, and overburdened sewage infrastructure, particularly in upstream stations. To forecast coliform levels, ARIMA, Logistic Regression, and Bidirectional Long Short-Term Memory (BiLSTM) models were employed and their predictive performance evaluated. Despite the constraints of a small dataset, the BiLSTM model outperformed others in most stations, emphasizing its ability to capture complex temporal relationships. Furthermore, a Mann–Kendall trend analysis of the BiLSTM predicted data over a five-year period and revealed significant upward trends in coliform levels. This study highlights the potential of combining advanced predictive models with robust analytical techniques and focused data collection efforts to support sustainable water quality management in data-scarce environments. Full article

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21 pages, 1584 KiB

Open AccessArticle

An Alternative Procedure for the Description of Seismic Intensity Parameter-Based Damage Potential

by Emmanouil Chaitas, Ioannis E. Kavvadias, Kosmas E. Bantilas and Anaxagoras Elenas

Appl. Sci. 2025, 15(7), 3949; https://doi.org/10.3390/app15073949 (registering DOI) - 3 Apr 2025

Abstract

This study presents an alternative statistical approach for describing the damage potential of R/C structures using various seismic intensity parameters. By employing a comprehensive set of 34 Intensity Measures (IMs) and three well-known Global Damage Indices (DIs), a correlation study was initially conducted [...] Read more.

This study presents an alternative statistical approach for describing the damage potential of R/C structures using various seismic intensity parameters. By employing a comprehensive set of 34 Intensity Measures (IMs) and three well-known Global Damage Indices (DIs), a correlation study was initially conducted to assess the predictive capacity of the selected IMs in estimating a structure’s damage grade. Multiple regression analyses were performed to determine the most suitable IMs for damage prediction, utilizing only the highest correlated IMs with the selected DIs, employing both conventional regression models and a novel alternative approach by transforming the IMs for each predicted DI. The IMs were modified through exponentiation, using powers directly dependent on each IM’s rank correlation coefficient with the respective DI. Employing the rank correlation coefficients to modify the IMs effectively amplifies the influence of those that present the highest agreement with the observed damage. The results demonstrate that energy-related and spectral-based IMs correlate highly with structural damage. The generated models exhibit high accuracy in predicting the observed damage grade, with the models based on the proposed approach showing improved performance in estimating the sustained damage grade while maintaining computational efficiency in terms of their computational time and results’ accuracy. Full article

(This article belongs to the Special Issue Structural Mechanics: Theory, Method and Applications)

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20 pages, 1569 KiB

Open AccessArticle

IESSP: Information Extraction-Based Sparse Stripe Pruning Method for Deep Neural Networks

by Jingjing Liu, Lingjin Huang, Manlong Feng, Aiying Guo, Luqiao Yin and Jianhua Zhang

Sensors 2025, 25(7), 2261; https://doi.org/10.3390/s25072261 (registering DOI) - 3 Apr 2025

Abstract

Network pruning is a deep learning model compression technique aimed at reducing model storage requirements and decreasing computational resource consumption. However, mainstream pruning techniques often encounter challenges such as limited precision in feature selection and a diminished feature extraction capability. To address these [...] Read more.

Network pruning is a deep learning model compression technique aimed at reducing model storage requirements and decreasing computational resource consumption. However, mainstream pruning techniques often encounter challenges such as limited precision in feature selection and a diminished feature extraction capability. To address these issues, we propose an information extraction-based sparse stripe pruning (IESSP) method. This method introduces an information extraction module (IEM), which enhances stripe selection through a mask-based mechanism, promoting inter-layer interactions and directing the network’s focus toward key features. In addition, we design a novel loss function that links output loss to stripe selection, enabling an effective balance between accuracy and efficiency. This loss function also supports the adaptive optimization of stripe sparsity during training. Experimental results on benchmark datasets demonstrate that the proposed method outperforms existing techniques. Specifically, when applied to prune the VGG-16 model on the CIFAR-10 dataset, the proposed method achieves a 0.29% improvement in accuracy while reducing FLOPs by 75.88% compared to the baseline. Full article

(This article belongs to the Special Issue Machine Learning in Image/Video Processing and Sensing)

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29 pages, 16785 KiB

Open AccessArticle

Strategy for the Conversion of 2D to 3D Cadastral Maps by Standardizing the Height Limit of Land Rights Space Based on Land Use/Land Cover

by Fransisko Rohanda Rebong, Irwan Meilano, Vera Sadarviana, Andri Hernandi, Rizqi Abdulharis and Resy Meilani

Land 2025, 14(4), 763; https://doi.org/10.3390/land14040763 (registering DOI) - 3 Apr 2025

Abstract

This study examines the conversion strategy of 2D to 3D cadastral maps by standardizing the height limits of land rights based on LU/LC. To achieve 3D cadastral maps, the research proposes a conversion strategy considering height factors. The height dimension of cadastral maps [...] Read more.

This study examines the conversion strategy of 2D to 3D cadastral maps by standardizing the height limits of land rights based on LU/LC. To achieve 3D cadastral maps, the research proposes a conversion strategy considering height factors. The height dimension of cadastral maps faces challenges in determining maximum heights for features like buildings, given varying regional regulations. As a solution, the concept of surface feature height (SFH) is applied along with LU/LC classification. Economic considerations, such as state revenue from taxes, are also factored into the proposed height limits. The results indicate that building/property heights in Bekasi Regency show significant development potential. In the residential sector, the maximum height reaches 24 m, lower than Bekasi City (48 m) and Bandung City (30 m). In the industrial sector, while heights can reach 25 m, the regulatory limit is only 9 m, posing challenges for investment. In the commercial sector, the maximum height can reach 45 m, but the low regulatory limit of 10 m restricts further development. This research provides a foundation for policy development and an effective 3D cadastral system, emphasizing the need for Bekasi Regency to re-evaluate its building height regulations to maximize its development potential. Full article

(This article belongs to the Special Issue Developing 3D Cadastre for Urban Land Use)

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30 pages, 2511 KiB

Open AccessArticle

Reliable Vehicle Routing Problem Using Traffic Sensors Augmented Information

by Ahmed Almutairi and Mahmoud Owais

Sensors 2025, 25(7), 2262; https://doi.org/10.3390/s25072262 (registering DOI) - 3 Apr 2025

Abstract

The stochastic routing transportation network problem presents significant challenges due to uncertainty in travel times, real-time variability, and limited sensor data availability. Traditional adaptive routing strategies, which rely on real-time travel time updates, may lead to suboptimal decisions due to dynamic traffic fluctuations. [...] Read more.

The stochastic routing transportation network problem presents significant challenges due to uncertainty in travel times, real-time variability, and limited sensor data availability. Traditional adaptive routing strategies, which rely on real-time travel time updates, may lead to suboptimal decisions due to dynamic traffic fluctuations. This study introduces a novel routing framework that integrates traffic sensor data augmentation and deep learning techniques to improve the reliability of route selection and network observability. The proposed methodology consists of four components: stochastic traffic assignment, multi-objective route generation, optimal traffic sensor location selection, and deep learning-based traffic flow estimation. The framework employs a traffic sensor location problem formulation to determine the minimum required sensor deployment while ensuring an accurate network-wide traffic estimation. A Stacked Sparse Auto-Encoder (SAE) deep learning model is then used to infer unobserved link flows, enhancing the observability of stochastic traffic conditions. By addressing the gap between limited sensor availability and complete network observability, this study offers a scalable and cost-effective solution for real-time traffic management and vehicle routing optimization. The results confirm that the proposed data-driven approach significantly reduces the need for sensor deployment while maintaining high accuracy in traffic flow predictions. Full article

(This article belongs to the Special Issue Data and Network Analytics in Transportation Systems)

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13 pages, 1376 KiB

Open AccessArticle

Switching to Faricimab in Therapy-Resistant Macular Edema Due to Retinal Vein Occlusion: Initial Real-World Efficacy Outcomes

by Michael Hafner, Tina R. Herold, Alexander Kufner, Ben Asani, Andreas Anschütz, Franziska Eckardt, Siegfried G. Priglinger and Johannes Schiefelbein

J. Clin. Med. 2025, 14(7), 2454; https://doi.org/10.3390/jcm14072454 (registering DOI) - 3 Apr 2025

Abstract

Background/Objectives: Macular edema (ME), due to retinal vein occlusion (RVO), is a major cause of vision impairment. Many patients experience suboptimal responses to anti-vascular endothelial growth factor (anti-VEGF) monotherapy, necessitating alternative treatment approaches. Faricimab, a bispecific antibody targeting VEGF-A and angiopoietin-2 (Ang-2), [...] Read more.

Background/Objectives: Macular edema (ME), due to retinal vein occlusion (RVO), is a major cause of vision impairment. Many patients experience suboptimal responses to anti-vascular endothelial growth factor (anti-VEGF) monotherapy, necessitating alternative treatment approaches. Faricimab, a bispecific antibody targeting VEGF-A and angiopoietin-2 (Ang-2), introduces a novel dual-mechanism therapy. This study evaluates the short-term real-world efficacy of switching to Faricimab in patients with treatment-resistant ME secondary to RVO. Methods: This retrospective study included patients from LMU University Hospital who were switched to Faricimab due to an inadequate response or adverse events related to prior intravitreal therapy (Ranibizumab, Aflibercept, or Ozurdex^TM). All patients completed a structured loading phase of four monthly injections. Key outcome measures included changes in best-corrected visual acuity (BCVA, logMAR), central subfield thickness (CST, µm), and intraretinal fluid (IRF) presence on optical coherence tomography (OCT). Changes were assessed from baseline (mo0) to three months (mo3). Results: The study included 19 eyes from 19 patients (mean age 63.0 ± 14.2 years). BCVA improved from 0.20 logMAR at baseline to 0.00 logMAR at mo3 (p < 0.01). CST decreased from 325 µm to 280 µm (p < 0.01). The proportion of eyes with IRF reduced from 100% to 32% (p < 0.01). Significant reductions in retinal volume within the 1 mm and 6 mm (both p < 0.01) circles of the ETDRS grid were observed. Conclusions: Switching to Faricimab in patients resulted in significant short-term improvements in BCVA, CST, and IRF resolution. Given the small sample size and retrospective design, these findings should be interpreted as exploratory and hypothesis-generating. Further studies are needed to evaluate long-term efficacy and optimal treatment regimens. Full article

(This article belongs to the Special Issue Causes and Advanced Treatments of Macular Edema)

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22 pages, 1839 KiB

Open AccessArticle

The Spatial Impact of PM_2.5 Pollution on Economic Growth from 2012 to 2022: Evidence from Satellite and Provincial-Level Data in Thailand

by Thanakhom Srisaringkarn and Kentaka Aruga

Urban Sci. 2025, 9(4), 110; https://doi.org/10.3390/urbansci9040110 (registering DOI) - 3 Apr 2025

Abstract

This study examines the spatial relationship of PM_2.5 concentrations across provinces in Thailand and explores the relationship between socio-economic factors and PM_2.5 levels from 2012 to 2022. The study results indicate that PM_2.5 pollution in Thailand is spatially clustered, meaning [...] Read more.

This study examines the spatial relationship of PM_2.5 concentrations across provinces in Thailand and explores the relationship between socio-economic factors and PM_2.5 levels from 2012 to 2022. The study results indicate that PM_2.5 pollution in Thailand is spatially clustered, meaning that PM_2.5 spills over into nearby provinces and is not confined to a single area. The factors that positively affect PM_2.5 concentrations include population density and energy consumption per capita, while industrial density has a negative effect on PM_2.5 levels. Additionally, an Environmental Kuznets Curve (EKC) analysis found that the Gross Provincial Product (GPP) per capita has a U-shaped relationship with the PM_2.5 concentration. In the initial stage of economic growth, as the GPP per capita increases, PM_2.5 concentrations gradually decrease. However, once income reaches USD 56,715 and the economy becomes significantly large, further increases in GPP per capita lead to rising PM_2.5 concentrations. In other words, during the early phase of economic development, PM_2.5 pollution does not intensify significantly. However, once Thailand’s economy reaches a certain scale, continued economic expansion exacerbates PM_2.5 pollution, leading to greater economic and social consequences. The study highlights the importance of integrated collaboration among various organizations in mitigating the widespread impacts of PM_2.5 pollution. Full article

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24 pages, 5355 KiB

Open AccessArticle

Complexation of Lanthanides(III) Ions with Terephthalic Acid in Aqueous Solutions by Potentiometric Titration Combined with Photoluminescence Spectroscopy

by Polina B. Guseva, Alexander R. Badikov, Oleg S. Butorlin, Yulia N. Toikka, Sergey N. Orlov, Mikhail N. Ryazantsev, Nikita A. Bogachev, Mikhail Yu. Skripkin and Andrey S. Mereshchenko

Chemistry 2025, 7(2), 57; https://doi.org/10.3390/chemistry7020057 (registering DOI) - 3 Apr 2025

Abstract

The complexation behavior of lanthanide(III) ions with terephthalic acid (1,4-benzene-dicarboxylic acid) in 0.01 M KNO₃ aqueous solutions was studied across a broad pH range and at two metal-to-ligand ratios using potentiometric titration combined with photoluminescence spectroscopy. Chemometric analysis of titration curves enabled [...] Read more.

The complexation behavior of lanthanide(III) ions with terephthalic acid (1,4-benzene-dicarboxylic acid) in 0.01 M KNO₃ aqueous solutions was studied across a broad pH range and at two metal-to-ligand ratios using potentiometric titration combined with photoluminescence spectroscopy. Chemometric analysis of titration curves enabled the determination of relative molar fractions, stability constants, and probable stoichiometry of the formed complexes. In solutions with a 1:2 metal-to-ligand ratio, bis-complexes (two terephthalate ligands per lanthanide ion) predominated, while ligand-rich conditions favored the formation of tetra-complexes (four ligands per metal ion). In alkaline media, bis-complexes transform into mixed hydroxy-terephthalate species. Meanwhile, for the tetra-complexes, the addition of NaOH results in the formation of lanthanide ion hydroxo complexes without organic ligands. The structural diversity of these complexes, driven by the terephthalate ligand’s tendency to maximize denticity, suggested dimeric or oligomeric configurations. The stability constants and structural features of complexes in solution were found to align with those of known solid-state lanthanide–terephthalate polymers, highlighting their potential as models for polymeric structures. Full article

(This article belongs to the Section Physical Chemistry and Chemical Physics)

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22 pages, 1650 KiB

Open AccessReview

Long-Term Outcomes of Surgical and Transcatheter Interventions for Tricuspid Regurgitation: A Comprehensive Review

by Vasiliki Tasouli-Drakou, Ibrahim Youssef, Arsalan Siddiqui and Tahir Tak

J. Clin. Med. 2025, 14(7), 2451; https://doi.org/10.3390/jcm14072451 (registering DOI) - 3 Apr 2025

Abstract

Impacting more than 70 million people worldwide, tricuspid regurgitation (TR) refers to the retrograde flow of blood from the right ventricle to the right atrium due to the improper closure of the tricuspid valve. Depending on the severity of TR, signs and symptoms [...] Read more.

Impacting more than 70 million people worldwide, tricuspid regurgitation (TR) refers to the retrograde flow of blood from the right ventricle to the right atrium due to the improper closure of the tricuspid valve. Depending on the severity of TR, signs and symptoms can range from asymptomatic to features of right heart failure, including dyspnea, exercise intolerance, peripheral edema, and ascites. Severe features such as these necessitate treatment. In recent years, advancements in management, including surgical and transcatheter interventions, have taken prominence, leading to improved short-term outcomes in this patient population. However, there is still a dearth of evidence regarding the long-term outcomes of surgical and transcatheter interventions for TR. This comprehensive review aims to present clinicians with recent findings from pivotal clinical studies on interventional clinical outcomes in an effort to help guide their judgment when it comes to deciding the best course of treatment for their patients. Full article

(This article belongs to the Special Issue Current Advances in Valvular Heart Diseases)

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25 pages, 5808 KiB

Open AccessArticle

Synergistic Effects of Mineralization Degree and Sodium Adsorption Ratio on the Rhizosphere Bacterial Community and Soil Nutrients of Upland Cotton Under Saline Water Irrigation

by Chenfan Zhang, Guang Yang, Huifeng Ning, Yucai Xie, Yinping Song and Jinglei Wang

Agronomy 2025, 15(4), 895; https://doi.org/10.3390/agronomy15040895 (registering DOI) - 3 Apr 2025

Abstract

In global drought-prone cotton-growing (Gossypium hirsutum L.) areas, saline water irrigation has become a key strategy to alleviate the shortage of freshwater resources. Against this backdrop, the synergistic effect of mineralization degree (MD) and sodium adsorption ratio (SAR) on the rhizosphere microecological [...] Read more.

In global drought-prone cotton-growing (Gossypium hirsutum L.) areas, saline water irrigation has become a key strategy to alleviate the shortage of freshwater resources. Against this backdrop, the synergistic effect of mineralization degree (MD) and sodium adsorption ratio (SAR) on the rhizosphere microecological regulation mechanism remains unclear. To address this issue, this study constructed an experimental framework of the interaction between MD and SAR, aiming to explore their effects on the bacterial community structure in the rhizosphere of cotton and the soil environment. The soil type in the study area is saline–sodic sandy loam. In the experimental design, three MD levels (3 g/L, 5 g/L, 7 g/L) were set, and under each mineralization condition, three SAR levels (10 (mmol/L)^1/2, 15 (mmol/L)^1/2, 20 (mmol/L)^1/2) were arranged. In addition, local freshwater irrigation was used as the control group (CG), resulting in a total of 10 treatment schemes. The aim of this study was to investigate the effects of varying levels of irrigation water MD and SAR on the structure of bacterial communities in cotton rhizosphere soil and the soil environment. The results indicated that saline water irrigation could enhance the diversity and richness of the bacterial community in the rhizosphere soil of cotton and alter its community structure. Under treatment with the MD of 3 g/L and the SAR of 10 (mmol/L)^1/2, the diversity and richness of the bacterial community in the cotton rhizosphere reached their peak levels. Compared with the CG, the Chao1 index significantly increased by 260 units, while the Shannon index increased by 0.464. When the MD does not exceed 5 g/L, reducing SAR can enhance the diversity and network stability of the rhizosphere bacterial community, thereby synergistically promoting the accumulation of soil nutrients. The key soil environmental factors driving changes in the rhizosphere bacterial community structure mainly include soil moisture content, total nitrogen, nitrate nitrogen, and total organic carbon. The concentrations of total nitrogen, nitrate nitrogen, available phosphorus, and available potassium significantly increased by 19.66%, 26.10%, 89.41%, and 49.76% respectively (p < 0.05). This study provides a theoretical basis for sustainable irrigation and microbial regulation strategies in saline–alkali cotton fields at the theoretical level, and offers a new perspective for revealing the mutual feedback mechanism between bacterial community assembly and soil environment under saline conditions. From a practical perspective, this research offers valuable hands-on experience for optimizing agricultural ecological management in saline–alkali sandy loam soils, thereby contributing to the sustainable development of agriculture on such lands. Full article

(This article belongs to the Special Issue Water and Fertilizer Regulation Theory and Technology in Crops)

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20 pages, 322 KiB

Open AccessArticle

Parents’ Reflective Functioning, Emotion Regulation, and Health: Associations with Children’s Functional Somatic Symptoms

by Aikaterini Fostini, Foivos Zaravinos-Tsakos, Gerasimos Kolaitis and Georgios Giannakopoulos

Psychol. Int. 2025, 7(2), 31; https://doi.org/10.3390/psycholint7020031 (registering DOI) - 3 Apr 2025

Abstract

Functional somatic symptoms (FSSs) in children—such as headaches, stomachaches, and muscle pain without clear medical explanations—pose a significant clinical challenge, often leading to repeated healthcare visits and impairments in daily functioning. While the role of parental psychological factors in shaping children’s FSSs has [...] Read more.

Functional somatic symptoms (FSSs) in children—such as headaches, stomachaches, and muscle pain without clear medical explanations—pose a significant clinical challenge, often leading to repeated healthcare visits and impairments in daily functioning. While the role of parental psychological factors in shaping children’s FSSs has been suggested, empirical evidence remains limited and fragmented. This study addresses this gap by systematically examining the associations between parents’ reflective functioning, emotion regulation, alexithymia, and physical and mental health, and the frequency and severity of children’s FSSs. A total of 339 parents of children aged 6–12 completed surveys assessing their capacity to understand mental states, regulate emotions, and identify or describe feelings, as well as their self-reported physical and mental health. They also indicated whether their child experienced FSSs (e.g., headaches, stomachaches) more than once per week. Results revealed that parents of children with FSSs reported significantly lower levels of reflective functioning (lower certainty, higher uncertainty), higher alexithymic traits, and greater emotion regulation difficulties, alongside poorer physical and mental health indices. Logistic regression analyses demonstrated that emotion regulation difficulties and poorer mental health significantly increased the likelihood of a child exhibiting FSSs, while lower reflective functioning also emerged as a significant predictor. Furthermore, multiple linear regression indicated that emotion regulation challenges and poor mental health predicted greater severity of FSSs. These findings offer novel insights into how parents’ psychological and health characteristics can shape children’s somatic symptom expression, highlighting the need for family-focused interventions. By identifying and addressing parental emotional and cognitive difficulties, clinicians may be able to mitigate the intergenerational transmission of maladaptive stress responses, ultimately reducing the burden of FSSs in children. Full article

12 pages, 3543 KiB

Open AccessArticle

Layout Design Strategies for Scaling Down Semiconductor Systems Based on Current Flow Analysis in Interconnect

by Seung Hwan Oh, Tae Yeong Hong, Sarah Eunkyung Kim, Jong Kyung Park and Seul Ki Hong

Appl. Sci. 2025, 15(7), 3944; https://doi.org/10.3390/app15073944 (registering DOI) - 3 Apr 2025

Abstract

As the demand for high-density integrated circuits increases, scaling down devices has already reached its limit, making the optimization of interconnect–via layout an important research challenge. Conventional semiconductor design adopts conservative margins to ensure process reliability, but this often results in inefficient space [...] Read more.

As the demand for high-density integrated circuits increases, scaling down devices has already reached its limit, making the optimization of interconnect–via layout an important research challenge. Conventional semiconductor design adopts conservative margins to ensure process reliability, but this often results in inefficient space utilization and degraded electrical performance. This study evaluates the possibility of optimizing design rules by analyzing the impact of reduced contact area in interconnect–via structures on the current flow and resistance. Finite element method analysis (FEM) using Ansys Workbench revealed that current is concentrated in approximately 20% of the interconnect height and the diagonal region of the via. A resistance model reflecting this current distribution demonstrated high accuracy, with an error range of 1–3% compared to simulation results. Resistance measurements of various fabricated structures produced through photolithography and lift-off processes showed a significant increase in resistance when the contact area was reduced to 50% or less, consistent with simulation results. This study demonstrates the potential to optimize both space utilization and electrical performance by minimizing the conservative margins between interconnects and vias, contributing to next-generation high-density integrated circuit design. Full article

(This article belongs to the Section Electrical, Electronics and Communications Engineering)

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22 pages, 23066 KiB

Open AccessArticle

Indoor Evaluation of a Temperature-Controlled Gel Intelligent Diversion System

by Zhifeng Luo, Qunlong Wu, Weiyu Chen, Haoran Fu, Kun Xu and Haojiang Xi

Nanomaterials 2025, 15(7), 547; https://doi.org/10.3390/nano15070547 (registering DOI) - 3 Apr 2025

Abstract

The Bohai SZ36-1 oilfield, the largest offshore oilfield in China, features a high-porosity, high-permeability reservoir with significant heterogeneity and permeability variations. After extended water injection, the reservoir’s pore structure evolved, increasing heterogeneity and reducing the effectiveness of traditional production methods. To address these [...] Read more.

The Bohai SZ36-1 oilfield, the largest offshore oilfield in China, features a high-porosity, high-permeability reservoir with significant heterogeneity and permeability variations. After extended water injection, the reservoir’s pore structure evolved, increasing heterogeneity and reducing the effectiveness of traditional production methods. To address these issues, this study introduces an intelligent diversion and balanced unblocking technology, using a temperature-controlled diversion system to block dominant flow channels and ensure even distribution of treatment fluids while maintaining reservoir integrity. The technology’s scientific validity and feasibility were confirmed through extensive testing. Results show that the diversion system offers excellent injectability, with controllable solidification time, phase change temperature, and strong compatibility, allowing for a “liquid–solid–liquid” phase transition in the reservoir. The technology also demonstrates high plugging strength, rapid plugging rate, significant diversion effects, and moderate injection intensity, all meeting construction requirements. Full article

(This article belongs to the Section Theory and Simulation of Nanostructures)

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18 pages, 3368 KiB

Open AccessArticle

Influence of Different Diets on Growth and Development of Eastern Honey Bee (Apis cerana)

by Ruonan Liang, Cheng Liang, Yi Zhang, Jiaxing Huang and Guiling Ding

Insects 2025, 16(4), 383; https://doi.org/10.3390/insects16040383 (registering DOI) - 3 Apr 2025

Abstract

In recent years, honey bees have been stressed by multiple factors, with malnutrition posing a significant threat to the healthy development of honey bee colonies. To keep a colony healthy and productive, beekeepers supply their colonies with supplementary pollen or commercial pollen substitutes [...] Read more.

In recent years, honey bees have been stressed by multiple factors, with malnutrition posing a significant threat to the healthy development of honey bee colonies. To keep a colony healthy and productive, beekeepers supply their colonies with supplementary pollen or commercial pollen substitutes during periods of pollen dearth or insufficient pollen quantity or quality. In this study, we evaluated the effects of four natural pollen types (oilseed rape pollen, camellia pollen, lotus pollen and buckwheat pollen) and two commercial pollen substitutes (Diet 1 and Diet 2) against a control group (sucrose solution) on Apis cerana through cage experiments. The food consumption, live body weight, longevity, hypopharyngeal gland development and midgut proteolytic enzyme activity of caged workers were measured. The food consumption rates of oilseed rape pollen and buckwheat pollen were greater than the other diets. Oilseed rape pollen and camellia pollen were recognized as excellent-quality diets for hypopharyngeal gland development and midgut proteolytic enzyme activity. Over the entire experimental period, the caged workers fed with lotus pollen had a similar diet consumption and body weight to those fed with pollen substitutes, and these bees had a significantly higher survival rate than those fed with other diets. The results indicated that the commercial pollen substitutes appeared to be less beneficial to caged A. cerana workers than the natural pollen resources. Full article

(This article belongs to the Special Issue Biology and Conservation of Honey Bees)

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15 pages, 1467 KiB

Open AccessReview

Cell Lineage Affiliation During Hematopoiesis

by Geoffrey Brown

Int. J. Mol. Sci. 2025, 26(7), 3346; https://doi.org/10.3390/ijms26073346 (registering DOI) - 3 Apr 2025

Abstract

By the mid-1960s, hematopoietic stem cells (HSCs) were well described. They generate perhaps the most complex array of functionally mature cells in an adult organism. HSCs and their descendants have been studied extensively, and findings have provided principles that have been applied to [...] Read more.

By the mid-1960s, hematopoietic stem cells (HSCs) were well described. They generate perhaps the most complex array of functionally mature cells in an adult organism. HSCs and their descendants have been studied extensively, and findings have provided principles that have been applied to the development of many cell systems. However, there are uncertainties about the process of HSC development. They center around when and how HSCs become affiliated with a single-cell lineage. A longstanding view is that this occurs late in development and stepwise via a series of committed oligopotent progenitor cells, which eventually give rise to unipotent progenitors. A very different view is that lineage affiliation can occur as early as within HSCs, and the development of these cells to a mature end cell is then a continuous process. A key consideration is the extent to which lineage-affiliated HSCs self-renew to make a major contribution to hematopoiesis. This review examines the above aspects in relation to our understanding of hematopoiesis. Full article

(This article belongs to the Collection Feature Papers in “Molecular Biology”)

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18 pages, 1173 KiB

Open AccessArticle

Dysregulation of the Immune System in Advanced Periimplantitis: Systemic Implications and Inflammatory Mechanisms—A Hematological and Immunological Study

by Michał Łobacz, Mansur Rahnama-Hezavah, Paulina Mertowska, Sebastian Mertowski, Katarzyna Wieczorek, Grzegorz Hajduk and Ewelina Grywalska

J. Clin. Med. 2025, 14(7), 2453; https://doi.org/10.3390/jcm14072453 (registering DOI) - 3 Apr 2025

Abstract

Objectives: This study aimed to assess the systemic and local inflammatory responses in patients with periimplantitis, focusing on key immune markers and clinical parameters. The study further explores the relationship between inflammatory markers, clinical indices, and immune dysregulation, particularly regarding T-cell exhaustion and [...] Read more.

Objectives: This study aimed to assess the systemic and local inflammatory responses in patients with periimplantitis, focusing on key immune markers and clinical parameters. The study further explores the relationship between inflammatory markers, clinical indices, and immune dysregulation, particularly regarding T-cell exhaustion and systemic inflammation. Methods: A cohort of patients with periimplantitis, classified into moderate and advanced stages, was compared to a control group of healthy individuals with dental implants. Clinical parameters, including plaque index (API), bleeding on probing (BoP), probing pocket depth (PPD), and peri-implant sulcus depth (PSI), were recorded. Hematological, immunological, and biochemical analyses were performed, with a focus on immune cell populations (NK cells, T-cells, and their exhaustion markers PD-1 and PD-L1). Results: Patients with periimplantitis exhibited significantly higher clinical indices (API, BoP, PSI, and PPD) than the control group, with the most pronounced differences in the advanced periimplantitis group. Hematological analysis revealed increased leukocyte and neutrophil counts, whereas NK cell levels were significantly reduced. Immunological profiling indicated elevated PD-1 and PD-L1 expression on T-cells, suggesting T-cell exhaustion and immune dysregulation. Furthermore, strong correlations were found between increased PPD values and elevated inflammatory marker levels, highlighting the relationship between peri-implant pocket depth and systemic inflammation. Conclusions: The findings confirm that immune dysregulation plays a central role in periimplantitis progression. The association between increased inflammatory markers, immune alterations, and clinical indices emphasizes the need for a multifactorial diagnostic and treatment approach. Integrating immune modulation strategies, clinical assessments, and lifestyle modifications, such as improved oral hygiene and smoking cessation, could improve disease management and reduce recurrence. Full article

(This article belongs to the Section Dentistry, Oral Surgery and Oral Medicine)

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15 pages, 1857 KiB

Open AccessArticle

Bioactive Compounds and Pigmenting Potential of Vaccinium corymbosum Extracts Separated with Aqueous Biphasic Systems Aided by Centrifugation

by Mayra Carranza-Gomez, Salvador Valle-Guadarrama, Ricardo Domínguez-Puerto, Ofelia Sandoval-Castilla and Diana Guerra-Ramírez

Processes 2025, 13(4), 1072; https://doi.org/10.3390/pr13041072 (registering DOI) - 3 Apr 2025

Abstract

The blueberry fruit (Vaccinium corymbosum L.) exhibits a high content of bioactive compounds, including anthocyanins, that can be used as pigmenting agents, but they are mixed with sugars, which can hinder their utilization. The objective was to evaluate the use of aqueous [...] Read more.

The blueberry fruit (Vaccinium corymbosum L.) exhibits a high content of bioactive compounds, including anthocyanins, that can be used as pigmenting agents, but they are mixed with sugars, which can hinder their utilization. The objective was to evaluate the use of aqueous two-phase extraction aided by centrifugation to separate bioactive compounds, particularly anthocyanins, from blueberry fruits, considering the reduction of sugars, for their use as pigmenting agents in a food product. A mixture of trisodium citrate (Na₃C₃H₅O(COO)₃; Na₃Cit) and polyethylene glycol ([HO-(CH₂CH₂O)n-CH₂OH]; poly (ethane-1,2-diol); PEG) with a molecular weight of 4 kDa was used. Based on the cloud point method, a binodal diagram was developed. After the evaluation of several systems with composition located on a tie line, conditions were identified to form biphasic systems with phases of equal volume. Passive sedimentation for 0, 15, and 30 min, followed by centrifugation and also passive sedimentation for 24 h without centrifugation, were evaluated. A system with 17.73% Na₃Cit, 21.33% PEG, 30 min of passive sedimentation, and 15 min of centrifugation at 2940× g produced an extract with a high concentration of soluble phenols (0.353 mg/mL) and anthocyanins (0.202 mg/mL) and, likewise, high antioxidant activity (910.0 mmol gallic acid equivalents per mL), with reduced sugar content, which demonstrated to have the potential to pigment food beverages with a reddish tone. Full article

(This article belongs to the Section Food Process Engineering)

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18 pages, 12348 KiB

Open AccessArticle

MESTR: A Multi-Task Enhanced Ship-Type Recognition Model Based on AIS

by Nanyu Chen, Luo Chen, Xinxin Zhang and Ning Jing

J. Mar. Sci. Eng. 2025, 13(4), 715; https://doi.org/10.3390/jmse13040715 (registering DOI) - 3 Apr 2025

Abstract

With the rapid growth in maritime traffic, navigational safety has become a pressing concern. Some vessels deliberately manipulate their type information to evade regulatory oversight, either to circumvent legal sanctions or engage in illicit activities. Such practices not only undermine the accuracy of [...] Read more.

With the rapid growth in maritime traffic, navigational safety has become a pressing concern. Some vessels deliberately manipulate their type information to evade regulatory oversight, either to circumvent legal sanctions or engage in illicit activities. Such practices not only undermine the accuracy of maritime supervision but also pose significant risks to maritime traffic management and safety. Therefore, accurately identifying vessel types is essential for effective maritime traffic regulation, combating maritime crimes, and ensuring safe maritime transportation. However, the existing methods fail to fully exploit the long-term sequential dependencies and intricate mobility patterns embedded in vessel trajectory data, leading to suboptimal identification accuracy and reliability. To address these limitations, we propose MESTR, a Multi-Task Enhanced Ship-Type Recognition model based on Automatic Identification System (AIS) data. MESTR leverages a Transformer-based deep learning framework with a motion-pattern-aware trajectory segment masking strategy. By jointly optimizing two learning tasks—trajectory segment masking prediction and ship-type prediction—MESTR effectively captures deep spatiotemporal features of various vessel types. This approach enables the accurate classification of six common vessel categories: tug, sailing, fishing, passenger, tanker, and cargo. Experimental evaluations on real-world maritime datasets demonstrate the effectiveness of MESTR, achieving an average accuracy improvement of 12.04% over the existing methods. Full article

(This article belongs to the Section Ocean Engineering)

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21 pages, 9833 KiB

Open AccessArticle

Artificial Intelligence for Objective Assessment of Acrobatic Movements: Applying Machine Learning for Identifying Tumbling Elements in Cheer Sports

by Sophia Wesely, Ella Hofer, Robin Curth, Shyam Paryani, Nicole Mills, Olaf Ueberschär and Julia Westermayr

Sensors 2025, 25(7), 2260; https://doi.org/10.3390/s25072260 (registering DOI) - 3 Apr 2025

Abstract

Over the past four decades, cheerleading evolved from a sideline activity at major sporting events into a professional, competitive sport with growing global popularity. Evaluating tumbling elements in cheerleading relies on both objective measures and subjective judgments, such as difficulty and execution quality. [...] Read more.

Over the past four decades, cheerleading evolved from a sideline activity at major sporting events into a professional, competitive sport with growing global popularity. Evaluating tumbling elements in cheerleading relies on both objective measures and subjective judgments, such as difficulty and execution quality. However, the complexity of tumbling—encompassing team synchronicity, ground interactions, choreography, and artistic expression—makes objective assessment challenging. Artificial intelligence (AI) revolutionised various scientific fields and industries through precise data-driven analyses, yet their application in acrobatic sports remains limited despite significant potential for enhancing performance evaluation and coaching. This study investigates the feasibility of using an AI-based approach with data from a single inertial measurement unit to accurately identify and objectively assess tumbling elements in standard cheerleading routines. A sample of 16 participants (13 females, 3 males) from a Division I collegiate cheerleading team wore a single inertial measurement unit at the dorsal pelvis. Over a 4-week seasonal preparation period, 1102 tumbling elements were recorded during regular practice sessions. Using triaxial accelerations and rotational speeds, various ML algorithms were employed to classify and evaluate the execution of tumbling manoeuvres. Our results indicate that certain machine learning models can effectively identify different tumbling elements with high accuracy despite inter-individual variability and data noise. These findings demonstrate the significant potential for integrating AI-driven assessments into cheerleading and other acrobatic sports in order to provide objective metrics that complement traditional judging methods. Full article

(This article belongs to the Section Sensing and Imaging)

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