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This study proposes a method for estimating the kinetic coefficient of friction (COF) for asphalt pavements by improving and applying Persson’s friction theory. The method utilizes the power spectral density (PSD) of the top surface topography instead of the full PSD to better reflect the actual contact conditions. This approach avoids including deeper roughness components that do not contribute to real rubber–pavement contact due to surface skewness. The key aspect of the method is determining an appropriate cutting plane to isolate the top surface. Four cutting strategies were evaluated. Results show that the cutting plane defined at 0.5 times the root mean square (RMS) height exhibits the highest robustness across all pavement types, with the estimated COF closely matching the measured values for all four tested surfaces. This study presents an improved method for estimating the kinetic coefficient of friction (COF) of asphalt pavements by employing the power spectral density (PSD) of the top surface roughness, rather than the total surface profile. This refinement is based on Persson’s friction theory and aims to exclude the influence of deep surface irregularities that do not make actual contact with the rubber interface. The core of the method lies in defining an appropriate cutting plane to isolate the topographical features that contribute most to frictional interactions. Four cutting strategies were investigated. Among them, the cutting plane positioned at 0.5 times the root mean square (RMS) height demonstrated the best overall applicability. COF estimates derived from this method showed strong consistency with experimentally measured values across all four tested asphalt pavement surfaces, indicating its robustness and practical potential. Full article

(This article belongs to the Section Construction and Building Materials)

16 pages, 1196 KiB

Open AccessArticle

Integrated Additive Manufacturing of TGV Interconnects and High-Frequency Circuits via Bipolar-Controlled EHD Jetting

by Dongqiao Bai, Jin Huang, Hongxiao Gong, Jianjun Wang, Yunna Pu, Jiaying Zhang, Peng Sun, Zihan Zhu, Pan Li, Huagui Wang, Pengbing Zhao and Chaoyu Liang

Micromachines 2025, 16(8), 907; https://doi.org/10.3390/mi16080907 (registering DOI) - 2 Aug 2025

Abstract

Electrohydrodynamic (EHD) printing offers mask-free, high-resolution deposition across a broad range of ink viscosities, yet combining void-free filling of high-aspect-ratio through-glass vias (TGVs) with ultrafine drop-on-demand (DOD) line printing on the same platform requires balancing conflicting requirements: for example, high field strengths to drive ink into deep and narrow vias; sufficiently high ink viscosity to prevent gravity-induced leakage; and stable meniscus dynamics to avoid satellite droplets and charge accumulation on the glass surface. By coupling electrostatic field analysis with transient level-set simulations, we establish a dimensionless regime map that delineates stable cone-jetting regime; these predictions are validated by high-speed imaging and surface profilometry. Operating within this window, the platform achieves complete, void-free filling of 200 µm × 1.52 mm TGVs and continuous 10 µm-wide traces in a single print pass. Demonstrating its capabilities, we fabricate transparent Ku-band substrate-integrated waveguide antennas on borosilicate glass: the printed vias and arc feed elements exhibit a reflection coefficient minimum of –18 dB at 14.2 GHz, a –10 dB bandwidth of 12.8–16.2 GHz, and an 8 dBi peak gain with 37° beam tilt, closely matching full-wave predictions. This physics-driven, all-in-one EHD approach provides a scalable route to high-performance, glass-integrated RF devices and transparent electronics. Full article

42 pages, 5770 KiB

Open AccessReview

Echoes from Below: A Systematic Review of Cement Bond Log Innovations Through Global Patent Analysis

by Lim Shing Wang, Muhammad Haarith Firdaous and Pg Emeroylariffion Abas

Inventions 2025, 10(4), 67; https://doi.org/10.3390/inventions10040067 (registering DOI) - 2 Aug 2025

Abstract

Maintaining well integrity is essential in the oil and gas industry to prevent environmental hazards, operational risks, and economic losses. Cement bond log (CBL) tools are essential in evaluating cement bonding and ensuring wellbore stability. This study presents a patent landscape review of CBL technologies, based on 3473 patent documents from the Lens.org database. After eliminating duplicates and irrelevant entries, 167 granted patents were selected for in-depth analysis. These were categorized by technology type (wave, electrical, radiation, neutron, and other tools) and by material focus (formation, casing, cement, and borehole fluid). The findings reveal a dominant focus on formation evaluation (59.9%) and a growing reliance on wave-based (22.2%) and other advanced tools (25.1%), indicating a shift toward high-precision diagnostics. Geographically, 75% of granted patents were filed through the U.S. Patent and Trademark Office, and 97.6% were held by companies, underscoring the dominance of corporate innovation and the minimal presence of academia and individuals. The review also identifies notable patents that reflect significant technical innovations and discusses their role in advancing diagnostic capabilities. These insights emphasize the need for broader collaboration and targeted research to advance well integrity technologies in line with industry goals for operational performance and safety. Full article

(This article belongs to the Section Inventions and Innovation in Energy and Thermal/Fluidic Science)

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13 pages, 849 KiB

Open AccessArticle

Morphofunctional Profile Focusing on Strength and Ultrasound of the Upper Limbs in Female Breast Cancer Survivors: A Comparative Cross-Sectional Study Between Groups with and Without Lymphoedema and Between Ipsilateral and Contralateral Limbs

by Ana Rafaela Cardozo Da Silva, Juliana Netto Maia, Vanessa Maria Da Silva Alves Gomes, Naiany Tenório, Juliana Fernandes de Souza Barbosa, Ana Claudia Souza da Silva, Vanessa Patrícia Soares de Sousa, Leila Maria Alvares Barbosa, Armèle de Fátima Dornelas de Andrade and Diego Dantas

Biomedicines 2025, 13(8), 1884; https://doi.org/10.3390/biomedicines13081884 (registering DOI) - 2 Aug 2025

Abstract

Background: Breast cancer is the most common neoplasm in women. Despite effective treatments, sequelae such as decreased muscle strength, upper limb dysfunction, and tissue changes are common, highlighting the need for functional assessments during rehabilitation. This study analysed the morphofunctional profile of the upper limbs in breast cancer survivors, comparing muscle strength and ultrasound findings between groups with and without lymphoedema, as well as between ipsilateral and contralateral limbs. Methods: This cross-sectional study included female breast cancer survivors treated at an oncology physical therapy clinic. Muscle strength was measured using dynamometry (handgrip and arm flexor strength), and ultrasound assessed the thickness of the dermal–epidermal complex (DEC), subcutaneous tissue (SUB), and muscle (MT). Results: The upper limbs of 41 women were evaluated. No significant differences were observed between those with and without breast cancer-related lymphoedema (BCRL). When comparing the ipsilateral and contralateral limbs, significant reductions were observed in arm flexor strength (p < 0.001; 95% CI: −9.77 to −2.50), handgrip strength (p < 0.001; 95% CI: −4.10 to −1.22), and tissue thickness, with increased DEC thickness on the forearm (0.20 mm; p = 0.022) and arm flexors (0.25 mm; p < 0.001) of the ipsilateral limb. Conclusion: Significant differences in muscle strength and tissue structure between ipsilateral and contralateral limbs may reflect surgical and local pathophysiological effects. A trend toward reduced values for these parameters was also noted in limbs with BCRL, reinforcing the importance of future research to elucidate underlying mechanisms and guide more effective therapeutic strategies. Full article

(This article belongs to the Section Molecular and Translational Medicine)

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24 pages, 1376 KiB

Open AccessArticle

Smart Agriculture in Ecuador: Adoption of IoT Technologies by Farmers in Guayas to Improve Agricultural Yields

by Ruth Rubí Peña-Holguín, Carlos Andrés Vaca-Coronel, Ruth María Farías-Lema, Sonnia Valeria Zapatier-Castro and Juan Diego Valenzuela-Cobos

Agriculture 2025, 15(15), 1679; https://doi.org/10.3390/agriculture15151679 (registering DOI) - 2 Aug 2025

Abstract

The adoption of digital technologies, such as the Internet of Things (IoT), has emerged as a key strategy to improve efficiency, sustainability, and productivity in the agricultural sector, especially in contexts of modernization and digital transformation in developing regions. This study analyzes the key factors influencing the adoption of IoT technologies by farmers in the province of Guayas, Ecuador, and their impact on agricultural yields. The research is grounded in innovation diffusion theory and technology acceptance models, which emphasize the role of perception, usability, training, and economic viability in digital adoption. A total of 250 surveys were administered, with 232 valid responses (92.8% response rate), reflecting strong interest from the agricultural sector in digital transformation and precision agriculture. Using structural equation modeling (SEM), the results confirm that general perception of IoT (β = 0.514), practical functionality (β = 0.488), and technical training (β = 0.523) positively influence adoption, while high implementation costs negatively affect it (β = −0.651), all of which are statistically significant (p < 0.001). Furthermore, adoption has a strong positive effect on agricultural yield (β = 0.795). The model explained a high percentage of variance in both adoption (R² = 0.771) and performance (R² = 0.706), supporting its predictive capacity. These findings underscore the need for public and private institutions to implement targeted training and financing strategies to overcome economic barriers and foster the sustainable integration of IoT technologies in Ecuadorian agriculture. Full article

(This article belongs to the Special Issue Internet of Things and Wireless Sensor Networks for Smart Vegetable Growing)

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13 pages, 462 KiB

Open AccessArticle

Genetic Landscape of Congenital Cataracts in a Swiss Cohort: Addressing Diagnostic Oversights in Nance–Horan Syndrome

by Flora Delas, Jiradet Gloggnitzer, Alessandro Maspoli, Lisa Kurmann, Beatrice E. Frueh, Ivanka Dacheva, Darius Hildebrand, Wolfgang Berger and Christina Gerth-Kahlert

Biomedicines 2025, 13(8), 1883; https://doi.org/10.3390/biomedicines13081883 (registering DOI) - 2 Aug 2025

Abstract

Congenital cataracts (CCs) are a leading cause of preventable childhood blindness, with genetic factors playing a crucial role in their etiology. Nance–Horan syndrome (NHS) is a rare X-linked dominant disorder associated with CCs but is often underdiagnosed due to variable expressivity, particularly in female carriers. Objective: This study aimed to explore the genetic landscape of CCs in a Swiss cohort, focusing on two novel NHS and one novel GJA8 variants and their phenotypic presentation. Methods: Whole-exome sequencing (WES) was conducted on 20 unrelated Swiss families diagnosed with CCs. Variants were analyzed for pathogenicity using genetic databases, and segregation analysis was performed. Clinical data, including cataract phenotype and associated systemic anomalies, were assessed to establish genotype–phenotype correlations. Results: Potentially pathogenic DNA sequence variants were identified in 10 families, including three novel variants, one in GJA8 (c.584T>C) and two NHS variants (c.250_252insA and c.484del). Additional previously reported variants were detected in CRYBA1, CRYGC, CRYAA, MIP, EPHA2, and MAF, reflecting genetic heterogeneity in the cohort. Notably, NHS variants displayed significant phenotypic variability, suggesting dose-dependent effects and X-chromosome inactivation in female carriers. Conclusions: NHS remains underdiagnosed due to its variable expressivity and the late manifestation of systemic features, often leading to misclassification as isolated CC. This study highlights the importance of genetic testing in unexplained CC cases to improve early detection of syndromic forms. The identification of novel NHS and GJA8 variants provides new insights into the genetic complexity of CCs, emphasizing the need for further research on genotype–phenotype correlations. Full article

(This article belongs to the Special Issue Ophthalmic Genetics: Unraveling the Genomics of Eye Disorders)

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18 pages, 5178 KiB

Open AccessArticle

Quantification of Suspended Sediment Concentration Using Laboratory Experimental Data and Machine Learning Model

by Sathvik Reddy Nookala, Jennifer G. Duan, Kun Qi, Jason Pacheco and Sen He

Water 2025, 17(15), 2301; https://doi.org/10.3390/w17152301 (registering DOI) - 2 Aug 2025

Abstract

Monitoring sediment concentration in water bodies is crucial for assessing water quality, ecosystems, and environmental health. However, physical sampling and sensor-based approaches are labor-intensive and unsuitable for large-scale, continuous monitoring. This study employs machine learning models to estimate suspended sediment concentration using images captured in natural light, named RGB, and near-infrared (NIR) conditions. A controlled dataset of approximately 1300 images with SSC values ranging from 1000 mg/L to 150,000 mg/L was developed, incorporating temperature, time of image capture, and solar irradiance as additional features. Random forest regression and gradient boosting regression were trained on mean RGB values, red reflectance, time of captured, and temperature for natural light images, achieving up to 72.96% accuracy within a 30% relative error. In contrast, NIR images leveraged gray-level co-occurrence matrix texture features and temperature, reaching 83.08% accuracy. Comparative analysis showed that ensemble models outperformed deep learning models like Convolutional Neural Networks and Multi-Layer Perceptrons, which struggled with high-dimensional feature extraction. These findings suggest that using machine learning models and RGB and NIR imagery offers a scalable, non-invasive, and cost-effective way of sediment monitoring in support of water quality assessment and environmental management. Full article

(This article belongs to the Special Issue Water Modeling Using Combined Machine Learning and Fieldwork Investigation)

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15 pages, 1899 KiB

Open AccessArticle

Lipidomic Profile of Individuals Infected by Schistosoma mansoni

by Thainá Rodrigues de Souza Fialho, Ronald Alves dos Santos, Yuri Tabajara, Ane Caroline Casaes, Michael Nascimento Macedo, Bruna Oliveira Lopes Souza, Kelvin Edson Marques de Jesus, Leonardo Paiva Farias, Camilla Almeida Menezes, Isadora Cristina de Siqueira, Carlos Arterio Sorgi, Adriano Queiroz and Ricardo Riccio Oliveira

Int. J. Mol. Sci. 2025, 26(15), 7491; https://doi.org/10.3390/ijms26157491 (registering DOI) - 2 Aug 2025

Abstract

Schistosoma mansoni infection is associated with hepatic inflammation and fibrosis, but its systemic metabolic effects remain poorly understood. This study aimed to investigate changes in the serum lipidomic profile associated with S. mansoni infection and parasite load in individuals from an endemic area. This cross-sectional analysis was nested within a longitudinal cohort study conducted in northeastern Brazil. Parasitological diagnosis and quantification were performed using the Kato–Katz technique. A total of 45 individuals were selected and divided into three groups: high parasite load (HL), low parasite load (LL), and uninfected controls (NegE). Serum samples were analyzed using mass-spectrometry-based lipidomics. The most abundant lipid subclasses across all groups were phosphatidylcholines (PC), triacylglycerols (TAG), and phosphatidylethanolamines (PE). However, individuals in the HL group exhibited distinct lipidomic profiles, with increased levels of specific phosphatidylinositols (PI) and reduced levels of certain TAG species compared to the NegE group. These changes may reflect host–parasite interactions and immune–metabolic alterations driven by intense infection. Our findings suggest that S. mansoni infection, particularly at higher parasite burdens, can influence the host’s serum lipid profile and may contribute to metabolic disturbances in endemic populations. Full article

(This article belongs to the Special Issue Omics Science and Research in Human Health and Disease)

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11 pages, 1083 KiB

Open AccessArticle

Assessment of ¹³⁷Cs and ⁴⁰K Transfer Factors in Croatian Agricultural Systems and Implications for Food Safety

by Tomislav Bituh, Branko Petrinec, Dragutin Hasenay and Sanja Stipičević

Environments 2025, 12(8), 269; https://doi.org/10.3390/environments12080269 (registering DOI) - 2 Aug 2025

Abstract

Croatian agricultural legislation acknowledges the significance of radionuclides as pollutants in agricultural lands; however, it lacks specific thresholds or reference values for contamination levels, in contrast to other contaminants. This absence highlights the necessity for a comprehensive assessment of radionuclides across various agricultural systems in Croatia. This study investigates the transfer of radionuclides ¹³⁷Cs and ⁴⁰K from soil to agricultural crops throughout Croatia and estimates the consequent annual ingestion dose for the population. The samples collected comprised food crops and animal feed, with corresponding soil samples analyzed to calculate transfer factors. Activity concentrations of ¹³⁷Cs exhibited regional and crop-type variability, reflecting the uneven distribution of fallout and differing soil properties. Transfer factors were found to range from 0.003 to 0.06 for ¹³⁷Cs and from 0.15 to 3.1 for ⁴⁰K, with the highest uptake occurring in kidney beans. The total estimated annual effective ingestion dose was calculated to be a maximum of 0.748 mSv/year for children aged 2–7, predominantly attributable to ⁴⁰K. Given the homeostatic regulation of potassium in the human body, the dose associated with ¹³⁷Cs poses a more significant radiological concern. These findings underscore the need for radionuclide-specific agricultural legislation in Croatia and offer a baseline for recommending reference values and informing future regulations regarding agricultural soil contamination. Full article

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38 pages, 6505 KiB

Open AccessReview

Trends in Oil Spill Modeling: A Review of the Literature

by Rodrigo N. Vasconcelos, André T. Cunha Lima, Carlos A. D. Lentini, José Garcia V. Miranda, Luís F. F. de Mendonça, Diego P. Costa, Soltan G. Duverger and Elaine C. B. Cambui

Water 2025, 17(15), 2300; https://doi.org/10.3390/w17152300 (registering DOI) - 2 Aug 2025

Abstract

Oil spill simulation models are essential for predicting the oil spill behavior and movement in marine environments. In this study, we comprehensively reviewed a large and diverse body of peer-reviewed literature obtained from Scopus and Web of Science. Our initial analysis phase focused on examining trends in scientific publications, utilizing the complete dataset derived after systematic screening and database integration. In the second phase, we applied elements of a systematic review to identify and evaluate the most influential contributions in the scientific field of oil spill simulations. Our analysis revealed a steady and accelerating growth of research activity over the past five decades, with a particularly notable expansion in the last two. The field has also experienced a marked increase in collaborative practices, including a rise in international co-authorship and multi-authored contributions, reflecting a more global and interdisciplinary research landscape. We cataloged the key modeling frameworks that have shaped the field from established systems such as OSCAR, OIL-MAP/SIMAP, and GNOME to emerging hybrid and Lagrangian approaches. Hydrodynamic models were consistently central, often integrated with biogeochemical, wave, atmospheric, and oil-spill-specific modules. Environmental variables such as wind, ocean currents, and temperature were frequently used to drive model behavior. Geographically, research has concentrated on ecologically and economically sensitive coastal and marine regions. We conclude that future progress will rely on the real-time integration of high-resolution environmental data streams, the development of machine-learning-based surrogate models to accelerate computations, and the incorporation of advanced biodegradation and weathering mechanisms supported by experimental data. These advancements are expected to enhance the accuracy, responsiveness, and operational value of oil spill modeling tools, supporting environmental monitoring and emergency response. Full article

(This article belongs to the Special Issue Advanced Remote Sensing for Coastal System Monitoring and Management)

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33 pages, 4098 KiB

Open AccessSystematic Review

Pharmacological Inhibition of the PI3K/AKT/mTOR Pathway in Rheumatoid Arthritis Synoviocytes: A Systematic Review and Meta-Analysis (Preclinical)

by Tatiana Bobkova, Artem Bobkov and Yang Li

Pharmaceuticals 2025, 18(8), 1152; https://doi.org/10.3390/ph18081152 (registering DOI) - 2 Aug 2025

Abstract

Background/Objectives: Constitutive activation of the PI3K/AKT/mTOR signaling cascade underlies the aggressive phenotype of fibroblast-like synoviocytes (FLSs) in rheumatoid arthritis (RA); however, a quantitative synthesis of in vitro data on pathway inhibition remains lacking. This systematic review and meta-analysis aimed to (i) aggregate standardized effects of pathway inhibitors on proliferation, apoptosis, migration/invasion, IL-6/IL-8 secretion, p-AKT, and LC3; (ii) assess heterogeneity and identify key moderators of variability, including stimulus type, cell source, and inhibitor class. Methods: PubMed, Europe PMC, and the Cochrane Library were searched up to 18 May 2025 (PROSPERO CRD420251058185). Twenty of 2684 screened records met eligibility. Two reviewers independently extracted data and assessed study quality with SciRAP. Standardized mean differences (Hedges g) were pooled using a Sidik–Jonkman random-effects model with Hartung–Knapp confidence intervals. Heterogeneity (τ², I²), 95% prediction intervals, and meta-regression by cell type were calculated; robustness was tested with REML-HK, leave-one-out, and Baujat diagnostics. Results: PI3K/AKT/mTOR inhibition markedly reduced proliferation (to –5.1 SD), IL-6 (–11.1 SD), and IL-8 (–6.5 SD) while increasing apoptosis (+2.7 SD). Fourteen of seventeen outcome clusters showed large effects (|g| ≥ 0.8), with low–moderate heterogeneity (I² ≤ 35% in 11 clusters). Prediction intervals crossed zero only in small k-groups; sensitivity analyses shifted pooled estimates by ≤0.05 SD. p-AKT and p-mTOR consistently reflected functional changes and emerged as reliable pharmacodynamic markers. Conclusions: Targeted blockade of PI3K/AKT/mTOR robustly suppresses the proliferative and inflammatory phenotype of RA-FLSs, reaffirming this axis as a therapeutic target. The stability of estimates across multiple analytic scenarios enhances confidence in these findings and highlights p-AKT and p-mTOR as translational response markers. The present synthesis provides a quantitative basis for personalized dual-PI3K/mTOR strategies and supports the adoption of standardized long-term preclinical protocols. Full article

(This article belongs to the Special Issue Pharmacological Modulation of Inflammation in Autoimmune Diseases and Cancer)

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Graphical abstract

23 pages, 2750 KiB

Open AccessArticle

Seasonal Sea Surface Temperatures from Mercenaria spp. During the Plio-Pleistocene: Oxygen Isotope Versus Clumped Isotope Paleothermometers

by Garrett F. N. Braniecki, Donna Surge and Ethan G. Hyland

Geosciences 2025, 15(8), 295; https://doi.org/10.3390/geosciences15080295 (registering DOI) - 2 Aug 2025

Abstract

The Mid-Piacenzian Warm Interval (MPWI) is marked by warmer temperatures and higher atmospheric CO₂ levels than today, making it an analogue for late-21st-century-warming, whereas the early Pleistocene cooling is more like today. We compare seasonal growth temperatures derived from oxygen isotope ratios (δ¹⁸O) and clumped isotopes (∆₄₇) in Mercenaria. Modern shells were previously collected from coastal NC. The fossil shells are from the Duplin (MPWI) and Waccamaw Formations (early Pleistocene), NC. Oxygen isotope ratios range from −2.2‰ to 2.3‰ (modern), −0.9‰ to 2.4‰ (MPWI), and −0.9‰ to 2.9‰ (early Pleistocene). The values of Δ₄₇ range from 0.576‰ to 0.639‰ (modern), 0.566‰ to 0.621‰ (MPWI), and 0.581‰ to 0.615‰ (early Pleistocene). We show that Mercenaria do not require a species-specific ∆₄₇ calibration. Modern and MPWI ∆₄₇-derived summer/winter temperatures (SST_∆47) and seasonal amplitudes are indistinguishable from δ¹⁸O-derived temperatures. The early Pleistocene summer SST_∆47 is indistinguishable from δ¹⁸O-derived temperatures, but the winter SST_∆47 is warmer by 5 °C and may reflect within-shell time averaging. The modern summer/winter SST_∆47 are indistinguishable from the MPWI, but the MPWI has a lower seasonal amplitude by 5 °C. Compared to our calculated δ¹⁸O_sw values, modeled values for the MPWI are within error but are much lower, and they are not within error for the early Pleistocene. Full article

(This article belongs to the Special Issue Pliocene Studies in Paleobiology, Paleoenvironment and Paleoclimate)

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18 pages, 1476 KiB

Open AccessArticle

Ambiguities, Built-In Biases, and Flaws in Big Data Insight Extraction

by Serge Galam

Information 2025, 16(8), 661; https://doi.org/10.3390/info16080661 (registering DOI) - 2 Aug 2025

Abstract

I address the challenge of extracting reliable insights from large datasets using a simplified model that illustrates how hierarchical classification can distort outcomes. The model consists of discrete pixels labeled red, blue, or white. Red and blue indicate distinct properties, while white represents unclassified or ambiguous data. A macro-color is assigned only if one color holds a strict majority among the pixels. Otherwise, the aggregate is labeled white, reflecting uncertainty. This setup mimics a percolation threshold at fifty percent. Assuming that directly accessing the various proportions from the data of colors is infeasible, I implement a hierarchical coarse-graining procedure. Elements (first pixels, then aggregates) are recursively grouped and reclassified via local majority rules, ultimately producing a single super-aggregate for which the color represents the inferred macro-property of the collection of pixels as a whole. Analytical results supported by simulations show that the process introduces additional white aggregates beyond white pixels, which could be present initially; these arise from groups lacking a clear majority, requiring arbitrary symmetry-breaking decisions to attribute a color to them. While each local resolution may appear minor and inconsequential, their repetitions introduce a growing systematic bias. Even with complete data, unavoidable asymmetries in local rules are shown to skew outcomes. This study highlights a critical limitation of recursive data reduction. Insight extraction is shaped not only by data quality but also by how local ambiguity is handled, resulting in built-in biases. Thus, the related flaws are not due to the data but to structural choices made during local aggregations. Although based on a simple model, these findings expose a high likelihood of inherent flaws in widely used hierarchical classification techniques. Full article

(This article belongs to the Section Artificial Intelligence)

24 pages, 673 KiB

Open AccessArticle

Bridge Tower Warning Method Based on Improved Multi-Rate Fusion Under Strong Wind Action

by Yan Shi, Yan Wang, Lu-Nan Wang, Wei-Nan Wang and Tao-Yuan Yang

Buildings 2025, 15(15), 2733; https://doi.org/10.3390/buildings15152733 (registering DOI) - 2 Aug 2025

Abstract

The displacement of bridge towers is relatively large under strong wind action. Changes in tower displacement can reflect the usage status of the bridge towers. Therefore, it is necessary to conduct performance warning research on tower displacement under strong wind action. In this paper, the triple standard deviation method, multiple linear regression method, and interpolation method are used to preprocess monitoring data with skipped points and missing anomalies. An improved multi-rate data fusion method, validated using simulated datasets, was applied to correct monitoring data at bridge tower tops. The fused data were used to feed predictive models and generate structural performance alerts. Spectral analysis confirmed that the fused displacement measurements achieve high precision by effectively merging the low-frequency GPS signal with the high-frequency accelerometer signal. Structural integrity monitoring of wind-loaded bridge towers used modeling residuals as alert triggers. The efficacy of this proactive monitoring strategy has been quantitatively validated through statistical evaluation of alarm accuracy rates. Full article

(This article belongs to the Special Issue Intelligent Materials and Structural Health: Mechanics, Damage Detection, Performance Enhancement, and AI-Driven Techniques)

21 pages, 5182 KiB

Open AccessArticle

Effects of High-Phenolic Extra Virgin Olive Oil (EVOO) on the Lipid Profile of Patients with Hyperlipidemia: A Randomized Clinical Trial

by Christos Kourek, Emmanouil Makaris, Prokopios Magiatis, Virginia Zouganeli, Vassiliki Benetou, Alexandros Briasoulis, Andrew Xanthopoulos, Ioannis Paraskevaidis, Eleni Melliou, Georgios Koudounis and Philippos Orfanos

Nutrients 2025, 17(15), 2543; https://doi.org/10.3390/nu17152543 (registering DOI) - 2 Aug 2025

Abstract

Background/Objectives: Hyperlipidemia is a major risk factor for cardiovascular disease and atherosclerosis. Polyphenols found in polyphenol-rich extra virgin olive oil (EVOO) have been shown to possess strong antioxidant, anti-inflammatory, and cardioprotective properties. The present study aimed to assess the effects of two types of EVOO with different polyphenol content and dosages on the lipid profile of hyperlipidemic patients. Methods: In this single-blind, randomized clinical trial, 50 hyperlipidemic patients were randomized to receive either a higher-dose, lower-phenolic EVOO (414 mg/kg phenols, 20 g/day) or a lower-dose, higher-phenolic EVOO (1021 mg/kg phenols, 8 g/day), for a period of 4 weeks. These doses were selected to ensure equivalent daily polyphenol intake in both groups (~8.3 mg of total phenols/day), based on chemical analysis performed using NMR spectroscopy. The volumes used (8–20 g/day) reflect typical daily EVOO intake and were well tolerated by participants. A group of 20 healthy individuals, separated into two groups, also received the two types of EVOO, respectively, for the same duration. Primary endpoints included blood levels of total blood cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, lipoprotein-a (Lpa), and apolipoproteins A1 and B. Measurements were performed at baseline and at the end of the 4-week intervention. Linear mixed models were performed for the data analysis. Results: The higher-phenolic, lower-dose EVOO group showed a more favorable change in total blood cholesterol (p = 0.045) compared to the lower-phenolic, higher-dose group. EVOO intake was associated with a significant increase in HDL (p < 0.001) and reduction in Lp(a) (p = 0.040) among hyperlipidemic patients in comparison to healthy individuals. Conclusions: EVOO consumption significantly improved the lipid profile of hyperlipidemic patients. Higher-phenolic EVOO at lower dosages appears to be more effective in improving the lipid profile than lower-phenolic EVOO in higher dosages. Full article

(This article belongs to the Section Clinical Nutrition)

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