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Search Results (1,225)

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12 pages, 1041 KiB  
Article
Investigating the Influence of Conventional vs. Ultra-High Dose Rate Proton Irradiation Under Normoxic or Hypoxic Conditions on Multiple Developmental Endpoints in Zebrafish Embryos
by Alessia Faggian, Gaia Pucci, Enrico Verroi, Alberto Fasolini, Stefano Lorentini, Sara Citter, Maria Caterina Mione, Marco Calvaruso, Giorgio Russo, Emanuele Scifoni, Giusi Irma Forte, Francesco Tommasino and Alessandra Bisio
Cancers 2025, 17(15), 2564; https://doi.org/10.3390/cancers17152564 (registering DOI) - 3 Aug 2025
Abstract
Objectives: To investigate how the FLASH effect modulates radiation response on multiple developmental endpoints of zebrafish embryos under normoxic and hypoxic conditions, after irradiation with proton beams at a conventional and an ultra-high dose rate (UHDR). Methods: Embryos were obtained from adult zebrafish [...] Read more.
Objectives: To investigate how the FLASH effect modulates radiation response on multiple developmental endpoints of zebrafish embryos under normoxic and hypoxic conditions, after irradiation with proton beams at a conventional and an ultra-high dose rate (UHDR). Methods: Embryos were obtained from adult zebrafish and irradiated with a 228 MeV proton beam 24 h post-fertilization (hpf) at a dose rate of 0.6 and 317 Gy/s. For the hypoxic group, samples were kept inside a hypoxic chamber prior to irradiation, while standard incubation was adopted for the normoxic group. After irradiation, images of single embryos were acquired, and radiation effects on larval length, yolk absorption, pericardial edema, head size, eye size, and spinal curvature were assessed at specific time points. Results: Data indicate a general trend of significantly reduced toxicity after exposure to a UHDR compared to conventional regimes, which is maintained under both normoxic and hypoxic conditions. Differences are significant for the levels of pericardial edema induced by a UHDR versus conventional irradiation in normoxic conditions, and for eye and head size in hypoxic conditions. The toxicity scoring analysis shows a tendency toward a protective effect of the UHDR, which appears to be associated with a lower percentage of embryos in the high score categories. Conclusions: A radioprotective effect at a UHDR is observed both for normoxic (pericardial edema) and hypoxic (head and eye size) conditions. These results suggest that while the UHDR may preserve a potential to reduce radiation-induced damage, its protective effects are endpoint-dependent; the role of oxygenation might also be dependent on the tissue involved. Full article
(This article belongs to the Section Cancer Therapy)
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17 pages, 2828 KiB  
Article
Augmented Reality in Cardiovascular Education (HoloHeart): Assessment of Students’ and Lecturers’ Needs and Expectations at Heidelberg University Medical School
by Pascal Philipp Schlegel, Florian Kehrle, Till J. Bugaj, Eberhard Scholz, Alexander Kovacevic, Philippe Grieshaber, Ralph Nawrotzki, Joachim Kirsch, Markus Hecker, Anna L. Meyer, Katharina Seidensaal, Thuy D. Do, Jobst-Hendrik Schultz, Norbert Frey and Ann-Kathrin Rahm
Appl. Sci. 2025, 15(15), 8595; https://doi.org/10.3390/app15158595 (registering DOI) - 2 Aug 2025
Abstract
Background: A detailed understanding of cardiac anatomy and physiology is crucial in cardiovascular medicine. However, traditional learning methods often fall short in addressing this complexity. Augmented reality (AR) offers a promising tool to enhance comprehension. To assess its potential integration into the Heidelberger [...] Read more.
Background: A detailed understanding of cardiac anatomy and physiology is crucial in cardiovascular medicine. However, traditional learning methods often fall short in addressing this complexity. Augmented reality (AR) offers a promising tool to enhance comprehension. To assess its potential integration into the Heidelberger Curriculum Medicinale (HeiCuMed), we conducted a needs assessment among medical students and lecturers at Heidelberg University Medical School. Methods: Our survey aimed to evaluate the perceived benefits of AR-based learning compared to conventional methods and to gather expectations regarding an AR course in cardiovascular medicine. Using LimeSurvey, we developed a questionnaire to assess participants’ prior AR experience, preferred learning methods, and interest in a proposed AR-based, 2 × 90-min in-person course. Results: A total of 101 students and 27 lecturers participated. Support for AR in small-group teaching was strong: 96.3% of students and 90.9% of lecturers saw value in a dedicated AR course. Both groups favored its application in anatomy, cardiac surgery, and internal medicine. Students prioritized congenital heart defects, coronary anomalies, and arrhythmias, while lecturers also emphasized invasive valve interventions. Conclusions: There is significant interest in AR-based teaching in cardiovascular education, suggesting its potential to complement and improve traditional methods in medical curricula. Further studies are needed to assess the potential benefits regarding learning outcomes. Full article
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23 pages, 5773 KiB  
Article
Climate Activism in Our Part of The World and Methodological Insights on How to Study It
by Rezvaneh Erfani
Youth 2025, 5(3), 80; https://doi.org/10.3390/youth5030080 (registering DOI) - 1 Aug 2025
Viewed by 45
Abstract
This paper presents an ethnographically informed analysis of research in Cairo and Sharm El-Sheikh (Egypt) surrounding the 2022 United Nations Framework Convention on Climate Change (UNFCCC) Conference of Parties (COP27) summit. I discuss the geopolitics and geopolitical disruptions of researching activism and activist [...] Read more.
This paper presents an ethnographically informed analysis of research in Cairo and Sharm El-Sheikh (Egypt) surrounding the 2022 United Nations Framework Convention on Climate Change (UNFCCC) Conference of Parties (COP27) summit. I discuss the geopolitics and geopolitical disruptions of researching activism and activist lives in politically sensitive environments. As shown here, developing new methodological interventions plays a crucial role in understanding contextual methodological limitations, dealing with logistical challenges, and building authentic relationships with research participants. Here, I introduce counter-interviews as a methodological strategy to build trust and invest in researcher–participant relationships. This article draws on participant observation, conversations with environmental and climate activists and non-activists in Cairo prior to and after COP27 and in Sharm El-Sheikh during the second week of the summit, reflective field notes, and 20 semi-structured interviews conducted online between February and August 2023. Here, I use the term “environmental non-activism” to draw attention to the sensitivity, complexity, and fragility of political or apolitical environmental and climate action in an authoritarian context where any form of collective action is highly monitored, regulated, and sometimes criminalized by the state. The main argument of this paper is that examining interlocking power dynamics that shape and reshape the activist space in relation to the state is a requirement for understanding and researching the complexities and specificities of climate activism and non-activism in authoritarian contexts. Along with this argument, this paper invites climate education researchers to reevaluate what non-movements and non-activists in the Global South offer to their analyses of possible alternatives, socio-political change, and politics of hope (and to the broader field of activism in educational research, where commitment to disruption, refusal, and subversion play a key role. Full article
(This article belongs to the Special Issue Politics of Disruption: Youth Climate Activisms and Education)
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13 pages, 1189 KiB  
Article
Positive Effects of Reduced Tillage Practices on Earthworm Population Detected in the Early Transition Period
by Irena Bertoncelj, Anže Rovanšek and Robert Leskovšek
Agriculture 2025, 15(15), 1658; https://doi.org/10.3390/agriculture15151658 - 1 Aug 2025
Viewed by 128
Abstract
Tillage is a major factor influencing soil biological communities, particularly earthworms, which play a key role in soil structure and nutrient cycling. To address soil degradation, less-intensive tillage practices are increasingly being adopted globally and have shown positive effects on earthworm populations when [...] Read more.
Tillage is a major factor influencing soil biological communities, particularly earthworms, which play a key role in soil structure and nutrient cycling. To address soil degradation, less-intensive tillage practices are increasingly being adopted globally and have shown positive effects on earthworm populations when applied consistently over extended periods. However, understanding of the earthworm population dynamics in the period following the implementation of changes in tillage practices remains limited. This three-year field study (2021–2023) investigates earthworm populations during the early transition phase (4–6 years) following the conversion from conventional ploughing to conservation (<8 cm depth, with residue retention) and no-tillage systems in a temperate arable system in central Slovenia. Earthworms were sampled annually in early October from three adjacent fields, each following the same three-year crop rotation (maize—winter cereal + cover crop—soybeans), using a combination of hand-sorting and allyl isothiocyanate (AITC) extraction. Results showed that reduced tillage practices significantly increased both earthworm biomass and abundance compared to conventional ploughing. However, a significant interaction between tillage and year was observed, with a sharp decline in earthworm abundance and mass in 2022, likely driven by a combination of 2022 summer tillage prior to cover crop sowing and extreme drought conditions. Juvenile earthworms were especially affected, with their proportion decreasing from 62% to 34% in ploughed plots and from 63% to 26% in conservation tillage plots. Despite interannual fluctuations, no-till showed the lowest variability in earthworm population. Long-term monitoring is essential to disentangle management and environmental effects and to inform resilient soil management strategies. Full article
(This article belongs to the Section Agricultural Soils)
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20 pages, 2320 KiB  
Article
Electric Vehicle Energy Management Under Unknown Disturbances from Undefined Power Demand: Online Co-State Estimation via Reinforcement Learning
by C. Treesatayapun, A. D. Munoz-Vazquez, S. K. Korkua, B. Srikarun and C. Pochaiya
Energies 2025, 18(15), 4062; https://doi.org/10.3390/en18154062 (registering DOI) - 31 Jul 2025
Viewed by 200
Abstract
This paper presents a data-driven energy management scheme for fuel cell and battery electric vehicles, formulated as a constrained optimal control problem. The proposed method employs a co-state network trained using real-time measurements to estimate the control law without requiring prior knowledge of [...] Read more.
This paper presents a data-driven energy management scheme for fuel cell and battery electric vehicles, formulated as a constrained optimal control problem. The proposed method employs a co-state network trained using real-time measurements to estimate the control law without requiring prior knowledge of the system model or a complete dataset across the full operating domain. In contrast to conventional reinforcement learning approaches, this method avoids the issue of high dimensionality and does not depend on extensive offline training. Robustness is demonstrated by treating uncertain and time-varying elements, including power consumption from air conditioning systems, variations in road slope, and passenger-related demands, as unknown disturbances. The desired state of charge is defined as a reference trajectory, and the control input is computed while ensuring compliance with all operational constraints. Validation results based on a combined driving profile confirm the effectiveness of the proposed controller in maintaining the battery charge, reducing fluctuations in fuel cell power output, and ensuring reliable performance under practical conditions. Comparative evaluations are conducted against two benchmark controllers: one designed to maintain a constant state of charge and another based on a soft actor–critic learning algorithm. Full article
(This article belongs to the Special Issue Forecasting and Optimization in Transport Energy Management Systems)
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16 pages, 2174 KiB  
Article
TwinFedPot: Honeypot Intelligence Distillation into Digital Twin for Persistent Smart Traffic Security
by Yesin Sahraoui, Abdessalam Mohammed Hadjkouider, Chaker Abdelaziz Kerrache and Carlos T. Calafate
Sensors 2025, 25(15), 4725; https://doi.org/10.3390/s25154725 (registering DOI) - 31 Jul 2025
Viewed by 185
Abstract
The integration of digital twins (DTs) with intelligent traffic systems (ITSs) holds strong potential for improving real-time management in smart cities. However, securing digital twins remains a significant challenge due to the dynamic and adversarial nature of cyber–physical environments. In this work, we [...] Read more.
The integration of digital twins (DTs) with intelligent traffic systems (ITSs) holds strong potential for improving real-time management in smart cities. However, securing digital twins remains a significant challenge due to the dynamic and adversarial nature of cyber–physical environments. In this work, we propose TwinFedPot, an innovative digital twin-based security architecture that combines honeypot-driven data collection with Zero-Shot Learning (ZSL) for robust and adaptive cyber threat detection without requiring prior sampling. The framework leverages Inverse Federated Distillation (IFD) to train the DT server, where edge-deployed honeypots generate semantic predictions of anomalous behavior and upload soft logits instead of raw data. Unlike conventional federated approaches, TwinFedPot reverses the typical knowledge flow by distilling collective intelligence from the honeypots into a central teacher model hosted on the DT. This inversion allows the system to learn generalized attack patterns using only limited data, while preserving privacy and enhancing robustness. Experimental results demonstrate significant improvements in accuracy and F1-score, establishing TwinFedPot as a scalable and effective defense solution for smart traffic infrastructures. Full article
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10 pages, 1225 KiB  
Article
Development of an LC-MS Method for the Analysis of Birch (Betula sp.) Bark Bioactives Extracted with Biosolvents
by Inmaculada Luque-Jurado, Jesús E. Quintanilla-López, Rosa Lebrón-Aguilar, Ana Cristina Soria and María Luz Sanz
Molecules 2025, 30(15), 3181; https://doi.org/10.3390/molecules30153181 - 29 Jul 2025
Viewed by 139
Abstract
Birch (Betula sp.) bark is a well-known natural source of betulin (Bet) and betulinic acid (BAc), both of which have several bioactive properties. The evaluation of the extraction performance, relative to these lupane-type triterpenoids, provided by different biosolvents requires the development of [...] Read more.
Birch (Betula sp.) bark is a well-known natural source of betulin (Bet) and betulinic acid (BAc), both of which have several bioactive properties. The evaluation of the extraction performance, relative to these lupane-type triterpenoids, provided by different biosolvents requires the development of a high-resolution and high-sensitivity liquid chromatography-mass spectrometry (LC-MS) approach that is also compatible with challenging extractants such as natural deep eutectic solvents (NADESs). In this work, an LC-MS method was developed and analytically characterized prior to its application for the quantitation of Bet and BAc in birch bark extracts obtained using conventional solvents (methanol and acetone) and biosolvents (limonene and NADESs). High precision (RSD < 3.3%), sensitivity (LOD: 23 ng mL−1 and 29 ng mL−1 for Bet and BAc, respectively), and accuracy (95–102% recovery) were found for this optimized method, using an acidulated water–methanol mixture as the mobile phase and sodium acetate as an additive. Extraction experiments conducted at 55 °C revealed that the NADESs, particularly thymol:1-octanol (1:1 molar ratio), outperformed the other solvents and were highly effective for the recovery of both triterpenoids (17.50 mg g−1 and 0.92 mg g−1 of Bet and BAc, respectively). This method can also be applied to similar extracts obtained from other biomasses. Full article
(This article belongs to the Special Issue New Advances in Deep Eutectic Solvents, 2nd Edition)
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17 pages, 627 KiB  
Review
Non-Invasive Positive Pressure Ventilation for Pre-Oxygenation of Critically Ill Patients Before Intubation
by Luigi La Via, Giuseppe Cuttone, Tarek Senussi Testa, Gilberto Duarte-Medrano, Natalia Nuno-Lambarri, Cristian Deana, Antonino Maniaci, Daniele Salvatore Paternò, Ivana Zdravkovic and Massimiliano Sorbello
J. Clin. Med. 2025, 14(15), 5356; https://doi.org/10.3390/jcm14155356 - 29 Jul 2025
Viewed by 374
Abstract
Pre-oxygenation is the key step prior to endotracheal intubation, particularly in a critically ill patient, to prevent life-threatening peri-procedural hypoxemia. This narrative review explores the emerging interest of Non-Invasive Positive Pressure Ventilation (NIPPV) as a pre-oxygenation modality in the intensive care unit (ICU) [...] Read more.
Pre-oxygenation is the key step prior to endotracheal intubation, particularly in a critically ill patient, to prevent life-threatening peri-procedural hypoxemia. This narrative review explores the emerging interest of Non-Invasive Positive Pressure Ventilation (NIPPV) as a pre-oxygenation modality in the intensive care unit (ICU) context. We reviewed data from randomized controlled trials (RCTs) and observational studies published from 2000 to 2024 that compare NIPPV to conventional oxygen therapy and High Flow Nasal Cannula Oxygen (HFNCO). The pathophysiological mechanisms for the successful use of NIPPV, including alveolar recruitment, the decrease of shunting, and the maintenance of functional residual capacity, were reviewed in depth. Existing studies show that NIPPV significantly prolongs the apnea time, reduces the rate of peri-intubation severe hypoxaemia in selected patients and is especially effective for patients with acute hypoxaemic respiratory failure. Nevertheless, appropriate patient selection is still crucial because some diseases can contraindicate or even be harmful with NIPPV. We further discussed the practical aspects of how to use this ventilatory support (the best ventilator settings, which interface, and when to apply it). We lastly discuss unanswered questions and offer suggestions and opportunities for future exploration in guiding the role of NIPPV use in the pre-oxygenation of the critically ill patient requiring emergent airway management. Full article
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22 pages, 2239 KiB  
Article
10-Year Fracture Risk Assessment with Novel Adjustment (FRAXplus): Type 2 Diabetic Sample-Focused Analysis
by Oana-Claudia Sima, Ana Valea, Nina Ionovici, Mihai Costachescu, Alexandru-Florin Florescu, Mihai-Lucian Ciobica and Mara Carsote
Diagnostics 2025, 15(15), 1899; https://doi.org/10.3390/diagnostics15151899 - 29 Jul 2025
Viewed by 257
Abstract
Background: Type 2 diabetes (T2D) has been placed among the risk factors for fragility (osteoporotic) fractures, particularly in menopausal women amid modern clinical practice. Objective: We aimed to analyze the bone status in terms of mineral metabolism assays, blood bone turnover [...] Read more.
Background: Type 2 diabetes (T2D) has been placed among the risk factors for fragility (osteoporotic) fractures, particularly in menopausal women amid modern clinical practice. Objective: We aimed to analyze the bone status in terms of mineral metabolism assays, blood bone turnover markers (BTM), and bone mineral density (DXA-BMD), respectively, to assess the 10-year fracture probability of major osteoporotic fractures (MOF) and hip fracture (HF) upon using conventional FRAX without/with femoral neck BMD (MOF-FN/HF-FN and MOF+FN/HF+FN) and the novel model (FRAXplus) with adjustments for T2D (MOF+T2D/HF+T2D) and lumbar spine BMD (MOF+LS/HF+LS). Methods: This retrospective, cross-sectional, pilot study, from January 2023 until January 2024, in menopausal women (aged: 50–80 years) with/without T2D (group DM/nonDM). Inclusion criteria (group DM): prior T2D under diet ± oral medication or novel T2D (OGTT diagnostic). Exclusion criteria: previous anti-osteoporotic medication, prediabetes, insulin therapy, non-T2D. Results: The cohort (N = 136; mean age: 61.36 ± 8.2y) included T2D (22.06%). Groups DM vs. non-DM were age- and years since menopause (YSM)-matched; they had a similar osteoporosis rate (16.67% vs. 23.58%) and fracture prevalence (6.66% vs. 9.43%). In T2D, body mass index (BMI) was higher (31.80 ± 5.31 vs. 26.54 ± 4.87 kg/m2; p < 0.001), while osteocalcin and CrossLaps were lower (18.09 ± 8.35 vs. 25.62 ± 12.78 ng/mL, p = 0.002; 0.39 ± 0.18 vs. 0.48 ± 0.22 ng/mL, p = 0.048), as well as 25-hydroxyvitamin D (16.96 ± 6.76 vs. 21.29 ± 9.84, p = 0.013). FN-BMD and TH-BMD were increased in T2D (p = 0.007, p = 0.002). MOF+LS/HF+LS were statistically significant lower than MOF-FN/HF-FN, respectively, MOF+FN/HF+FN (N = 136). In T2D: MOF+T2D was higher (p < 0.05) than MOF-FN, respectively, MOF+FN [median(IQR) of 3.7(2.5, 5.6) vs. 3.4(2.1, 5.8), respectively, 3.1(2.3, 4.39)], but MOF+LS was lower [2.75(1.9, 3.25)]. HF+T2D was higher (p < 0.05) than HF-FN, respectively, HF+FN [0.8(0.2, 2.4) vs. 0.5(0.2, 1.5), respectively, 0.35(0.13, 0.8)] but HF+LS was lower [0.2(0.1, 0.45)]. Conclusion: Type 2 diabetic menopausal women when compared to age- and YSM-match controls had a lower 25OHD and BTM (osteocalcin, CrossLaps), increased TH-BMD and FN-BMD (with loss of significance upon BMI adjustment). When applying novel FRAX model, LS-BMD adjustment showed lower MOF and HF as estimated by the conventional FRAX (in either subgroup or entire cohort) or as found by T2D adjustment using FRAXplus (in diabetic subgroup). To date, all four types of 10-year fracture probabilities displayed a strong correlation, but taking into consideration the presence of T2D, statistically significant higher risks than calculated by the traditional FRAX were found, hence, the current model might underestimate the condition-related fracture risk. Addressing the practical aspects of fracture risk assessment in diabetic menopausal women might improve the bone health and further offers a prompt tailored strategy to reduce the fracture risk, thus, reducing the overall disease burden. Full article
(This article belongs to the Special Issue Diagnosis and Management of Metabolic Bone Diseases: 2nd Edition)
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17 pages, 3650 KiB  
Article
Towards Intelligent Threat Detection in 6G Networks Using Deep Autoencoder
by Doaa N. Mhawi, Haider W. Oleiwi and Hamed Al-Raweshidy
Electronics 2025, 14(15), 2983; https://doi.org/10.3390/electronics14152983 - 26 Jul 2025
Viewed by 154
Abstract
The evolution of sixth-generation (6G) wireless networks introduces a complex landscape of cybersecurity challenges due to advanced infrastructure, massive device connectivity, and the integration of emerging technologies. Traditional intrusion detection systems (IDSs) struggle to keep pace with such dynamic environments, often yielding high [...] Read more.
The evolution of sixth-generation (6G) wireless networks introduces a complex landscape of cybersecurity challenges due to advanced infrastructure, massive device connectivity, and the integration of emerging technologies. Traditional intrusion detection systems (IDSs) struggle to keep pace with such dynamic environments, often yielding high false alarm rates and poor generalization. This study proposes a novel and adaptive IDS that integrates statistical feature engineering with a deep autoencoder (DAE) to effectively detect a wide range of modern threats in 6G environments. Unlike prior approaches, the proposed system leverages the DAE’s unsupervised capability to extract meaningful latent representations from high-dimensional traffic data, followed by supervised classification for precise threat detection. Evaluated using the CSE-CIC-IDS2018 dataset, the system achieved an accuracy of 86%, surpassing conventional ML and DL baselines. The results demonstrate the model’s potential as a scalable and upgradable solution for securing next-generation wireless networks. Full article
(This article belongs to the Special Issue Emerging Technologies for Network Security and Anomaly Detection)
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19 pages, 28897 KiB  
Article
MetaRes-DMT-AS: A Meta-Learning Approach for Few-Shot Fault Diagnosis in Elevator Systems
by Hongming Hu, Shengying Yang, Yulai Zhang, Jianfeng Wu, Liang He and Jingsheng Lei
Sensors 2025, 25(15), 4611; https://doi.org/10.3390/s25154611 - 25 Jul 2025
Viewed by 249
Abstract
Recent advancements in deep learning have spurred significant research interest in fault diagnosis for elevator systems. However, conventional approaches typically require substantial labeled datasets that are often impractical to obtain in real-world industrial environments. This limitation poses a fundamental challenge for developing robust [...] Read more.
Recent advancements in deep learning have spurred significant research interest in fault diagnosis for elevator systems. However, conventional approaches typically require substantial labeled datasets that are often impractical to obtain in real-world industrial environments. This limitation poses a fundamental challenge for developing robust diagnostic models capable of performing reliably under data-scarce conditions. To address this critical gap, we propose MetaRes-DMT-AS (Meta-ResNet with Dynamic Meta-Training and Adaptive Scheduling), a novel meta-learning framework for few-shot fault diagnosis. Our methodology employs Gramian Angular Fields to transform 1D raw sensor data into 2D image representations, followed by episodic task construction through stochastic sampling. During meta-training, the system acquires transferable prior knowledge through optimized parameter initialization, while an adaptive scheduling module dynamically configures support/query sets. Subsequent regularization via prototype networks ensures stable feature extraction. Comprehensive validation using the Case Western Reserve University bearing dataset and proprietary elevator acceleration data demonstrates the framework’s superiority: MetaRes-DMT-AS achieves state-of-the-art few-shot classification performance, surpassing benchmark models by 0.94–1.78% in overall accuracy. For critical few-shot fault categories—particularly emergency stops and severe vibrations—the method delivers significant accuracy improvements of 3–16% and 17–29%, respectively. Full article
(This article belongs to the Special Issue Signal Processing and Sensing Technologies for Fault Diagnosis)
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17 pages, 2508 KiB  
Article
Transfer Learning-Based Detection of Pile Defects in Low-Strain Pile Integrity Testing
by Övünç Öztürk, Tuğba Özacar and Bora Canbula
Appl. Sci. 2025, 15(15), 8278; https://doi.org/10.3390/app15158278 - 25 Jul 2025
Viewed by 149
Abstract
Pile foundations are critical structural elements, and their integrity is essential for ensuring the stability and safety of construction projects. Low-strain pile integrity testing (LSPIT) is widely used for defect detection; however, conventional manual interpretation of reflectograms is both time-consuming and susceptible to [...] Read more.
Pile foundations are critical structural elements, and their integrity is essential for ensuring the stability and safety of construction projects. Low-strain pile integrity testing (LSPIT) is widely used for defect detection; however, conventional manual interpretation of reflectograms is both time-consuming and susceptible to human error. This study presents a deep learning-driven approach utilizing transfer learning with convolutional neural networks (CNNs) to automate pile defect detection. A dataset of 328 reflectograms collected from real construction sites, including 246 intact and 82 defective samples, was used to train and evaluate the model. To address class imbalance, oversampling techniques were applied. Several state-of-the-art pretrained CNN architectures were compared, with ConvNeXtLarge achieving the highest accuracy of 98.2%. The accuracy reported was achieved on a dedicated test set using real reflectogram data from actual construction sites, distinguishing this study from prior work relying primarily on synthetic data. The proposed novelty includes adapting pre-trained CNN architectures specifically for real-world pile integrity testing, addressing practical challenges such as data imbalance and limited dataset size through targeted oversampling techniques. The proposed approach demonstrates significant improvements in accuracy and efficiency compared to manual interpretation methods, making it a promising solution for practical applications in the construction industry. The proposed method demonstrates potential for generalization across varying pile lengths and geological conditions, though further validation with broader datasets is recommended. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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13 pages, 217 KiB  
Article
An Investigation of Alternative Pathways to Teacher Qualifications in Australia
by Merryn Lesleigh Dawborn-Gundlach
Educ. Sci. 2025, 15(8), 956; https://doi.org/10.3390/educsci15080956 - 24 Jul 2025
Viewed by 324
Abstract
In alignment with global educational trends, Australia has adopted a pluralistic approach to initial teacher education (ITE), encompassing traditional university-based programs, employment-integrated models and vocational training routes. This diversification of pathways has emerged as a strategic response to persistent workforce challenges, including chronic [...] Read more.
In alignment with global educational trends, Australia has adopted a pluralistic approach to initial teacher education (ITE), encompassing traditional university-based programs, employment-integrated models and vocational training routes. This diversification of pathways has emerged as a strategic response to persistent workforce challenges, including chronic shortages, uneven distribution of qualified educators, and limited demographic diversity within the profession. Rather than supplanting conventional ITE models, these alternative pathways serve as complementary options, broadening access and enhancing system responsiveness to evolving societal and educational needs. The rise in non-traditional routes represents a deliberate response to the well-documented global teacher shortage, frequently examined in comparative educational research. Central to their design is a restructuring of traditional program elements, particularly duration and delivery methods, to facilitate more flexible and context-sensitive forms of teacher preparation. Such approaches often create opportunities for individuals who may be excluded from conventional pathways due to socioeconomic constraints, geographic isolation, or non-linear career trajectories. Significantly, the diversity introduced by alternative entry candidates has the potential to enrich school learning environments. These educators often bring a wide range of prior experiences, disciplinary knowledge, and cultural perspectives, contributing to more inclusive and representative teaching practices. The implications for student learning are substantial, particularly in disadvantaged communities where culturally and professionally diverse teachers may enhance engagement and academic outcomes. From a policy perspective, the development of flexible, multifaceted teacher education pathways constitutes a critical component of a sustainable workforce strategy. As demand for qualified teachers intensifies, especially in STEM disciplines and in rural, regional and remote areas, the role of alternative pathways is likely to become increasingly pivotal in achieving broader goals of equity, quality and innovation in teacher preparation. Full article
(This article belongs to the Special Issue Innovation in Teacher Education Practices)
36 pages, 528 KiB  
Review
Advancements in Modern Nucleic Acid-Based Multiplex Testing Methodologies for the Diagnosis of Swine Infectious Diseases
by Jingneng Wang, Lei Zhou and Hanchun Yang
Vet. Sci. 2025, 12(8), 693; https://doi.org/10.3390/vetsci12080693 - 24 Jul 2025
Viewed by 246
Abstract
Swine infectious diseases, often caused by multiple co-infecting agents, pose severe global threats to pig health and industry economics. Conventional single-plex testing assays, whether relying on pathogen antigens or nucleic acids, exhibit limited efficacy in the face of co-infection events. The modern nucleic [...] Read more.
Swine infectious diseases, often caused by multiple co-infecting agents, pose severe global threats to pig health and industry economics. Conventional single-plex testing assays, whether relying on pathogen antigens or nucleic acids, exhibit limited efficacy in the face of co-infection events. The modern nucleic acid-based multiplex testing (NAMT) methods demonstrate substantial strengths in the simultaneous detection of multiple pathogens involving co-infections owing to their remarkable sensitivity, exceptional specificity, high-throughput, and short turnaround time. The development, commercialization, and application of NAMT assays in swine infectious disease surveillance would be advantageous for early detection and control of pathogens at the onset of an epidemic, prior to community transmission. Such approaches not only contribute to saving the lives of pigs but also aid pig farmers in mitigating or preventing substantial economic losses resulting from infectious disease outbreaks, thereby alleviating unwanted pressure on animal and human health systems. The current literature review provides an overview of some modern NAMT methods, such as multiplex quantitative real-time PCR, multiplex digital PCR, microarrays, microfluidics, next-generation sequencing, and their applications in the diagnosis of swine infectious diseases. Furthermore, the strengths and weaknesses of these methods were discussed, as well as their future development and application trends in swine disease diagnosis. Full article
(This article belongs to the Special Issue Exploring Innovative Approaches in Veterinary Health)
18 pages, 774 KiB  
Article
Bayesian Inertia Estimation via Parallel MCMC Hammer in Power Systems
by Weidong Zhong, Chun Li, Minghua Chu, Yuanhong Che, Shuyang Zhou, Zhi Wu and Kai Liu
Energies 2025, 18(15), 3905; https://doi.org/10.3390/en18153905 - 22 Jul 2025
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Abstract
The stability of modern power systems has become critically dependent on precise inertia estimation of synchronous generators, particularly as renewable energy integration fundamentally transforms grid dynamics. Increasing penetration of converter-interfaced renewable resources reduces system inertia, heightening the grid’s susceptibility to transient disturbances and [...] Read more.
The stability of modern power systems has become critically dependent on precise inertia estimation of synchronous generators, particularly as renewable energy integration fundamentally transforms grid dynamics. Increasing penetration of converter-interfaced renewable resources reduces system inertia, heightening the grid’s susceptibility to transient disturbances and creating significant technical challenges in maintaining operational reliability. This paper addresses these challenges through a novel Bayesian inference framework that synergistically integrates PMU data with an advanced MCMC sampling technique, specifically employing the Affine-Invariant Ensemble Sampler. The proposed methodology establishes a probabilistic estimation paradigm that systematically combines prior engineering knowledge with real-time measurements, while the Affine-Invariant Ensemble Sampler mechanism overcomes high-dimensional computational barriers through its unique ensemble-based exploration strategy featuring stretch moves and parallel walker coordination. The framework’s ability to provide full posterior distributions of inertia parameters, rather than single-point estimates, helps for stability assessment in renewable-dominated grids. Simulation results on the IEEE 39-bus and 68-bus benchmark systems validate the effectiveness and scalability of the proposed method, with inertia estimation errors consistently maintained below 1% across all generators. Moreover, the parallelized implementation of the algorithm significantly outperforms the conventional M-H method in computational efficiency. Specifically, the proposed approach reduces execution time by approximately 52% in the 39-bus system and by 57% in the 68-bus system, demonstrating its suitability for real-time and large-scale power system applications. Full article
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