Search Results (248)

Thermal Power Plants (TPPs), as widely used industrial facilities for electricity generation, represent a key task in remote sensing image interpretation. However, detecting TPPs remains a challenging task due to their complex and irregular composition. Many traditional approaches focus on detecting compact, small-scale objects, while existing composite object detection methods are mostly part-based, limiting their ability to capture the structural and textural characteristics of composite targets like TPPs. Moreover, most of them rely on single-modality data, failing to fully exploit the rich information available in remote sensing imagery. To address these limitations, we propose a novel Cross-Modal Frequency-Responsive Attention Network (CFRANet). Specifically, the Modality-Aware Fusion Block (MAFB) facilitates the integration of multi-modal features, enhancing inter-modal interactions. Additionally, the Frequency-Responsive Attention (FRA) module leverages both spatial and localized dual-channel information and utilizes Fourier-based frequency decomposition to separately capture high- and low-frequency components, thereby improving the recognition of TPPs by learning both detailed textures and structural layouts. Experiments conducted on our newly proposed AIR-MTPP dataset demonstrate that CFRANet achieves state-of-the-art performance, with a ${\mathrm{mAP}}_{50}$ of 82.41%. Full article

Background/Objectives: Different risk factors are involved in the initiation and progression of melanoma. In particular, genetic and epigenetic pathways are involved in all stages of melanoma and are exploited in therapeutic approaches. This study investigated the role of circular RNA circ_0001591 in melanoma cell migration. Methods: Three different melanoma cell lines were transfected with siRNA targeting circ_0001591 and with mimic or inhibitor molecules for miR-20a-3p and miR-34a-5p. Gene and protein expression levels were analyzed by RT-qPCR and Western blot, respectively. Dual luciferase reporter assays were performed to confirm the direct interaction of miR-20a-3p and miR-34a-5p with circ_0001591, as well as with the 3’UTRs of AXL (for both miRNAs) and FOSL1 (miR-34a-5p only). Wound healing assays were conducted to assess cell migration velocity. Results: The silencing of circ_0001591 significantly reduces the migration ability of melanoma cell lines. This downregulation was associated with an increased expression of miR-20a-3p and miR-34a-5p. Dual luciferase reporter assays confirmed the direct binding of both miRNAs to circ_0001591, supporting its role as a molecular sponge. The same assays also verified that miR-20a-3p directly targets the 3’UTR of AXL, while miR-34a-5p binds the 3’UTRs of both AXL and FOSL1. Western blot analysis showed that the modulation of this axis affects the expression levels of the AXL and FRA1 oncoproteins. Conclusions: Our findings demonstrate that circ_0001591 promotes melanoma migration by sponging miR-20a-3p and miR-34a-5p, thereby indirectly modulating the expression of AXL and FRA1 oncoprotein. Further investigations of this new regulatory network are needed to better understand its role in melanoma progression and to support the development of targeted therapies. Full article

Background: Peyronie’s disease (PD) is a chronic inflammatory condition that affects the penile albuginea. Oxidative stress (OS) plays a crucial role in the development of the disease, prompting us to investigate OS levels at the site of the disease and in peripheral blood. This article presents our second study in which the OS was evaluated by calculating the OS index (OSI) in blood samples taken directly from the penile corpora cavernosa of patients with PD. Our innovative diagnostic method, which focuses on the analysis of oxidative stress (OS) in the corpora cavernosa of the penis, allows us to accurately identify the “chemical” signals (OS levels) of the pathology in the area where it is present. Methods: Our study included 102 PD patients from our Peyronie’s care center and 100 control cases. To conduct a comprehensive OS analysis, we measured both the total oxidant status (TOS) and total antioxidant status (TAS) and calculated the oxidative stress index (OSI) as OSI = TOS/TAS × 100. Blood samples were collected from the penis and a vein in the upper extremity, and OS was measured using d-ROMs and PATs (FRAS kit). Results: Pearson’s analyses revealed a significant statistical correlation between penile OSI values and PD plaque volumes (p = 0.003), while no correlation was found between systemic OSI values and plaque volumes (p = 0.356). Penile OSI values decreased significantly after PD plaque removal (p < 0.0001). A comparison of penile OSI values in PD patients (post plaque removal) and the control group showed no significant differences (p = 0.418). Conclusions: The lack of correlation between systemic OSI values and Peyronie’s plaque volume suggests that direct sampling from the site of the disease is preferable for OS studies. Conducting a penile OSI study could provide a precise oxidative marker dependent on plaque volume. In addition, the penile OSI study can biochemically monitor the therapeutic result, alongside penile ultrasound imaging. Full article

In this paper, a wideband circularly polarized folded reflectarray antenna (CPFRA) based on a transmissive linear-to-circular polarization converter is proposed. The CPFRA consists of a primary reflector and a sub-reflector. To achieve broadband performance, a metasurface-based RA element on the primary reflector surface and a transmissive linear-to-circular polarization converter on the sub-reflector surface are applied. Moreover, the transmissive linear-to-circular polarization converter on the sub-reflector surface helps convert linear polarization to circular polarization. To verify the proposed CPFRA, a prototype is designed, fabricated, and tested. The measured results exhibit that the proposed CPFRA presents a 3 dB gain bandwidth of 27.4% and a 3 dB axial ratio bandwidth of 23%. The CPFRA achieves a peak gain of 21.2 dBi with an aperture efficiency of 27.2%. The proposed CPFRA is a promising candidate for millimeter-wave (mm-W) satellite communication applications because of its advantages of high gain, low cost, low profile, and broad bandwidth. Full article

Background: This study aimed to explore the therapeutic potential of a dietary regimen of banaba leaf extract (BNB), policosanol (PCO, Raydel^®), and their combination (BNB+PCO), to mitigate high cholesterol (HC) and high galactose (HG) diet-induced dyslipidemia, hyperglycemia, oxidative stress, senescence, and organ damage in zebrafish (Danio rerio). Methodology: Zebrafish (n = 28/group) were fed with HC (4% w/w)+HG (30% w/w) or HC+HG supplemented either with BNB (0.1% w/w) or PCO (0.1% w/w) or BNB+PCO (0.1% w/w each). Following 6 weeks of dietary intervention, biochemical and histopathological examinations across the groups were performed. Results: Post 6 weeks of consumption, the BNB+PCO group exhibited a significant 40% decrease in body weight (BW) relative to the BW of the HC+HG group, while the BNB or PCO groups displayed nonsignificant changes in BW. Both BNB and PCO reduced HC+HG-induced dyslipidemia and hyperglycemia; however, co-administration (BNB+PCO) demonstrated a significantly greater therapeutic effect in countering these conditions compared to either BNB or PCO alone. A similar effect of the BNB+PCO combination was observed on the elevation of plasma sulfhydryl content, paraoxonase (PON), and ferric ion reduction activity (FRA), with notably ~1.2-times (p < 0.01) higher levels compared to their corresponding values observed in the BNB or PCO groups. Significantly diminished plasma AST, ALT, hepatic interleukin 6 (IL-6) levels, and fatty liver changes were observed in response to BNB+PCO, compared to either BNB or PCO alone. Also, BNB+PCO displayed a higher curative effect against HC+HG-induced impairment of tissue regeneration than BNB or PCO alone. A notable effect of BNB+PCO was perceived in protecting kidneys, testis, and ovary damage. Consistently, BNB+PCO showed a profound impact on mitigating HC+HG elevated reactive oxygen species (ROS) generation, apoptosis, cellular senescence, and accumulation of brain-binding lipid proteins (BLBPs) and 4-hydroxynoneal (4-HNE) in the brain. Conclusions: The findings highlight the synergistic effects of the BNB and PCO combination to mitigate the adversity posed by the consumption of the HC+HG diet. Full article

This scientific research presents the most significant aspects of the structural analysis and verification of the main steel railway bridges in Peru in accordance with the American standard. To this end, linear and finite element analyses (FEMs) were performed using calculation notes in MATHCAD and structural validation software (SAP2000, CSI Bridge, IDEA STATICA and GE05), among others, based on on-site inspections, which allowed results to be obtained to analyze, evaluate and determine the structural performance factors (RF) of the main railway bridges in Peru. For this, data obtained from several railway corridors in Peru were taken into consideration, such as the lines of the Southern Railway Train, Central Andean Railway, Huancayo–Huancavelica Railway Train and the Tacna–Arica Train; in addition to the feasibility studies on the Interoceanic Train project: Iquitos–Yurimaguas; projects administered through Public–Private Partnership PPP as well as by the Regionals Government and MTC-Peru. These data were used in order to be able to warn of certain technical aspects that would influence the recommendations for a locomotive replacement project in which new units had different load distributions between the axles, which would make it necessary to review the tracks and bridges of the same in order to determine if they would be able to withstand the new forces safely, as well as to reinforce structural elements according to the material and the structural condition, and finally, to assess the variation in the increase in train speed in some road corridors to achieve a better FRA (Federal Railway Administration) classification of Class 3, where the presence of structures dating back to the last century has been verified as well (1851–1856–1908). Likewise, the seismic criteria and geotechnical conditions of the most representative areas of the country (acceleration 0.30 g) were included in order to also be able to make technical recommendations that would allow us to ensure the useful life of the structure in service, operation and maintenance conditions. Full article

Standardizing data collection, management, and analysis processes can improve the reliability and efficiency of fisheries monitoring programs, yet few studies have examined the operationalization of these tasks within agency settings. We reviewed the Mississippi Department of Wildlife, Fisheries, and Parks, Fisheries Bureau’s inland recreational fisheries monitoring program—a 30+-year effort to standardize field protocols, data handling procedures, and automated analyses through a custom-built computer application, the Fisheries Resources Analysis System (FRAS). Drawing on quantitative summaries of sampling trends and qualitative interviews with fisheries managers, we identified key benefits, challenges, and opportunities associated with the Bureau’s standardization efforts. Standardized procedures improved sampling consistency, data reliability, and operational efficiency, enabling the long-term tracking of fish population and angler metrics across more than 270 managed waterbodies. However, challenges related to analytical transparency and spatiotemporal comparisons persist. Simulations indicated that under current conditions, 5.8, 22.9, and 37.1 years would be required to sample (boat electrofishing) 50%, 75%, and 95% of the Bureau’s waterbodies at least once, respectively; these figures should translate to other agencies, assuming similar resource availability per waterbody. The monitoring program has reduced manual processing effort and enhanced staff capacity for waterbody-specific management, yet several opportunities remain to improve efficiency and utility. These include expanding FRAS functionalities for trend visualization, integrating mobile field data entry to reduce transcription errors, linking monitoring results with management objectives, and enhancing automated report generation for management support. Strengthening these elements could not only streamline workflows but better position agencies to apply standardized data in adaptive management embedded into the monitoring program. Full article

Transformer winding faults (TWFs) can lead to insulation breakdown, internal short circuits, and catastrophic transformer failure. Due to their low current magnitude—particularly at early stages such as inter-turn short circuits, axial or radial displacement, or winding looseness—TWFs often induce minimal impedance changes and generate fault currents that remain within normal operating thresholds. As a result, conventional protection schemes like overcurrent relays, which are tuned for high-magnitude faults, fail to detect such internal anomalies. Moreover, frequency response deviations caused by TWFs often resemble those introduced by routine phenomena such as tap changer operations, load variation, or core saturation, making accurate diagnosis difficult using traditional FRA interpretation techniques. This paper presents a novel diagnostic framework combining Discrete Wavelet Transform (DWT) and Support Vector Machine (SVM) classification to improve the detection of TWFs. The proposed system employs region-based statistical deviation labeling to enhance interpretability across five well-defined frequency bands. It is validated on five real FRA datasets obtained from operating transformers in Gauteng Province, South Africa, covering a range of MVA ratings and configurations, thereby confirming model transferability. The system supports post-processing but is lightweight enough for near real-time diagnostic use, with average execution time under 12 s per case on standard hardware. A custom graphical user interface (GUI), developed in MATLAB R2022a, automates the diagnostic workflow—including region identification, wavelet-based decomposition visualization, and PDF report generation. The complete framework is released as an open-access toolbox for transformer condition monitoring and predictive maintenance. Full article

Transformers, serving as critical components in power systems, are predominantly affected by winding faults that compromise their operational safety and reliability. Frequency Response Analysis (FRA) has emerged as the prevailing methodology for the status assessment of transformer windings in contemporary power engineering practice. To mitigate the accuracy limitations of single-classifier approaches in winding status assessment, this paper proposes a differentiated M-training classification algorithm based on White Shark Optimization (WSO). The principal contributions are threefold: First, building upon the fundamental principles of the M-training algorithm, we establish a classification model incorporating diversified classifiers. For each base classifier, a parameter optimization method leveraging WSO is developed to enhance diagnostic precision. Second, an experimental platform for transformer fault simulation is constructed, capable of replicating various fault types with programmable severity levels. Through controlled experiments, frequency response curves and associated characteristic parameters are systematically acquired under diverse winding statuses. Finally, the model undergoes comprehensive training and validation using experimental datasets, and the model is verified and analyzed by the actual transformer test results. The experimental findings demonstrate that implementing WSO for base classifier optimization enhances the M-training algorithm’s diagnostic precision by 8.92% in fault-type identification and 8.17% in severity-level recognition. The proposed differentiated M-training architecture achieves classification accuracies of 98.33% for fault-type discrimination and 97.17% for severity quantification, representing statistically significant improvements over standalone classifiers. Full article

Extracting nodal features is crucial for analyzing rock structure stability and plays a significant role in designing engineering projects. This study presents an enhanced version of the FraSegNet algorithm, focusing on improving its ability to identify nodal features in images. The updated FraSegNet incorporates the ResNet101 backbone and integrates the Squeeze-and-Excitation (SE) attention mechanism, enabling better concentration on key nodal characteristics. The primary improvements are as follows: (1) Multi-scale feature extraction: Leveraging the ResNet101 architecture for the effective extraction of detailed information from nodal images. (2) Better attention mechanisms: The SE module focuses on nodal regions, resulting in clearer and more refined feature representations. (3) Dynamic learning strategies: I incorporation of cosine annealing and warm-up techniques to optimize training efficiency. The algorithm was validated with the Barton–Bandis model and Hoek–Brown criterion. The experimental results demonstrate its superior performance, achieving 97.1% accuracy in nodal feature detection with an average error of only 1.5% compared to the rock mass parameter. This small error proves the model works well. FraSegNet offers accurate segmentation and precise geometric parameter extraction, making it a valuable tool for advancing rock stability analysis and practical applications in rock mechanics. Full article

This paper introduces a novel diagnostic approach called partial-discharge-activated impulse frequency response analysis (PD-IFRA), developed to overcome the limitations of conventional frequency response analysis (FRA) in detecting partial discharges (PDs) in power transformers. While traditional FRA with low-impulse-voltage excitation (LIVE) effectively identifies mechanical deformations, inter-turn shorts, and insulation faults, it fails to detect incipient PD activity since PD phenomena require excitation beyond the PD inception voltage (PDIV) to initiate. This study proposes, for the first time, the extension of IFRA to moderate impulse voltage levels—without exceeding insulation limits—enabling the early and non-destructive detection of PDs. Experimental validation on a 315 kVA, 11 kV/420 V Dyn11 transformer shows that PD-IFRA effectively identifies PD-related impedance deviations within the 10 kHz–2 MHz frequency range, especially for PD sources associated with floating metal parts. Furthermore, the comparative analysis between normal, short-circuited, and PD-induced conditions demonstrates that PD-IFRA significantly enhances the precursory diagnosis of PDs where conventional FRA fails. This contribution advances transformer condition assessment by integrating PD sensitivity into FRA-based methods without compromising equipment safety. Full article

Winding deformities in distribution transformers pose significant risks to operational reliability and system safety. Frequency response analysis (FRA) is a well-established technique for identifying mechanical faults; however, its diagnostic reliability is hindered by subjectivity in interpreting response signatures. This study proposes a novel diagnostic technique, termed FRA6σ, which integrates Six Sigma (6σ) statistical tools with FRA to enable objective fault detection. The methodology employs control charts ($\overline{X}$ chart, $\overline{R}$-chart) to monitor deviations from baseline signatures and utilizes process capability indices ($C_p$ and $C_{pk}$) to quantify the severity of deviations. Three transformer cases were evaluated across five defined frequency regions (10 Hz to 2 MHz), each associated with distinct physical fault types. The FRA6σ approach successfully identified early-stage faults across all cases. In one instance, axial and radial winding deformation was detected with a $C_p$ of 1.0 and corresponding range chart violations, preceding any visible damage. Another case revealed inter-turn insulation degradation in the 100 kHz–1 MHz band with $C_{pk}$ values below 0.9, prompting immediate intervention. Compared to traditional FRA interpretation, the proposed method improved diagnostic sensitivity by 31.25% and enabled fault detection earlier based on retrospective physical inspection benchmarks. The integration of Six Sigma with FRA provides a structured, quantifiable, and repeatable approach to transformer fault diagnostics. FRA6σ enhances early detection of winding deformities and dielectric issues, offering a robust alternative to subjective analysis and supporting predictive maintenance strategies in power systems. Full article

This paper serves as a comprehensive “starter pack” for electrical diagnostic methods for power transformers. It offers a thorough review of electrical diagnostic techniques, detailing the required instrumentation and highlighting key research directions. The methods discussed include frequency response analysis, partial discharge testing, dielectric dissipation factor (tan delta), direct current (DC) insulation resistance, polarization index, transformer turns ratio test, recovery voltage measurement, polarization–depolarization currents, frequency domain spectroscopy, breakdown voltage testing, and power factor and capacitance testing. Additionally, the paper brings attention to less-explored electrical diagnostic techniques from the past decade. For each method, the underlying principles, applications, necessary instrumentation, advantages, and limitations are carefully examined, alongside emerging trends in the field. A notable shift observed over the past decade is the growing emphasis on hybrid diagnostic approaches and artificial intelligence (AI)-driven data analytics for fault detection. This study serves as a structured reference for researchers—particularly those in the early stages of their careers—as well as industry professionals seeking to explore electrical diagnostic techniques for power transformer condition assessment. It also outlines promising research avenues, contributing to the ongoing evolution of transformer diagnostics. Full article

Inherited neurological disorders, such as spinocerebellar ataxia (SCA) and fragile X (FraX), are frequently caused by short tandem repeat (STR) expansions. The detection and assessment of STRs is important for diagnostics and prognosis. We tested the abilities of nanopore long-read sequencing (LRS) using a custom panel including the nine most common SCA-related genes and FraX and created raw data to report workflow. Using known STR lengths for 23 loci in 12 patients, a pipeline was validated to detect and report STR lengths. In addition, we assessed the capability to detect SNVs, indels, and the methylation status in the same test. For the 23 loci, 22 were concordant with known STR lengths, while for the last, one of three replicates differed, indicating an artefact. All positive control STRs were detected as likely pathogenic, with no additional findings after a visual assessment of repeat motifs. Out of 226 SNV and Indel variants, two were false positive and one false negative (accuracy 98.7%). In all FMR1 controls, a methylation status could be determined. In conclusion, LRS is suitable as a diagnostic workflow for STR analysis in neurological disorders and can be generalized to other diseases. The addition of SNV/Indel and methylation detection promises to allow for a one-test-fits-all workflow. Full article

Background: The efficacy of banaba leaf extract was tested against carboxymethyllysine (CML)-induced toxicity in embryos and adult zebrafish. Additionally, the individual and combined effects of banaba (BNB) and policosanol (PCO) were analyzed to alleviate dyslipidemia, hyperglycemia, and associated effects in streptozotocin (STZ)-induced hyperlipidemic diabetic zebrafish. Methodology: The high cholesterol diet (HCD, final 4%, w/w)-fed zebrafish were injected with STZ to develop diabetes and were subsequently fed with either HCD or HCD+BNB (final 0.1% w/w) or HCD+PCO (final 0.1% w/w) or HCD+BNB+PCO (each final 0.1%, w/w) each for 14 days. The zebrafish tail fin was amputated to assess tissue regeneration, while the organs and blood were collected for histological and biochemical analysis. Results: Severely compromised embryo survivability and developmental defects were noticed in the CML-injected group that significantly improved following BNB exposure. Similarly, CML-induced acute paralysis and mortality of adult zebrafish were effectively mitigated by the treatment with BNB. In the hyperlipidemic diabetic zebrafish, both BNB and PCO supplementation displayed the hypoglycemic effect; however, a remarkable reduction (p < 0.05) in blood glucose levels was observed in the BNB+PCO group, around 14% and 16% less than the BNB group and PCO group, respectively. Likewise, higher tail fin regeneration was noticed in response to BNB+PCO supplementation. Both BNB and PCO have a substantial counter-effect against HCD+STZ-induced dyslipidemia. However, the combined supplementation (BNB+PCO) displayed a significantly better effect than that of BNB and PCO alone to alleviate total cholesterol (TC), triglycerides (TGs), and low-density lipoprotein cholesterol (LDL-C). The most impressive impact of BNB+PCO was noticed in the elevation of high-density lipoprotein cholesterol (HDL-C), which was ~1.5 times higher than the HDL-C level in response to BNB and PCO. Also, BNB+PCO effectively reduced the malondialdehyde (MDA) and elevated the plasma sulfhydryl content, paraoxonase (PON), and ferric ion reduction (FRA) activity. Histological analyses revealed a significant effect of BNB+PCO in preventing inflammatory infiltration, fatty liver changes, and interleukin-6 production. Similarly, a notably better effect of BNB+PCO compared to their individual effect was noticed in preventing kidney damage and mitigation of ROS generation, apoptosis, and cellular senescence. Conclusions: The finding establishes the substantial effect of BNB and PCO in countering hyperglycemia, dyslipidemia, and associated disorders, which synergistically improved following the combined supplementation with BNB+PCO. Full article