Sealing of cerium oxide coating primers on anodized AA2024-T3 alloy by boiling in Lourier buffers

Although their exceptional re-passivation ability, Al-alloys are susceptible to corrosion due to the amphoteric nature of the alumina passivation films. This issue is exacerbated by the disruption of these films by intermetallics on the surfaces of highly doped ones, like AA2024-T3 aircraft alloy. The combination of anodized aluminium oxide (AAO) and cerium conversion coatings (CeCC) shows promise as a coating primer. However, the defective structures of CeO2 and Al2O3 require additional sealing. This research proposes sealing the CeCC/AAO layer by boiling it for 10 minutes in two relatively neutral Lourier buffers, adjusted to pH 7.75, and in a mixture of them. The samples underwent a series of analyses to compare the impact of the sealing procedure on surface topology, properties (e.g., colour and wettability on two samples from each set), and corrosion protective ability. It was assessed after 24 hours of exposure to 3.5 % NaCl model corrosive medium on six samples from each set. The assessments included electrochemical impedance spectroscopy (EIS) and potentiodynamic scanning (PDS) techniques. The results indicate that the borate buffer improves the corrosion protection of the coating primers more effectively than the phosphate and mixed ones

Improving the Corrosion Resistance of Anodized Al 1050 Alloy by Sealing in Cerium-Containing and Mixed Sodium Phosphate Mono Basic and Calcium Nitrate Solutions

This investigation presents results on the improvement of the corrosion-protective effect of consecutive sealing treatments of anodized Al 1050 (AlAnod). The treatments were performed in cerium-containing and mixed NaH2PO4 + Ca(NO3)2 solutions. The changes of the surface morphology, structure and chemical composition, chemical state of the elements, and basic corrosion parameters of the studied systems were investigated by SEM, EDXS, XRD, XPS, and a complex of electrochemical techniques (PDP, EOCP vs. timeplot, chronoamperometric transients, Rp and CR at EOCP, etc.). The results obtained show that the basic components of the obtained sealing conversion layers (before and after exposure to model Cl−-containing corrosion media) are characterized by Ca10(PO4)6(OH)2, AlO(OH), CePO4, and CeAlO3 (after the corrosion tests, they are converted to insoluble Me-PO3 and Me-P4O10). We conclude that the observed decrease in the corrosion rate of Al and the corresponding increase in the polarization resistance are accomplished by the two-step sealing treatment, which fills up the AlAnod pores with insoluble deposits

Influence of the Chemical Composition of Ceria Conversion Coatings, Sealed in Solution of NaH2PO4 and Ca(NO3)2, on the Corrosion Behavior of Aluminum

The corrosion-protective influence of eco-friendly ceria conversion coatings deposited on Al-1050 alloy, additionally treated in mixed NaH2PO4 and Ca(NO3)2 solution, was studied. The main aim of this work was to investigate how the obtained mixed systems of coatings eliminates the negative role of cracks and pores on the surface formed after deposition only of ceria coating. For this purpose, the growth structure, main components and corrosion resistance of the so formed protective systems were investigated by SEM, EDS, XRD, XPS and electrochemical (PDP, Rp, etc.) methods. The results obtained show that the basic components of the conversion layers (before and after exposure in model corrosion media) are characterized by Al2O3, Al(OH)3, CePO4 and Ca5(PO4)3(OH). Based on these results, the optimal conditions of immersion treatment(s) of Al substrate are established. At these regimes, the relationship of co-deposited Ce3+, PO43+ and Ca2+-containing components of the conversion layers determine the maximum values of their polarization resistance—a basic criterion for corrosion protection of Al. This effect is related to the formation of fill out of the defects of the conversion coatings and additional Ca5(PO4)3(OH), CePO4 AlPO4 and Al(OH)3 deposits, leading to the decrease of the corrosion rate

Characterization of Different Types of Screen-Printed Carbon Electrodes Modified Electrochemically by Ceria Coatings

Electrochemical formation of ceria (mixed Ce2O3 and CeO2) coatings on different types of screen-printed carbon electrodes (SPCEs) (based on graphite (C110), carbon nanotubes (CNT), single-walled carbon nanotubes (SWCNT), carbon nanofibers (CNF), and mesoporous carbon (MC)) were studied. Their potential applications as catalysts for various redox reactions and electrochemical sensors were investigated. The ceria oxide layers were electrodeposited on SPCEs at various current densities and deposition time. The morphology, structure, and chemical composition in the bulk of the ceria layers were studied by SEM and EDS methods. XRD was used to identify the formed phases. The concentration, chemical composition and chemical state of the elements on the surface of studied samples were characterized by XPS. It was established that the increase of the concentration of CeCl3 in the solution and the cathode current density strongly affected the surface structure and concentration (relation between Ce3+ and Ce4+, respectively) in the formed ceria layers. At low concentration of CeCl3 (0.1M) and low values of cathode current density (0.5 mA·cm−2), porous samples were obtained, while with their increase, the ceria coatings grew denser

Impact of Prolonged High-Intensity Training on Autonomic Regulation and Fatigue in Track and Field Athletes Assessed via Heart Rate Variability

Background: Elite athletes are frequently subjected to high-intensity training regimens, which can result in cumulative physical stress, overtraining, and potential health risks. Monitoring autonomic responses to such load is essential for optimizing performance and preventing maladaptation. Objective: The present study aimed to assess changes in autonomic regulation immediately and two hours after training in athletes, using an integrated framework (combining time- and frequency-domain HRV indices with nonlinear and recurrence quantification analysis). It was investigated how repeated assessments over a 4-month period can reveal cumulative effects and identify athletes at risk. Special attention was paid to identifying signs of excessive fatigue, autonomic imbalance, and cardiovascular stress. Methods: Holter ECGs of 12 athletes (mean age 21 ± 2.22 years; males, athletes participating in competitions) over a 4-month period were recorded before, immediately after, and two hours after high-intensity training, with HRV calculated from 5-min segments. Metrics included HRV and recurrent quantitative analysis. Statistical comparisons were made between the pre-, post-, and recovery phases to quantify autonomic changes (repeated-measures ANOVA for comparisons across the three states, paired t-tests for direct two-state contrasts, post hoc analyses with Holm–Bonferroni corrections, and effect size estimates η2). Results: Immediately after training, significant decreases in SDNN (↓ 35%), RMSSD (↓ 40%), and pNN50 (↓ 55%), accompanied by increases in LF/HF (↑ 32%), were observed. DFA α1 and Recurrence Rate increased, indicating reduced complexity and more structured patterns of RR intervals. After two hours of recovery, partial normalization was observed; however, RMSSD (−18% vs. baseline) and HF (−21% vs. baseline) remained suppressed, suggesting incomplete recovery of parasympathetic activity. Indications of overtraining and cardiac risk were found in three athletes. Conclusion: High-intensity training in elite athletes induces pronounced acute autonomic changes and incomplete short-term recovery, potentially increasing fatigue and cardiovascular workload. Longitudinal repeated testing highlights differences between well-adapted, fatigued, and at-risk athletes. These findings highlight the need for individualized recovery strategies and ongoing monitoring to optimize adaptation and minimize the risk of overtraining and health complications

Impact on Competitive Performance and Assessment of Fatigue and Stress Based on Heart Rate Variability

Background: Optimizing training load and recovery is crucial for achieving peak performance in competitive wrestling, a sport characterized by high physical, technical, and psychological demands. Methods: This study compared the effects of two different training programs—one emphasizing high-intensity interval training (HIIT) sessions and the other based on traditional volume-oriented training—on both competitive performance and autonomic regulation measured by heart rate variability (HRV). A total of 24 elite wrestlers were divided into two equal groups, each following a different weekly training regimen over a 3-month period. HRV was recorded using a wearable 3-channel ECG Holter before training, immediately after training, and during recovery phases (up to 2 h post-exercise). HRV parameters were analyzed to assess training-induced stress and recovery status. Competitive performance was evaluated using official national championship scores and ranking positions. Results: Both training programs improved competitive performance, the HIIT-based regimen induced greater short-term suppression of parasympathetic activity (RMSSD: −32% vs. −14%; HF power: −40% vs. −18%) and increased sympathetic dominance (LF/HF: +56% vs. +22%) after training. Wrestlers in the HIIT group achieved a mean competition score of 17.92 ± 4.50 points, compared to 15.08 ± 6.26 points in the volume-oriented group. These acute autonomic shifts may provide a higher readiness for intense and explosive actions, which is advantageous in short and dynamic matches. In contrast, the volume-oriented program induced smaller acute autonomic changes but showed a slower recovery to baseline. Conclusions: These findings suggest that HRV-derived measures can serve as sensitive indicators of training load tolerance, recovery capacity, and stress susceptibility in combat sports athletes. This study highlights the value of integrating HRV monitoring into the periodization of combat training to individualize the load, prevent overtraining, and optimize performance outcomes

Physiological State Recognition via HRV and Fractal Analysis Using AI and Unsupervised Clustering

Early detection of physiological dysregulation is critical for timely intervention and effective health management. Traditional monitoring systems often rely on labeled data and predefined thresholds, limiting their adaptability and generalization to unseen conditions. To address this, we propose a framework for label-free classification of physiological states using Heart Rate Variability (HRV), combined with unsupervised machine learning techniques. This approach is particularly valuable when annotated datasets are scarce or unavailable—as is often the case in real-world wearable and IoT-based health monitoring. In this study, data were collected from participants under controlled conditions representing rest, stress, and physical exertion. Core HRV parameters such as the SDNN (Standard Deviation of all Normal-to-Normal intervals), RMSSD (Root Mean Square of the Successive Differences), DFA (Detrended Fluctuation Analysis) were extracted. Principal Component Analysis was applied for dimensionality reduction. K-Means, hierarchical clustering, and Density-based spatial clustering of applications with noise (DBSCAN) were used to uncover natural groupings within the data. DBSCAN identified outliers associated with atypical responses, suggesting potential for early anomaly detection. The combination of HRV descriptors enabled unsupervised classification with over 90% consistency between clusters and physiological conditions. The proposed approach successfully differentiated the three physiological conditions based on HRV and fractal features, with a clear separation between clusters in terms of DFA α1, α2, LF/HF, and RMSSD (with high agreement to physiological labels (Purity ≈ 0.93; ARI = 0.89; NMI = 0.92)). Furthermore, DBSCAN identified three outliers with atypical autonomic profiles, highlighting the potential of the method for early warning detection in real-time monitoring systems

Healthcare Monitoring Using an Internet of Things-Based Cardio System

This study describes an IoT-based health monitoring system designed to notify attending physicians when necessary. The developed IoT system incorporates sensors for ECG, PPG, and temperature; a gyroscope/accelerometer; and a microcontroller. A critical analysis of existing components in these areas was conducted to ensure the IoT system’s good performance, reliability, and suitability for continuous cardiac monitoring and data processing. This study addresses the challenge of monitoring cardiac activity in patients with arrhythmias, focusing on the differences in heart rate variability (HRV) parameters between healthy individuals and those with extrasystolic arrhythmia. The purpose of this research is to evaluate the effectiveness of IoT-based systems using PPG and ECG sensors for cardiac data registration and HRV analysis. The system leverages time domain and frequency domain methods for HRV analysis to assess the states of the autonomic nervous system. Significant differences were observed in HRV parameters, such as the SDNN, SDANN, RMSSD, and the LF/HF ratio. The results demonstrated that both the PPG and ECG methods provide comparable HRV measurements, despite PPG’s higher susceptibility to noise. This study concludes that IoT-based monitoring systems with PPG and ECG integration can reliably detect arrhythmias and offer real-time data for cardiac care

Heteronuclear Complexes of Hg(II) and Zn(II) with Sodium Monensinate as a Ligand

The commercial veterinary antibiotic sodium monensinate (MonNa) binds mercury(II) or zinc(II) cations as thiocyanate [Hg(MonNa)2(SCN)2] (1) or isothiocyanate [Zn(MonNa)2(NCS)2] (2) neutral coordination compounds. The structure and physicochemical properties of 1 and 2 were evaluated by the methods of single crystal and/or powder X-ray diffraction, infrared, nuclear magnetic resonance, X-ray photoelectron spectroscopies, and electrospray-mass spectrometry. The primary cores of the two complexes comprise HgS2O2 (1) and ZnN2O2 (2) coordination motifs, respectively, due to the ambidentate binding modes of the SCN–ligands. The directly bound oxygen atoms originate from the carboxylate function of the parent antibiotic. Sodium cations remain in the hydrophilic cavity of monensin and cannot be replaced by the competing divalent metal ions. Zinc(II) binding does not influence the monensin efficacy in the case of Bacillus cereus and Staphylococcus aureus whereas the antimicrobial assay reveals the potential of complex 2 as a therapeutic candidate for the treatment of infections caused by Bacillus subtilis, Kocuria rhizophila, and Staphylococcus saprophyticus