Researchers have created cryptography algorithms that encrypt data using a public or private key to secure it from intruders. It is insufficient to protect the data by using such a key. No research article has identified an algorithm capable of protecting both the data and the associated key, nor has any mechanism been developed to determine whether access to the data is permissible or impermissible based on the authentication of the key. This paper presents a WEDEx-Kerberotic Framework for data protection, in which a user-defined key is firstly converted to a cipher key using the “Secure Words on Joining Key (SWJK)” algorithm. Subsequently, a WEDEx-Kerberotic encryption mechanism is created to protect the data by encrypting it with the cipher key. The first reason for making the WEDEx-Kerberotic Framework is to convert the user-defined key into a key that has nothing to do with the original key, and the length of the cipher key is much shorter than the original key. The second reason is that each ciphertext and key value are interlinked. When an intruder utilizes the snatching mechanism to obtain data, the attacker obtains data or a key unrelated to the original data. No matter how efficient the algorithm is, an attacker cannot access the data when these methods and algorithms are used to protect it. Finally, the proposed algorithm is compared to the previous approaches to determine the uniqueness of the algorithm and assess its superiority to the previous algorithms. Full article

Compaction quality significantly influences the strength and durability of concrete in structures. Under-compacting can retain entrapped air, reducing strength, while over-compacting can lead to segregation, creating local variances in strength distribution and modulus of elasticity in the concrete structure. This study examines the widely adopted concept that compaction is optimal when bubbles cease to emerge on the concrete surface. We recorded the surface activity of six comparable concrete specimens during the compaction process using a 4K video camera. Four specimens were compacted using a table vibrator and two with a poker vibrator. From the video frames, we isolated the bubbles for analysis, employing digital image processing techniques to distinguish newly risen bubbles per frame. It was found that the bubbles continuously rose to the surface in all specimens throughout the compaction process, suggesting a need for extended compaction, with some specimens showing a slow in the rate of the bubbles’ emergence. However, upon examining the segregation levels, it was discovered that all the specimens were segregated, some severely, despite the continued bubble emergence. These findings undermine the reliability of using bubble emergence as a principle to stop compaction and support the need for developing online measurement tools for evaluating compaction quality. Full article

Particle Swarm Optimization (PSO) algorithms within control structures are a realistic approach; their task is often to predict the optimal control values working with a process model (PM). Owing to numerous numerical integrations of the PM, there is a big computational effort that leads to a large controller execution time. The main motivation of this work is to decrease the computational effort and, consequently, the controller execution time. This paper proposes to replace the PSO predictor with a machine learning model that has “learned” the quasi-optimal behavior of the couple (PSO and PM); the training data are obtained through closed-loop simulations over the control horizon. The new controller should preserve the process’s quasi-optimal control. In identical conditions, the process evolutions must also be quasi-optimal. The multiple linear regression and the regression neural networks were considered the predicting models. This paper first proposes algorithms for collecting and aggregating data sets for the learning process. Algorithms for constructing the machine learning models and implementing the controllers and closed-loop simulations are also proposed. The simulations prove that the two machine learning predictors have learned the PSO predictor’s behavior, such that the process evolves almost identically. The resulting controllers’ execution time have decreased hundreds of times while keeping their optimality; the performance index has even slightly increased. Full article

In synthetic aperture radar (SAR) signal processing, compared with the raw data of level-0, level-1 SAR images are more readily accessible and available in larger quantities. However, an amount of level-1 images are affected by radio frequency interference (RFI), which typically originates from Linear Frequency Modulation (LFM) signals emitted by ground-based radars. Existing research on interference suppression in level-1 data has primarily focused on two methods: transforming SAR images into simulated echo data for interference suppression, or focusing interference in the frequency domain and applying notching filters to reduce interference energy. However, these methods overlook the effective utilization of the interference parameters or are confined to suppressing only one type of LFM interference at a time. In certain SAR images, multiple types of LFM interference manifest bright radiation artifacts that exhibit varying lengths along the range direction while remaining constant in the azimuth direction. It is necessary to suppress multiple LFM interference on SAR images when original echo data are unavailable. This article proposes a joint sparse recovery algorithm for interference suppression in the SAR image domain. In the SAR image domain, two-dimensional LFM interference typically exhibits differences in parameters such as frequency modulation rate and pulse width in the range direction, while maintaining consistency in the azimuth direction. Based on this observation, this article constructs a series of focusing operators for LFM interference in SAR images. These operators enable the sparse representation of dispersed LFM interference. Subsequently, an optimization model is developed that can effectively suppress multi-LFM interference and reduce image loss with the assistance of a regularization term in the image domain. Simulation experiments conducted in various scenarios validate the superior performance of the proposed method. Full article

Knee osteoarthritis is the most prevalent type of osteoarthritis. Patients frequently encounter pain triggered by movement that evolves into impaired joint function. Needing persistent rest or having night-time pain signifies advanced disease. Qualitative research is considered the most effective method for comprehending patients’ needs and contexts. Methods: This study employed a qualitative research design, allowing the researchers to acquire insights into the patients’ beliefs and values, and the contextual factors influencing the formation and expression of these beliefs and values. Results: A cohort of nine patients awaiting total knee replacement (TKR) surgery was included and they were interviewed until data saturation was achieved. The results of the phenomenological analysis resulted in the identification of three themes: “The existence of pain impedes the capacity to participate in daily life activities”; “TKR induced fears and uncertainties regarding the progression of the disease”; “Severe nighttime pain compromising sleep quality”. Conclusions: This study analyzes the experiences of people awaiting TKR surgery, emphasizing the importance of addressing their unique needs to improve preoperative education and rehabilitation. In this way, patients’ recovery during the postoperative phase can be improved. Full article

Alcohol consumption, associated with various cancers, mental disorders, and aggressive behavior, leads to three million deaths globally each year. In Brazil, the alcohol per capita consumption among drinkers aged 15 and over is 41.7 g of pure alcohol/day (~1 L beer/day), which falls into the risky consumption category and exceeds the global average by almost 30%. An effective way to mitigate alcohol-related harm is to increase its retail price. This study assesses the costs of consuming leading brands of beer and sugarcane spirit cachaça (Brazil’s most popular alcoholic beverages) against the expenditure on staple foods. Data on food and alcoholic beverage prices were collected in João Pessoa, Brazil, for 2020 and 2021. The cost per gram of pure alcohol and food were considered to establish consumption patterns of 16.8 g/day (moderate), 41.7 g/day, and 83.4 g/day (heavy), distributed in three scenarios involving the beverages alone or combined (64% beer and 36% cachaça), and a balanced 2000 kcal/day staple diet. The study finds that all heavy consumption scenarios cost less or significantly less (cachaça alone) than a 2000 kcal/day staple diet, highlighting an urgent need for fiscal policies, such as a minimum unit pricing for alcohol, to address public health concerns. Full article

 In the realm of accelerated testing within controlled laboratory settings, the fidelity of the service environment assumes paramount importance. It is imperative to replicate real-world conditions while compressing the testing duration to facilitate early evaluations, thereby optimizing time and cost efficiencies. Traditional immersion protocols, reflective solely of full ballast tank conditions, inadequately expedite the corrosion process representative of an average ballast tank environment. Through the integration of immersion with fog/dry conditions, aligning the test protocol more closely with the internal conditions of an average ballast tank, heightened rates of general corrosion are achieved. This augmentation yields an acceleration factor of 7.82 times the standard test duration, under the assumption of a general corrosion rate of 0.4 mm/year for uncoated ballast tank steel, with both sides exposed. Subsequently, the fog/dry test protocol, albeit only resembling the environment of an empty ballast tank, closely trails in terms of acceleration efficacy. The fog/dry test protocol offers cost-effectiveness and replicability compared to the AMACORT CIFD-01 protocol, making it a strong competitor despite the relatively close acceleration factor. Full article

During robot-assisted rehabilitation, failure to recognize lower limb movement may efficiently limit the development of exoskeleton robots, especially for individuals with knee pathology. A major challenge encountered with surface electromyography (sEMG) signals generated by lower limb movements is variability between subjects, such as motion patterns and muscle structure. To this end, this paper proposes an sEMG-based lower limb motion recognition using an improved support vector machine (SVM). Firstly, non-negative matrix factorization (NMF) is leveraged to analyze muscle synergy for multi-channel sEMG signals. Secondly, the multi-nonlinear sEMG features are extracted, which reflect the complexity of muscle status change during various lower limb movements. The Fisher discriminant function method is utilized to perform feature selection and reduce feature dimension. Then, a hybrid genetic algorithm-particle swarm optimization (GA-PSO) method is leveraged to determine the best parameters for SVM. Finally, the experiments are carried out to distinguish 11 healthy and 11 knee pathological subjects by performing three different lower limb movements. Results demonstrate the effectiveness and feasibility of the proposed approach in three different lower limb movements with an average accuracy of 96.03% in healthy subjects and 93.65% in knee pathological subjects, respectively. Full article

In order to increase the utilization rate of stainless steel slag, reduce storage needs, and mitigate environmental impacts, this study replaces a portion of limestone with varying amounts of stainless steel slag in the calcination of Portland cement clinker. The study primarily examines the influence of stainless steel slag on the phase composition, microstructure, compressive strength, and free calcium oxide (ƒ-CaO) content of Portland cement clinker. The results show the following: (1) Using stainless steel slag to calcine Portland cement clinker can lower the calcination temperature, reducing industrial production costs and energy consumption. (2) With an increase in the amount of stainless steel slag, the dicalcium silicate (C₂S) and tricalcium silicate (C₃S) phases in Portland cement clinker initially increase and then decrease; the C₃S crystals gradually transform into continuous hexagonal plate-shaped distributions, while the tricalcium aluminate (C₃A) and tetracalcium aluminoferrite (C₄AF) crystal structures become denser. When the stainless steel slag content is 15%, the dicalcium silicate and tricalcium silicate phases are at their peak; the C₃S crystals are continuously distributed with a relatively dense structure, and C₃A and C₄AF crystals melt and sinter together, becoming distributed around C₃S. (3) As stainless steel slag content increases, the compressive strength of Portland cement clinker at 3 days, 7 days, and 28 days increases and then decreases, while ƒ-CaO content decreases and then increases. When the stainless steel slag content is 15%, the compressive strength at 28 days is at its highest, 64.4 MPa, with the lowest ƒ-CaO content, 0.78%. The test results provide a basis for the utilization of stainless steel slag in the calcination of Portland cement clinker. Full article

The present study aimed to investigate the chemical content of Romanian juneberries (Amelanchier lamarckii), their effect on antioxidant and enzyme inhibition activities, and their bioaccessibility after simulated in-vitro digestion. In Amelanchier lamarckii extract (AME), 16 polyphenolic compounds were identified by LC-ESI+-MS analysis. The most representative compounds found in the extract were cyanidin-galactoside, 3,4-dihydroxy-5-methoxybenzoic acid, feruloylquinic acid, and kaempferol, all belonging to the anthocyanins, phenolic acids, and flavonols subclasses. The polyphenols of AME exert quenching abilities of harmful reactive oxygen species, as the CUPRAC antioxidant assay value was 323.99 µmol Trolox/g fruit (FW), whereas the FRAP antioxidant value was 4.10 μmol Fe²⁺/g fruit (FW). Enzyme inhibition assays targeting tyrosinase (IC50 = 8.843 mg/mL), α-glucosidase (IC50 = 14.03 mg/mL), and acetylcholinesterase (IC50 = 49.55 mg/mL) were used for a screening of AME’s inhibitory potential against these key enzymes as a common approach for the discovery of potential antidiabetic, skin pigmentation, and neurodegenerative effects. The screening for the potential antidiabetic effects due to the α-glucosidase inhibition was performed in glucose-induced disease conditions in a human retinal pigmented epithelial cell experimental model, proving that AME could have protective potential. In conclusion, AME is a valuable source of phenolic compounds with promising antioxidant potential and metabolic disease-protective effects, warranting further investigation for its use in the nutraceutical and health industries. Full article

Since SARS-CoV-2 is a highly transmissible virus, alternative reliable, fast, and cost-effective methods are still needed to prevent virus spread that can be applied in the laboratory and for point-of-care testing. Reverse transcription real-time fluorescence quantitative PCR (RT-qPCR) is currently the gold criteria for detecting RNA viruses, which requires reverse transcriptase to reverse transcribe viral RNA into cDNA, and fluorescence quantitative PCR detection was subsequently performed. The frequently used reverse transcriptase is thermolabile; the detection process is composed of two steps: the reverse transcription reaction at a relatively low temperature, and the qPCR performed at a relatively high temperature, moreover, the RNA to be detected needs to pretreated if they had advanced structure. Here, we develop a fast and sensitive one-tube SARS-CoV-2 detection platform based on Ultra-fast RTX-PCR and Pyrococcus furiosus Argonaute-mediated Nucleic acid Detection (PAND) technology (URPAND). URPAND was achieved ultra-fast RTX-PCR process based on a thermostable RTX (exo-) with both reverse transcriptase and DNA polymerase activity. The URPAND can be completed RT-PCR and PAND to detect nucleic acid in one tube within 30 min. This method can specifically detect SARS-CoV-2 with a low detection limit of 100 copies/mL. The diagnostic results of clinical samples with one-tube URPAND displayed 100% consistence with RT-qPCR test. Moreover, URPAND was also applied to identify SARS-CoV-2 D614G mutant due to its single-nucleotide specificity. The URPAND platform is rapid, accurate, tube closed, one-tube, easy-to-operate and free of large instruments, which provides a new strategy to the detection of SARS-CoV-2 and other RNA viruses. Full article

Nanosatellites are proliferating as low-cost, dedicated remote sensing opportunities for small nations. However, nanosatellites’ performance as remote sensing platforms is impaired by low downlink speeds, which typically range from 1200 to 9600 bps. Additionally, an estimated 67% of downloaded data are unusable for further applications due to excess cloud cover. To alleviate this issue, we propose an image segmentation and prioritization algorithm to classify and segment the contents of captured images onboard the nanosatellite. This algorithm prioritizes images with clear captures of water bodies and vegetated areas with high downlink priority. This in-orbit organization of images will aid ground station operators with downlinking images suitable for further ground-based remote sensing analysis. The proposed algorithm uses Convolutional Neural Network (CNN) models to classify and segment captured image data. In this study, we compare various model architectures and backbone designs for segmentation and assess their performance. The models are trained on a dataset that simulates captured data from nanosatellites and transferred to the satellite hardware to conduct inferences. Ground testing for the satellite has achieved a peak Mean IoU of 75% and an F1 Score of 0.85 for multi-class segmentation. The proposed algorithm is expected to improve data budget downlink efficiency by up to 42% based on validation testing. Full article

In addition to the detrimental health consequences, the early stages of the COVID-19 pandemic have yielded unforeseen benefits in terms of reducing air pollution emissions. This study investigated air pollution changes in Novi Sad, Serbia, during the COVID-19 lockdown (March–June 2020) and their correlation with acute exacerbations of chronic obstructive pulmonary disease (AECOPD) hospitalizations. Using quasi-Poisson generalized linear models (GLM) and distributed lag non-linear models (DLNM), we examined the relationship between the number of AECOPD hospitalizations and the concentrations of selected air pollutants (PM₁₀, PM_2.5, SO₂, and NO₂) from March to June of 2019, 2020, and 2021. During the COVID-19 lockdown, significant reductions in most air pollutant concentrations and the number of AECOPD hospitalizations were observed. However, neither the study year nor its interaction with air pollutant concentration significantly predicted AECOPD hospitalizations (p > 0.05). The 95% confidence intervals of the relative risks for the occurrence of AECOPD hospitalizations at each increase in the examined air pollutant by 10 μg/m³ overlapped across years, suggesting consistent effects of air pollution on the risk of AECOPD hospitalizations pre-pandemic and during lockdown. In conclusion, reduced air pollution emissions during the COVID-19 lockdown did not lead to a statistically significant change in the number of AECOPD hospitalizations. Full article

Acute hypoxemic respiratory failure (AHRF) is defined as acute and progressive, and patients are at a greater risk of developing acute respiratory distress syndrome (ARDS). Until now, most studies have focused on prognostic and diagnostic biomarkers in ARDS. Since there is evidence supporting a connection between dysregulated coagulant and fibrinolytic pathways in ARDS progression, it is plausible that this dysregulation also exists in AHRF. The aim of this study was to explore whether levels of soluble endothelial protein C receptor (sEPCR) and plasminogen differentiate patients admitted to the emergency department (ED) with AHRF. sEPCR and plasminogen levels were measured in 130 AHRF patients upon ED presentation by ELISA. Our results demonstrated that patients presenting to the ED with AHRF had elevated levels of sEPCR and plasminogen. It seems that dysregulation of coagulation and fibrinolysis occur in the early stages of respiratory failure requiring hospitalisation. Further research is needed to fully comprehend the contribution of sEPCR and plasminogen in AHRF. Full article

The profound transformations of traditional rural landscapes have heightened attention towards the recovery and valorisation of their buildings, often abandoned, to accommodate new landscape usage needs. This aligns with the principles of sustainable landscape management. However, knowledge of the rural real estate market remains largely unexplored. This research aims to define and examine the key features influencing the purchase of rural buildings, for shedding light on their market. The objective is to provide useful new insight to the property appraisers and real estate agents involved in the sale of traditional rural buildings, even if in conditions of degradation or abandonment and in traditional landscape contexts. Furthermore, these results could serve as a valuable resource for policymakers, enabling them to indirectly evaluate the impacts of urban and landscape policies on buyers’ preferences regarding key features of rural properties. The research focused on the ‘trulli’, traditional buildings located in the Valle d’Itria (Puglia, Southern Italy). First, a detailed market analysis was carried out with the support of local real estate experts, to survey the transactions of trulli and identify the features influencing their purchase. Second, the obtained dataset was analysed through network analysis, which enabled us to explore the role and importance assigned by buyers to the identified features. The results highlighted that the quality of the landscape where trulli are located changed the buyers’ viewpoint on the purchase features. In greater detail, price, area, potable water accessibility and level of maintenance of trulli were the most crucial features, particularly in high and medium landscape value zones, compatible with touristic and recreational activities. On the other hand, the annex agricultural surface covered a central function in low landscape value zone for possible agricultural uses. Full article

Although the simulated moving bed (SMB) process boasts advantages such as high productivity and low consumption, the cost of obtaining optimized parameters through practical experiments to control the separation process can be enormous due to its complex nonlinear characteristics. Consequently, the successful transformation of the SMB separation process into a mathematical dynamic model for computer simulation would greatly reduce the research costs associated with experimental studies. In this study, the Crank–Nicolson method was employed to discretize and dynamize the SMB process, enabling the simulation of processes under both linear and Langmuir isotherms. The results of the simulation experiments demonstrated the feasibility and high efficiency of this approach, thereby establishing a solid foundation for further advancements in online control strategies. Full article

Infrared small target detection (IRSTD) is crucial for applications in security surveillance, unmanned aerial vehicle identification, military reconnaissance, and other fields. However, small targets often suffer from resolution limitations, background complexity, etc., in infrared images, which poses a great challenge to IRSTD, especially due to the noise interference and the presence of tiny, low-luminance targets. In this paper, we propose a novel dual enhancement network (DENet) to suppress background noise and enhance dim small targets. Specifically, to address the problem of complex backgrounds in infrared images, we have designed the residual sparse enhancement (RSE) module, which sparsely propagates a number of representative pixels between any adjacent feature pyramid layers instead of a simple summation. To handle the problem of infrared targets being extremely dim and small, we have developed a spatial attention enhancement (SAE) module to adaptively enhance and highlight the features of dim small targets. In addition, we evaluated the effectiveness of the modules in the DENet model through ablation experiments. Extensive experiments on three public infrared datasets demonstrated that our approach can greatly enhance dim small targets, where the average values of intersection over union ($IoU$), probability of detection ($P_d$), and false alarm rate ($F_a$) reached up to 77.33%, 97.30%, and 9.299%, demonstrating a performance superior to the state-of-the-art IRSTD method. Full article

Increasing soil salinity and degraded irrigation water quality are major challenges for agriculture. This study investigated the effects of irrigation water quality and incorporating compost (3% dry mass in soil) on minimizing soil salinization and promoting sustainable cropping systems. A greenhouse study used brackish water (electrical conductivity of 2010 µS/cm) and agricultural water (792 µS/cm) to irrigate Dundale pea and clay loam soil. Compost treatment enhanced soil water retention with soil moisture content above 0.280 m³/m³, increased plant carbon assimilation by ~30%, improved plant growth by >50%, and reduced NO₃⁻ leaching from the soil by 16% and 23.5% for agricultural and brackish water irrigation, respectively. Compared to no compost treatment, the compost-incorporated soil irrigated with brackish water showed the highest plant growth by increasing plant fresh weight by 64%, dry weight by 50%, root length by 121%, and plant height by 16%. Compost treatment reduced soil sodicity during brackish water irrigation by promoting the leaching of Cl⁻ and Na⁺ from the soil. Compost treatment provides an environmentally sustainable approach to managing soil salinity, remediating the impact of brackish water irrigation, improving soil organic matter, enhancing the availability of water and nutrients to plants, and increasing plant growth and carbon sequestration potential. Full article

Incremental nonlinear dynamic inversion (INDI) is a widely used approach to controlling UAVs with highly nonlinear dynamics. One key element of INDI-based controllers is the control allocation realizing pseudo controls using available actuators. However, the tracking of commanded pseudo controls is not the only objective considered during control allocation. Since the approach only works locally due to linearization and the solution is often ambiguous, additional aspects like control efforts or penalizing the deviation of certain states must be considered. Conducting the control allocation by solving a quadratic program this results in a considerable number of weighting parameters, which must be tuned during control design. Currently, this is conducted manually and is therefore time consuming. An automated approach for tuning these parameters is therefore highly beneficial. Thus, this paper presents and evaluates a model-based approach automatically tuning the control allocation parameters of a tiltrotor VTOL using an optimization algorithm. This optimization algorithm searches for optimal parameters minimizing a cost functional that reflects the design target. This cost functional is calculated based on a test mission for the VTOL which is conducted within a simulation environment. The test mission represents the common operating range of the VTOL. The simulation environment consists of an aircraft model as well as a model of the INDI-based controller which is dependent on the control allocation parameters. On this basis, model-based optimization is conducted and the optimal parameters are identified. Finally, successful real-world tests on a 4-degrees-of-freedom testbench using the identified parameters are presented. Since the control allocation parameters can significantly influence the aircraft’s stability, the 4-DOF testbench for the aircraft is required for rapid validation of the parameters at a minimum amount of risk. Full article

To explore the law of load-carrying performance enhancement of concrete beams reinforced with corrugated steel plates (CSPs), three groups of controlled bending tests were conducted on five beam specimens. The load-bearing capacity of concrete members commensurately increased with the thickness of reinforcing flat and corrugated steel plates. Additionally, for the same amount of steel, the load-bearing capacity of concrete beams improved more with CSP reinforcement than with reinforcement with flat steel plates. Accordingly, a theoretical formula for the moment of inertia of the combined section of a CSP-reinforced concrete beam was derived. Comparison verification showed that the calculation results for the beams reinforced with CSPs of different thicknesses were highly accurate. Finally, based on the damage mode of the CSP-reinforced concrete beam specimens, a formula for calculating the flexural bearing capacity of the positive cross-section of the beam with corrugated steel reinforcement was established. The calculated values agreed with the experimental values, which validated the flexural load capacity theory pertaining to positive sections and the flexural capacity model for reinforced beams. Full article

As women age, oocytes are susceptible to a myriad of dysfunctions, including mitochondrial dysfunction, impaired DNA repair mechanisms, epigenetic alterations, and metabolic disturbances, culminating in reduced fertility rates among older individuals. Ferredoxin (FDX) represents a highly conserved iron–sulfur (Fe–S) protein essential for electron transport across multiple metabolic pathways. Mammalian mitochondria house two distinct ferredoxins, FDX1 and FDX2, which share structural similarities and yet perform unique functions. In our investigation into the regulatory mechanisms governing ovarian aging, we employed a comprehensive multi-omics analysis approach, integrating spatial transcriptomics, single-cell RNA sequencing, human ovarian pathology, and clinical biopsy data. Previous studies have highlighted intricate interactions involving excessive lipid peroxide accumulation, redox-induced metal ion buildup, and alterations in cellular energy metabolism observed in aging cells. Through a multi-omics analysis, we observed a notable decline in the expression of the critical gene FDX1 as ovarian age progressed. This observation prompted speculation regarding FDX1’s potential as a promising biomarker for ovarian aging. Following this, we initiated a clinical trial involving 70 patients with aging ovaries. These patients were administered oral nutritional supplements consisting of DHEA, ubiquinol CoQ10, and Cleo-20 T3 for a period of two months to evaluate alterations in energy metabolism regulated by FDX1. Our results demonstrated a significant elevation in FDX1 levels among participants receiving nutritional supplementation. We hypothesize that these nutrients potentiate mitochondrial tricarboxylic acid cycle (TCA) activity or electron transport chain (ETC) efficiency, thereby augmenting FDX1 expression, an essential electron carrier in metabolic pathways, while concurrently mitigating lipid peroxide accumulation and cellular apoptosis. In summary, our findings underscore the potential of nutritional intervention to enhance in vitro fertilization outcomes in senescent cells by bolstering electron transport proteins, thus optimizing energy metabolism and improving oocyte quality in aging women. Full article

This review offers a comprehensive analysis of thermal barrier coatings (TBCs) applied to metallic materials. By reviewing the recent literature, this paper reports on a collection of technical information, involving the structure and role of TBCs, various materials and coating processes, as well as the mechanisms involved in the durability and failure of TBCs. Although TBCs have been successfully utilized in advanced applications for nearly five decades, they continue to be a subject of keen interest and ongoing study in the world of materials science, with overviews of the field’s evolution remaining ever relevant. Thus, this paper outlines the current requirements of the main application areas of TBCs (aerospace, power generation and the automotive and naval industries) and the properties and resistance to thermal, mechanical and chemical stress of the different types of materials used, such as zirconates, niobates, tantalates or mullite. Additionally, recent approaches in the literature, such as high-entropy coatings and multilayer coatings, are presented and discussed. By analyzing the failure processes of TBCs, issues related to delamination, spallation, erosion and oxidation are revealed. Integrating TBCs with the latest generations of superalloys, as well as examining heat transfer mechanisms, could represent key areas for in-depth study. Full article