Degradation Pattern Research Articles

The role of renewable energy and foreign direct investment toward environmental degradation convergence to achieve sustainability: evidence from ASEAN countries

The role of renewable energy and foreign direct investment toward environmental degradation convergence to achieve sustainability: evidence from ASEAN countries

Uncoupled: investigating the lack of correlation between the transcription of putative plastic-degrading genes in the global ocean microbiome and marine plastic pollution

BackgroundPlastic pollution is a severe threat to marine ecosystems. While some microbial enzymes can degrade certain plastics, the ability of the global ocean microbiome to break down diverse environmental plastics remains limited. We employed metatranscriptomic data from an international ocean survey to explore global and regional patterns in microbial plastic degradation potential.ResultsOn a global oceanic scale, we found no significant correlation between levels of plastic pollution and the expression of genes encoding enzymes putatively identified as capable of plastic degradation. Even when looking at different regional scales, ocean depth layers, or plastic types, we found no strong or even moderate correlation between plastic pollution and relative abundances of transcripts for enzymes with presumed plastic biodegradation potential. Our data, however, indicate that microorganisms in the Southern Ocean show a higher potential for plastic degradation, making them more appealing candidates for bioprospecting novel plastic-degrading enzymes.ConclusionOur research contributes to understanding the complex global relationship between plastic pollution and microbial plastic degradation potential. We reveal that the transcription of putative plastic-degrading genes in the global ocean microbiome does not correlate to marine plastic pollution, highlighting the ongoing danger that plastic poses to marine environments threatened by plastic pollution.

Finite element analysis of precast concrete beam‐column joint based on bolt connection

SummaryA novel proposal for an assembled bolted joint between a precast reinforced concrete beam and column is presented in this paper. In order to evaluate the behavior of the joint, a comprehensive experiment was carried out on a full‐scale precast concrete beam‐column joint based on bolted connection subjected to pseudo‐static loading. The experiment aims to investigate the failure mode, load carrying capacity, and energy dissipation characteristics of the joint. To further understand the performance of the joint, a finite element model was developed using ABAQUS. The difference in failure mode and ultimate bearing capacity between the bolted joints and cast‐in‐situ joints were analyzed in conjunction with the experimental results. Moreover, the impact of various parameters on the performance of the bolted joints was quantified. The characteristics of the bolted joints, such as the span‐depth ratio, reinforcement ratio of the beam, the stirrup ratio at the beam‐column junction, T‐end length, and the bolt strength grade, were meticulously analyzed through an examination of bearing capacity curve, stiffness degradation patterns, and energy dissipation capability. The results show that, in comparison with the traditional cast‐in‐situ joints, the damage failure extent exhibited by the bolted joints is notably smaller, thereby rendering it more advantageous for seismic restoration and replacement. Furthermore, the span‐depth ratio, reinforcement ratio of the beam, and the stirrup ratio have a greater influence on the seismic performance of bolted joints than the T‐end length and bolt strength grade.

A knowledge distillation based cross-modal learning framework for the lithium-ion battery state of health estimation

The accurate prediction of a lithium-ion battery’s State of Health is of critical importance for efficient battery health management. Existing data-driven estimation methodologies grapple with issues such as high model complexity and a dearth of guidance from prior knowledge, which impose constraints on their efficacy. This work introduces a novel cross-modal distillation network for battery State of Health estimation, structured around a TransformerEncoder as the teacher network and a Convolutional Neural Network as the student network. Initially, the teacher model is pre-trained offline using State of Health degradation data to learn the degradation patterns. The directly measurable feature data (such as voltage, temperature, and current) is subsequently fed into the student network for online training and computation of a hard loss. the student network’s output is then directed into the pre-trained the teacher network to compute a soft loss, thereby offering prior knowledge of degradation laws and steering the optimization process of the student network. Rigorous experiments are conducted utilizing various datasets, with the outcomes validating the superior estimation accuracy and degradation rule adherence of the model. Notably, among five different models, this model demonstrates the best performance on almost all datasets, achieving an RMSE of 0.0097 and an MAE of 0.0065 on Cell1 of the Oxford dataset. Moreover, the model also demonstrates robust performance across different usage scenarios, inclusive of multi-battery estimation. Furthermore, this paper also introduces a fine tuning method for State of Health predictions only using the first half of the data. Comparative analysis with other models underscores the competitiveness of the proposed model, showcasing its potential for broader application.

Evaluation of fate of organic matter in sediment through microcosm experiments

AbstractLaboratory microcosm experiments help to understand the degradation pattern of different sources derived from organic matter (OM) at the sediment–water interface and relate it to field processes. Microcosm experiments were carried out for 65 days to assess the degradation of organic materials such as diatoms, zooplankton, and mangrove leaves using source‐specific fatty acid (FA) biomarkers. The viable bacterial population in the microcosm sediment was low on day 1, but on day 3, it increased substantially by two to threefold in all the treatments. An increase in the bacterial population resulted in a decrease in the FAs specific to organic materials during the initial incubation phase (10 days), suggesting the degradation of organic materials derived from different sources. The FAs specific to diatoms showed faster degradation when compared to zooplankton and mangrove‐specific FAs. The degradation of FAs was influenced by the nature of the source material, unsaturation of FAs, and the sediment type. Sandy sediment facilitated higher degradation of diatom and zooplankton‐specific FAs, whereas mangrove‐specific FAs showed higher degradation in silty‐clay sediment. Thus, bacterial community composition coupled with the habitat characteristics, the OM composition, and the grain size of the sediment, influenced the degradation of FAs. The degradation of mangrove‐specific long‐chain FAs was ~1.11–2.5 times higher when spiked with plankton‐derived labile OM from mixed sources, which otherwise took a longer time for degradation pointing toward co‐metabolism (priming effect), which could play a significant role in the cycling of terrestrial plant‐derived OM in an estuarine ecosystem.

How Credible Is the 25-Year Photovoltaic (PV) Performance Warranty?—A Techno-Financial Evaluation and Implications for the Sustainable Development of the PV Industry

To support the bankability of PV projects, PV manufacturers have been offering some of the longest warranties in the world, typically in the range of 25–30 years. During the warranty period, PV manufacturers guarantee that the degradation of PV modules will not exceed 0.4–0.6% each year, or the buyer can at any time make a claim to the manufacturer for replacement or compensation for the shortfall. Due to PV popularity, the performance warranty terms have become more and more competitive each year. However, long-term PV operating data are very limited, and the bankruptcy of PV manufacturers has been quite common. Without a proper methodology to assess the adequacy of the warranty fund (WF) reserves of PV manufacturers, the 25-year performance warranty can reflect an empty promise. To ensure sustainable development of the PV industry, this study develops a probability-weighted expected value method to determine the necessary WF reserve based on benchmark field degradation data and a prevailing degradation cap of 0.55% per year. The simulation results show that, unless the manufacturer’s degradation pattern is significantly better than the benchmark degradation profile, 1.302% of the sales value is required for the WF reserve. To the best of our knowledge, this is the first study that provides WF reserve requirement estimation for 25-year PV performance warranties. The results will provide transparency for PV investors and motivation for PV manufacturers to engage in continuous quality improvement, as all such achievements can now be reflected in the annual report results of manufacturers.

Annual atrazine residue estimation in Chinese agricultural soils by integrated modeling of machine learning and mechanism-based models

This study presents a comprehensive approach to estimating annual atrazine residues in China's agricultural soils, integrating machine learning algorithms and mechanism-based models. First, machine learning was used to predict essential parameters influencing atrazine's adsorption, degradation, and dispersivity of solute transport. The results demonstrated that soil organic matter was the most important input variable for predicting adsorption and degradation; clay content was the primary variable for predicting dispersivity. The SHapley Additive exPlanations (SHAP) contribution of various soil properties on target variables were also analyzed to reveal whether each input variable has a positive, negative, or complex effect. Subsequently, these parameters inform the construction of a detailed model across 23,692 subregions of China, with a 20 km × 20 km resolution. The model considered regional variations and soil layer heterogeneity, including rainfall, soil depth-specific properties, and parameters for adsorption, degradation, and dispersivity. Utilizing the convection-dispersion equations and the Phydrus, the model simulated atrazine's transport and degradation patterns across diverse soil environments after applying 250 mL of atrazine (40%) per Chinese mu. The outcomes provided a spatially explicit distribution of atrazine residues, specifying that the arid areas have the highest residual risk, followed by the Northeast, Southwest, and Southeast. Atrazine levels may exceed national drinking water standards at 50 cm depth in Inner Mongolia, the Qinghai-Tibet Plateau, and the Jungar Basin. This study's integrative approach may also offer valuable insights and tools for evaluating residues of various pesticides and herbicides in agricultural soils.

Research on performance degradation patterns of metal rubber components under the coupling of static compression and full immersion corrosive environment

Metal rubber component (MRC) is commonly used in special work conditions such as high temperature/corrosive environments primarily due to its excellent vibration damping/insulation properties. But in special work conditions for a long time, the performance of MRC will deteriorate to a failure to meet the work requirements. Therefore, it is imperative to enhance the performance of MRC and study its performance degradation in special work conditions. In this paper, pickling, silanization and pickle-silanization surface treatments for metal rubber components (MRCs) were carried out. The properties of MRCs after surface treatment under static compression and full immersion corrosive test were studied, and a remaining service life prediction model of MRCs under corrosion condition was established. Compared with MRC without surface treatment (U-MRC), the performance degradation degree of several MRCs was evaluated based on four physical and mechanical parameters - the amplitude of variation in height, average stiffness, energy dissipation, and loss factor. The results indicated that MRCs exhibited different degrees of performance degradation. Among them, pickling-silanized MRC (PS-MRC) has the best corrosion resistance. The stiffness variation amplitude must be nearly 8% smaller than that of U-MRC, and the energy consumption variation amplitude is about 12% smaller than that of U-MRC.

A novel transformer-based DL model enhanced by position-sensitive attention and gated hierarchical LSTM for aero-engine RUL prediction

Accurate prediction of remaining useful life (RUL) for aircraft engines is essential for proactive maintenance and safety assurance. However, existing methods such as physics-based models, classical recurrent neural networks, and convolutional neural networks face limitations in capturing long-term dependencies and modeling complex degradation patterns. In this study, we propose a novel deep-learning model based on the Transformer architecture to address these limitations. Specifically, to address the issue of insensitivity to local context in the attention mechanism employed by the Transformer encoder, we introduce a position-sensitive self-attention (PSA) unit to enhance the model's ability to incorporate local context by attending to the positional relationships of the input data at each time step. Additionally, a gated hierarchical long short-term memory network (GHLSTM) is designed to perform regression prediction at different time scales on the latent features, thereby improving the accuracy of RUL estimation for mechanical equipment. Experiments on the C-MAPSS dataset demonstrate that the proposed model outperforms existing methods in RUL prediction, showcasing its effectiveness in modeling complex degradation patterns and long-term dependencies.

Neutrophil-mediated Inflammatory Plasminogen Degradation, Rather Than High Plasminogen-Activator Inhibitor-1, May Underly Failures and Inefficiencies of Intrapleural Fibrinolysis

Complex pleural space infections often require treatment with multiple doses of intrapleural tissue plasminogen activator (tPA) and deoxyribonuclease, with treatment failure frequently necessitating surgery. Pleural infections are rich in neutrophils, and neutrophil elastase degrades plasminogen, the target substrate of tPA, that is required to generate fibrinolysis. We hypothesized that pleural fluid from patients with pleural space infection would show high elastase activity, evidence of inflammatory plasminogen degradation, and low fibrinolytic potential in response to tPA that could be rescued with plasminogen supplementation. Does neutrophil elastase degradation of plasminogen contribute to intrapleural fibrinolytic failure? We obtained infected pleural fluid and circulating plasma from hospitalized adults (n= 10) with institutional review board approval from a randomized trial evaluating intrapleural fibrinolytics vssurgery for initial management of pleural space infection. Samples were collected before the intervention and on days 1, 2, and 3 after the intervention. Activity assays, enzyme-linked immunosorbent assays, and Western blot analysis were performed, and turbidimetric measurements of fibrinolysis were obtained from pleural fluid with and without exogenous plasminogen supplementation. Results are reported as median (interquartile range) or number (percentage) as appropriate, with an α value of .05. Pleural fluid elastase activity was more than fourfold higher (P= .02) and plasminogen antigen levels were more than threefold lower (P= .04) than their corresponding plasma values. Pleural fluid Western blot analysis demonstrated abundant plasminogen degradation fragments consistent with elastase degradation patterns. We found that plasminogen activator inhibitor 1 (PAI-1), the native tPA inhibitor, showed high antigen levels before the intervention, but the overwhelming majority of this PAI-1 (82%) was not active (P= .003), and all PAI-1 activity was lost by day 2 after the intervention in patients receiving intrapleural tPA and deoxyribonuclease. Finally, using turbidity clot lysis assays, we found that the pleural fluid of 9 of 10 patients was unable to generate a significant fibrinolytic response when challenged with tPA and that plasminogen supplementation rescued fibrinolysis in all patients. Our findings suggest that inflammatory plasminogen deficiency, not high PAI-1 activity, is a significant contributor to intrapleural fibrinolytic failure. ClinicalTrials.gov; No.: NCT03583931; URL: www. gov.

Investigating cartilage-related diseases by polarization-resolved second harmonic generation (P-SHG) imaging.

Establishing quantitative parameters for differentiating between healthy and diseased cartilage tissues by examining collagen fibril degradation patterns facilitates the understanding of tissue characteristics during disease progression. These findings could also complement existing clinical methods used to diagnose cartilage-related diseases. In this study, cartilage samples from normal, osteoarthritis (OA), and rheumatoid arthritis (RA) tissues were prepared and analyzed using polarization-resolved second harmonic generation (P-SHG) imaging and quantitative image texture analysis. The enhanced molecular contrast obtained from this approach is expected to aid in distinguishing between healthy and diseased cartilage tissues. P-SHG image analysis revealed distinct parameters in the cartilage samples, reflecting variations in collagen fibril arrangement and organization across different pathological states. Normal tissues exhibited distinct χ33/χ31 values compared with those of OA and RA, indicating collagen type transition and cartilage erosion with chondrocyte swelling, respectively. Compared with those of normal tissues, OA samples demonstrated a higher degree of linear polarization, suggesting increased tissue birefringence due to the deposition of type-I collagen in the extracellular matrix. The distribution of the planar orientation of collagen fibrils revealed a more directional orientation in the OA samples, associated with increased type-I collagen, while the RA samples exhibited a heterogeneous molecular orientation. This study revealed that the imaging technique, the quantitative analysis of the images, and the derived parameters presented in this study could be used as a reference for disease diagnostics, providing a clear understanding of collagen fibril degradation in cartilage.

Decarbonization, critical minerals, and tribal sovereignty: Pathways towards conflict transformation

The Inflation Reduction Act, the largest US investment in renewable energy development and climate mitigation, provides incentives for critical minerals to be mined in North America. The rise in domestic mineral procurement is already reigniting historic conflicts between the Federal Government and Indigenous peoples over Tribal sovereignty. This study utilizes a Conflict Transformation framework to investigate the structural roots of mining conflicts and their impacts on Tribal Nations through two parts. Part One examines the extent to which Tribes were engaged in the formulation of the Inflation Reduction Act. Part Two presents three case studies of the local impacts of mining conflicts and includes the perspectives of a range of stakeholders involved in mining conflicts. The study finds that Tribal Nations were not sufficiently included in the formulation of the Inflation Reduction Act and that local conflicts are rooted in patterns of environmental degradation, colonialism, and broken promises to Tribal communities. Recommendations for transforming this conflict include strengthening environmental regulations, improving Tribal consultation, and commencing a long-term Truth and Reconciliation process between the Federal government and Tribal Nations.

Studying the Role of Soil Factors on Degree of Degradation of DNA of Human Remains

Generating a DNA profile using autosomal Short Tandem Repeat (STR) DNA allele from skeletal remains is a crucial step in the identification process for mass disaster and unidentified person situations. The capacity to extract substantial amounts of relevant DNA from bones, which were highly durable biological components that can withstand soil elements and climatic conditions over long periods of time, would be advantageous. 70 femur male bone samples were collected from two different environmental mass graves (Al-Mahaweel massgrave) in Babil governorate and (Al-Saqlawiya massgrave) in Al-Anbar governorate in Iraq. The DNA from bone samples extracts were assessed by capillary electrophoresis and a standardized set of short tandem repeat (STR) loci are analyzed using Mutiplex 21 STR loci System to allow human identification by matching the profile of the dead individuals with their relatives. From these two different sites; soil samples were collected to analyze and study the different environmental factors and find a relation between the degree of preservation or degradation with these factors like temperature, humidity, salinity, PH and texture of soil and find how these factors can affect on pattern of degradation of DNA profiles. The average of the percentage of the detected alleles in each locus in the two sites; were 87\% for Al-Mahaweel site and 32\% for Al- Saqlawiya site. we found that clay soil, low salt concentration, PH slightly alkaline and low humidity for Al-Mahaweel site; all participate in DNA preservation while the chalky and very high salt concentration of Al- Saqlawiya site soil; all participate in DNA degradation. Predicting the effect of these factors on the quality of the DNA profiles can be helpful in finding better solutions for many complications that may face the process of analyzing samples and finding sufficient informative profiles.

The capacity degradation path prediction for the prismatic lithium-ion batteries based on the multi-features extraction with SGPR

Accurate capacity degradation path estimation of lithium-ion batteries plays a crucial role in ensuring the safety and reliability of electric vehicles. In recent years, the evolution of the status of health (SOH) prediction with machine learning techniques has become a research hotspot because of its powerful computing power and robustness. Thus, this study employes the sparse gaussian process regression (SGPR) data-driven approach with multi-features extracted from the battery cycling processes to project the potential degradation patterns of the lithium-ion batteries. Firstly, a battery life test platform was built. The accelerated life aging tests of batteries at different temperatures (25 °C, or 60 °C) and different discharge rates (1C, or 2C) were conducted to establish the dataset for the multi-features extraction and training of the SGPR algorithm. Secondly, different battery characteristic features were extracted based on the battery cycle charge-discharge curves. Various order-reduction treatments, i.e., the filter-based, embedding-based, and fusion-based selection algorithms, were performed to suppress the over-fitting and improve the estimate's accuracy. Finally, using the extracted features as inputs, SGPR models are constructed to estimate the degradation path of the battery. With the 50 % training data, the SGPR has a higher estimation accuracy than the regular GPR, and the average maximum absolute errors for the batteries are 2.80 %, 1.22 %, 3.57 %, and 1.83 %, respectively.

Ion-migration analysis of degradation caused by outdoor exposure and accelerated stress testing in perovskite solar cells

In this study, we conducted outdoor exposure testing and investigated the degradation mechanism of perovskite solar cells deployed in the field. We conducted a detailed failure analysis to identify specific degradation modes induced by outdoor exposure, using current–voltage curve measurements, maximum power evaluation, and mobile-ion analysis. This analysis revealed a significant change in the ion-migration current response of the devices after exposure. These changes suggest that the modification of mobile ions and formation of defects within the perovskite materials are likely the primary causes of degradation. Additionally, we compared the solar cell characteristics observed after the field test with the results of controlled indoor accelerated stress tests, which included exposure to visible light, ultraviolet (UV) irradiation, and thermal stress. Our findings highlight that the degradation patterns induced by UV irradiation at elevated temperatures closely resemble those caused by outdoor stress. We also discuss indoor test conditions that replicate the degradation phenomena experienced during outdoor exposure. This ability to replicate outdoor degradation phenomena under laboratory conditions is crucial for accelerating the development of robust and durable perovskite solar cells.

Degradation mechanisms in PBSAT nets immersed in seawater

Fishing gears are known to continue fishing after being abandoned, lost, or discarded through a phenomenon called ghost fishing. After this ghost fishing period, disintegrated nets contribute to plastic pollution. Biodegradable nets could be an alternative to conventional nets to reduce ghost fishing but must strike a delicate balance between durability and degradation. This study evaluates the seawater degradation of a net made of polybutylene(succinate-co-adipate-co-terepthalate) (PBSAT) at several scales: monofilament, knot, and net. Mechanical testing was used to monitor the strength at each scale during immersion at several temperatures: 4 °C, 15 °C, 25 °C, 40 °C. Steric exclusion chromatography (SEC), scanning electron microscopy (SEM) and X-ray tomography were used to investigate degradation processes. While no degradation was observed for samples immersed for 240 days at 4 °C, hydrolysis led to embrittlement at 40 °C. Biotic degradation was observed at both 15 °C and 25 °C with distinct degradation patterns and bacteria shapes. At both temperatures, the degradation was accelerated in the knot, leading to an unusable net after 240 days at 15 °C while no loss of strength was detected at the monofilament scale. These findings suggest that the durability of the knot is critical for successful development of a biodegradable polymer for application in gillnets.

Effect of PLGA raw materials on in vitro and in vivo performance of drug-loaded microspheres.

Poly(lactide-co-glycolide) and poly(lactic-co-glycolic acids) (PLGAs) play a critical role in the development of commercial long-acting injectable microsphere formulations. However, very little information is available describing the impact of PLGA manufacturer and monomer distribution along the polymer chain (e.g., glycolic blockiness (Rc) and average lactic block length (LL)) on the degradation and release behavior of PLGA drug carriers in vitro and in vivo. Here, we compared the in vitro and in vivo performance of (a) four leuprolide-loaded microsphere formulations prepared from similar low-molecular-weight acid-capped PLGAs (10-14 kD, i.e., Expansorb® DLG 75-2A, Purasorb® PDLG 7502A, Resomer® RG 752H and Wako® 7515) and (b) two triamcinolone acetonide-loaded (Tr-A) microsphere formulations from similar medium-molecular-weight ester-capped PLGAs (i.e., Expansorb® DLG 75-4E and Resomer® RG 753S). Lupron Depot® and Zilretta® were used as reference commercial products. The six 75/25 PLGAs displayed block lengths that were either above or below values expected from a random copolymer. Drug release and polymer degradation were monitored simultaneously in vitro and in vivo using a cage implant system. The four leuprolide-loaded formulations showed similar release and degradation patterns with some notable differences between each other. Microspheres from the Expansorb® polymer displayed lower LL and higher Rc relative to the other 3 PLGA 75/25 microspheres, and likewise exhibited distinct peptide release and degradation behavior compared to the other 3 formulations. For each formulation, leuprolide release was erosion-controlled up to about 30% release after the initial burst followed by a faster than erosion release phase. In vitro release was similar as that in vivo over the first phase but notably different from the latter release phase, particularly for the most blocky Expansorb® formulation. The Purasorb® and Wako® formulations displayed highly similar performance in release, degradation, and erosion analysis. By contrast, the two ester-capped Expansorb® DLG 75-4E and Resomer® RG 753S used to prepare Tr-A microspheres shared essentially identical LL and higher Rc and behaved similarly although the Expansorb® degraded and released the steroid faster in vivo, suggestive of other factors responsible (e.g., residual monomer). The in vivo release performance for both drugs from the six microsphere formulations was similar to that of the commercial reference products. In summary, this work details information on comparing the similarities and differences in in vitro and in vivo performance of drug-loaded microspheres as a function of manufacturing and microstructural variables of different types of PLGA raw materials utilized and could, therefore, be meaningful in guiding the source control during development and manufacturing of PLGA microsphere-based drug products. Future work will expand the analysis to include a broader range of LL and higher Rc, and add additional important formulation metrics (e.g., thermal analysis, and residual monomer, moisture, and organic solvent levels).

Comprehensive effects of aerodynamic performance and dynamic strength of aircraft wings after bird strike in numerical simulation

ABSTRCT To enhance the bird strike resistance of fixed-wing aircraft wings, a combined computational approach integrating nonlinear solid mechanics and fluid dynamics was employed to analyze the bird strike characteristics of both traditional aluminum alloy skins and novel composite materials skins. Additionally, a standardized procedure was established to simulate aircraft structural damage more comprehensively, swiftly, and accurately during bird strikes, along with diagnostic analysis of flow field changes near the wing post-impact. This method not only quantifies wing strength damage but also establishes corresponding relationships between damage severity and aerodynamic performance degradation. The research findings indicate that the deformation of composite material skin wings is only a quarter of that of aluminum alloy skin wings. Composite material skins absorb less harmful energy compared to aluminum alloy skins, with consistently lower stiffness reduction rates at various bird strike velocities. Velocity distribution on deformed wings with composite material skins exhibits minimal deviation compared to normal wings, thereby preventing airflow separation. The research results provide more comprehensive guidance for the selection of materials for bird strike resistance of aircraft wings and the airworthiness evaluation after bird strikes. Highlights This paper establishes a standardized procedure that enables a more comprehensive, faster, and higher-precision simulation of structural damage to the aircraft during a bird strike on the wing and allows for the diagnostic analysis of the flow field changes near the wing after bird strike. By coupling nonlinear solid mechanics and fluid dynamics computational methods, the aerodynamic performance of the wings at different angles of attack post-deformation is investigated. This approach not only quantifies the strength damage to the wings but also establishes corresponding relationships between the degree of damage and the deterioration in aerodynamic performance. The research yields insights into the aerodynamic performance degradation patterns with varying angles of attack for both composite material skin and aluminum alloy skin deformed wings. These findings can serve as valuable references for pilots in emergency situations, aiding in their decision-making regarding aircraft control.

Efficient drug delivery potential and antimicrobial activity of biocompatible hydrogels of dextrin/Na-alginate/PVA

Ceftriaxone sodium belongs to the third-generation cephalosporin group and is used intramuscular and intravenous route as a broad-spectrum antibiotic. This research aims to prepare biocompatible hydrogels for targeted delivery of ceftriaxone sodium by parental route. Different proportions of polymers (natural and synthetic) in the presence of cross-linker were synthesized by solvent casting method. Ceftriaxone sodium was loaded in hydrogels in different concentrations and its drug release behavior was evaluated along with swelling and biodegradation analysis. The characterization of hydrogel was done by scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) to analyze surface morphology and functional groups involved in the formation of dextrin/Na-alginate/PVA hydrogels loaded with the drug. Thermogravimetric analysis (TGA) was confirmed by thermal stability and degradation pattern of loaded and unloaded hydrogels. The drug-loaded samples presented promising antimicrobial activity against S. aureus and P. multocida and their cytotoxic nature was also studied. Drug release analysis using simulated intestinal fluid (SIF) and phosphate buffer saline(PBS) for the circulatory system shows the consistent release of the drug. The findings unveiled the development of a biocompatible and innovative hydrogel, which has potential advantages for biomedical application, particularly in enhancing the therapeutic efficacy of ceftriaxone sodium drug.

Lifetime Distribution for a Mixed Redundant System with Imperfect Switch and Components Having Phase–Type Time-to-Failure Distribution

Recently, a mixed redundancy was introduced among the redundant design strategies to achieve a more reliable system within the equivalent resources. This study deals with a lifetime distribution for a mixed redundant system with an imperfect fault detector/switch. The lifetime distribution model was formulated using a structured continuous Markov chain (CTMC) and considers the time-to-failure (TTF) distribution of a component as a phase-type distribution (PHD). The model’s versatility and practicality are enhanced because the PHD can represent diverse degradation patterns of the components exposed to varied operating environments. The model provides accurate reliability for a mixed redundant system by advancing the approximate reliability function suggested in previous studies. Furthermore, the model would be useful in system design and management because it provides information such as the nth moment of the system’s lifetime distribution. In numerical experiments on some examples, the mixed redundancy was confirmed to devise a more reliable system than the existing active and standby redundancies, and the improvement effect increased as the number of redundant components decreased. The optimal structure for maximizing the expected lifetime of the system changes depends on the reliability of the components and fault detector/switch.