Mechanical Defects Research Articles

Identification of novel variants of XPA and POLH/XPV genes in xeroderma pigmentosum patients in Vietnam.

Xeroderma pigmentosum (XP) disorder is recognized as a genetic condition inherited by autosomal recessive fashion. XP results from a defective DNA repair mechanism that significantly increases skin cancer risk. Fifteen Vietnamese patients were investigated with typical clinical manifestations of XP. Eight XP genes (XPA to XPG and POLH/XPV) were sequenced using peripheral blood samples. Overall, three novel variants on the XPA and XPV genes were detected in members of two families. One novel missense variant c.388A>G (p.R130G) of XPA was found in three patients with XP group A, two novel variants: c.680G>A (p.C227Y) and c.1652dupC (p.Gln553Profs*8) of XPV in one patient with XP group F/G. Our study contributes to the recognition of new mutations in XP patients which have not been reported in Human Gene Mutation Database (HGMD).

Improvement of the Performance of An Industrial Wringer

Objective: To maximize the machine's availability through periodic monitoring and propose design improvements to prevent future issues. Context: Overview of the recycling process and the role of the wringer in filtering recycled plastic. Problem Statement: Description of mechanical defects affecting the wringer, including imbalance due to bearing and rotor shaft deformation. Theoretical Analysis: Root Cause Identification, Impact of Imbalance, System Modelling and Simulation Experimental Studies and Strategy: - Practical experiments validate the theoretical and numerical findings and enhance the vibration analysis approach.- Effective scheduling of interventions and repairs is based on the machine's condition, ensuring continuous monitoring through vibration analysis devices. Results and Discussion: Explanation of the proposed modification, including the specific angle adjustment, Discussion on how the adjustment would reduce rotational speed and maintain high wringing performance.

Compressive response and failure mode of glass fiber reinforced polyimide composite honeycomb with cell wall defects

Obtaining some functions for honeycombs can be normally realized by perforating holes on the cell walls. However, excessive perforations, which are always identified as defects, have been shown to reduce the mechanical properties of the honeycomb. Continuous glass fiber reinforced polyimide composite(GF/PI) honeycombs are prepared in this work to investigate their compression processes by finite element analysis and 3D-DIC assisted quasi-static compression tests in order to further reveal the influence mechanism of perforation-induced cell wall defects on their out-of-plane compressive responses and failure modes. The results show that the failure mode of defect-free GF/PI honeycomb is progressive crushing mode, while the GF/PI honeycombs with certain configurations of cell wall defects fail in a fracture mode and fracture/progressive crushing mixed mode. These failure modes ultimately lead to the degradation of the energy absorption performance of the GF/PI honeycombs with cell wall defects. Subsequently, by increasing the matrix content, the failure modes of GF/PI honeycombs with cell wall defects are altered to progressive crushing owing to the reduction of the average maximum damage strain of the cell wall. In addition, the energy absorption performance of GF/PI honeycomb with the same defects configuration is effectively enhanced by 14.24%. This method significantly improves the compressive response and provides theoretical guidance for the structural-functional integrated design of honeycomb sandwich structures in high-performance radomes.

A Novel Detection Scheme for Motor Bearing Structure Defects in a High-Speed Train Using Stator Current.

Railway traction motor bearings (RTMB) are critical components in high-speed trains (HST) that are particularly susceptible to failure due to the high stress and rotational frequency they experience. To address the challenge of high false-positive rates in existing monitoring systems, this paper introduces a novel sensorless monitoring scheme that leverages stator current to detect fault-related characteristics, eliminating the need for additional sensors. This approach employs a hybrid signal preprocessing algorithm that integrates adaptive notch filtering (ANF) with envelope spectrum analysis (ESA) to effectively sparse the stator current and extract relevant fault features. A deep belief network (DBN) is utilized for the classification of the health status of the RTMB. To validate the scheme's feasibility and effectiveness, we conducted experiments on a 1:1 scale high-speed railway traction motor, demonstrating that mechanical defects in RTMB can be reliably indicated by changes in stator current. Based on the analysis of experimental results, it was concluded that the fault detection accuracy of RTMB based on stator current is at least 17.3% higher than that of the fault diagnosis methods based on vibration in diagnosing whether the system has a fault. Among them, the method proposed in this paper is the best in diagnosing the presence and type of faults, with an accuracy that is at least 8.9% higher than other methods. This study not only presents a new method for RTMB monitoring but also contributes to the field by offering a more accurate and efficient alternative to current practices.

FUT8 Regulates Cerebellar Neurogenesis and Development Through Maintaining the Level of Neural Cell Adhesion Molecule Cntn2.

Core fucosylation at N-glycans, which is uniquely catalyzed by fucosyltransferase FUT8, plays essential roles in post-translational regulation of protein function. Aberrant core fucosylation leads to neurological disorders in individuals with congenital glycosylation disorders (CDG). However, the underlying mechanisms for these neurological defects remain largely unknown. In this study, we have showed that FUT8 and fucosylation are abundant in cerebellum. Specific deletion of Fut8 in cerebellar granule neuron progenitors (GNPs) results in the impaired proliferation and differentiation of GNPs, as well as the compromised neuronal development, synaptic physiology and motor coordination. Mechanistically, we have showed that Fut8 deficiency reduced Contactin 2 (Cntn2) expression, a member of neural cell adhesion molecules (NCAMs). Furthermore, ectopic Cntn2 can rescue the neuronal defects induced by Fut8 deficiency. Collectively, our study has revealed the important roles of FUT8 and core fucosylation in regulating cerebellar development and function through modulating Cntn2 expression.

Causes, influencing factors, and prediction modeling of crystallization blockage of tunnel drainage blind pipe in non-karst area

The complete functioning of the tunnel drainage system is critical in ensuring the stability of tunnel lining structures and safe operations. Therefore, the issue of crystalline blockage in the tunnel drainage system needs to be solved urgently. In this study, the formation mechanism of tunnel crystallization defects in non-karst areas was investigated, and the influencing factors of calcium ion dissolution of shotcrete were evaluated by field investigation. Also, the sampling analysis was carried out to determine the ionic composition and content of seepage water. The source and composition of crystallites were determined by X-ray diffraction (XRD), inductively coupled plasma mass spectrometry (ICP-MS), and field-emission scanning electron microscope (SEM). The mechanism and role of pH in CaCO3 crystal formation were explored by simulation using MINTEQ 3.1 software. In addition, a new accelerated leaching test model was developed to examine the flow rate, concentration, and temperature effects on Ca2+ leaching rate in shotcrete. The analysis of water quality and crystal showed that the white and yellow crystals in the tunnel were calcite-type calcium carbonate, occurring as a paste. Micro-morphology of new crystals showed densely-distributed prismatic spherical and scaly crystal structure. The other parts were irregular squares, spindles, rhombuses, and other forms of scattered distribution. The Ca2+ originated from the shotcrete. The accelerated leaching test demonstrated that the optimal test conditions for the leaching rate of Ca2+ in shotcrete were a flow rate of 4 L/min, concentration of 5 mol/L, and temperature of 20 °C. Based on these findings, the prediction model of the Ca2+ leaching rate of shotcrete is established.

Analysis of reasons for visit in completely edentulous patients requiring repeat prosthetic rehabilitation

Background: Complete laminar dentures are currently the most common prosthetic rehabilitation approach in completely edentulous patients. However, acrylic resin, the primary structural material used in these dentures, has certain well-known disadvantages. Identifying the primary reasons for visit in patients requiring replacement of acrylic complete laminar dentures will help determine the best course of action for improving this type of prosthetic rehabilitation. Aim: To assess the reasons for visit in patients requiring replacement of complete laminar dentures. Materials and methods: Between 2021 and 2022, a comprehensive dental examination was performed in completely edentulous patients who had previously used complete laminar dentures and needed to replace them. The primary factors determining the need for replacement dentures of this type were identified, and their frequency during specific time periods was assessed. The risk of functional defects, mechanical failures, and poor esthetic condition was calculated. Nonparametric analysis (chi-squared test) was used to assess statistical differences between the parameters. The frequency of a specific reason for visit was assessed using relative risk (RR) with a 95% confidence interval (CI). Results: Mechanical failure was the main reason for visit (63.3%) in completely edentulous patients requiring replacement of complete laminar dentures within three years after the dentures were manufactured. After three years of wearing these dentures, the risk of mechanical failure and functional defects significantly increases by 1.8 times (RR=1.4; 95% CI: 0.9–1.9) and 1.6 times (RR=1.6; 95% CI: 1.1–2.6), respectively (p 0.05), with approximately equal frequency (47.8% and 43.7%, respectively). When wearing these dentures for more than six years, visits due to functional defects become the most common (58.3%). Conclusion: The service life of complete laminar dentures is directly associated with the reasons for visit for their replacement. The increased risk of functional defects, such as impaired fixation and stabilization, necessitates developing a set of measures for the prevention of maxillary ridge and mandibular alveolar bone atrophy, as well as dystrophic changes of the mucosa in the denture-supporting area.

Research on deterioration mechanism of graded gravel in high-speed railway subgrade layer based on machine vision

This study aims to investigate the macro-micro deterioration mechanism of graded gravel under cyclic loading, which is of great significance in revealing the generation mechanism of high-speed railway subgrade defects in service and guiding the subgrade reinforcement. Initially, a precise-rapid quantification method for particle shape based on machine vision was established. To further improve the existing traditional semantic segmentation model (U-Net), a novel semantic segmentation model named VGG16-UNet-CA was established, which incorporated the U-Net, VGG16 model, Bilinear interpolation, and Coordinate attention (CA). Moreover, the high-precision binary images obtained by the established model were imported into Open Source Computer Vision Library (OpenCV) to calculate the particle shape indicators rapidly. Additionally, the cyclic loading tests were carried out to characterize the macro deterioration of graded gravel based on the mechanical indicator dynamic stiffness K, and the key factor of deterioration was explored through the established machine vision method. Finally, biaxial compression models with different deterioration degree were established by Discrete Element Method (DEM) to explore the micro deterioration mechanism. It was found that the segmentation accuracy indicators F1-score, Mean Pixel Accuracy (MPA) and Mean Intersection over Union (MIoU) of VGG16-UNet-CA were 98.56 %, 97.89 % and 98.01 %, which were higher than U-Net, SegNet, PSPNet, and DeepLabv3+. During the cyclic loading, the changes of the equivalent particle diameter De and slenderness ratio Ei of coarse particles in three filler groups were not significant, while the average values of roundness Rc increased by 28 %, 31 % and 25 %, indicating that the coarse particle abrasion was the key factor of deterioration. In the DEM simulation, with the increase of Rc, the mechanical strength of graded gravel decreased and the micro indicators (e.g., sliding rate, strong force chains, and anisotropy parameter an) inside the fillers gradually decreased, while the particle rotation continuously increased. Consequently, the interlocking ability of coarse particles decreased, leading to the bearing capacity and structural stability of particle skeleton reduced. This study not only provides a novel approach to investigate the deterioration mechanism of graded gravel under cyclic loading, which contributes to revealing the generation mechanism of high-speed railway subgrade defects in service, but also provides theoretical support for subgrade reinforcement.

Utilizing cationic vacancy defects to switch oxygen evolution mechanisms on atomically dispersed ru for enhanced acidic catalytic performance

Achieving the oxide path mechanism (OPM) through bimetallic catalysis is a promising approach for developing highly active and stable electrocatalysts for the acidic oxygen evolution reaction (OER). However, optimizing atomic-level and local ligand structures to enhance the synergistic interaction of bimetallic active sites still remains a challenge. Here, through the introduction of tetrahedral Co (Cotet) cationic defects and selectively substituting atomic Ru on the octahedral Co (Cocot) sites in Co3O4, we present an effective strategy to significantly enhance the orbital hybridization and the synergistic interaction of bimetallic active sites. Experimental and theoretical calculations show that this approach facilitates thermodynamic mechanism for diatomic oxygen formation. Cationic defects are utilized as electron acceptors, facilitating the transfer of electrons from Ru to Co, enhancing the overlap in the density of states, and optimizing the d-band center of Ru and Co. Therefore, the orbital hybridization and synergistic effect of bimetallic active sites are improved. Remarkably, the catalyst with a minimal Ru mass loading of around 45.5 μg∙cm−2, featuring a low overpotential of 150 mV and a minimal potential decay rate of just 0.35 mV∙h−1 at 10 mA∙cm−2. Our work offers an effective strategy to enhance the synergistic interaction of bimetallic sites, and the mechanism of cationic defects improve the acidic OER performance of bimetallic sites has been thoroughly investigated, which is expected to contribute to clean energy production.

Hypercrosslinked Metal-Organic Polyhedra Electrolyte with High Transference Number and Fast Conduction of Li Ions.

Solid-state electrolytes (SSEs) with high Li-ion transference numbers and fast ionic conductivity are urgently needed for technological innovations in lithium-metal batteries. To promote the dissociation of ion pairs and overcome the mechanical brittleness and interface defects caused by traditional fillers in polymeric electrolytes, we designed and fabricated a cationic hypercrosslinking metal-organic polyhedra (HCMOPs) polymer as SSE. Benefiting a three-component synergistic effect: cationic MOPs, branched polyethyleneimine macromonomer and polyelectrolyte units, the Li-HCMOP electrolyte possesses a high Li-ion conductivity, a high Li-ion transference number and a low activation energy. Their LiFePO4/Li batteries exhibit high capacity with superior rate performance and cycling stability. Moreover, soluble MOPs serve as high crosslinking nodes to provide excellent mechanical strength for electrolytes and good compatibility with polymers. This work highlights an effective idea of high-performance MOP-based solid-state electrolytes applied in LMBs.

Genomic rare variant mechanisms for congenital cardiac laterality defect: A digenic model approach.

Laterality defects are defined by perturbations in the usual left-right asymmetry of organs. Due to low known genetic etiology of congenital heart disease (CHD) cases (less than 40%), we used a digenic model approach for the identification of contributing variants in known laterality defect genes (N = 115) in the exome/genome sequencing (ES/GS) data from individuals with clinically diagnosed laterality defects. The unsolved ES/GS data were analyzed from three CHD cohorts: Baylor College of Medicine-Genomics Research to Elucidate the Genetics of Rare Diseases (BCM-GREGoR; N = 247 proband ES), Gabriella Miller Kids First Pediatric Research program (Kids First; N = 158 trio GS), and Pediatric Cardiac Genomics Consortium (PCGC; N = 163 trio ES), and trans-heterozygous digenic variants were identified in 2.8% (inherited digenic variants in 0.4%), 8.2%, and 13.5% cases respectively, which was significantly higher as compared to 602 control trios provided by the 1000 Genomes Project (p = 0.001, 1.4e-07, and 8.9e-13, respectively). Trans-heterozygous digenic variants were also identified in 0.4%, and 1.4% cases with non-laterality CHD in Kids First and PCGC datasets, respectively, which was not statistically significant as compared to control trios ( p = 1, and 0.059, respectively). Altogether, in laterality cohorts, 23% of digenic pairs were in the same structural complex of motile cilia. Out of 39 unique digenic pairs in laterality CHD, 29 are more likely to be potential digenic hits as predicted by DiGePred tool. These findings provide further evidence that digenic epistatic interaction can contribute to the complex genetics of laterality defects.

Complex defects in Al0.5Ga0.5N by first principles calculations

The complex native point defects in Al0.5Ga0.5N are studied by density functional theory (DFT) and Heyd, Scuseria and Ernzerhof (HSE) hybrid functional. The lower formation energy as well as the donor and acceptor properties of Al0.5Ga0.5N with different complex native point defects are obtained. It is found that VGa-GaN exhibits donor property under p-type conditions while VAl-VN and VGa -VN exhibit acceptor properties under n-type conditions. Then, the density of states studies indicate that the defect peaks in the Al0.5Ga0.5N bandgap are all contributed by the defect atoms or atoms near the defects. Moreover, the charge distribution and bonding states analyses show that the Ali atom in VAl -Ali forms ionic bonds with the N atoms in Al0.5Ga0.5N and the antisite Ga atom in VGa-GaN forms ionic bonds with the N atoms in Al0.5Ga0.5N. Furthermore, the thermodynamic transition energy levels exploration reveals that VGa-GaN is most likely to undergo thermodynamic transitions. Meanwhile, the binding energies analyses elucidate that VGa-GaN is the most stable in Al0.5Ga0.5N. The formation mechanism of complex native point defects in Al0.5Ga0.5N has been revealed, which helps to get a deeper insight to the growth and doping of AlGaN and expands its application in high-power and high-frequency optoelectronic devices.

BIOM-64. EXPLOITING CELL-FREE DNA TO DISSECT MECHANISMS OF RESISTANCE TO TEMOZOLOMIDE IN GLIOBLASTOMA CELLS

Abstract Temozolomide (TMZ) is a cytotoxic alkylating agent that serves as a cornerstone in glioblastoma (GBM) treatment, yet is notorious for eliciting hypermutation in recurrent tumors that have developed drug resistance by downregulating mismatch repair (MMR). We reasoned that cell-free DNA (cfDNA), a non-invasive measure for detecting tumor-derived biomarkers, could be used to temporally examine the mechanism of resistance to TMZ. We therefore designed an in-vitro experiment using the patient-derived GBM43 cell line. Over five days, batches of cells were treated with either TMZ or vehicle. Cell counts and cfDNA were collected every 24 hours. We observed an associated increase in both dead cell counts and cfDNA yield in treated cells compared to untreated cells. In TMZ-treated samples, cfDNA showed a periodic fragmentation pattern consistent with internucleosomal cleavage and TMZ-induced apoptosis. Intriguingly, higher numbers of variants were found in the cfDNA of untreated samples when compared to treated cfDNA, possibly reflecting TMZ-induced selection of resistant subclones in treated samples. This was further supported by the finding that the average variant allele frequency (VAF) increased over time in TMZ-treated samples, consistent with purifying selection. Conversely, cfDNA from vehicle-treated samples demonstrated a decrease in the average VAF over time, consistent with clonal diversification. Although we did not observe an enrichment of the TMZ-associated mutational signature SBS11, we did find higher levels of defective MMR mutation signature SBS44 in treated samples, potentially indicating the selection of subclones with defective MMR mechanisms. Overall, our preliminary findings show that cfDNA can be used to resolve mechanisms of TMZ resistance over time. We are addressing open questions by performing longer treatment times, testing other patient-derived cell lines, and performing murine xenotransplantation experiments to test TMZ-associated hypermutation in vivo. Our work will contribute to our understanding of TMZ resistance, and importantly push the development of cfDNA-based biomarkers for measuring TMZ-sensitivity in patients.

Unravelling the incorporation mechanisms of water in aluminous orthoenstatite: I. First-principles calculations

We performed first-principles calculations on the energy, and NMR and polarized infrared (IR) spectra for anhydrous and hydrous aluminous orthoenstatite (OEn) models to help clarify the incorporation mechanisms of Al and OH defects in OEn. Our calculations revealed that proton pairs in M2 vacancies ((2H)M2) adjacent to a tetrahedral Al (AlIV) are energetically more favorable than those remote from Al, and may contribute to the observed correlated 1H NMR peaks near 3.7 and 8.0 ppm, and IR bands near 3550–3570 and 3066 cm−1 (A4 band) for aluminous OEn. Coupled substitutions of AlVI (octahedral Al) + H for 2Mg were found to adopt multiple configurations, and may contribute to the observed IR bands near 3520, 3475 and 3320 cm−1. Coupled substitution of AlIV + H for 1Si may contribute to the observed IR band near 3380–3400 cm−1. 4H in SiB vacancies ((4H)SiB) adjacent to an AlVI were found to be energetically more favorable than those remote from Al, and may be the origin for an IR band observed near 3600–3620 cm−1. These results allow the incorporation mechanisms of water in synthetic and natural aluminous orthopyroxenes to be deciphered from the available NMR and IR data, and suggest that both (2H)M2 defects associated with Al and simultaneous coupled substitutions of Al + H for 2Mg and 1Si contribute to the observed correlation between Al and water incorporation, and the nearly unity AlIV/AlVI ratio. (4H)SiB defects associated with Al may also be present in some synthetic OEn and mantle-derived orthopyroxene.

Quantitative loss analysis of opaque perovskite solar cells using transient and steady-state characterization

Perovskite solar cells have emerged as a promising technology in the field of photovoltaics, owing to their notable advancements in power-conversion efficiency. Recent investigations have revealed a crucial dependency of efficiency on the source of bromide within the perovskite absorption layer. To elucidate the underlying nature of traps within these solar cells, a comprehensive series of measurements was conducted under varying light intensities. Subsequently, employing an electrodynamic theoretical model, the intrinsic processes inherent to caesium and lead-based perovskite solar cells with different bromide sources were analyzed. The study reveals significant differences in transient photocurrent measurements and photocurrent-voltage characteristics among perovskites originating from different bromide sources, measured under different light intensities. Leveraging theoretical analyses on the picosecond scale, the recombination mechanism of crystal defects was meticulously described revealing the pronounced influence of capture rates on electron-hole recombination dynamics. Furthermore, the investigation substantiated the presence of a band-bending phenomenon at the interface between the hole transport layer (HTL) and perovskite, elucidating the observed transient photocurrent phenomena. The findings significantly advance the understanding of the mechanisms underlying perovskite solar cells, offering valuable insights into their performance and paving the way for enhanced efficiency and stability in future device design and optimization. Published by the American Physical Society 2024

Analysis of the vibration behaviour of a gas turbine during operation

The vibratory behaviour of the gas turbine during operation is analysed in this article. The modern method consists of studying the state of a machine during its operation, to intervene only when the parameters allow it. However, experience has shown that vibration analysis is the most widely used technique to make a reliable diagnosis and to detect the appearance and evolution of most mechanical and hydraulic defects. In our study, we applied the method of vibration analysis of the gas turbine line using monitoring methods to diagnose mechanical defects in shaft bearings. In this sense, the experimental was carried out by measuring and monitoring the level of vibration produced by the turbine, an indicator on its condition was obtained. Should the rise in vibration levels of the machine facilitate the identification of a fault, the subsequent analysis of the machine's vibration characteristics will enable the source of the fault to be determined. It is then possible to determine with accuracy the time before the situation becomes critical.

Study on the Mechanism of Bubble Defects in the PECVD Amorphous Silicon Films on Dielectric Substrate

The amorphous silicon (a-Si) grown by plasma enhanced chemical vapor deposition (PECVD) has been widely applied in advanced semiconductor devices. However, it still suffers from the bubble defects when the deposition temperature goes above 450 °C. In this work, we have investigated the influence of underlying materials on the formation of bubbles of a-Si. The a-Si was deposited on different dielectric substrates, including silicon nitrides (SiN) and silicon dioxide (SiO2), using PECVD technique at a substrate temperature of 500 °C. A large number of bubbles of the a-Si has been observed on the thermal ALD deposited SiN underlayer, and some of them even burst. In contrast, no bubble defects were observed at the a-Si grown on PECVD SiN and PECVD SiO2 films. Such deviation may be attributed to the quality of the underlying material, which induces the H/H2 diffusion during the growth of a-Si and results in bubbles. A solution based on the model has been used to suppress the formation of such bubbles. An inserting layer of SiO2 was introduced in between SiN and a-Si to improve the density of the lower layer material and the adhesion between the two materials. As a result, there is no bubble defects at the surface of a-Si observed using optical microscope. Our work reveals the mechanism of the formation of bubble defects and paves a new method to eliminate the bubbles defects and to form high-quality a-Si, which shows potential in the manufacture of semiconductor devices.

Oxygen Defect Site Filling Strategy Induced Moderate Enrichment of Reactants for Efficient Electrocatalytic Biomass Upgrading.

The electrocatalytic oxidation of 5-hydroxymethylfurfural (HMF) provides a feasible approach for the efficient utilization of biomass. Defect regulation is an effective strategy in the field of biomass upgrading to enhance the adsorption capacity of reactants and thus increase the activity. However, how to select appropriate strategies to regulate the over-enrichment of reactants induced by excessive oxygen vacancy is still a huge challenge. In this work, the defect-filling strategy to design and construct an element-filled oxygen vacancy site layered double hydroxide (S─Ov─LDH) is adopted, which achieves a significant reduction in the electrolysis potential of biomass platform molecule HMF oxidation reaction and a significant increase in current density. Physical characterizations, electrochemical measurements, and theoretical calculations prove that the formation of metal─S bond in the second shell effectively regulates the electronic structure of the material, thus weakening the over-strong adsorption of HMF and OH- induced by excessive oxygen vacancy, promoting the formation of high-valence Co3+ during the reaction, and forming new adsorption sites. This work discusses the catalytic enhancement mechanism of defect filling in detail, fills the gap of defect filling in the field of biomass upgrading, and provides favorable guidance for the further development of defect regulation strategies.

Machine vision-based detection of surface defects in cylindrical battery cases

Automotive 21700 series lithium batteries are prone to surface defects during production and transportation, thus affecting their performance, so we propose a full-surface defect detection method for battery cases based on the synthesis of traditional image processing and deep learning to address this problem. First, the mechanism of surface defects on a battery case is analysed, and the types of surface defects are summarized. A suitable platform for image acquisition is designed for the severely reflective surface. Since there is no publicly available defect dataset for cylindrical battery cases, a defect dataset is established, and the dataset is augmented and expanded via the traditional method and the ACGAN model. For the defects on the top of the battery case, a traditional image processing algorithm is used to combine the roundness and the area of the area pixels to make a comprehensive judgement. For the defects on the bottom and side of the battery case, after comparing and analysing a variety of deep learning networks, the YOLOv7 model is selected to address the data characteristics of the large experimental inputs and the small targeted defects. To improve the accuracy of the model to meet the needs of real-time detection in industry, the CA attention mechanism, the DYHEAD dynamic detector head, and the slicing-assisted super inference (SAHI) method are used, with a final map accuracy reaching 98.1 %, which is 2.7 % higher than that of the initial model. Compared with mainstream target detection algorithms, the algorithm in this paper has good detection performance for cylindrical battery case defect detection and can be better applied to real-time detection in industry.

A probabilistic assessment of ship blackout incident with Fault Tree Analysis into (FTA) Bayesian Network (BN)

Blackouts in maritime activities can cause propulsion loss and dangerous maritime conditions. Bayesian risk analysis is applied to ship blackout incidents in this study to improve understanding and reduce risks. Using Fault Tree Analysis (FTA), a Bayesian Network (BN) model incorporates fuel quality, lubricating oil quality, sensor error, injector error, and mechanical defects to estimate blackout probability. The model analyses how hazards and their interactions affect this situation using probabilistic inference. Sensitivity analysis identifies variables that affect blackout probabilities and prioritises risk mitigation solutions. Based on prior and posterior probabilities, ‘Automatic Voltage Regulator Failure’ (0.03 prior, 0.17 posterior), ‘Rotor Mechanical Fault’ (0.03 prior, 0.15 posterior), and ‘High Cooling Water Temperature’ (0.03 prior, 0.13 posterior) are the top three blackout causes. Other significant variables include ‘Switchboard Line Failure,’ ‘Faulty Fuel Pump,’ ‘Rotor Open Circuit,’ and ‘Temperature Sensor Failure’ in relative amounts. Bayesian risk analysis can identify and minimise marine blackout concerns, giving decision-makers a comprehensive framework for informed decision-making and proactive risk management. This research emphasises blackout accidents’ importance, improving maritime transportation safety and reliability.