Search Results (1,364)

The present study introduces a comprehensive machine-learning framework for modeling, interpretation and optimization of the CNC turning procedure employing coated cutting inserts. The primary novelty of this work lies in the integrated pipeline that leverages a multimodal experimental dataset in order to simultaneously model surface roughness and residual stresses, as well as to interpret these predictions within a unified optimization scheme. Particularly, a deep learning model was developed incorporating a convolutional encoder for analyzing time-series signals and a static encoder for the investigated machining parameters. This fused representation enabled accurate multi-task predictions, capturing the thermo-mechanical interactions that govern surface integrity. Additionally, to ensure interpretability, a surrogate meta-model based on the deep model’s predictions was established and evaluated via Shapley Additive Explanations. This analysis quantified the relative influence of each cutting parameter, linking data-driven insights to contact-mechanical principles. Furthermore, a multi-objective optimization scheme was implemented to derive Pareto optimal trade-offs among the examined parameters that could enhance the machining efficiency. Overall, the integration of deep learning, interpretable modeling and optimization established a coherent framework for data-driven decision making in turning, highlighting the importance of model transparency in advancing intelligent manufacturing systems. Full article

Human neuroglobin (Ngb) is a globin featuring a disulfide bond (Cys46–Cys55) and a redox-active cysteine residue (Cys120) and plays a dual role in cellular stress responses. In this study, we investigated how wild-type (WT) Ngb and its two mutants, C120S Ngb, in which Cys120 is replaced by serine, and A15C Ngb, which contains an engineered Cys15–Cys120 disulfide bridge, modulate oxidative stress in triple-negative breast cancer (MDAMB231) and hormone receptor-positive breast cancer (MCF-7) cells. In both cell lines, WT Ngb enhanced cell survival under H₂O₂-induced oxidative stress by scavenging reactive oxygen species (ROS) through oxidation of Cys120. In contrast, the C120S and A15C mutants lost this protective capacity and instead promoted apoptosis. Mass spectrometry analysis confirmed the oxidation of Cys120 to sulfenic acid in WT Ngb, whereas both mutants exhibited impaired redox activity, leading to elevated ROS levels, lipid peroxidation, and activation of caspase-9/3. AO/EB staining further revealed that WT Ngb attenuated DNA damage, while the mutants exacerbated apoptosis in both MDAMB231 and MCF-7 cells. These results demonstrate that Cys120 acts as a critical redox switch, dictating whether Ngb exerts cytoprotective or pro-apoptotic effects across different breast cancer cell types. Our findings suggest that WT Ngb may help protect normal tissues during cancer therapy, whereas engineered Ngb mutants could be used to selectively sensitize both triple-negative and hormone receptor-positive breast cancer cells to oxidative damage, offering a novel redox-targeted therapeutic strategy. Full article

The pressing need for sustainable, plant-based alternatives is highlighted by the growing resistance of agricultural pests to synthetic pesticides. This study examined the pesticidal potential of phytocompounds from C. tora discovered by GC–MS analysis against important tomato insect (T. absoluta) and fungal pathogen (A. solani). The binding stability and interaction dynamics of specific metabolites with fungal virulence (polygalacturonase, MAP kinase HOG1, and effector AsCEP50) and insect neuromuscular (ryanodine receptor and sodium channel protein) targets were assessed using molecular docking and 100 ns molecular dynamics simulations. Among the screened compounds, squalene and 4,7,10,13,16,19-docosahexaenoic acid, methyl ester (DHAME) exhibited the strongest binding affinities and conformational stability, with MM-GBSA binding free energies of −38.09 kcal·mol⁻¹ and −52.81 kcal·mol⁻¹ for squalene complexes in T. absoluta and A. solani, respectively. Persistent hydrophobic and mixed hydrophobic–polar contacts that stabilised active-site residues and limited protein flexibility were found by ProLIF analysis. These lively and dynamic profiles imply that DHAME and squalene may interfere with calcium signalling and stress-response pathways, which are essential for the survival and pathogenicity of pests. Hydrophobic interactions were further confirmed as the primary stabilising force by the preponderance of van der Waals and nonpolar solvation energies. The findings show that C. tora metabolites, especially squalene and DHAME, are promising environmentally friendly biopesticide candidates that have both insecticidal and antifungal properties. Their development as sustainable substitutes in integrated pest management systems are supported by their stability, binding efficacy and predicted biosafety. Full article

This study aims to optimize the process parameters for manufacturing stainless steel AISI 316L (SS316L) components using Laser Powder Bed Fusion (LPBF) with a Laser-Adapted Powder Deposition System. The influence of volumetric energy density (VED), laser intensity, and interaction time on the topography, defect formation, and hardness of the manufactured parts was investigated. The LPBF process parameters were systematically varied, including laser power (50–250 W) and scanning speed (15–250 mm/s). This resulted in VED values ranging from 55.6 to 647.5 J/mm³. The optimization process revealed ideal process conditions at VED values of 170.9, 256.4, and 641.0 J/mm³, with a minimum laser intensity of 11.8 kW/mm² and interaction times ranging from 0.36 to 2.70 ms. Microstructural analysis revealed a predominantly austenitic phase with residual stresses associated with the LPBF process’s high cooling rates. Mechanical testing showed that parts manufactured under optimized conditions exhibited superior hardness (234–244 HV) compared to conventionally processed SS316L (170–220 HV). It was demonstrated that the laser-adapted powder deposition system can effectively fabricate high-precision components by understanding the interdependencies of parameters in LPBF. This approach contributes to optimizing manufacturing strategies for SS316L components. Full article

Diamond wire sawing, as the core process for monocrystalline silicon wafering, has gained widespread application in the photovoltaic and microelectronics industries due to its high efficiency and low material loss. This study investigates the cutting mechanism of monocrystalline silicon with (100) crystal orientation under multi-abrasive and multi-scratch conditions using explicit finite element dynamics simulation. It focuses on analyzing the effects of radial spacing and height difference between abrasive grains on surface morphology, cutting force, and residual stress. Based on the Johnson-Holmquist-II (JH-II) constitutive model, a high-precision three-dimensional finite element simulation model was constructed. Simulation results indicate that the spacing and height difference between abrasive grains significantly affect the grain-to-grain coupling, thereby influencing the peak cutting force and the surface damage characteristics of the scratches. To address cutting force and residual stress responses, this study proposes an algorithmic optimization scheme based on a multifactor orthogonal experimental design. The analysis indicates that the optimal parameters—U = 1385 m/min, V = 142°, and W = 6.2 μm—reduce residual stress by 33% and cutting force by 75%. Full article

A three-dimensional finite element analysis (FEA) was performed to evaluate stress accumulation and distribution in endodontically treated immature and mature mandibular molars restored with endocrowns. Three tooth models representing different stages of root development (Cvek 2, Cvek 3, and mature) were generated from cone-beam computed tomography data. Endocrowns were fabricated using lithium disilicate (LDS) and resin nanoceramic (RNC). In immature teeth, two apexification strategies were simulated: a 3 mm mineral trioxide aggregate (MTA) apical plug followed by gutta-percha obturation, and complete canal obturation with MTA. All models were subjected to axial (600 N) and oblique (200 N) loading. A total of 20 finite element models were analysed. Endocrown material and loading direction were the main factors affecting von Mises stress distribution, whereas root development stage and apexification technique showed limited influence. LDS resulted in reduced stress transmission to the residual dentin, despite higher stress accumulation within the restoration itself. In the LDS groups, von Mises stress values in the root dentin ranged from 35.24 to 35.96 MPa under oblique and from 42.93 to 44.45 MPa under axial loading, while the RNC group exhibited higher values (39.36–40.40 MPa and 51.59–53.66 MPa, respectively). These findings indicate that endocrown restoration after apexification is a reliable treatment option for immature mandibular molars with extensive structural loss, with LDS demonstrating more favorable biomechanical behavior. Full article

Intense thermo-mechanical coupling effects during cutting generate residual stress within the surface layer of a workpiece. This residual stress is a critical factor influencing the fatigue life, corrosion resistance, and dimensional stability of mechanical components, making its accurate prediction and control essential for improving product performance. To address the often generalized treatment of residual stress prediction modeling in existing literature, this paper presents a systematic review of recent advances in surface residual stress prediction for cutting operations. It details the formation mechanisms and significance of residual stress, focusing on four primary modeling approaches: empirical models based on experimental data, analytical models founded on metal cutting and elastoplastic theory, finite element models that simulate actual machining conditions, and hybrid models. A comprehensive analysis and comparison of these four model types is provided, summarizing their respective advantages and limitations. Furthermore, this paper identifies potential future research directions and development trends in residual stress prediction modeling, serving as a valuable reference for work in this field. Full article

To address the depletion of shallow coal resources, mining activities have progressed to greater depths, where rock masses contain numerous fractures due to complex geological conditions, making grouting reinforcement essential for ensuring stability. Using digital image correlation, this study investigated the strain evolution characteristics of grouted fractured specimens of three rock types—mudstone, coal–rock, and sandstone—under uniaxial compression. Analysis of the strain evolution process focused on two typical fracture inclinations of 0° and 60°, while examination of the peak strain characteristics covered five inclinations, namely 0°, 15°, 30°, 45°, and 60°. The findings indicate that the mechanical response varies systematically with lithology and fracture inclination. The post-peak curves differ significantly among rock types: coal–rock shows a gentle descent, mudstone exhibits a rapid strength drop but higher residual strength, and sandstone is characterized by “serrated” fluctuations. The failure mode transitions from tensile splitting at a horizontal inclination of 0° to shear failure at inclinations of 15°, 30°, 45°, and 60°. Strain nephograms corresponding to the peak stress point D reveal sharp, band-shaped zones of strain localization. The maximum principal strain exhibits a non-monotonic trend, first increasing and then decreasing with increasing inclination angle. For grouted coal–rock and sandstone, the peak values of 47.47 and 45.00 occur at α = 45°. In contrast, grouted mudstone reaches a maximum value of 26.80 at α = 30°, indicating its lower susceptibility to damage. The study systematically clarifies the strain evolution behavior of grouted fractured rock masses, providing a theoretical basis for evaluating the effectiveness of reinforcement and predicting failure mechanisms. Crucially, the findings highlight mudstone’s role as a high-integrity medium and the particular vulnerability of horizontal fractures, offering direct guidance for the targeted grouting design in stratified rock formations. Full article

Recent developments in discrete probability models play a crucial role in reliability and survival analysis when lifetimes are recorded as counts. Motivated by this need, we introduce the discrete ZLindley (DZL) distribution, a novel discretization of the continuous ZL law. Constructed using a survival-function approach, the DZL retains the analytical tractability of its continuous parent while simultaneously exhibiting a monotonically decreasing probability mass function and a strictly increasing hazard rate—properties that are rarely achieved together in existing discrete models. We derive key statistical properties of the proposed distribution, including moments, quantiles, order statistics, and reliability indices such as stress–strength reliability and the mean residual life. These results demonstrate the DZL’s flexibility in modeling skewness, over-dispersion, and heavy-tailed behavior. For statistical inference, we develop maximum likelihood and symmetric Bayesian estimation procedures under censored sampling schemes, supported by asymptotic approximations, bootstrap methods, and Markov chain Monte Carlo techniques. Monte Carlo simulation studies confirm the robustness and efficiency of the Bayesian estimators, particularly under informative prior specifications. The practical applicability of the DZL is illustrated using two real datasets: failure times (in hours) of 18 electronic systems and remission durations (in weeks) of 20 leukemia patients. In both cases, the DZL provides substantially better fits than nine established discrete distributions. By combining structural simplicity, inferential flexibility, and strong empirical performance, the DZL distribution advances discrete reliability theory and offers a versatile tool for contemporary statistical modeling. Full article

The basic/helix-loop-helix (bHLH) transcription factors are crucial regulators of plant development and stress responses. In this study, we conducted a genome-wide analysis of the bHLH family in Rosa roxburghii, an economically important fruit crop. A total of 89 non-redundant RrbHLHs were identified and unevenly distributed across the seven chromosomes. Phylogenetic analysis classified them into 23 subfamilies and 7 Arabidopsis subfamilies were absent, indicating lineage-specific evolutionary trajectories. Conserved motif and gene structure analyses showed that members within the same subfamily generally shared similar architectures, yet subfamily-specific variations were evident, suggesting potential functional diversification. Notably, key residues involved in DNA-binding and dimerization were highly conserved within the bHLH domain. Promoter analysis identified multiple cis-acting elements related to hormone response, stress adaptation, and tissue-specific regulation, hinting at broad regulatory roles. Expression profiling across fruit developmental stages and in response to GA₃ treatment revealed dynamic expression patterns. Furthermore, 21 duplicated gene pairs (17 segmental and 4 tandem duplicated pairs) were identified, with most evolving under purifying selection. Detailed analysis of these pairs revealed that segmental duplication, coupled with structural variations such as exon indels, dissolution/joining, and exonization/pseudoexonization, substantially contributed to their functional divergence during evolution. Our results provide a basis for understanding the evolution and potential functions of the RrbHLHs. Full article

Edge cracks in hot-rolled sheets of industrial grain-oriented electrical steel significantly affect the yield rate and pose substantial challenges to cold rolling fabrication. Eliminating such structural defects through hot rolling requires a thorough understanding of their formation mechanism. This study investigates the formation mechanism of edge cracks in hot-rolled sheets, which are characterized by coarse strip-like grains with typical thicknesses ranging from 20 μm to 100 μm. Coarse, strip-shaped grains have low fracture stress, which is the cause of edge cracks. They originate from abnormally developed columnar grains in continuous casting slabs after reheating, which is unavoidable in industrial large-scale production. Inadequate fragmentation and insufficient recrystallization during rough rolling result in residual coarse grains of intermediate slabs, and their preferential deformation and outward protrusion lead to the formation of grooves. In the subsequent finishing rolling process, deformed coarse grains near the grooves undergo further elongation, developing into distinct strip-like structures. Based on the above mechanistic understanding, the edge microstructure under various rolling parameters was investigated, and targeted improvement measures for edge cracks were proposed. It is concluded that the edge quality can be significantly enhanced through increasing the total width reduction, additional rough rolling passes, and the implementation of edge heating during rough rolling. Quantitative analysis demonstrates that increasing the rolling passes from D to E significantly reduces the fraction of band structure from 64% to 48% and the average width of elongated grains from 43.5 μm to 38.4 μm. Full article

Background: Due to chronic venous insufficiency, venous leg ulcers (VLUs) develop as chronic wounds characterized by impaired healing, persistent inflammation, and endothelial dysfunction. Nitrosative stress, mitochondrial damage, and tissue apoptosis caused by excess nitric oxide (NO) produced by iNOS in macrophages and fibroblasts are contributing factors in the chronic wound environment; therefore, pharmacological modulation of iNOS presents an attractive mechanistic target in chronic wound pathophysiology. Methods: Herein, we present the use of a structure-based computational strategy to assess the inhibition of tavaborole, a boron-based antifungal agent, against iNOS using human iNOS crystal structure (PDB ID: iNOS) by molecular docking using AutoDock 4.2, 500 ns simulation of molecular dynamics (MD), with equilibration within ~50 ns and analyses over full trajectory and binding free energy calculations through the MM-PBSA approach. Results: Docking studies showed favorable binding of tavaborole (–6.1 kcal/mol) in the catalytic domain, which stabilizes contacts with several key residues (CYS200, PRO350, PHE369, GLY371, TRP372, TYR373, and GLU377). MD trajectories for 1 ns showed stable structural configurations with negligible deviations (RMSD ≈ 0.44 ± 0.10 nm) and hydrogen bonding, and MM-PBSA analysis confirmed energetically favorable complex formation (ΔG_binding ≈ 18.38 ± 63.24 kJ/mol) similar to the control systems (L-arginine and 1400W). Conclusions: Taken together, these computational findings indicate that tavaborole can stably occupy the iNOS active site and interact with key catalytic residues, providing a mechanistic basis for further in vitro and ex vivo validation of its potential as an iNOS inhibitor to reduce nitrosative stress and restore endothelial homeostasis in venous leg ulcers, rather than direct therapeutic proof. Full article

With advances in deep-sea exploration technologies, utilizing human-occupied vehicles (HOV) in marine science has become widespread. The observation window is a critical component, as its structural strength affects submersible safety and performance. Under load, it experiences stress concentration, deformation, cracking, and catastrophic failure. The observation window will experience different stress distributions in high-pressure environments. The maximum principal stress is the most significant phenomenon that determines the most likely failure of materials in windows of HOV. This study proposes an artificial intelligence-based method to predict the maximum principal stress of observation windows in HOV for rapid safety assessment. Samples were designed, while strain data with corresponding maximum principal stress values were collected under different loading conditions. Three machine learning algorithms—transformer–CNN-BiLSTM, CNN-LSTM, and Gaussian process regression (GP)—were employed for analysis. Results show that the transformer–CNN-BiLSTM model achieved the highest accuracy, particularly at the point exhibiting the maximum the principal stress value. Evaluation metrics, including mean squared error (MSE), mean absolute error (MAE), and root squared residual (RSR), confirmed its superior performance. The proposed hybrid model incorporates a positional encoding layer to enrich input data with locational information and combines the strengths of bidirectional long short-term memory (LSTM), one-dimensional CNN, and transformer–CNN-BiLSTM encoders. This approach effectively captures local and global stress features, offering a reliable predictive tool for health monitoring of submersible observation windows. Full article

The shale oil reservoir is characterized by ultra-low porosity and permeability and multi-scale strong heterogeneity. During the sampling process of downhole cores, the rocks can easily be affected by drilling fluid contamination, mechanical stress damage, and other factors, altering the original distribution of oil–water and the characteristics of pore structures. Oil removal and oil saturation are critical steps in core pre-treatment, yet the mechanism of its impact on cores has not been systematically studied. This research focuses on oil removal in six cores from the Jimsar shale oil reservoir with different oil saturations. The necessity and effectiveness of the oil removal saturation and its impact on the microstructure of the cores were systematically evaluated by employing nuclear magnetic resonance (NMR), CT scanning, and permeability testing methods. The results indicate that there are significant differences in fluid composition, pore structure, and wettability among downhole cores, making oil removal saturation treatment a necessary prerequisite for subsequent experiments. High-temperature and high-pressure oil removal shows significant effectiveness, with an average core weight reduction of 2.46% and average reduction in T₂ peak area of 73.75%. The efficacy of oil saturation is influenced by the initial pore-throat distribution in the cores. The oil removal process significantly alters petrophysical parameters, with an average increase in porosity of 3.21 times and permeability rising by an average of 2.16 times, although individual variations exist. Microstructural analysis demonstrates that the oil removal process preferentially removes crude oil from larger pores, while residual oil is mainly distributed in smaller pores, indicated by a left shift in T₂ peak values. Meanwhile, high-temperature and high-pressure conditions induce microfracture development, promoting the migration of crude oil into smaller pores. This research reveals the complex impact mechanism of the oil removal saturation process on shale cores, providing a theoretical basis for accurately evaluating shale reservoir characteristics and optimizing experimental design. Full article

The objective of this study was to evaluate the protective effect of curcumin (Cur) on reproductive toxicity induced by fumonisin B₁ (FB₁) in laying ducks during the peak egg-laying period. A total of seventy-two 50-week-old Cherry Valley ducks were randomly assigned to four groups: control, FB₁ (30 mg/kg), Cur (200 mg/kg), and Cur + FB₁ (200 mg/kg + 30 mg/kg). The experiment lasted for 35 days. Our results showed that cur supplementation effectively restored the reductions in final body weight (p = 0.005) and oviduct length (p = 0.020) induced by FB₁ exposure. Residual FB₁ concentrations in serum, liver, and ovaries were markedly increased in the FB₁-treated group, while Cur significantly decreased the FB₁ residual in duck liver (p < 0.05). Meanwhile, Cur supplementation markedly counteracted the FB₁-induced reductions in serum total protein, albumin, triglycerides, and high-density lipoprotein induced by FB₁ exposure. Cur supplementation effectively regulated FB₁-induced oxidative stress, inflammation, and endocrine disruption. Specifically, Cur lowered FB₁-induced malondialdehyde levels (p < 0.010), attenuated interleukin-1β increase (p = 0.083), and reversed the reduction in immunoglobulin G levels. FB increased the levels of hormones associated with duck reproduction, including estradiol, follicle-stimulating hormone, and luteinizing hormone; in contrast, curcumin supplementation decreased the levels of these hormones (p < 0.010). Histopathological analysis revealed that Cur significantly alleviated the inflammation and necrosis in the liver, kidneys, ovaries, and oviducts induced by FB₁. In conclusion, dietary Cur supplementation effectively alleviated FB₁-induced reproductive toxicity in laying ducks by enhancing antioxidant capacity, improving lipid metabolism, and restoring hormonal homeostasis. Full article