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Unravelling the role of silica nanoparticles in alleviating chromium heavy metal stress in Mexican marigold (Tagetes erecta L.)
The surface texture properties after electrical discharge machining with negative polarity using graphite electrodes of different grain sizes
Abstract Electrical discharge machining (EDM) is a precise, unconventional manufacturing technique widely used for machining difficult-to-cut materials. Hastelloy C-22, a nickel-chromium alloy, presents significant challenges for conventional machining due to its high hardness and melting point. Graphite electrodes are commonly employed in EDM because of their favourable technological and economic properties. In this study, two commercially available POCO graphite electrodes with different grain sizes were used: 1 $$\upmu$$ m (AF-5) and 10 $$\upmu$$ m (S-180). The investigation focused on the effect of graphite grain size and EDM electrical parameters on the surface roughness of Hastelloy C-22 under negative polarity, which is often selected to improve material removal efficiency and surface finish. Surface topography was quantitatively characterised using Sa , Sz , St , Sds , Sdr , and Sfd parameters. The results indicate that surface roughness is primarily determined by electrical parameters (current intensity, discharge duration, and time interval), with the influence of graphite grain size being relatively minor. Grain size affects tool wear and the stability of electrical discharges, which can induce surface irregularities. Statistical models were developed to predict surface roughness based on EDM parameters, providing guidance for optimising the machining of Hastelloy C-22 with different graphite electrodes.
Factors affecting delays in oil and gas construction projects
Abstract Ensuring the timely completion of construction projects is vital for overall efficiency. This study aims to identify, classify, and rank the main factors of delay in Egyptian oil and gas construction projects related to project stakeholders. A mixed-methods approach was used to Sharkia collect and analyze both quantitative and qualitative data. Data was gathered from 71 sector respondents. Expert interviews refined the delay factors from the literature to 20 for contractors, 17 for owners, and 13 related to consultants. Financial difficulties, late payments to suppliers and subcontractors, and supplier material delivery delays were the significant causes related to the contractor. Delays associated with owners came from ineffective contractor selection and government regulations. Consultants contributed to delays in finalizing drawings and designs. To provide a deeper understanding of the interrelationships among these factors and their collective effect on project delay, a structural model was developed and evaluated. The structural model demonstrated that deficiencies in project planning, design management, and owner decision-making collectively contribute to delays. This provides a basis for developing integrated management approaches to mitigate future delays and improve project performance in Egypt’s oil and gas construction sector.
IHBA-optimized DR-SE-NPCNet for robust open-circuit fault diagnosis in three-level NPC inverters under mixed and noisy conditions
Prognostic factors in patients with interstitial lung disease treated with nintedanib: a multicenter retrospective study in Japan
Abstract Nintedanib is widely used to slow disease progression and prevent acute exacerbations in patients with idiopathic pulmonary fibrosis (IPF) and progressive fibrosing interstitial lung disease (PF-ILD). We retrospectively analysed patients who initiated nintedanib for IPF or PF-ILD between August 2019 and July 2023 across 15 institutions in Japan, focusing on prognosis and disease progression. Patients were divided into two groups based on whether they survived for ≥ 3 years after nintedanib initiation, and their characteristics were compared. We also evaluated factors associated with annual forced vital capacity (FVC) decline and acute exacerbations. A total of 413 patients (171 with IPF and 242 with PF-ILD) were included. Median survival was 1,177 days for IPF and 1,268 days for PF-ILD, with no significant difference ( P = 0.20). Patients surviving < 3 years were older (75.0 vs. 71.0 years), more frequently had resting arterial oxygen saturation (SpO 2 ) < 95% (44.5% vs. 18.0%), and lower body mass index (BMI) (21.9 vs. 24.1 kg/m 2 ). Additionally, patients with a BMI < 22 kg/m 2 showed greater annual relative FVC decline. In conclusion, patients with IPF and PF-ILD showed comparable outcomes following nintedanib treatment. Age ≥ 65 years, resting SpO 2 < 95%, and BMI < 22 kg/m 2 were associated with shorter survival after nintedanib initiation.
Enhancing the yield of bucket brigade quantum random access memory using redundancy repair
Hydraulic support pressure prediction via deep learning with multilevel temporal feature integration
Energy and daylighting trade-offs in residential window design: multi-objective optimization for hot-arid regions
Functional extracellular vesicles enable injectable hydrogels with stable osteogenic properties for minimally invasive bone defect repair
Fault feature extraction for centrifugal pump impellers via EMD and cyclic bispectral slicing
Alpha-synuclein amyloids catalyze the degradation of ATP and other nucleotides
Recognition method for the flight parameters of multiple projectiles with light-screen array sensor
A new green method to NiO/MnO2 nanocomposite synthesis for efficient and sustainable dye removal from aqueous media
Abstract The bimetallic nickel oxide/manganese oxide nanocomposite (NiO/MnO 2 NC) was prepared for the first time using a one-pot plant-mediated route and applied for the adsorption of malachite green (MG) dye from aqueous media compared with the monometallic nickel oxide nanoparticles (NiO NPs). The materials were characterized by TGA, FTIR, XRD, EDX, SEM, TEM, and BET analyses. The adsorption parameters, including pH, MG initial concentration, agitation time, adsorbent mass, and temperature, were systematically studied. The results indicated a significant effect of all parameters on the MG removal percent, attaining 90.4% by NiO NPs and 99.64% by NiO/MnO 2 NC within 60 min. The experimental data are best fitted by the Freundlich model for NiO NPs and the Langmuir model for NiO/MnO 2 NC, having maximum adsorption capacities of 39.84 and 208.3 mg/g, respectively. This can be attributed to the higher surface area of NiO/MnO 2 NC (143.65 m 2 /g) than NiO NPs (3.75 m 2 /g), as well as the presence of different metal atoms in the nanocomposite, which form unique adsorption sites with variable energies, thereby improving adsorption. Although the pseudo-second-order kinetic model more accurately describes kinetics, isotherm models, particularly the D-R isotherm model, show that physisorption is the primary mechanism. The combined data point to a multi-mechanistic adsorption process, with physisorption being the primary mechanism.The thermodynamic findings displayed that MG adsorption process is spontaneous, feasible, and endothermic. Both adsorbents are stable after five adsoption cycles, and the MG adsorption is mainly due to electrostatic attraction, hydrogen bonds, and π-π stacking. These results conclude that NiO/MnO 2 NC is a better alternative to NiO NPs for removing MG, providing insights into designing more efficient adsorbents for dye removal in the water treatment systems.
Simultaneous prediction and optimisation of rock fragmentation and ground vibration using an ANN–RF ensemble in open-pit blasting
Advancing leprosy risk prediction through identification of a whole blood host transcriptomic biomarker signature including non-coding genes
Automatic background animation generation aligned with LLM-generated lyrics for children’s songs
Abstract Media content creation is a labor-intensive and expensive process requiring significant time. Recent developments in artificial intelligence have introduced generative models, which have significant potential in the entertainment industry. Meanwhile, demand for video content tailored to children’s songs has steadily increased, reflecting their significant contribution to early education and entertainment. In this paper, we present a generative model-based approach to automated video creation for children’s songs. The proposed pipeline consists of three key steps: generating lyrics using a language model, producing background images with a diffusion model, and overlaying dynamic visual effects to enhance the final output. Our experiments include a comparison of conventional diffusion models and prompt engineering methods, highlighting the superior performance of CascadeSD and the efficacy of landscape or image-style prompting. Lastly, we provide experimental results comparing text-to-video models with our pipeline. The code for our project is available in the following repository: https://github.com/KhrTim/BAGen .