Objective: To test the ability of both zinc oxide nanoparticles (ZnONPs) and silver nanoparticles (SNPs) to ameliorate the oxidative stress resulted from diabetes in diabetic rats. Methods: Fifty male albino rats were used; ten of them were served as control group and forty, as the experiment group, were injected with streptozotocin at the single intraperitoneal dose of 100 mg/kg. Then, the experiment group was subdivided into, diabetic, diabetic + ZnONPs, diabetic + SNPs and diabetic + insulin groups. The activities and mRNA expression levels of superoxide dismutase, catalase, glutathione peroxidase and glutathione reductase were determined in brain tissues. Malondialdehyde, total antioxidant capacity, zinc and silver concentrations were estimated in the brain tissues of all rats. Results: A significant increase in the activities and mRNA expression levels of superoxide dismutase, catalase, glutathione peroxidase and glutathione reductase was shown. Malondialdehyde levels were significantly decreased while there was a significant increase in the zinc, silver concentrations and total antioxidant capacity in brain of ZnONPs and SNPs treated rats, compared with diabetic or diabetic + insulin group and their control group. Conclusions: ZnONPs and SNPs can be used to ameliorate the oxidative stress in brain resulted from diabetes mellitus.
As society moves towards a low-carbon future, the global emphasis on efficient and sustainable energy storage platforms increases and has intensified the search for advanced electrode materials that offer high capacitance, fast charge-discharge capability, and long-term cycling stability. However, most conventional materials suffer from limited electrical conductivity, poor rate performance, or structural degradation over extended cycling. To address these limitations, a novel composite electrode material based on a Pb-based MOF (YK-2) and functionalized carbon nanotubes (FCNTs) was developed and systematically studied. A series of composites, YK-2@FCNT(5), YK-2@FCNT(10), and YK-2@FCNT(15), were successfully synthesized and thoroughly investigated by cyclic voltammetry (CV), galvanostatic charge-discharge (GCD), and electrochemical impedance spectroscopy (EIS) in a three-electrode system. Among them, YK-2@FCNT(10) demonstrated the highest specific capacitance of 913.57 F g-1 at 0.5 A g-1, significantly outperforming the pristine YK-2 electrode. EIS analysis revealed a marked reduction in both solution and charge transfer resistance due to the incorporation of FCNTs, enhancing conductivity and ion diffusion. Dunn's method further confirmed a mixed charge storage mechanism with a b-value of 0.747, where the proportion of capacitive contribution rose significantly from 32.02% to 65.33% as the scan rate increased from 5 to 80 mV s-1. Additionally, YK-2@FCNT(10) retained 92.87% of its initial capacitance even after 5000 consecutive charge-discharge cycles at 10 A g-1, indicating excellent long-term electrochemical stability. Furthermore, a symmetrical supercapacitor device assembled using YK-2@FCNT(10) electrodes delivered a high specific capacitance of 216.9 F g-1 at 0.5 A g-1 and maintained an excellent cycling stability of 86.67% over 5000 cycles. The device also achieved a remarkable energy density of 30.12 Wh kg-1 and a maximum power density of 4998.69 W kg-1, confirming its strong potential for practical high-performance energy storage applications.
As demand grows for personalized, scalable assessments in higher education (including both scoring and feedback provision), large language models (LLMs) have emerged as promising tools. While human educators typically perform scoring and feedback in a sequential and interrelated manner, existing research has largely addressed these tasks separately. This raises important questions about LLMs' ability to handle scoring and feedback within a single workflow and the extent to which task sequencing affects their performance. To address this gap, this study investigates how prompting LLMs to perform scoring and feedback either together in one single prompt (prompt composition) or separately in two consecutive prompts (prompt decomposition), and the order in which these tasks are prompted affect the performance of GPT-4o, a cutting-edge LLM, in postgraduate open-ended assessments. We analyzed the scoring performance across student groups of varying performance levels. To tailor GPT-4o-generated feedback to individual student learning needs, we embedded well-established learner-centered feedback principles into the prompt design and assessed the quality of the generated feedback based on these principles. The scoring results revealed that prompt effectiveness varied modestly across student groups, with higher scoring errors on lower quality submissions. In terms of generated feedback, GPT-4o demonstrated greater support for learner agency. Task order influenced how this agency was expressed: prompting feedback first fostered learner autonomy, while prompting it after scoring emphasized the student-teacher connection.
Safranin O dye threatens human health and aquatic systems through persistent color and cellular toxicity. Its presence in water lowers light transmission and suppresses primary production. Novel MgO/BaCO3/CaCO3/Ca(OH)2 nanocomposites were synthesized by a facile Pechini sol-gel route at two set temperatures (600 and 800 °C) and are denoted BMC600 and BMC800, respectively. XRD confirms multiphase products with an average crystal size of 60.52 nm regarding BMC600 and 68.64 nm regarding BMC800. EDX detects C, O, Mg, Ca, and Ba with atomic percentages for BMC600 equal to 13.2, 57.8, 12.0, 12.7, and 4.3
There has been increasing world interest in evaluating nanoparticle-infused PMMA/PLA nanocomposite films, as they are suitable for multifunctional applications. In this research work, we emphasize the design of nanocomposite films based on a PMMA/PLA blend with different high loadings of Zn0.5Co0.5Fe2O4 nanoparticles (ZCFO NPs), based on the solution-casting method. Various techniques were used to evaluate the different properties of the obtained films. The interaction and complexation of the polymer blend with the nanofillers were evidenced by X-ray diffraction and Fourier transform infrared spectroscopy. The optical properties of the composites were found to be dependent on the amount of nanoparticles; that is, direct and indirect optical band gaps reduced as ZCFO increased to 8 % by weight. Furthermore, the Urbach energy increased with the addition of biochar due to the addition of more energy traps in the blend, allowing lower energy transitions. Electrical characterizations and dielectric properties were examined in all the samples, with increased AC conductivity and dielectric behavior with increasing frequency and nanofiller weight. Of all the formulation compositions, PMMA/PLA-6 %ZCFO showed the best performance. Notably, when compared to the pristine blend, the energy density significantly increased with the addition of 6 wt percent ZCFO nanoparticles. The ZCFO NPs were shown to considerably improve the thermal characteristics of PMMA/PLA using thermogravimetric analysis (TGA). It exhibited better mechanical strength with tensile strength (23.93 MPa) and Young's modulus (14.89 MPa) at 8 wt % nanoparticle loading. With the improvement in structural optical, electric, and dielectric characteristics, this specific composition (PMMA/PLA-6 %ZCFO) is highly eligible to be used for multifunctional applications.
