Numerical Solution of Coupled System of Nonlinear Partial Differential Equations Using Laplace-Adomian Decomposition Method

Aim of the paper is to investigate applications of Laplace Adomian Decomposition Method (LADM) on nonlinear physical problems. Some coupled system of non-linear partial differential equations (NLPDEs) are considered and solved numerically using LADM. The results obtained by LADM are compared with those obtained by standard and modified Adomian Decomposition Methods. The behavior of the numerical solution is shown through graphs. It is observed that LADM is an effective method with high accuracy with less number of components

Nanocrystalline Na0.1V2O5.nH2Oxerogel Thin Film for Gas Sensing

Nanocrystalline thin film of Na0.1V2O5.nH2O xerogel obtained by sol-gel synthesis was used as a gas sensor. Gas sensing properties of different gases such as hydrogen, petroleum and humidity were investigated. Applying XRD and TEM the size of the nanocrystals is found to be 7.5 nm. SEM shows a highly porous structure with submicron meter-sized voids present throughout the sample. FTIR measurement shows different chemical groups identifying the obtained series of gels. The sample was n-type semiconductor according to the thermoelectric power and electrical conductivity. It can be seen that the sensor response curves from 130°C to 150°C show a rapid increase in sensitivity for all types of gas injection, low response values for heating period and the rapid high response values for cooling period. This result may suggest that this material is able to act as gas sensor during the heating and cooling process

Nanocrystalline Na0.1V2O5.nH2Oxerogel Thin Film for Gas Sensing

Nanocrystalline thin film of Na0.1V2O5.nH2O xerogel obtained by sol-gel synthesis was used as a gas sensor. Gas sensing properties of different gases such as hydrogen, petroleum and humidity were investigated. Applying XRD and TEM the size of the nanocrystals is found to be 7.5 nm. SEM shows a highly porous structure with submicron meter-sized voids present throughout the sample. FTIR measurement shows different chemical groups identifying the obtained series of gels. The sample was n-type semiconductor according to the thermoelectric power and electrical conductivity. It can be seen that the sensor response curves from 130°C to 150°C show a rapid increase in sensitivity for all types of gas injection, low response values for heating period and the rapid high response values for cooling period. This result may suggest that this material is able to act as gas sensor during the heating and cooling process

An extremely low-noise heralded single-photon source: a breakthrough for quantum technologies

Low noise single-photon sources are a critical element for quantum technologies. We present a heralded single-photon source with an extremely low level of residual background photons, by implementing low-jitter detectors and electronics and a fast custom-made pulse generator controlling an optical shutter (a LiNbO3 waveguide optical switch) on the output of the source. This source has a second-order autocorrelation g^{(2)}(0)=0.005(7), and an "Output Noise Factor" (defined as the ratio of the number of noise photons to total photons at the source output channel) of 0.25(1)%. These are the best performance characteristics reported to date

Electrocatalytic Evolution of Oxygen Gas at Cobalt Oxide Nanoparticles Modified Electrodes

The electrocatalysis of oxygen evolution reaction (OER) at cobalt oxide nanoparticles (nano-CoOx) modified GC, Au and Pt electrodes has been examined using cyclic voltammetry. The OER is significantly enhanced upon modification of the electrodes with nano-CoOx, as demonstrated by a negative shift in the polarization curves at the nano-CoOx modified electrodes compared to that obtained at the unmodified ones. Scanning electron microscopy (SEM) revealed the electrodeposition of nanometer-size CoOx (average particle size of 200 nm) onto GC electrode. Optimization of the operating experimental conditions (i.e., solution pH and loading level of nano-CoOx) has been achieved to maximize the electrocatalytic activity of nano-CoOx modified electrodes. It has been found that the electrocatalytic activity of the nano-CoOx modified electrodes towards the OER is pH and loading level dependent, while it is substrate independent. The low cost as well as the marked stability of the thus-modified electrodes make them promising candidates in industrial water electrolysis proces

Possible Potentiation by Certain Antioxidants of the Anti-Inflammatory Effects of Diclofenac in Rats

In the present study, we investigated the potential beneficial impact of the addition of antioxidant supplements to diclofenac regimen in a model of carrageenan-induced paw. Rats were treated daily with antioxidants, that is, a-lipoic acid (50 mg/kg), selenium (2.5 mg/kg), vitamin C (1 g/kg), vitamin E (300 mg/kg), or zinc (25 mg/kg) on seven successive days and then received a single treatment with diclofenac or saline before carrageenan was injected to induce paw inflammation. The results indicated that these combinations did not significantly affect the percentage inhibition of paw edema caused by diclofenac alone; however, some combination treatments ameliorated signs of concomitant oxidative stress (such as alterations in plasma malondialdehyde (MDA) levels, hemolysate reduced glutathione levels, and erythrocytic superoxide dismutase enzyme activities) imparted by diclofenac alone. In some cases, few tested antioxidants in combination with diclofenac resulted in increased plasma levels of interleukin- (IL-) 6 and C-reactive protein (CRP). In conclusion, the results of these studies suggested to us that the added presence of natural antioxidants could be beneficial as standard anti-inflammatory therapeutics for a patient under diclofenac treatment, albeit that these effects do not appear to significantly build upon those that could be obtained from this common anti-inflammatory agent per se

Predicting Students' end-of-term Performances using ML Techniques and Environmental Data

Abstract: This study introduces a machine learning-based model for predicting student performance using a comprehensive dataset derived from educational sources, encompassing 15 key features and comprising 62,631 student samples. Our five-layer neural network demonstrated remarkable performance, achieving an accuracy of 89.14% and an average error of 0.000715, underscoring its effectiveness in predicting student outcomes. Crucially, this research identifies pivotal determinants of student success, including factors such as socio-economic background, prior academic history, study habits, and attendance patterns, shedding light on the nuanced dynamics of student performance. The key influential features identified in this study offer valuable insights into the complex factors shaping student achievement. These insights are vital for educators, policymakers, and institutions seeking to enhance educational outcomes and promote equitable access to quality education. This research provides a data-driven foundation for proactive interventions, personalized learning strategies, and support systems, ultimately contributing to improved student performance and academic success. The high accuracy of the predictive model and the feature analysis it provides empower decision-makers in the education sector. This model holds significant potential for applications in student performance monitoring, early intervention, and tailored educational strategies. By adopting a data-driven approach, this work advances the field of educational analytics and contributes to the goal of fostering student success and educational equity

An efficient green ionic liquid for the corrosion inhibition of reinforcement steel in neutral and alkaline highly saline simulated concrete pore solutions

The effect of the green ionic liquid compound, Quaternium-32 (Q-32), on the corrosion inhibition performance of reinforcement steel, in a simulated concrete pore solution, was investigated at different temperatures and pH values, using electrochemical impedance spectroscopy (EIS). The inhibition efficiency was improved as the concentration of Q-32 and pH values were increased. However, it decreased as the temperature was raised. A Q-32 concentration of 20 µmol L–1 exhibited a 94% inhibition efficiency at 20 °C. The adsorption isotherm was evaluated using EIS measurements, and it was found to obey the Langmuir isotherm. The surface topography was examined using an atomic force microscope and scanning electron microscope. The effect of the Q-32 concentration with the highest corrosion efficiency on the mechanical properties of the mortars was also explained by flexure and compression techniques.The authors express their gratitude to the Center for Advanced Materials at Qatar University for technical support. Additionally, the authors are grateful to Qatar University for funding this work through the QUCG-CAM-20/21-2 Grant. The publication of this article was funded by the Qatar National Library