In this work, composite materials were prepared by mixing different concentrations of ferrites with polyacrylonitrile (PAN) polymer. Using the electrospinning technique, these composites were deposited on a p-type silicon wafer. The prepared samples demonstrated nanofibers in both pure PAN polymers and their composites with ferrite. Prior to examining the humidity sensing effectiveness with a percentage of relative humidity at a frequency of 10 kHz, based on ambient temperature and a relative humidity range of 50–100%, the composite nanofibers demonstrated stronger humidity sensing compared to the pure PAN nanofibers, which demonstrated a powerful resistance response. More precisely, the PAN@ferrite nanocomposite showed a broad adsorption/desorption hysteresis loop.
Etodolac is choice of drug for pain and inflammation but has major side effects of gastric ulcers that are due to free carboxylic group. Etodolac belongs to the chemical class of non-selective COX-inhibitor but preferentially COX-2 inhibitor. Here the ester linked mutual prodrugs of etodolac with phytophenols like vanillin, carvacrol, umbelliferone, guaiacol, sesamol and syringaldehyde were synthesized. All the prodrugs were characterized by IR-spectroscopy, 1H-NMR, 13C-NMR and mass spectrometry. Among the synthesized prodrugs, the Eto-van, Eto-umbe, Eto-sesa and Eto-syr showed improved analgesic and anti-inflammatory activity compared to etodolac. All the synthesized prodrugs showed less ulcerogenic side effects co
... Show MoreThe synthesis of zeolite NaX from locally available kaolin has been studied. The operating conditions for zeolite NaX production from kaolin with good crystallinity were as follows; a gel formation step of metakaolin in alkaline medium in presence of additional silica to crystallize the zeolite was achieved at 60 oC for 1 hr,and with stirring. In ageing step of the reactants at room temperature for 5 days and crystallization step at 87±2 oC for 24 hr. The catalytic activity of catalyst prepared from local kaolin was studied by using cumene cracking as a model for catalytic cracking and compared with standard HY zeolite and HX zeolite catalysts. The activity test was carried out in a laboratory continuous flow unit with fixed bed reactor
... Show MoreMagnetic plaster kiln dust (MPKD) was synthesized as a unique, low-cost composite reused of byproduct plaster kiln dust (PKD), which is considered a source of air pollution. The FESEM, EDS, XRD, FTIR, VSM, and BET tests were used to characterize the MPKD. The characterization revealed that the MPKD was nanotubes non-agglomerated and super-paramagnetic with a high specific surface area (102.7 m2/g). Compared with the specific area of other materials (composites), the MPKD could be considered a promising substance in the field of water/wastewater treatment.
Nanosponges (NS) of etodolac(ETO) was prepared using the emulsion solvent diffusion method ; the effects of drug: polymer ratio, the effect of level concentration of internal phase and stirring time and other variables that effect on the physical characteristics of NS were investigated and characterized, The selected formula was lyophilized then incorporated into hydrogel ; which also evaluated .The results show that the formulation that contain Drug: PVA:EC in ratio 1:3:2 is the best with smallest particle size 40.2±0.098 with polydispersibility0.005 and in vitro release 97.6±0.11%, , ETO NS Carbopol hydrogel produced a significant(p<0.05) improvement of the in vitro release than pure ETO hydrogel.
Modern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for