In this study, novel Schiff base complexes with Zn(II) and Co(II) ions were successfully synthesized. The malonic acid dihydrazide was converted into the Schiff base ligand by combining it with 1-hydroxy-2-naphthaldehyde, and the last step required reacting it with the appropriate metal(II) chloride to produce pure target complexes. The generated complexes were thoroughly characterized using FTIR, 1H-NMR, 13C-NMR, GC-mass, and UV-Vis spectroscopies. In order to photo-stabilize polystyrene (PS) and reduce the photodegradation of its polymeric chains, these chemicals have been used in this work. The efficiency of the generated complexes as photo-stabilizers was evaluated using a variety of techniques, including FTIR, weight loss, viscosity average molecular weight, light and atomic force microscopy, scanning electron microscopy (SEM), and energy dispersive X-ray (EDX) mapping. These tests corroborated each other and demonstrated how effectively new compounds stabilize PS photographs. As a result, compared to blank PS, they reduce the photodegradation of PS films containing these complexes after 300 h of exposure to UV radiation with a wavelength of 313 nm. Also, it has demonstrated how effective the cobalt complex is as a photo-stabilizer. The highly conjugated systems in these chemicals are to blame for this.
. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
... Show MoreIn recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc
... Show MoreThis study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.
The current study introduces a novel technique to handle electrochemical localized corrosion in certain limited regions rather than applying comprehensive cathodic protection (CP) treatment. An impressed current cathodic protection cell (ICCPC) was fabricated and firmly installed on the middle of a steel structure surface to deter localized corrosion in fixed or mobile steel structures. The designed ICCPC comprises three essential parts: an anode, a cathode, and an artificial electrolyte. The latter was developed to mimic the function of the natural electrolyte in CP. A proportional-integrated-derivative (PID) controller was designed to stabilize this potential below the ICCPC at a cathodic potential of −850 mV, which is crucial for prote
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In this work, a novel technique to obtain an accurate solutions to nonlinear form by multi-step combination with Laplace-variational approach (MSLVIM) is introduced. Compared with the traditional approach for variational it overcome all difficulties and enable to provide us more an accurate solutions with extended of the convergence region as well as covering to larger intervals which providing us a continuous representation of approximate analytic solution and it give more better information of the solution over the whole time interval. This technique is more easier for obtaining the general Lagrange multiplier with reduces the time and calculations. It converges rapidly to exact formula with simply computable terms wit
... Show MoreA three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
... Show MoreThis study has been performed for knowing the nutritional and chemical content of one kind chamomile tea for infant and children available in the pharmacy. The results have been showed that the percentage of essential compounds which represented with moisture, protein, fat, carbohydrate, ash and calories as 7.09%,0.01%,0.01%,92,81%, 0.08% and 371,37 Kal./100g, respectively of dry weight. Also the results have been showed that the percentage of chamomile plant extract that added to the tea as 5.74%. And the result of chemical test for effective materials in alcoholic extract showed consist Tannis, Glycosides, Flavonoids, Alkialoids,and Resins.
In this research, the performance of a two kind of membrane was examined to recovering the nutrients (protein and lactose) from the whey produced by the soft cheese industry in the General Company for Food Products inAbo-ghraab.Wheyare treated in two stages, the first including press whey into micron filter made of poly vinylidene difluoride (PVDF) standard plate type 800 kilo dalton, The membrane separates the whey to permeate which represent is the main nutrients and to remove the fat and microorganisms.The second stage is to isolate the protein by using ultra filter made of polyethylsulphone(PES)type plate with a measurement of 10,60 kilo dalton and the recovery of lactose in the form of permeate.
The results showed that the percen