Local wheat peel as a solid surface to remove Azure B dye from aqueous solution:Equilibrium isotherms and thermodynamic study

In this research local wheat peel was used as an adsorbent surface for removal of Azure B (AB) dye from the aqueous solution. The adsorption process was performed at different experimental parameters, equilibrium time, temperature, ionic strength and solution pH. The isotherms of adsorption are of H-type as compared with Giles curves and the adsorption data were coincide with Freundlich equation. The adsorption kinetic data were analyzed using pseudo- first and second order kinetic models. The effect of temperature was studied and the amount of dye adsorbed was found to increase with the increasing of temperature from 25 to 50 oC. The values of thermodynamic functions like enthalpy and entropy have been estimated. The quantity of adsorbed dye on the wheat peel increase according to the sequence follows: pH 9.3? 8 ? 7 ?6 ?5.2.The adsorption phenomenon is influenced by the sodium chloride concentration of solution. The obtained data refer to a decrease in amount of Azure B adsorbed in the existence of electrolyte

Almost unbiased ridge estimator in the zero-inated Poisson regression model

The zero-inflated Poisson regression (ZIP) model is a very popular model for count data that have extra zeros. In some situations, the count data are correlated and so multicollinearity exists among the explanatory variables. Thus, the traditional maximum likelihood estimator (MLE) becomes not a reliable estimator because the mean squared error (MSE) becomes inflated. The ridge estimator (RE) is used to overcome this problem. In this work, an almost unbiased ridge estimator for the ZIP model (AUZIPRE) is proposed to tackle the multicollinearity problem in count data. We investigate the behavior of the proposed estimator using a simulation study. Using the MSE measure, the results of the proposed estimator are compared with those of the RE and the MLE. Furthermore, we apply the proposed estimator on a real dataset. The results show that the performance of AUZIPRE outperforms for that of the RE and the MLE in the existing of the multicollinearity among the count data in the ZIP model.Publisher's Versio

Some almost unbiased ridge regression estimators for the zero-inflated negative binomial regression model

Zero-inflated negative binomial regression (ZINB) models are commonly used for count data that show overdispersion and extra zeros. The correlation among variables of the count data leads to the presence of a multicollinearity problem. In this case, the maximum likelihood estimator (MLE) will not be an efficient estimator as the value of the mean squared error (MSE) will be large. Several alternative estimators, such as ridge estimators, have been proposed to solve the multicollinearity problem. In this paper, we propose an estimator called an almost unbiased ridge estimator for the ZINB model (AUZINBRE) to solve the multicollinearity problem in the correlated count data. The performance of the AUZINBRE is investigated using a Monte Carlo simulation study. The MSE is used as a measure to compare the results of the proposed estimators with those of the ridge estimators and the MLE. In addition, the AUZINBRE is applied to a real dataset

Towards Exploiting Implicit Human Feedback for Improving RDF2vec Embeddings

RDF2vec is a technique for creating vector space embeddings from an RDF knowledge graph, i.e., representing each entity in the graph as a vector. It first creates sequences of nodes by performing random walks on the graph. In a second step, those sequences are processed by the word2vec algorithm for creating the actual embeddings. In this paper, we explore the use of external edge weights for guiding the random walks. As edge weights, transition probabilities between pages in Wikipedia are used as a proxy for the human feedback for the importance of an edge. We show that in some scenarios, RDF2vec utilizing those transition probabilities can outperform both RDF2vec based on random walks as well as the usage of graph internal edge weights.Comment: Workshop paper accepted at Deep Learning for Knowledge Graphs Workshop 202

Phenolic Compounds from the Natural Sources and Their Cytotoxicity

Natural phenolic compounds are considered as one of the important secondary metabolites for their chemopreventive and chemotherapeutic effects in cancer. These compounds show potent activities for cancer prevention and its treatment. There are many phenolic compounds present in medicinal and edible plants such as, flavonoids, bioflavonoids, stilbenes, chalconoids, chromones, phenylpropanoids, curcuminoids, coumarins, tannins, lignans, neolignans, anthraquinones, quinones, xanthones, phenolic acids and their glycosides and many more. The antioxidant potential of phenolic compounds is almost bolded in the treatment and prevention of cancer. Mono phenolic, polyphenolic and phenolic acids compounds from a large variety of plants, foods, spices, insects, fungus, beverages, lichens, algae and mammals have been shown to inhibit or attenuate the initiation, progression and spread of cancers in cells in vitro and in animals in vivo. In this chapter, we try to cover general view and the recent literature to summarize structural information and cytotoxic effects of phenolic compounds on different cancer cell lines from medicinal herbs and plants

Robust Video Watermarking Based On 3D-DWT Domain.

The digital watermarks have recently been recognized as a solution for protecting the copyright of the digital multimedia

Green Chemistry and Synthesis of Anticancer Molecule

Green chemistry is a modern area of chemistry merged with chemical engineering methods. It highlighted the synthesis of molecules in a manner of using environment-friendly chemical reagents with low waste material for enhancing environmental performance which reduce the formation of hazard substances. Modern researches are trying to reduce the risk of human kind health and the environment of our world by doing magnificent work in the field of green chemistry. In the pharmaceutical field, green chemistry works very well with the formation of many drugs and it utilizes non-hazards, reproducible and environment-friendly solvents with low time and money costs by using catalyst, microwave, ultrasonic, solid phase and solvent-free synthesis. Until now, scientist has synthesized many anticancer molecules by using these modern green chemistry techniques. These compounds showed significant anticancer activities against many human cancer cell lines. In this chapter, we will cover different views and the recently published literature to summarize the role of green chemistry in the synthesis of anticancer compounds

Uranium and Plutonium Recovery by Tributylphosphate Solvation and Trioctylamine Ion association Mechanisms

In this work a flowsheet has been put for the recovery of uranium and plutonium from 2.5M nitric acid solutions using 17.5% tributyl phosphate (TBP) and 2.5% trioctylamine (TOA) in kerosene diluent . The fission products (resulting from irradiated of uranium samples in nuclear research reactor) were removed from the desired actinides U & Pu .The organic phase TBP/TOA/Kerosene, containing both actinides U&Pu were stripped using 0.1 M HNO3. Trioctylamine (2.5 volume ratio ) in mesitylene , has been used in conditions appropriate for the recovery of Pu . From the experiments done using mixer- settler , the concentration of uranium in the organic phase in such conditions was very low ,not exceeding parts of a million