Abstract:Leukemia is a cancer of early blood forming cells. Most of them are cancers of white blood cells , however some leukemias start in other blood cell types.Electrolytes have modulatory effects on several biological mechanisms in the body namely as stabilizers,element of structures, essential element for hormonal function and also co-factors for a number of enzymes.In this study serum electrolytes levels were measured in patients with acute leukemia (AL) disorders before and after chemotherapy(anthracycline, doxorubicin, cytarabine ,prednisone, vincristine and doxorubicin) during one month and compared with that of control group. Blood samples were obtained from (43) patients (28 males and 15 females) aged (15-55)years;juset before and after chemotherapy. The control group contained samples from (40) healthy volunteers (26 males and 14 females) aged (15-55) years.Serum electrolytes levels(sodium Na+1,potassium K+1,calcium Ca+1,chloride Cl-1,magnesium Mg+2and phosphate PO4-3) were estimated using flame atomic absorbtion photometry. Serum levels of Na, K,Ca and Cl were significantly decreased in patients before chemotherapy in comparasion with that of control group. The mean concentration of serum phosphoruse and magnesium in acute leukemia patients was non significant compared with that of control group. In this study, determination of serum electrolytes in leukemic patients indicates an abnormal metabolic process in these patients
In this paper, we consider a new approach to solve type of partial differential equation by using coupled Laplace transformation with decomposition method to find the exact solution for non–linear non–homogenous equation with initial conditions. The reliability for suggested approach illustrated by solving model equations such as second order linear and nonlinear Klein–Gordon equation. The application results show the efficiency and ability for suggested approach.
The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.
In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.
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... Show MoreThe main purpose of this paper is to study some results concerning reduced ring with another concepts as semiprime ring ,prime ring,essential ideal ,derivations and homomorphism ,we give some results a bout that.
This paper deals with the F-compact operator defined on probabilistic Hilbert space and gives some of its main properties.
In this paper, we introduce and study the concept of S-coprime submodules, where a proper submodule N of an R-module M is called S-coprime submodule if M N is S-coprime Rmodule. Many properties about this concept are investigated.
Let R be a commutative ring with identity 1 and M be a unitary left R-module. A submodule N of an R-module M is said to be approximately pure submodule of an R-module, if for each ideal I of R. The main purpose of this paper is to study the properties of the following concepts: approximately pure essentialsubmodules, approximately pure closedsubmodules and relative approximately pure complement submodules. We prove that: when an R-module M is an approximately purely extending modules and N be Ap-puresubmodulein M, if M has the Ap-pure intersection property then N is Ap purely extending.
This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.
Let R be associative ring with identity and M is a non- zero unitary left module over R. M is called M- hollow if every maximal submodule of M is small submodule of M. In this paper we study the properties of this kind of modules.
In this paper, integrated quantum neural network (QNN), which is a class of feedforward
neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that
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