The presence of heavy metal in environment associated with several health problems. The clean up environment from lead (Pb) and Nickel (Ni) represent major challenges. In his study, planktonic and immobilized bacteria were used to purify the water from Pb and Ni in Lab. In the present study, three bacterial isolates of Staphylococcus aureus (isolated from wound swaps), Pseudomonas aeruginosa (isolated from wound swaps) and Pantoea (isolated from urine samples) and identified using biochemical methods to check their ability to biosorb Pb and Ni. Ten PPM of Pb and Ni were added to the deionized distilled water and 107 c.f.u. of planktonic bacteria were used to biosorpe Pb and Ni. Similar experiment was repeated but in this case, the immobilized bacteria (S. aureus, Pantoea, and P. aeruginosa) on silica gel and eggshells were used. It was found that S. aureus decreased the level of Pb and Ni significantly (P<0.05) in planktonic and immobilized form. Pantoea decreases the level of Ni only in planktonic form. This bacteria decreased the level of Pb and Ni significantly when it immobilized on silica gel and eggshells (P<0.05). P. aeruginosa could not decrease the level of Pb and Ni when it was in planktonic form but it can decrease the level of heavy metals in the immobilized form on silica and eggshells (P<0.05). It can be concluded that the studied bacteria can purify water from heavy metals in immobilized status more efficiently than planktonic form.
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 MoreBackground: The world health organization estimates that worldwide 2 billion people still have iodine deficiency Objectives: Is to make comparison between the effect of identification of recurrent laryngeal nerve (RLN) and non-identification of the nerve on incidence of recurrent laryngeal nerve injury (RLNI) in different thyroidectomy procedures.
Type of the study: cross –sectional study.
Methods: 132 patients with goiters underwent thyroidectomy .Identification of RLN visually by exposure were done for agroup of them and non-identification of the nerves for the other group. The outcomes of RLNI in the two groupsanalyzed statistically for the effect of
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The 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.
Image steganography is undoubtedly significant in the field of secure multimedia communication. The undetectability and high payload capacity are two of the important characteristics of any form of steganography. In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image. The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT. The cover image is divided into non overlapping blocks of size (3*3). After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text. The cover image is converted using DT-CWT, then the p
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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 L be a commutative ring with identity and let W be a unitary left L- module. A submodule D of an L- module W is called s- closed submodule denoted by D ≤sc W, if D has no proper s- essential extension in W, that is , whenever D ≤ W such that D ≤se H≤ W, then D = H. In this paper, we study modules which satisfies the ascending chain conditions (ACC) and descending chain conditions (DCC) on this kind of submodules.
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.
Background:Non-host-adapted Salmonella serovar Typhimurium is a facultative intracellular bacterium, which invades and multiplies within mononuclear phagocytes in liver, spleen, lymph nodes and Peyer’s plaques. Salmonella infection is a crucial medical and veterinary problem globally. S. Typhimurium causes various clinical symptoms, from asymptomatic infection to typhoid-like syndromes in infants or highly susceptible animals, for instance mice.
Objective: The present study was carried out to investigate the efficacy of anthrax protective antigen (PA)as a potent adjuvant mixed with killed Salmonella Typhimurium (S.T.) to enhance the immunization capacity of the last.
Materials and Methods: Two groups of mice were immunized with e
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.