This study investigated the efficacy of nasal injection of rhodamine B nanospanlastic (RBN) for magnetic vesicle imaging of specific brain locations. Effective delivery of RBN, which functions as fluorescence agents, to specific brain regions is necessary to achieve fluorescence particle imaging (FPI). There has been interest in nasal administration as a means of administering drugs directly to the brain, thereby circumventing the blood-brain barrier. We offered experimental nasal fluorescence agent administration by in vivo research. Fluorescent tests confirmed that, upon nasal delivery, the intended nanospanlastic migrated into the brain. Furthermore, using fluorescent microscopy, we demonstrated how these nanospanla

Multipoint forming process is an engineering concept which means that the working surface of the punch and die is produced as hemispherical ends of individual active elements (called pins), where each pin can be independently, vertically displaced using a geometrically reconfigurable die. Several different products can be made without changing tools saved precious production time. Also, the manufacturing of very expensive rigid dies is reduced, and a lot of expenses are saved. But the most important aspects of using such types of equipment are the flexibility of the tooling. This paper presents an experimental investigation of the effect of three main parameters which are blank holder, rubber thickness and forming speed th

Objective: To determine the effectiveness of the Nursing Management Education Program upon the Nurse
Managers' Knowledge about planning in Nursing Management at Baghdad City Hospitals.
Methodology: A Quasi-experimental study in which a purposive "non-probability" sample of (50) Nurse
Managers was selected from Baghdad City Hospitals. These Managers were divided into two equal groups of
(25) Nurse Managers for each (study and control ones). A questionnaire was developed as a tool for data
collection. A pilot study was carried out to test the reliability of the questionnaire for the period from April 2nd to
June 20th 2007. The pre-post test approach was applied to the study and control groups as mean for the quasiexperime

Speech recognition is a very important field that can be used in many applications such as controlling to protect area, banking, transaction over telephone network database access service, voice email, investigations, House controlling and management ... etc. Speech recognition systems can be used in two modes: to identify a particular person or to verify a person’s claimed identity. The family speaker recognition is a modern field in the speaker recognition. Many family speakers have similarity in the characteristics and hard to identify between them. Today, the scope of speech recognition is limited to speech collected from cooperative users in real world office environments and without adverse microphone or channel impairments.

The proposed design of neural network in this article is based on new accurate approach for training by unconstrained optimization, especially update quasi-Newton methods are perhaps the most popular general-purpose algorithms. A limited memory BFGS algorithm is presented for solving large-scale symmetric nonlinear equations, where a line search technique without derivative information is used. On each iteration, the updated approximations of Hessian matrix satisfy the quasi-Newton form, which traditionally served as the basis for quasi-Newton methods. On the basis of the quadratic model used in this article, we add a new update of quasi-Newton form. One innovative features of this form's is its ability to estimate the energy functio

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

Iraq is highly dependent on international markets to provide food for its residents. As imported food prices are highly dependent on crude oil prices in global markets, any shock in oil prices will have an impact on food consumption in the country. As a result, it is essential to study the demand for imported food at every time period. To the best of our knowledge as researchers, as not even a single study is available in the literature, this paper is considered the first to study the demand for imported food groups in Iraq. Therefore, the main objective of this research is to estimate demand elasticities for several imported food categories in Iraq. This study uses an Almost Ideal Demand System model to analyze the demand for imported f

Integrated project delivery is collaboratively applying the skills and knowledge of all participants to optimize the project's results, increase owner value, decrease waste, and maximize efficiency during the design, fabrication, and construction processes. This study aims to determine IPD criteria positively impacting value engineering. To do this, the study has considered 9 main criteria according to PMP classification that already covers all project phases and 183 sub-criteria obtained from theoretical study and expert interviews (fieldwork). In this study, the SPSS (V26) program was used to analyze the main criteria and sub-criteria priorities from top to bottom according to their values of the Relative Importance In

Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data