Schizophrenia (SZ) is severe mental disorder and characterized by fundamental disturbances in thinking, perception and emotions. Immune deregulation has been postulated to be one of the mechanisms underlying the pathogenesis of schizophrenia. This study hypothesized that interleukins would have a link with schizophrenia patients. The serum IL-2 and IL-10 levels were examined by enzyme-linked immunosorbent assay (ELISA) in schizophrenia patients (n=60) and healthy controls (n = 30). The results showed that serum IL-2 and IL-10 levels were significantly different among schizophrenia patients. The observations indicate a significant decrease (P < 0.05) in schizophrenic patients serum levels of IL-2 compared with healthy control. Whereas

This study includes 15 male healthy and 30 male patients diagnosed with prostate
cancer inciude (18 cases in stages I & II and 12 cases in III – stage). All the patients
were suffered from urinary tract infection ( UTI) . The mean age is (57.33± 5.02)
years range ( 45-63) years, as cases and controls Patients with prostate cancer were
treated admits an Educational Baghdad Hospital, and Central Public Health
Laboratory and Radiation and Nuclear Medicine Hospital in Baghdad, during
period 1/6/2008 to 1/12/2010 are included in this study. The markers Prostatespecific
antigen (CA PSA), Interleukins ( IL -1 , IL-2, IL-3, IL-5) and
Immunoglobulins ( IgG, IgM, IgE) are estimated by using ELISA method. The
Cl

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

The Study aims to show the role of Flexible Budget in planning and control The Factory over head.

The study consists four reaserchs the First introduction for the role of Budget in planning and control The second definition Flexible Badget the Third Factory overhed cost variances Analysis The four conclusions and recommendations.

The factory overhead cost represents great ratio from product cost so the management must planning and control on cost Through the year by the Budget of factory over head in the beginning of the year and determind overhead rater.

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

In the present paper, three reliable iterative methods are given and implemented to solve the 1D, 2D and 3D Fisher’s equation. Daftardar-Jafari method (DJM), Temimi-Ansari method (TAM) and Banach contraction method (BCM) are applied to get the exact and numerical solutions for Fisher's equations. The reliable iterative methods are characterized by many advantages, such as being free of derivatives, overcoming the difficulty arising when calculating the Adomian polynomial boundaries to deal with nonlinear terms in the Adomian decomposition method (ADM), does not request to calculate Lagrange multiplier as in the Variational iteration method (VIM) and there is no need to create a homotopy like in the Homotopy perturbation method (H

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a