Leishmaniasis is a global illness that is endemic in many countries, including Iraq. The characteristic of cutaneous leishmaniasis (CL) is the development of skin ulcers that are controlled by the immune system. Tumor necrosis factor-alpha (TNF-α), a cytokine generated by the innate immune response to CL infection, can influence disease clearance in the human host. The effect of this pro-inflammatory cytokine in CL ulcer development during the infection is not well established. In this study TNF-α level was detected in the patients who suffered from cutaneous leishmaniasis. This level was also assessed in the newly diagnosed patients and others who were undergoing different stages of pentostam treatment. Notably the result

     Pseudomonas aeruginosa is an opportunistic pathogen. Quorum sensing (QS) is one of processes that are responsible for biofilm formation. P. aeruginosa can live in different environments, some of which are pathogenic (clinical isolates) and some that are found outside the body (environmental isolates). The present study aimed to determine the presence of a number of genes responsible for QS in clinical and environmental isolates of P. aeruginosa. In the present study full DNA was separated from all environmental and clinical isolates that contained seven genes (rhlA, rhlR, rhlI, lasR, lasI, lasB, phzA1) associated with QS occurrence. The tot

Currently, the prominence of automatic multi document summarization task belongs to the information rapid increasing on the Internet. Automatic document summarization technology is progressing and may offer a solution to the problem of information overload. 

Automatic text summarization system has the challenge of producing a high quality summary. In this study, the design of generic text summarization model based on sentence extraction has been redirected into a more semantic measure reflecting individually the two significant objectives: content coverage and diversity when generating summaries from multiple documents as an explicit optimization model. The proposed two models have been then coupled and def

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

 Fluoroscopic images are a field of medical images that depends on the quality of image for correct diagnosis; the main trouble is the de-nosing and how to keep the poise between degradation of noisy image, from one side, and edge and fine details preservation, from the other side, especially when fluoroscopic images contain black and white type noise with high density. The previous filters could usually handle low/medium black and white type noise densities, that expense edge, =fine details preservation and fail with high density of noise that corrupts the images. Therefore, this paper proposed a new Multi-Line algorithm that deals with high-corrupted image with high density of black and white type noise. The experiments achieved i

A roundabout is a highway engineering concept meant to calm traffic, increase safety, reduce stop-and-go travel, reduce accidents and congestion, and decrease traffic delays. It is circular and facilitates one-way traffic flow around a central point. The first part of this study evaluated the principles and methods used to compare the capacity methods of roundabouts with different traffic conditions and geometric configurations. These methods include gap acceptance, empirical, and simulation software methods. Previous studies mentioned in this research used various methods and other new models developed by several researchers. However, this paper's main aim is to compare different roundabout capacity models for acceptabl