Background: Toll-like receptors (TLRs) play a significant role in the activation of adaptive immunity and may have an essential role in the development of rheumatoid arthritis (RA). Objectives: To assess the gene expression of TLR4 in individuals with RA compared to healthy individuals. Methods: From July to December 2022. A total of 100 individuals were encompassed in the study, consisting of 50 individuals diagnosed with RA, of whom 42 were females and 8 were males, with an average age of 45.22 years. Additionally, there were 50 healthy control participants, 40 of whom were females and 10 were males, with an average age of 45.64 years. To assess the TLR4 transcript levels, blood samples were collected from each participant, and RN

With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

Sand production in unconsolidated reservoirs has become a cause of concern for production engineers. Issues with sand production include increased wellbore instability and surface subsidence, plugging of production liners, and potential damage to surface facilities. A field case in southeast Iraq was conducted to predict the critical drawdown pressures (CDDP) at which the well can produce without sanding. A stress and sanding onset models were developed for Zubair reservoir. The results show that sanding risk occurs when rock strength is less than 7,250 psi, and the ratio of shear modulus to the bulk compressibility is less than 0.8 1012 psi2. As the rock strength is increased, the sand free drawdown and depletion becomes larger. The CDDP