The research undertaken has provided a comprehensive insight into the practice of cupping therapy, a traditional treatment modality that has seen resurgence in. modern complementary medicine. This exploration, focusing on a spectrum of. Conditions such as migraines, lower back pain, neck pain, knee osteoarthritis, and chronic urticaria, highlights the potential benefits and the necessity for a deeper. Scientific understanding of cupping therapy. Cupping therapy, with its roots deeply embedded in ancient medical practices, offers a unique approach to treatment by promoting healing through increased blood flow and the release of toxins from the body. The application of this therapy in treating migraines has shown promising results, su

The main objective of this thesis is to study new concepts (up to our knowledge) which are P-rational submodules, P-polyform and fully polyform modules. We studied a special type of rational submodule, called the P-rational submodule. A submodule N of an R-module M is called P-rational (Simply, N≤_prM), if N is pure and Hom_R (M/N,E(M))=0 where E(M) is the injective hull of M. Many properties of the P-rational submodules were investigated, and various characteristics were given and discussed that are analogous to the results which are known in the concept of the rational submodule. We used a P-rational submodule to define a P-polyform module which is contained properly in the polyform module. An R-module M is called P-polyform if every es

The process of discovering pharmaceuticals is of great importance in our contemporary life, in a way that without life becomes almost impossible, as this process is the first building block in the field of pharmaceutical industries to search for new methods and means of treatment and treatment. This process results in the commitment of the discoverer to a set of obligations in the face of the volunteer. This responsibility or negation of intentional infliction of damage by means of what is known in the law as methods of paying liability

Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

Artificial intelligence (AI) offers significant benefits to biomedical research and academic writing. Nevertheless, using AI-powered writing aid tools has prompted worries about excessive dependence on these tools and their possible influence on writing proficiency. The current study aimed to explore the academic staff’s perspectives on the impact of AI on academic writing. This qualitative study incorporated in-person interviews with academic faculty members. The interviews were conducted in a semi-structured manner, using a predetermined interview guide consisting of open-ended questions. The interviews were done in person with the participants from May to November 2023. The data was analyzed using thematic analysis. Ten academics aged

A direct, sensitive and efficient spectrophotometric method for the determination of nitrofurantoin
drug (NIT) in pure as well as in dosage form (capsules) was described. The suggested method was
based on reduction NIT drug using Zn/HCl and then coupling with 3-methyl-2-benzothiazolinone
hydrazone hydrochloride (MBTH) in the presence of ammonium ceric sulfate. Spectrophotometric
measurement was established by recording the absorbance of the green colored product at 610 nm.
Using the optimized reaction conditions, beer’s law was obeyed in the range of 0.5-30 μg/mL, with
good correlation coefficient of 0.9998 and limits of detection and quantitation of 0.163 and 0.544
μg/mL, respectively. The accuracy and