This study was aimed to determine the mutations and single nucleotide polymorphisms (SNPs) in exon 3 and 7 of estrogen receptor beta (ESR2) gene in women with breast cancer from Iraq. Different samples (blood, fresh tissue with blood from same patient, and formalin fixed paraffin embedded, FFPE) were collected from women with breast cancer. Molecular analysis exon 3 and 7 in ESR2 has been studied by using PCR. It was found exon 3 and 7 in ESR2 were revealed as a single band with size 151 and 157 bp, respectively. There was no SNP in exon 3 has been identified. While three novel polymorphisms (ACT, AGG and GCA) were detected in exon 7, the type of those polymorphisms deletion for ACT and AGG while substitution polymorphism for GCA. From this

Background. Material tribology has widely expanded in scope and depth and is extended from the mechanical field to the biomedical field. The present study aimed to characterize the nanocoating of highly pure (99.9%) niobium (Nb), tantalum (Ta), and vanadium (V) deposited on 316L stainless steel (SS) substrates which considered the most widely used alloys in the manufacturing of SS orthodontic components. To date, the coating of SS orthodontic archwires with Nb, Ta, and V using a plasma sputtering method has never been reported. Nanodeposition was performed using a DC plasma sputtering system with three different sputtering times (1, 2, and 3 hours). Results. Structural and elemental analyses were conducted on the deposited coating

Industrial machining workshops generate substantial quantities of aluminum wire offcuts and filings that cannot be re-entered into bulk metal recycling circuits, posing both a resource management challenge and a potential environmental burden. This study demonstrates a closed-loop valorization route in which this low-grade aluminum waste is converted into nanostructured aluminum oxide (Al2O3) nanoparticles (NPs) by two scalable synthesis pathways (i) chemo-thermal calcination of precipitated Al(OH)₃ at 1000 °C and 1200 °C for 1 and 4 h, and (ii) direct chemical precipitation via AlCl3/Na2CO3 reaction, and then deployed as a functional additive in water-based drilling fluids (WBDFs) used by the oil and gas industry. Comprehensive chara

Baghdad, one of Iraq’s most crowded cities, faces severe air pollution caused by rapid population growth, dense traffic, and limited green spaces. Monitoring at five sites in Al-Rusafa during 2024–2025 showed that pollutant levels, especially PM₁₀, PM₂.₅, and TSP, exceed national and global limits. The most polluted areas lacked vegetation and had heavy traffic, while greener zones showed lower concentrations. Seasonal variations were evident: winter had the highest pollution, summer the lowest but with greater plant stress. Ascorbic acid and the Air Pollution Tolerance Index (APTI) proved reliable indicators of plant resistance. Overall, the study confirms plants’ role as effective bio monitors and stresses the need f

Cognitive stylistics also well-known as cognitive poetics is a cognitive approach to language. This study aims at examining literary language by showing how Schema Theory and Text World Theory can be useful in the interpretation of literary texts. Further, the study attempts to uncover how readers can connect between the text world and the real world. Putting it differently, the study aims at showing how the interaction between ‘discourse world’ and ‘text world’. How readers can bring their own experience as well as their background knowledge to interact with the text and make interpretive connections.       

Schema and text world theories are useful tools in cognitive stylistic stud

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select