The best proximity point is a generalization of a fixed point that is beneficial when the contraction map is not a self-map. On other hand, best approximation theorems offer an approximate solution to the fixed point equation . It is used to solve the problem in order to come up with a good approximation. This paper's main purpose is to introduce new types of proximal contraction for nonself mappings in fuzzy normed space and then proved the best proximity point theorem for these mappings. At first, the definition of fuzzy normed space is given. Then the notions of the best proximity point and - proximal admissible in the context of fuzzy normed space are presented. The notion of α ̃–ψ ̃- proximal contractive mapping is introduced.

The modification of hydrophobic rock surfaces to the water-wet state via nanofluid treatment has shown promise in enhancing their geological storage capabilities and the efficiency of carbon dioxide (CO2) and hydrogen (H2) containment. Despite this, the specific influence of silica (SiO2) nanoparticles on the interactions between H2, brine, and rock within basaltic formations remains underexplored. The present study focuses on the effect of SiO2 nanoparticles on the wettability of Saudi Arabian basalt (SAB) under downhole conditions (323 K and pressures ranging from 1 to 20 MPa) by using the tilted plate technique to measure the contact angles between H2/brine and the rock surfaces. The findings reveal that the SAB's hydrophobicity intensif

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

ليكاند ازو جديد. 4-((3-formyl-2-hydroxyphenyl)diazenyl)-N-(5-methylisoxazol-3-yl)benzenesulfonamide, الليكاند المحضر استعمل لتحضير معقدات من ايونات معادن مختلفة مثل الكروم الثلاثي والمنغنيز الثنائي والحديد الثلاثي  والبلاديوم الثنائي بنسب مولية (1:1) ( ليكاند : فلز) نتائج التشخيص للمركبات يتقنيات مطيافية الاشعة فوق البنفسجية الاشعة تحت الحمراء الرنين النووي المغناطيسي البروتوني والكربوني وطيف الكتلة والتحليل الدقيق للعناصر ومحتوى الفلز وال

Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing

Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak

Activated carbon prepared from date stones by chemical activation with ferric chloride (FAC) was used an adsorbent to remove phenolic compounds such as phenol (Ph) and p-nitro phenol (PNPh) from aqueous solutions. The influence of process variables represented by solution pH value (2-12), adsorbent to adsorbate weight ratio (0.2-1.8), and contact time (30-150 min) on removal percentage and adsorbed amount of Ph and PNPh onto FAC was studied. For PNPh adsorption,( 97.43 %) maximum removal percentage and (48.71 mg/g) adsorbed amount was achieved at (5) solution pH,( 1) adsorbent to adsorbate weight ratio, and (90 min) contact time. While for Ph adsorption, at (4) solution pH, (1.4) absorbent to adsorbate weight ratio, and (120 min) contact

Objectives: To compare early pregnancy outcomes, including miscarriage, ectopic pregnancy, multiple pregnancy, and congenital anomalies, among women who conceived following ovulation induction with letrozole or clomiphene citrate. Methods: A prospective comparative observational study was conducted at Al-Elwiya Maternity Teaching Hospital and a private clinic in Baghdad, Iraq, from March 2023 to December 2024. One hundred infertile women aged 21–35 years who conceived after ovulation induction with either letrozole (5 mg/day) or clomiphene citrate (100 mg/day) for five days (cycle days 3–7) were enrolled. Participants were followed through early pregnancy with serial sonography at 6, 8–11, and 18–20 weeks of gestation. Data