Recently, detecting dynamic patterns for growing communities in social networks have attracted significant attention. The objective of dynamic community detection is to analyze and identify clusters in complex networks that change over time. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of dynamic community detection. Although current evolutionary algorithms for identifying community structure can traverse extensive areas of partition space, they often become stuck in local minima. In addition, limited studies have addressed this issue by integrating local search strategies with evolutionary algorithms for community identification. This paper in

The use of sugarcane molasses (SCM) as a sustainable stabilizing agent for geomaterials, particularly granular subbase soils, has recently attracted growing attention as an alternative to traditional stabilization methods employing cement, lime, or bitumen, which are often associated with high costs and environmental concerns. This study presents a mechanistic–experimental evaluation of SCM for stabilizing granular subbase materials at dosages of 2.5%, 5%, 7.5%, and 10% by weight of dry granular material. A comprehensive testing program was conducted, including compaction characteristics, California Bearing Ratio (CBR), resilient modulus (Mr), permanent deformation under repeated loading, optical microscopy, and FTIR spectroscopy.

In addition to being a novel medication in treating obesity and type 2 diabetes mellitus, tirzepatide is currently being studied to assess its effectiveness and safety on various health parameters, specifically with an emphasis on the neurological field, including sleep medicine and neurodegenerative conditions. In this perspective, we highlight the recent FDA approval of tirzepatide’s use for the treatment of obstructive sleep apnea, with recommendations for future research to extend use in children and adolescents.

This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF

AlPO4 catalysts supported with WO3 were prepared by impregnating the catalysts with ammonium metatungstate. The catalysts were checked by X-ray Diffraction (XRD), AFM, and SEM; also, the catalysts analysis was done by X-Ray (EDX). Finally, the N2 adsorption-desorption was used to measure the pore volume and surface area of the catalyst. The prepared catalyst has a surface area of 185.83 m2/g, pore volume of 0.645 cm3/g at a calcination temperature of 500°C for 3 hrs, and particle size of AlPO4 with an average of 35.36 nm. Transesterification of edible oil using WO3/AlPO4 was performed, it was observed that WO3/AlPO4 catalysts give high conversion of edible oil, and this is attributed to the high surface area, smaller particle size, and the

Toxic substances have been released into water supplies in recent decades because of fast industrialization and population growth. Fenton electrochemical process has been addressed to treat wastewater which is very popular because of its high efficiency and straightforward design. One of the advanced oxidation processes (AOPs) is electro-Fenton (EF) process, and electrode material significantly affects its performance. Nickel foam was chosen as the source of electro-generated hydrogen peroxide (H2O2) due to its good characteristics. In the present study, the main goals were to explore the effects of operation parameters (FeSO4 concentration, current density, and electrolysis time) on the catalytic performance that was optimized by r

Objective: To study the effect of epidural spinal injection over one year in case of spinal stenosis. Methodology: This prospective study included 566 patients with spinal stenosis seen at Al-Kindy Teaching and Al-Sader, Hospitals who were treated by local epidural steroid injection. They were followed up for at least five subsequent visits after seven days, one month, three months, six months, and one year to assess efficacy. Result: Mean age of patients was 49.5 years, with a predominance of females (65%). L4/L5 was the most involved level in the spinal stenosis (70%). Grade II stenosis accounted for (45.4%) of cases. The pairwise comparison revealed that there was significant decrease in proportions of patients with pain in day

A new method for determination of allopurinol in microgram level depending on its ability to reduce the yellow absorption spectrum of (I-3) at maximum wavelength ( ?max 350nm) . The optimum conditions such as "concentration of reactant materials , time of sitting and order of addition were studied to get a high sensitivity ( ? = 27229 l.mole-1.cm-1) sandal sensitivity : 0.0053 µg cm-2 ,with wide range of calibration curve ( 1 – 9 µg.ml-1 ) good stability (more then24 hr.) and repeatability ( RSD % : 2.1 -2.6 % ) , the Recovery % : ( 98.17 – 100.5 % ) , the Erel % ( 0.50 -1.83 % ) and the interference's of Xanthine , Cystein , Creatinine , Urea and the Glucose in 20 , 40 , 60 fold of analyate were also studied .