Abstract
             Shorten the research problem that there is no system or model to evaluate the financial performance of the departments of municipalities where it is not possible for a person or institution both to know or to know their success in terms of the financial work of failure and where it is now than those without assessing the financial performed, authorized to be and necessities FATF is the financial performance assessment, which is the work unfinished aspects without Hence the work came in this study to study and diagnose and analyze financial data in a sample of municipal departments in order to develop a model to assess the financ

The development of low profile gamma-ray detectors has encouraged the production of small field of view (SFOV) hand-held imaging devices for use at the patient bedside and in operating theatres. Early development of these SFOV cameras was focussed on a single modality—gamma ray imaging. Recently, a hybrid system—gamma plus optical imaging—has been developed. This combination of optical and gamma cameras enables high spatial resolution multi-modal imaging, giving a superimposed scintigraphic and optical image. Hybrid imaging offers new possibilities for assisting clinicians and surgeons in localising the site of uptake in procedures such as sentinel node detection. The hybrid camera concept can be extended to a multimodal detec

Objective. Glass-ionomer and resin-modified glass-ionomer cements are versatile materials with the ability to form a direct bond with tooth tissues. The aim of this study was to formulate a novel class of dental bio-interactive restorative material (pRMGIC) based on resin-modified glass-ionomer cements via the inclusion of an organophosphorus monomer, ethylene glycol methacrylate phosphate, with a potential to improve the mechanical properties and also function as a reparative restorative material. Methods. pRMGIC was formulated with modification of the resin phase by forming mixes of ethylene glycol methacrylate phosphate (EGMP; 0–40%wt) and 2-hydroxyethyl methacrylate monomer into the liquid phase of a RMGIC (Fuji II LC, GC Corp.).

Due to their attractive properties, silver nanowires (Ag-NWs) are newly used as nanoelectrodes in continuous wave (CW) THz photomixer. However, since these nanowires have small contact area, the nanowires fill factor in the photomixer active region is low, which leads to reduce the nanowires conductivity. In this work, we proposed to add graphene nanoantenna array as nanoelectrodes to the silver nanowires-based photomixer to improve the conductivity. In addition, the graphene nanoantenna array and the silver nanowires form new hybrid nanoelectrodes for the CW-THz photomixer leading to improve the device conversion efficiency by the plasmonic effect. Two types of graphene nanoantenna array are proposed in two separate photomixer conf

In this communication, introduce the split Mersenne and Mersenne-Lucas hybrid quaternions, also obtaining generating functions and Binet formulas for these hybrid quaternions and investigating some properties among them.

In this work the fabrication and characterization of poly(3-hexylthiophene) P3HT-metallic nanoparticles (Ag, Al). Pulsed Laser Ablation (PLA) technique was used to synthesis the nanoparticles in liquid. The Fourier Transformer Infrared (FTIR) for all samples indicate the chemical interaction between the polymer and the nanoparticles. Scanning Electron Microscopic (SEM) analysis showed the particle size for P3HT-AgNps samples between 44.50 nanometers as well the spherical structure. While for P3HT-AlNps samples was flakes shape. Energy Dispersive X-ray (EDX) spectra show the existing of amount of metallic nanoparticles.

This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K